If you have ever been drawn to the words “artificial intelligence” in a sales pitch or wondered if machine learning could improve your business, you might have also questioned if your use case is even a good fit for what a machine learning model can do.
A good way to approach answering this question is to consider the data you need to provide this artificially intelligent system in order for it to produce the promised result. That sounds like a reasonable exchange, except, are you sure you know what data means in this context?
What is Data?
Let’s say you are interested in a machine learning model that can predict the contact reason for inbound support emails (surprise: this is Kustomer IQ!). The model needs to see examples of previous support conversations and how they were labeled in order to learn what to do when new, unlabeled emails show up in the future. These examples are your data: a collection of paired inputs and outputs from which a machine learning model will extract patterns to make predictions.
In this case, it’s up to you to determine the inputs (“Inbound Support Email”) and outputs (“Contact Reason”) and which input-output pairings best represent the predictions you want the model to make. And in general terms, the more data you expose the machine to, the smarter it gets.
Make sense? This is data. Without data, machine learning models can’t work. And a machine learning model will only learn from what’s in the training data: what doesn’t appear explicitly in the dataset will remain unknown to the system.
As we said before, the models extract patterns in order to apply outputs. You’ll notice in the above diagram, we did not tell the model how we were able to determine Contact Reason. We are just planning to show it input-output examples and trust it will eventually come up with a way to infer “Contact Reason” from an “Inbound Support Email”. This is where data quality becomes important: if we give the model poor quality data, the model will make bad patterns and ultimately incorrect predictions.
Poor quality data is noisy, conflicting, or perhaps consists of too few examples. In the diagram above, the last Inbound Support Email has been categorized as an “Exchange”. We already mentioned that it’s up to you to determine the output in the training dataset, so you or one of your agents decided the contact reason was an exchange. What if another agent decided the contact reason was “Return”? Technically, a return might need to happen for an exchange to occur, so the agent felt the return categorization made sense. Now, what if your agents made this mistake 50% or 25% of the time? This means your resulting training data does not reflect the truth of what you want the model to predict — sometimes the conversation is labeled as an “Exchange” and sometimes the same type of conversation is labeled as “Return”, but it should always be Exchange. In this case, the model will extract a pattern that might not consistently lead it to infer your preferred contact reason for future inbound support emails.
This is an example of one of the main causes of poor quality data: unclear and conflicting boundaries between categories or topics.
Here are the characteristics your data needs to have to be considered “high quality” by Kustomer IQ standards:
Heterogeneity (this is demonstrated in the scenario above): Clear and distinct topic boundaries between different tags and attributes
Stability: No big re-categorization changes 60-90 days prior to model training
Volume: Between 5,000 – 7,000 email conversations from the previous month, or about 500 conversations per topic
Recommendations for Creating High Quality Data for Kustomer IQ
Kustomer IQ relies on machine learning models to predict customer contact reasons and suggest conversation shortcuts to agents. It’s important for you to have high quality data to make these models work as expected.
There are a number of steps you can take to ensure the highest quality of your data and leverage automation from the very beginning. Here are our recommendations:
Design tags and custom fields that best suit your needs. While it’s impossible to cover all cases, try to focus on the most important ones in terms of expected volume. For example, order status, returns & refunds, or promo codes.
Create new tags to cover unlabelled information rather than redefining and remapping everything from scratch.
Add granularity in an incremental fashion. When possible, start with a broad category, such as pets, before attempting to split it into various, more specific categories, such as cats, dogs, or birds.
Try to use clearly defined tags and categories to organize your information. A good rule of thumb is to test them with people. If your team understands their boundaries correctly and knows when to apply them, a machine learning algorithm will be able to figure out their meanings.
Try to make your team work as consistently as possible. Again, this is easier to achieve when tag limits are clear.
Try to keep data stable for a while so that you can grow the amount of examples using your tags and custom fields. While you can iterate and re-define your tags and custom fields at any time, regularly changing this information will affect the amount of data points you get. Also, keep in mind that any re-definition of tags and categories will need the model to be re-trained.
Click here to learn more about how Kustomer IQ can help your organization.
Every business understands the importance of good service, but few are able to deliver an excellent customer experience that gets your most dedicated followers raving about you. Consumers value good customer service, and they’re much more likely to buy from a company again when they’ve had a good experience with a company representative., But how do you perfect the science of CX and deliver a consistent experience to every person who interacts with your brand?
With so many resources being focused on top-line revenue growth strategies, companies are really missing the mark by not optimizing their front-line experiences with their buyers. In order to deliver an excellent customer experience, you have to first take a look at what is missing in your organization and what is preventing you from delivering a stellar customer experience.
What’s the Difference: Excellent Customer Experience vs. Customer Service
The key difference between these two is that customer service is just one part of the puzzle. Customer service is directly serving a customer one-on-one and dealing with their unique challenges. The customer experience, however, takes a holistic view of everything the organization is doing to bring a joyful experience to the entire customer journey. This is the key piece that brings buyers back for more and turns a pseudo-buyer into a raving fan that can’t get enough.
When you create a strategic customer experience strategy, you’re no longer leaving each customer interaction up to chance. An excellent customer experience also increases brand trust, consistency, and trackability. People don’t just value good customer service, they value the personalized service a brand can bring into their experience. People want to feel like the brand cares about them and that the products and services are matching their needs and pain points.
However, brands are falling short in this department. A good customer service experience often falls to the bottom of the investment queue, while marketings and sales budgets take center stage. But don’t worry, there are ways a brand can maintain an excellent customer experience without breaking the bank.
The Importance of Good Customer Experience
A study by Nielsen showed that 73% of millennials were willing to spend more on a product if it was a socially conscious brand. This means a large demographic wants the companies they do business with to care about them and the types of products they’re bringing into the world. In another study conducted by Porter Novelli’s 2020 The Business Imperative For Social Justice Today, they highlighted that 71% of Americans believe companies have more responsibility than ever before to address social justice issues and 56% of participants said when companies do not talk about social justice issues in their marketing or communications, they’re perceived as out of touch. When you deliver a good customer experience that incorporates your core brand messaging and its values through impactful communication, it resonates and builds a stronger brand connection with your audience.
There are also devastating impacts to a business when they deliver a bad customer experience. It is estimated that more than $62 billion is lost each year due to a bad customer service experience, and roughly only 10% of buyers say that brands meet their expectations when it comes to a good customer experience. It’s not that these buyers have high expectations; brands are unconsciously making their customer experience services difficult to use, and not user-friendly.
An excellent customer experience strategy doesn’t involve reworking your entire organization top-to-bottom or even require excessive retraining of your support team. You’d be surprised how small incremental steps in the right direction can move the needle ten-fold. For example, putting yourself in your buyer’s shoes and going through ‘a common problem’ they experience can reveal interesting insights into how your brand can improve and lessen the frustration a customer may experience.
4 Ways to Improve the Customer Experience in Retail
Get to Know Your Customers
Do you know what’s important to your customers? Are there social issues they’re fighting against? Brands who stand up and advocate for the very same causes your ideal customers care about can earn more money, more praise, and more brand loyalty. Customers want to know that their brand is a part of a bigger vision than themselves. They do not want to support a company that’s just about the bottom line. There is a huge buyer sentiment shift happening, where modern consumers want brands to be transparent, they want employees to be treated fairly, and they want to know brands are supporting their local community.
By understanding what’s important to your customers, you can offer a personalized service that they haven’t seen or experienced anywhere before. You can do this by incorporating important initiatives throughout the customer service experience, whether that might be having one of your agents proactively explain the company’s values and social missions, or incorporating relevant statistics or facts within your website materials. This attention to detail ends up earning you a loyal customer who is happily recommending your services to their friends and family.
Develop Protocols to Quickly Act on Agent Feedback
Your customer service agents are on the frontlines, and can spot common themes and trends with your customers. What are your processes right now to help capture customer sentiment and data point they’re collecting “on the ground’? By quickly incorporating regular agent feedback, this can actually be the easiest way you can turn an ‘okay’ customer experience into an excellent customer experience.
Capture Customer Feedback in Real-Time
How happy are your customers after they’ve interacted with you? This is a critical piece in understanding more about your customer and what type of experiences they’re having with your brand. With the right technology, organizations can send an immediate and automatic feedback survey each time a customer has finished an interaction.
Provide a Unique Shopping Experience
Through the use of reporting and analytics, businesses are able to determine how satisfied a customer was after their shopping experience. You can re-engage your customers based on their preferences at a future time and get them to come back for more. Personalization is key in the digital world where every business is trying to grab your buyer’s attention. If you already know what your buyer likes, values, and believes in, it becomes an easy entry point to offer the right products and services..
How We Can Help Your CX
Companies are having a hard time finding unique ways to deliver a personalized customer experience, but through automation, AI, and machine learning, you can free up agent time to build more meaningful relationships with your customers, instead of being bogged down in busy work.
Kustomer can help identify key gaps within your systems and processes and help you fill them. Through our CRM platform, CX organizations are able to access customer history across channels and platforms seamlessly, resulting in a dramatic improvement in customer satisfaction. Consumers want to know you care about them, and by offering personalized service, leveraging effective systems to collect feedback, and the ability to act quickly on that feedback, you will earn your customers’ trust and drive more sales.
Don’t miss the chance to improve the customer experience. Through strategic implementation of the right tools, you can cultivate a loyal customer base that will never forget you.
Kustomer offers a seamless CRM platform that helps easily track and deliver on your brand promise across multiple channels. Interested in learning more? Check out this handy (and free!) buyer’s guide.
Consumers want options more than ever before and, more importantly, they want them quick. If you look at the three biggest customer service trends for the future, they all point toward automation and AI handling simpler tasks, and human agents dealing with complex issues.
Our buying trends have evolved too. More people prefer to shop online and have their packages delivered right from the comfort of their own home, rather than travel to a physical store. Digital natives have also grown up with technology, and interacting with this tech has essentially become second nature. Consumers are used to getting the answers they need in an instant, and they expect online businesses to fulfill these expectations.
Unfortunately, businesses are slowly adapting to this online trend and, even if they do incorporate some form of live chat, they’re only using a fraction of its full functionality. If you’re looking to get ahead of your competition, then providing a business live chat service directly on your website will be one of the key strategies to help you stand out and convert skeptical buyers into happy fans.
The simple fact is: e-mail is too slow, and very few people want to be put on hold and wait to speak to a customer representative when they can quickly ask the question in a chat widget right on the site. Chat allows consumers to get help directly on the platform they are using, while also allowing them the flexibility to continue browsing the internet while having a customer service conversation. Phone wait times can vary, and many people don’t like having one ear ‘on’ as they wait for customer support.
Millennials report feeling less stressed and pressured when they interact with a live chat feature, and users who engage in a chat and quickly get the answers to their questions are also more likely to spend more money. This means a business could be losing 30% in additional customer buying power just by not having a chat feature!
A live chat is when a customer support agent is helping a customer in real time through a chat widget on a company’s website. Agents can quickly answer a customer’s questions based on their needs and provide a more customized experience. This live chat experience is somewhat different from an automated chatbot experience because chatbots already have a pre-determined and pre-filled response repository for them to use and can quickly recall commonly asked questions. Live chat is a step up, for when a customer needs individualized support and wants to talk to a real person.
Live chat offers a competitive edge because customers feel like the company they are doing business with cares about their time and needs. The biggest source of frustration for many customers is the inability to speak to a live person. The chat box provides a low cost way to deliver that experience to their customers, and it’s incredibly simple to use, both for the customer and the agent.
How Does Live Chat Work? A Quick Walkthrough
For those who might be unfamiliar, a live chat interaction would look something like this: there is a popup on the client website, usually located at the bottom of the right-hand side of the webpage, that appears when a user or customer lands on that page. Within this automated chat popup, you will typically see a friendly customer agent profile picture and they will ask the user, “Hey there, how can I help you today?” This allows the user to quickly engage within chat if they are having trouble finding the right information they’re looking for. After that, the conversation with the customer has started and a personalized relationship with the customer gets built with a live agent.
On the back end, what the live agent sees is slightly different: They should have access to a single, holistic timeline view of the customer where the agent can quickly view aggregated data particular to that individual, and provide a personalized service to that customer.
Your live agents will actually have insights into what their potential customer is interested in, how long they’ve been a loyal customer, and utilize templated responses within the system to help respond faster to multiple customers asking for similar things.
When using a customer service CRM, businesses can integrate different apps and platforms into one central workspace, making it quick and easy for agents to service a customer on chat. Customers can be intelligently routed to the most appropriate representative at the beginning of the conversation, spam bot conversations can be automatically flagged with the help of AI, and customer feedback can be measured directly within the chat conversation.
What Are the Benefits of Live Chat on Your Website:
The biggest live chat benefit: it’s the most convenient channel for customers. They don’t have to switch platforms or switch ‘contexts’ in order to get the information they’re looking for. For example, if they’re forced to call a customer service agent, they’d have to get out their phone or switch applications on the phone (if they’re already on mobile), and wait in a queue for an agent to help them. For the average user, that’s a lot of frustration and wasted time. The same applies to e-mail. Although you don’t have to talk to someone, waiting 24 to 48 hours to get a response to a simple question can sour their experience.
Increases Purchase Conversions
Customers love to get an answer to their question within a few minutes, not hours, and often hop on chat to get what they’re looking for right away. This means the role of the customer service agent has changed. They no longer simply provide solutions to problems, but instead are offering upfront advice to customers and clearing any roadblocks they might have with the product or service. After having their queries answered, customers are more likely to make their purchase right then and there, leading to more purchases.
Cart abandonment is one of the biggest challenges an online store has, but if you have a live customer service agent ready to answer any questions, you give customers a real-time incentive to buy from you.
Low Cost … and It’s Personalized
It’s become rather inefficient to have a CS agent answer a phone call live: it doesn’t allow them to service more than one customer. Afterall, you can only speak to one person at a time on a call. With chat, this is no longer the case. An agent can manage multiple conversations at the same time while they’re waiting for customers to find their order number or look up additional information for the agent.
The power of personalized service also goes a long way for the customer; it gives them a sense of confidence and trust when they know there’s a real person on the other side of the conversation. When you have an increase in customer satisfaction, customers are more likely to buy from you again.
Removes Language Barrier
According to the U.S. Census, roughly 21% of the American population are non-native English speakers. That means a large swath of your customer base may not feel 100% confident in their speaking and writing ability. E-mails can appear too formal and nerve-wrecking for someone who speaks English as a second language and they may be overly critical of incorrect grammar. The same can happen with phone calls.
With the right customer service CRM, AI can identify the language the individual is speaking in during the live chat and route them to a native speaker. It gives non-English speakers a better, more informal way of communicating with a customer representative. If you don’t have a representative that speaks the customer’s native language, that’s okay too. Through technology, live chat can take translatable snippets of typical questions and answer it in the customer’s native tongue. Chat provides a more relaxed way for a non-native speaker to communicate, and it’s also very forgiving of any grammar mistakes too!
How Effective Is Live Chat?
We know the benefits of live chat, but what does the data say on its effectiveness? Based on research conducted by Econsultancy, live chat has the highest satisfaction levels compared to any other customer service channel at 73%. This compares to 61% for e-mail and 44% for phone.
According to data collected by Invespcro, 63% of consumers are more likely to return to a website that offers live chat, and 42% of customers prefer giving their contact information within chat, which is higher than any other lead generating method. People who engage in chat are also spending about 60% more per purchase than those who do not.
Do you have high shopping cart abandon rates? Live chat can help fix that. According to Baymard Institute, the average cart abandonment rate is 69.57% And another report from Barilliance shows that cart abandonment rates are even higher on mobile devices, up to a whopping 85.6%!
This research is further confirmed by Forrester: 57% of participants said they’d abandon a purchase if their questions weren’t answered quickly enough and 44% of consumers said that having their questions answered by a live person was “one of the most important features a company can offer.”
Business Benefits of Live Chat
Study after study has shown that live chat is an effective way to prevent cart abandonment, increase customer satisfaction, and customer loyalty. By having a live person on the other line, your buyers can have their complex issues fixed and you can give your customers a more personalized experience based on their unique challenges and needs at one of their most critical times: when they’re ready to buy.
Cart abandonment is a huge problem for businesses everywhere in the online world. A live agent is like having a personalized salesman to talk to your prospect and give them the boost of confidence they need in order for them to buy. It answers their questions and any objections they have in real time, which means purchases happen on the spot. You have the unique opportunity to guide a user through a roadblock, something that is not always possible with other forms of customer service communication.
Another benefit to providing a service in real-time is that the world is a very busy and distracted place, if a user has to ‘come back later’ to make a decision, chances are they’ve moved on completely, and once you’ve lost them, you’ve lost them forever.
Think about all the effort that goes into marketing and sales, but what about customer service? You have the people already knocking at your door, it’s just about taking that extra personalized step and leading them to the right place that will help solve their core problem.
Interested in Getting Live Chat on Your Website? Connect With Kustomer
If you’d like to find out more about Kustomer and how we can help, get in touch for a demo. You can also check out our handy (and free!) guide about The Undeniable Benefits of Live Chat, if you’re looking for more information on how to deliver superior customer service through the use of live chat, chatbots and more!
We’re back again with some fresh CX stories from the frontlines. In case you missed it, check out our previous issue on the blog, recounting real life anecdotes on how businesses have solved their customer service challenges with the help of Kustomer.
In this month’s edition, we discuss how a financial services company is improving agent efficiency, the power of data for a marketplace, and why intelligent routing is helping a subscription service deliver first-class service to VIPs.
Financial Services Company Gives Agents the Tools They Need to Succeed
A financial services company focused on making the cumbersome home loan application process as seamless as possible, had a problem. As is expected, the loan application process involves massive amounts of regulatory paperwork that simply cannot disappear, but they needed a way for agents to surface that paperwork and find customer information quickly.
The team leveraged Shortcuts Attachments to quickly surface things like detailed mortgage policy documents, shaving off a few seconds of agent handle time. While this doesn’t seem like a lot, this time adds up and ultimately defines staffing needs and impacts the overall customer experience. Additionally, the team is establishing new operational flows for their agents through Conditionally Required Attributes (CRAs). The loan process requires a litany of forms and stages to be completed, which often lead to additional forms. CRAs allow them to more cleanly track a customer’s stage in the loan process checklist during a key handoff period between agents.
Lastly, Timeline Pinning is proving to be a game changer for the business’ customer service agents. Now the agents are able to keep critical client and loan stage information right in front of the agent, eliminating the need to dig through old notes and documents. All of these developments are allowing the business to pull other teams in the Kustomer Platform and focus on streamlining their internal systems in a single hub.
Understanding Shipping Shortfalls Through Reason Codes
The amount of data that customer service organizations gather is a gamechanger. This information doesn’t simply impact the customer service organization, it can impact all aspects of a business, from the web experience and product development, to logistics and transportation. An international marketplace understood the impact of this data, and leveraged Kustomer to gather insights that could improve their bottom line.
The business is taking data gathered within the Kustomer platform, and both searching and filtering on particular data points to see where they are experiencing problems in different parts of the organization, with the ultimate goal of implementing process improvements. Specifically, they are currently using Reason Codes to pull reports for shipping operations, to show where they are missing the mark and working towards changing the process.
Monthly Subscription Service Supports VIP Customers at Lightning Speed
According to recent Kustomer research, 83% of consumers believe that they should be treated better for being a loyal customer. A leading subscription service realized this, and leveraged the Kustomer Platform in order to deliver on that promise. The team tapped into the power of intelligent routing in order to jump VIP customers up to the top of the queue, and the impact has been tremendous. Their first response time for VIPs is now about 400% faster, all without having to set up an additional queue & routing team. Now that’s first-class treatment.
We want to hear from you! Let us know if you’re tackling CX problems in an interesting way and we will feature you in the next CX Stories From the Frontlines.
Customer service agent friction can be a major pain point for many businesses, because there are innumerable variables in the customer journey that can be hard to account for. However, if businesses want to scale, they need to remove as many roadblocks as possible that might be preventing the customer from purchasing, resolving their problems, or having a seamless customer experience.
Customers have reported that they’d completely leave a website and abandon their cart if their questions or concerns weren’t answered quickly enough. More consumers value the ease of communicating with a brand than ever before, and customer service agents are on the forefront of representing a brand, becoming the single source of truth for customers to depend on.
If you have poor systems and processes in place during the customer service handoff, your customers will notice and become easily frustrated. With so much money going into marketing and sales budgets, it’s important to tighten up the backend so that your dollars go further and your customers report high satisfaction rates, finish the buyer cycle with ease, and are excited to come back for more personalized service.
What is Customer Service Agent Friction?
Customer service agent friction is when customer service agents are having a hard time fulfilling customer requests and getting to their conversation backlog quickly. This can be a big contributor as to why a customer might not have a pleasant experience. Many people prefer a frictionless experience, and if agents are struggling to keep up with inbound conversations, customers will get frustrated and potentially leave for the competition.
What is Customer Friction?
Customer friction refers to everything that a customer might face that brings their purchasing decision to a halt or prevents them from completing a transaction. It can also mean common questions or problems a customer might have, but can not find the solutions to. The goal in the end is to remove all obstacles a customer might face when they interact with your brand. There can be many factors as to why customer friction might occur. For one, the quality or usability of a brand’s website may not be up to par. The business might have limited operational hours, or it could be difficult for the customer to get to the payment form. Customer friction can also occur when dealing with uninformed staff or excessive customer service wait times.
Why Reducing Agent Friction Matters
Businesses need to take a hard look at their internal processes. Fifty-seven percent of consumers said they’d completely abandon their cart if their questions weren’t answered quickly enough. Delays can happen when a service agent doesn’t have all the information they need, and this leads to people taking their money elsewhere. Sometimes this information is dependent on other departments, like the fulfillment center or finance department, and agents need to individually reach out to a different team. You can prevent this from happening through the incorporation of CX software that already has an internal knowledge base that houses critical company information to help agents with their information roadblocks.
If customers aren’t satisfied with their customer service experience, they’re more likely to be vocal to their friends and family about it, and make a point to deter others from doing business with the brand. They are also less likely to return to a brand if they’ve had a negative customer service experience. Valuable dollars and additional revenue could be saved just by investing in a streamlined process to help agents be more efficient and effective.
The Most Common Agent Friction Problems
Many businesses operate on an old-school, or traditional CS model. A customer comes to the brand with an issue, a ticket gets created, this ticket gets assigned to an agent, and then they work on it until there’s a resolution. This all sounds great in theory, but we’re living in a more evolved world and customers are actually contacting brands on more than one platform. Here are some of the common problems CS teams face:
Under the traditional CS model, there is a common issue that occurs: duplicate tickets get created for the same customer when they reach out on different social platforms. This often leads to having two customer service agents dedicated to the same problem, causing the customer to repeat themselves more than once. It also causes the customer a lot of frustration because they might get two different solutions to their problem, and this gives them a dissatisfactory and disjointed brand experience. With an omnichannel solution, CX organizations can prevent this duplicate ticket creation right away because the customer is at the center of every interaction.
Customer conversation backlog
Agents might be diligently working through conversations, but because the internal processes on the backend are broken or not intuitive, your agents might actually be spending too much time on repetitive tasks that could be automated. This holds up the conversation with the customer or requires the customer to wait a long time for their problem to be solved. In this fast-paced world, customers do not want to wait 3-5 days to see if they’re eligible for a product exchange, refund, or whether their item will be back in stock.
A backlog of conversations is costly for any organization because it holds up not only the customer’s time, but the agent’s time as well. By reducing this agent friction, customers receive faster service and agents are able to focus 100% of their time on complex problems without having to waste resources on low-level, repetitive tasks. This is one of the easiest roadblocks to remove, and will set your agents up for success.
Long Wait Times
In conjunction with the problem above, customers hate long wait times, even when they know their agent is working in the background to help them. Customer service agents might depend on external factors or other departments in order for them to answer their customer’s question knowledgeably. The good news is that technology and automation can help you determine where you can shorten the process, reduce handoffs within the team, and get those response times down so that your customers leave feeling happy.
Lack of Data: What’s Working? What’s Not?
The biggest problem for companies when it comes to reducing customer service agent friction is due to the fact that they do not have the data to see why a customer might be slipping through the cracks. Many companies are going in blind when they’re interacting with their most important asset: their customers. Why leave it up to chance to see whether your customer leaves happy or not? By tracking key data points, you can use that data to improve your process and better prepare your CS team.
Kustomer – The Solution for You
If you’re tired of not having the data to make smart decisions and service customers quickly, Kustomer is your ally. Our omnichannel solution helps relieve customer service agent friction and gets you the data you need to see where you can optimize your internal processes. Our holistic customer view, knowledge base integration and powerful automations, allow customer service agents to focus on the most important issues without having to toggle between systems and tabs.
In this episode of the Customer Service Secrets Podcast, Gabe Larsen is joined by guests Matt Dixon from Tethr and Vikas Bhambri from Kustomer to discuss Matt’s most recent research on over one million customer service phone calls. In this episode, they discover what the research indicates and how leaders can utilize the data to their advantage. Listen to the full episode to learn more.
Adapting in the Biggest Stress Test Ever for CX
Soon after the WHO declared COVID-19 a global pandemic, Matt Dixon and his team of professionals quickly got to work analyzing data from 1,000,000+ customer service calls. This last year has been described as CX’s greatest stress test ever because teams are having to constantly adjust and adapt to the ever changing world. A year in the making, the data is showing what teams are and aren’t doing correctly in this new environment. Something that Matt hopes teams will make note of, is pre-pandemic, about 10% of customer service calls were classified as difficult. Seemingly overnight, the amount of difficult calls jumped to a whopping 20%, overwhelming underprepared CX agents. As history shows, greater difficulty in customer experience interactions leads to greater amounts of negative word of mouth marketing and upset customers. This then leads to more people being unwilling to purchase goods or services from a brand because of high difficulty interactions. To help teams adjust to a new normal and return to work, Matt offers some practical and actionable tips in the episode. He explains that making sense of collected data is key for all teams who want to be successful in the future. “Data is voluminous. It is unbiased. It’s unvarnished. It’s really actionable in the technology that exists today.”
Using Data Proactively Now and for the Future
Data is constantly being discussed in modern CX conversations on a global scale. It seems that more and more companies are turning to using data to gather helpful information about their customers. No longer are the days of QA teams and reps who had to take detailed, tedious notes on every customer interaction to gather data and search for opportunities for improvement. New technologies allow for that data to be automatically collected, scored, and reviewed. Brands would be wise to implement data collection and implementation on a company-wide basis, as it plays a major role in customer success and higher NPS scores across the spectrum. Matt believes that in order for that collected information to be holistically useful, teams have to be proactive about the way they utilize such data – to not only solve immediate issues, but to use it to predict future issues and customer difficulty. Matt explains that data can be used to prepare for “The thing they’re (customers) probably going to call you about in a couple of days or weeks or months. … It’s a very low effort way of thinking about the customer experience.” In addition to this, Matt believes that so many companies spend too much valuable time concentrating on gathering survey responses that would be better spent on analyzing data that is stored within the technology they already have access to. As CX leaders learn more about their technology and how they can use it to collect data, customer satisfaction is sure to skyrocket.
Employee Satisfaction Leads to Brand Loyalty
The topic of employee satisfaction has gained traction in the CX realm. Leaders are starting to recognize the importance of having teams of agents that are happy, rewarded for their efforts, and satisfied with their contributions to the company. The year of customer experience calls that Matt and his team analyzed revealed that big brands are being exposed and their weaknesses are being made public. Their lack of training and agent accountability is contributing to public distrust of these big brands. Vikas uses the example of reps working from home without direct supervision that are telling customers to complain on social media because they don’t have the tools, permission, or training to properly help them. Matt and Vikas believe that it is extremely important to hire the right people, train CX agents correctly, and establish a level of trust with them so that they can work independently and efficiently. “If you haven’t hired the right people and you haven’t helped coach them on the behaviors that’ll lead to success, when you put them in an at-home environment, that becomes really apparent really quickly.” When these agents feel that they are trusted and have the freedom to make crucial decisions on part of the customer, brands are more likely to win. Evidently, customer interactions prove that when the agents are happy, trusted, and feel like their efforts are important to the company, customers are happy and have a greater chance of staying loyal to the brand.
To learn more about 1,000,000+ customer calls and what the data shows, check out the Customer Service Secrets podcast episode below, and be sure to subscribe for new episodes each Thursday.
You can also listen and subscribe to our podcast here:
Full Episode Transcript:
What 1,000,000 Customer Service Calls Tells Us | With Matt Dixon & Vikas Bhambri
Intro Voice: (00:04)
You’re listening to the Customer Service Secrets Podcast by Kustomer.
Gabe Larsen: (00:11)
All right. Welcome everybody to today’s show. We’re excited to get going here. We’re going to be talking about customer service research. What 1 million, it’s more than a million phone calls, tell us what the heck you’re supposed to be doing to be successful in customer service. And to do that, we brought on a couple of special guests. One you know, Vikas Bhambri, and the other is Matt Dixon. Guys, why don’t you take just a minute and introduce yourself? Matt, let’s start with you.
Matt Dixon: (00:37)
Yeah, sure. Gabe, thanks for having me on. Matt Dixon, I am the Head of Product and Research at Tethr, which is an AI machine learning venture out of Austin, Texas. Prior to that, I hailed from CEB where I ran the customer experience and customer service practice for many years there. And I worked on all the research related to effortless experience, customer effort, score, effort reduction, some of which we’ll talk about today, hopefully.
Gabe Larsen: (01:04)
Awesome. Awesome. Vikas, over to you.
Vikas Bhambri: (01:06)
Sure. Happy Friday, everyone. Vikas Bhambri, Head of Sales and CX here at Kustomer. Looking forward to the chat with Matt and Gabe.
Gabe Larsen: (01:14)
And you know myself, Gabe Larsen. I run Growth over here at Kustomer. So Matt, what does it feel like to be a celebrity? I mean, people must come to you. This question, by the way, those of you that –
Matt Dixon: (01:24)
Gabe Larsen: (01:28)
People must come to you and be like, “You changed my life.” I mean you wrote Effortless Experience, you wrote Challenger. I mean, how does it feel to be a celebrity? I’m partially kidding, but those are big books. A lot of people have been impacted by them. So number one, thank you. But in all seriousness, what does that kind of done differently for you in the way you’ve kind of managed your career so far?
Matt Dixon: (01:49)
Well, thank, first, thank you for the kind words. I think they’re, the first thing I’ll say is this. Those books and all that research was a big team effort. So it, it’s a kind of an awkward thing to have your name on a book that you know there were dozens and dozens of people behind, putting that research together. But at the same time it’s been a pretty fun journey. We’re, I think in both sales and customer service, we’re a little bit different from a lot of the other folks out there. I mean, you and I know a lot of the same folks in the sales world. I know you hailed from that world as well prior to your time at Kustomer in the customer experience and customer service world. And I think there’s so many good expert, kind of subject matter experts and thought leaders out there. What I think makes some of this research different is the thing I still try to stick to today is I’ve never run a call center. I’ve never been a Head of Customer Experience. I’ve never been a call center rep. I think I’d be, probably be an awful call center rep. I’ve also never been a salesperson. I’ve never run a sales organization and I’ve not, I have not carried a bag for 20, 30 years like many of the other folks out there writing about sales. I think what makes me different, and some of the folks I worked with on that research, is that we’re researchers. We brought data to the air against some of the big questions people were asking.
Matt Dixon: (03:07)
So Challenger, it was, how do we sell the information to power buyers? And we’ve been taught for so long that it’s all about needs diagnosis and relationships and this kind of thing. Is that actually true? And we found with the Challenger research, a lot of that stuff was built on flawed assumptions, or at least it didn’t stand the test of time and the data currently shows a better way to do things from a sales perspective. In effortless experience, very similar. We’re all taught to believe that more is better. It’s all that delight and wowing and exceeding the customer’s expectations and we shouldn’t do that as companies. We should have a great brand that delights, a killer product that delights, great pricing that delights, a sales experience delights, but when things go wrong, we’ve found that’s not the time to delight. That’s the time to get things back on track and make it easy for the customer. Play good in customer service.
Matt Dixon: (03:52)
And so I think in some ways I like, I don’t know that I put myself up in the Pantheon of like the MythBuster guys from Discovery Channel, but I, and that’s kind of how I think of, my career has been a lot about that. Trying to bring science to bear, to test some of these assumptions that a lot of people have that feels so right. And then we never stopped to question whether or not they’re actually true and there’s a lot that we go and test and we find out it’s actually true, but there’s a lot that we tested we find out it’s actually wrong. And I think exposing that for sales leaders, customer experience leaders, contact center leaders, customer service leaders is really important and really valuable because it helps them proceed with clarity and allocate the resources better.
Gabe Larsen: (04:30)
Yeah. Well, I think that’s one of the things that I’ve appreciated about the methodology in the CX space. It seems like it’s fluffier at times, right? It’s a day on the phone with Zappos for 50 hours to make somebody feel good. There’s just so much kind of feel good stuff, that I remember reading the Effortless Experience and it was the first time I was like, “Oh my goodness, a data driven view into customer experience that I think maybe isn’t the standard.” So I do think it is nice to have some research. That’ll set up our conversation as we jump in. Vikas, I mean, your experience with the Effortless Experience, or it’s got to be one of those books, that’s just, you’ve talked to maybe a hundred thousand people about?
Vikas Bhambri: (05:09)
No, look it’s, Matt and team did a great job. It’s top of mind for a lot of folks right now, right? In terms of just how do you compete effectively? And I think the effortless experience in terms of that experience that you can deliver, not only externally, but internally with your team, and then how do you use data to iterate that experience, right? I think what Matt and team do is they’re looking at it at a macro level, across many customers and many trends. And then, what any operational leader needs to do is then apply it to their business and say, “Look, let me look at the metrics in my data. These are the bars that I want to aspire to. What do I need to do to get there?” And looking at the data within their own tools and tool sets and saying, “Where am I falling short?” So I think it’s that perfect convergence in terms of how do people effectively compete in what’s becoming a very challenging environment, right? New companies popping up in every space, almost on a daily basis.
Gabe Larsen: (06:05)
Yeah. Yeah. Well, let’s get into kind of then, some of the latest research and it may not be the latest latest, because it seems like every time I talk to Matt, he’s got something new on his, on his cuff, but –
Matt Dixon: (06:16)
[Inaudible] Now I feel lazy because I have –
Gabe Larsen: (06:23)
[Inaudible] four weeks old. What the hell?
Matt Dixon: (06:28)
[Inaudible] me lately.
Gabe Larsen: (06:28)
Yeah, that’s right. This isn’t good enough. So maybe kind of give us the backstory on this. Obviously it was COVID related. A lot of phone calls. Fill in the blanks as to why you started it, what it is.
Matt Dixon: (06:39)
Yeah. So we at, just a little bit of background. So at Tethr, we are in the conversational analytics space. I know a lot of the folks on the, listening on that are familiar with that technology. We’re one of the players in that space. And so we work with a lot of big companies around the world. And what was interesting is we take their phone date, phone call data, we take their chat interactions, their email changes, other other data, and we help them make sense of it. And to understand what’s going on in the customer experience, what the reps are doing to the good and to the bad. What the customer’s experience is with their product and their digital channels and so on and so forth. And one of the things we noticed is, with COVID in that, obviously it took the world like in a blink of an eye, just changed a lot of what we do. Think about a call center leader, multiple kind of dynamics at play. On the one hand, all of my reps who used to be sitting together in a contact center that are now all working from home. No access to peers, no access to supervisors, no shoulder to tap to ask for some help, really working on an island. And then you add onto that the fact that customers are now calling about maybe not entirely new issues, but much more acute issues. So think about, for instance, a utility company, we work with a number of utility companies. They’ve always had a certain percentage of customers that call for financial hardship reasons. I’ve lost my job. My spouse has lost their job. I can’t pay my electric bill this month. I need to go on a payment plan [inaudible] will shut my power off. That, we found in one company in our study, the number of financial hardship-related costs increased by 2.5x almost overnight in the span of like a couple of days. The number of people calling in saying, “I can’t pay my bill. I cannot have you turn the power off. And I don’t know when I’m going to be able to pay to pay you guys. So I need to, you got to come up with a plan and it’s got to be a new, creative plan, right? Because I don’t know when I can get back on track financially.” That produced this perfect storm for customer service leaders. So we started hearing from a lot of our customers, “Hey,” like, “let’s get under the hood of what’s going on in these conversations. What’s changed for our reps? What’s changed in the customers, with the customer’s expectations? What are the good reps doing that we need to do more of? What are the reps doing to the bad that we need to do less of, and let’s get our arms around this because this stuff is happening so fast.”
Matt Dixon: (08:57)
And so that’s what we did. We collected. We took a sample of calls. A million calls total from across 20 different companies. And we specifically picked those companies because we thought they represented a broad cross section of the economy. Some industries really effected like travel and leisure, some less so. And so we combined, we created the sample and we went in and we studied it. One of the first things we did was we scored all of the calls for the level of effort. So we had built an algorithm at Tethr, we call it the Tethr Effort Index, think of it like a predictive survey score. So rather than asking your customer at the end of a call to tell you how much effort that call was and for those of you familiar with the Effortless Experience, you know a customer effort score is one of these things that we talk about a book. That relies on a survey, but what we built a Tethr was a machine generated algorithm that could take a recorded phone call and the machine could tell you basically, here’s the score you would have gotten on the survey if the customer had filled it out, but without the high effort experience and the expense of asking the customer to fill out a survey.
Matt Dixon: (09:57)
So the first thing we did was we started collecting calls on March 11. We picked that date because it was the date the WHO declared COVID-19 as a global pandemic. We ran the study for two weeks to get a million calls sample from across 20 different companies. So that was a subset of the total call volume those companies do with us. And we scored those calls and we looked at what the scores were before and what they were after. And we saw a real increase overall in just the difficulty of calls, so the effort level of calls. And for those of you again, who know the research, know that effort corresponds with churn. It corresponds with negative word of mouth. It corresponds with customers unwilling to buy more from you, unwilling to accept the save offer, right? When they get transferred to the retention queue.
Matt Dixon: (10:42)
Specifically, we saw before the pandemic for the average company in our study, it was about 10% of their calls that would have been scored as difficult on our scale. It’s a zero to 10 scale. So we’re looking at the scores in the zero to four range. Those are the bad ones. In the study, so after March 11th, for those companies, that percentage doubled to 20%.
Vikas Bhambri: (11:02)
Matt Dixon: (11:03)
So now, one fifth of their total call volume was in that zone of customers who are likely to get on social media and badmouth you, likely to churn out, not likely to buy anything more. They’re going to go in and tell their neighbors and their friends and their colleagues, “Don’t do business with these guys. It’s a terrible company, they’re treating me,-” and again, a lot of the, it was compounded by the way the reps were handling that. The fact that they’re all working from home and we get into a little bit of that, but it was kind of a staggering overnight change in the dynamic.
Gabe Larsen: (11:31)
Well, and I think that’s obviously, I think we’re all experiencing that. So it’s not too surprising from an interpersonal perspective. I can relate. Obviously taking this call from home at the moment. So if I understand the basis of it though, it did start in March 11th, it went for two weeks. Million plus phone calls, cross segment of the industries, just touch on that real quick. It was, you did try, it was pretty variety. So it wasn’t just hospitality and travel. You felt like you got a pretty good cross section on that.
Matt Dixon: (11:57)
Good cross section. So we, we’ve got in there some consumer products companies, some travel and leisure companies, utilities, financial services, card issuers, telco, and cable. It was a broad cross section. We had a couple of more B2B tilted companies as well. So we felt like we had a pretty good sample that we could say, “It wasn’t all skewed towards travel and leisure.”
Gabe Larsen: (12:18)
I love these different industries. Go ahead, Vikas.
Vikas Bhambri: (12:20)
Let me touch on one thing, which I think is really interesting. I think this is about the data, right? And I think if people aren’t using their contact center or CX data in the best of times, shame on them. But especially now, and I think there’s a real opportunity for companies to do what we call proactive service. And I think a great example of this is if you’re an insurer and you’re seeing that 20% of your volume coming in is around, “Hey, I want a reduction in my premium because I’m not driving my car,” why not use that data? Go out to market like my insurer’s done and say, “Hey, we’re giving you a credit to your account because you haven’t even asked for it, but chances are, you’re not driving. So we’re giving all our,” and look at the positive press and you’re seeing some big insurers now are catching on to this. And people are like, “Wow. My insurer’s thinking about me in this time of need.” And I think using that data, because chances are, they were going to give people individually, those credits anyway. One, you’ve reduced your conversation volume into your contact center because now you’re proactive about it and you’re getting positive press. Any thoughts on that and how people might be using that data creatively?
Matt Dixon: (13:29)
Yeah, no, I mean, I think you’re right. So the, a couple comments, one is, being proactive, I think was one of the things we wrote about in The Effortless Experience. Not just solving this issue, but thinking about the next issue proactively for the customer. The thing they’re probably going to call you about in a couple of days or weeks or months, but you as a company know this, so you can use your data to predict that, and you can fully resolve it for the customer. It’s a very low effort way of thinking about the customer experience. But the other thing in general, I totally agree, Vikas, with what you’re saying. That I see, I’m constantly surprised by how little companies, big companies actually leverage all the found data in their enterprise and how much they obsess about getting more data from like, for instance, post-call surveys.
Matt Dixon: (14:17)
So that to me, I find to be like, it’s just this weird head snapping thing that I don’t understand at all, which is they all obsess about post-call surveys. What do we need to do to get more customers to respond to our survey so that they can tell us how much effort the experience was? And I always think, “Well, you’re recording all your phone calls and your email exchanges, and your chat interactions, your SMS exchange and all this stuff on WhatsApp and Facebook Messenger and social. Like you have enough data already to know what the experience was. Why are you obsessing about your survey response rate?” And it just, it’s so interesting the way, and even when you get down to it, I hate to be pessimistic here, but our data in this view, but I think part of the reason is they get paid on survey response rates and NPS scores and things like that. And so that’s why they obsess about it. It’s not, ultimately, if they really wanted to fix customer experience, there are way better sources of data in the systems they already use so that they can be more proactive, so they can find those effort causes and drivers and do something about it. It’s, that data is voluminous. It is unbiased. It’s unvarnished. It’s really actionable in the technology exists today, you know? Sure. 10 years ago you needed a QA team, kind of with headsets, listening to calls, making notes and surfacing opportunities to get for improvement. But you don’t have to do that today. Machines can do that at tremendous speed and scale and so, but it surprises me why more companies don’t do it.
Vikas Bhambri: (15:38)
Yeah. I mean, the thing is if you send somebody a 15 page survey after an interaction, right, if you’re in the travel industry, for example, right, after I’ve spoken to a customer service professional, it’s like you had good interaction. And I don’t think maybe it’s a, maybe it’s a lack of understanding at the executive level that what kind of data occurs in these conversations, right? If you’re a marketeer and you don’t realize that the best feedback you’re going to get about a promotion or an offer or a competitor, what a competitor’s doing, is in those conversations. If you’re a product person and you don’t realize, “Wow, like my contact center gets real-time feedback on a new feature or a new service that I’m providing,” there’s a lack of understanding there about the richness of the data that resides in the contact center environment.
Matt Dixon: (16:27)
Yeah. I agree. It’s, I think there’s this assumption that it’s the data in so far as leverage, it’s really just valuable for making contexts in our interactions better. So, but we find when we go into those conversations, it’s a gold mine, Vikas, as you’re saying, of the insight around your digital experience. What were all the things the customer was trying to do on your website or your app before they picked up the phone and called that they’re actually telling the rep or complaining about in the conversation and you’ve just recorded it? What are all the things they talk about with respect to your product or your feature or your pricing, or your competitive differentiation, or about the sales rep who oversold them on the product or service to begin with, and now they’re calling in disappointed? So there’s just tons of insight there for all parts of the enterprise, not just for the QA team at the call center.
Vikas Bhambri: (17:11)
Gabe Larsen: (17:12)
No, I love that. So this is one way I think companies are trying to kind of do things differently in this, it’s been called the new normal or the new world we live in, using data in a way maybe they haven’t done. There were some other things that you were alluding to, Matt based on findings you have, and we’ve put a link in the chat for the actual HBR article that you wrote. So if you want to see some of the additional findings but I want to get into some of these takeaways. Where did you kind of go based on then the data that was revealed? Can you maybe start at the top? So we got data, one, and then what’s next?
Matt Dixon: (17:43)
Yeah. So we, so the highest level again, we found a doubling of the predicted effort level of interactions from pre-pandemic to in the pandemic or pre-March 11 to post-March 11th. The other thing we found as we started digging into what was really driving this was, and I think you found that generally speaking at the highest level, this is this higher level of effort in these interactions was sort of born of two different things. And they’re kind of, there’s a little bit of overlap. And on the one hand I mentioned before, customers who are feeling a lot more emotion and anxiety, driven by things like financial hardship, coming in really frustrated because maybe it took them two hours to get through to a rep because now the call center doesn’t have access to the outsource that they used to provide overflow support. The call volume has spiked, and now there’s a longer hold time. So they’re frustrated to begin with. They’re doubly frustrated maybe because they went to a website and what in normal times wasn’t such a big deal, now it was a really big deal because the alternate option going in self-serving failed them. They’re talking to a rep who they feel like is dealing with policies that really haven’t been updated in light of the pandemic. So you might be asking for a bill payment, that utility example I used before, a bill payment extension or a payment plan. And they’re still pushing customers to the policies that existed before the pandemic. And they haven’t really updated us because the company moves really slowly and they just feel like they’re dealing with people who are just throwing out policy and hiding behind policies.
Matt Dixon: (19:11)
That’s kind of on the customer side. Then the agent side, think about it. And you’ve got to be empathetic to the agent situation here, too. Many of these agents who are now working from home, the fact of the matter is that before the pandemic, most of them were working in kind of a factory floor model of a contact center where they were, they sat in a group surrounded by colleagues who they could tap on the shoulder and ask for help. Supervisors they could wave their hand and flag down for assistance or a policy exception in the moment. They were given a script, they were given a checklist. They had access to all the resources they needed. There were kind of like cogs in the machine. What happens when you send all those folks out to their home offices and now they’re left to their own devices?
Matt Dixon: (19:52)
What you find is that in some cases, maybe we didn’t hire people, we didn’t hire the right people. And maybe in some cases we never coached them on the behaviors that could lead to them being successful. We just kind of told them to stick to the script and just follow the rules, follow the checklist. That doesn’t really work in a situation where customers are calling in about high-anxiety, high-emotion issues. And they’re asking reps to make exceptions and make up their minds and decide things on the fly. Then what do you do if there’s no tenured colleague or supervisor you can flag down? You’re sitting in your basement or your living room doing your job. It’s really, really tough. So what that means is agents are shirking responsibility. They’re citing policies. They’re saying, “Hey, I can’t really help you. Maybe you should write a letter to the company. Sometimes that gets their attention. And you know what you might want to do is just bad mouth them on Twitter, because if you do that, they usually jump to it and they can help you out.” You know? And I’m not kidding. There’s a lot of that going on and it, that then compounds the frustration from customers. So beyond that, we started to look at, I think the good news is there are things we found in the research that are, we think tools and ways forward and we’ve talked a little bit about those, but let me pause here and just see if you have any thoughts, Gabe or Vikas, on that piece of it.
Gabe Larsen: (21:03)
Yeah. Any response to that? I mean, definitely a customer side and an employee side. It sounds like.
Vikas Bhambri: (21:08)
No, I look, I think I, Matt, I’ve been saying for weeks as we’ve been doing these is, this is the biggest stress test that the contact center industry has ever gotten. And I think a lot of the fundamentals that were broken at a macro level across the industry, but individually are in for specific brands are being exposed. And I think that lack of training and empowerment is one that is absolutely coming to the forefront because for somebody who’s been walking the floors of contact centers for 20 years, this even today, there’s the culture of the supervisor walking the floor, looking over the shoulder, providing guidance, jumping in and saying, “Hey, let me listen to that call. Let me coach you through it,” and forget the technical limitations. How do you do that? Now when you’ve got, maybe you’re a supervisor of 20 people and now they’re disparate and they’re working from home, forget the, like I said, the technology limitations, how do you actually do that? So I think, like I said, we’re exposing a lot of the flaws and I think, what are some of the changes we’ll see going forward is that ability to empower and really create this into a knowledge worker role, right? Because as self-service takes care of the low level simple questions, you’re going to see, I think you’re going to see this in the contact center regardless of the work from home environment, but you’re really going to need people who can handle those difficult questions.
Matt Dixon: (22:36)
Yeah. We actually, there’s another one, I don’t know if, Gabe you throw this up on the, with the other article, but there’s an article we wrote in 2018 about T-Mobile’s journey toward a different in kind of knowledge work environment for their contact center, where they basically told their reps, “You guys are now small business owners and we are, our job as leaders is to figure out what’s getting in your way of delivering the right customer experience. Is it a policy? Is it that you don’t have the right tools? You don’t have the right, you’re not on the right platforms that the connection speeds too slow? What is the thing that’s getting in your way? But you tell us what you need. We’ll clear the road for you. Your job is to own the customer experience and come up with creative solutions, but use your own judgment.”
Matt Dixon: (23:15)
A lot of that really increases the importance of hiring great people, coaching them in a really effective way, giving them great manager support and putting them in a climate that really rewards people for using their own judgment; doesn’t just tell them to stick to the script. So that article was called Reinventing Customer Service and I encourage everyone to read that because it picks up on this story that Vikas is talking about. When the easy stuff goes away, by definition, what’s left is the more complicated stuff that the live rep is handling. And you need to have really good people who can exercise their own judgment, and that’s even more important. And what becomes apparent is when, if you haven’t hired the right people and you haven’t helped coach them on the behaviors that’ll lead to success, when you put them in an at-home environment, that becomes really apparent really quickly.
Matt Dixon: (24:01)
And so it really, this is, I think there are two trends that’ll be kind of shot through a tunnel of time with COVID. I think one is digital and specifically omni-channel capabilities. The ability for companies to seamlessly switch, obviously work that you guys do at Kustomer, to switch from one channel to the next. I think the ability, the effectiveness of asynchronous messaging in particular, chat effectiveness, SMS effectiveness, customers used to use that stuff for simple binary interactions. Now, when they’re looking at a two hour, wait time in the phone to queue, they’re going to go try that chat channel first, right? And see how far they can get. What that’s doing is it’s forcing chat to grow up really fast and forcing our chat bots to get really smart really quickly. I think the other trend that will be shot through a tunnel of time is agent empowerment and hiring great people, putting them in a climate of judgment where they can leverage the expertise of their peers, but more importantly, where they’re trusted to do what they know is right, because we trust that we hired great people and we showed them, here are the boundaries in the sandbox we can’t go across for regulatory reasons or legal reasons, but within that, use your judgment. Do what you think is right for the customer. We’re not going to script you. We’re not going to checklist you. And it turns out putting customer reps in those environments means they deliver actually better outcomes, more customer-centric outcomes, and they deliver better results for their companies, higher NPS scores, lower churn, higher cross-sell and up-sell. And that’s exactly what T-Mobile saw in their experience.
Vikas Bhambri: (25:27)
Yeah, and if I can just touch on what Matt said about that omni-channel experience. It’s really delivering that same experience, regardless of channel. I talked to a lot of customer service leaders that complain you gave the example of people going to Twitter to complain. And I didn’t know agents were actually coaching them to do that. I can see why. And it was really interesting. I remember a few years ago, I did some work with an airline where I met their social team, the Twitter team, and they were like, they walked into the room, like really like a group of alphas. They were talking about how they had a separate set of policies that they were able to do than the core contact center, because they were like, “When people complain on social, we have the ability to offer them refunds and things that the core team isn’t.” I was sitting there laughing. I’m like, “This is not a good thing. You’re basically training people to go to social media, to amplify their voice so that they get better customer service.” And I’m like, “That is a fail because what you’re doing then is you’re training them to go to these places.” And so for me, omni-channel experience, it’s not just about delivering the channels, but you should have a uniform experience regardless of which channel that customers coming to you with. So I thought that just, when you mentioned Twitter and agents guiding customers to that just triggered that airline story.
Gabe Larsen: (26:44)
Matt Dixon: (26:45)
Because they say, “Well, look. Actually the alpha team is on that group. I know several companies, big name companies that put their best reps, you graduate into the social team. When you reach the highest level of agent status, that’s where you go, like, that’s the destination job. There are no rules or no policies do whatever you want. And what they’re doing is teaching their customers that the way you get the best service from this company is by publicly complaining about it.
Gabe Larsen: (27:08)
Matt Dixon: (27:08)
And it’s just like –
Gabe Larsen: (27:11)
Yeah. It’s funny that that’s what, that’s the world we’re in though, you guys. Our time is unfortunately come to an end, such a fun talk track, always more to discuss. We did leave the link to the HBR so you can dive in a couple more of the findings and the research. Matt, it’s always great to have you. Vikas, thanks for joining. For the audience, have a fantastic day.
Matt Dixon: (27:29)
Vikas Bhambri: (27:29)
Matt Dixon: (27:29)
Take care guys, bye.
Exit Voice: (27:38)
Thank you for listening. Make sure you’re subscribed to hear more Customer Service Secrets.
In this episode of the Customer Service Secrets Podcast, Gabe Larsen is joined by Sami Nuwar to discuss how to successfully attain operational excellence in the CX realm. Sami has a diverse background as a customer experience and operational excellence practitioner. Listen to the podcast below to discover how Sami has become an expert at helping CX leaders reach excellence.
Utilizing Data for Operational Excellence
Senior Principal Experience Consultant at Medallia, Sami Nuwar, helps his team understand and interpret customer data through new technology. In his experience, Sami defines operational excellence as, “The thing that primarily distinguishes customer experience management, the discipline of CX, from traditional market research.” In instances where CX teams lack in this excellence category, Sami suggests that this is due to a lack of data gathering, interpretation, and action. Oftentimes when data is collected at firms, it is ignored and those within the company forget to ask questions regarding that data. It is impossible for effective changes to take place when no questions are being asked about interpreting the data. “Every organization is all about execute, execute, execute, and what we also need to do is have the habit of taking a step back. Let’s pause, let’s breathe and let’s have a retrospective view on things.” Once that data is collected, it needs to be placed into the hands of those who can utilize that data beneficially. To do so, Sami suggests translating data in a way with monetary value, as dollar signs attract key eyes.
Becoming Operationally Sound
Sami understands that converting a CX team to becoming completely operationally sound can be difficult and overwhelming at first. To help clear any confusion, Sami suggests that the main goal is turning data into information that can be used to the benefit of the company. Becoming operationally sound is initially rooted in understanding the company’s vision and the steps necessary to see that vision to fruition. When a vision is set and understood by the team, it allows space for empathetic conversations to take place. Additionally, listening to and empathizing with those in the company can help employers to gain a better understanding of the daily operations. “Whether it’s for-profit, not-for-profit, whatever, talk to the people in that business or in that environment and understand what it’s like to be in their shoes and empathize with them,” Sami elaborates. The last part of becoming operationally sound is to find balance within the organization and to translate data in a way that is relevant.
Advertising Successful Changes
One of the most important elements to operational excellence is often overlooked in Sami’s eyes, which is advertising the successful changes implemented by a department. When successful changes are implemented within the organization, Sami says that it is of the utmost importance to “sell your changes” to others within the firm. He goes on to explain that at first a lot of people won’t be onboard with new changes however, when successes are advertised within the company, people tend to hop onboard and support such changes. “It’s also incumbent upon us to tell people about the change, because if you don’t, then no one’s going to know about it other than you and maybe that other person in that other department. So you’ve got to advertise, you’ve got to promote.”
To learn more about achieving operational excellence, check out the Customer Service Secrets podcast episode below, and be sure to subscribe for new episodes each Tuesday and Thursday.
You can also listen and subscribe to our podcast here:
Full Episode Transcript:
Operational Excellence | Sami Nuwar
Intro Voice: (00:04)
You’re listening to the Customer Service Secrets Podcast by Kustomer.
Gabe Larsen: (00:11)
All right. Welcome everybody. Today, we’re going to be talking about operational excellence. This is an important one. We’ve asked about this. You’ve asked about this. So we wanted to bring on an expert in this topic. It’s Sami Nuwar. He’s currently the Senior Principal Experience Consultant at Medallia. Sami, thanks for joining and how are you?
Sami Nuwar: (00:29)
Yeah, I’m fantastic. Thanks for having me.
Gabe Larsen: (00:31)
Yeah, I think this will be a fun one, man. Tell us, before we dive in just a little bit about yourself and your background.
Sami Nuwar: (00:37)
Yeah. I’ve spent 16 years at Verizon Business as a Practitioner of Customer Experience Management. I’m traditionally a researcher. That’s where I kind of got my start and then I evolved into an Operational Excellence Practitioner and then evolved again into a Customer Experience Practitioner. Spent 16 years at Verizon and then a few years at a small manufacturing company. After that, and then joined Medallia around this time last year actually.
Gabe Larsen: (01:07)
I love it. I love it. And for those of us who don’t know a lot about Medallia, give us kind of the 30 second on Medallia.
Sami Nuwar: (01:13)
Yeah. It’s a customer experience management platform. It’s primarily technology that helps you manage the experience, understand that experience, and enables you to do much bigger things. So it’s a technology and a platform, but we like to talk about CX beyond the platform. The technology just makes it easier to do it and democratizes it and now it makes our jobs as people, much easier to spread the love and let other people jump in and help out.
Gabe Larsen: (01:47)
I love it. I love it. I do think Medallia, I mean, you guys have certainly made a name for yourself, so kudos. A lot of people use that technology, I think to deliver some good customer, great customer experiences. Well, let’s dive into this idea of operational excellence and maybe you can just say a big picture. Why is operational excellence so important?
Sami Nuwar: (02:08)
Yeah, I believe that operational excellence and other variants of the term, continuous improvement, to me, it’s the rubber meets the road. It’s where the action should take place for the business or the environment to get better. And it’s the thing that primarily distinguishes customer experience management, the discipline of CX, from traditional market research.
Gabe Larsen: (02:41)
Yeah. Why do you feel like people get lackadaisical on operational excellence? And then I want to get into a little bit, kind of the how here in a second, but is it just because it’s difficult to do? Is it devil’s in the details? But why do you think people don’t get as operationally minded or sound as they should?
Sami Nuwar: (02:59)
Yeah, I think in some cases there’s an assumption that someone is acting on the data that has been collected. That was certainly the case of Verizon for a long time. There was an assumption that people are doing something with it and no one is asking the questions. So how do you know that the, like what improvements have been made and how do you know those improvements are working? So those questions don’t tend to be asked. Those are the details that people tend to overlook. We’re so execution focused, every company is, every organization is all about execute, execute, execute, and what we also need to do is have the habit of taking a step back. Let’s pause, let’s breathe and let’s have a retrospective view on things and ask those questions. Is it working? How do we know it’s working? What else do we need to do and who else do we need to get the help from?
Gabe Larsen: (03:58)
I love that. I love that. Well, let’s dive in a little bit. I mean, you’ve obviously had some experience trying to get operationally sound and tight, et cetera. How do you start to think about doing that? Where do you begin this journey to become more, just operationally tight?
Sami Nuwar: (04:12)
Yeah, I think to build that habit, you have to have a clear understanding of what your current state is and at least get an idea, have a vision of where you want to be. And if you don’t have that vision, then at least at a minimum, understand where your current state is and that’ll help you form your vision. So that’s step number one. You’ve got to knock that out. You’ve got to collect the data to gain that understanding and you have to have the conversations with the people inside your business. Whether it’s for-profit, not-for-profit, whatever, talk to the people in that business or in that environment and understand what it’s like to be in their shoes and empathize with them. So, and at the same time balance that understanding with talking with customers and partners and external parties to understand what it’s like to be them too. And so collect all that data so that it becomes relevant for you and then it turns data into information that can be used.
Gabe Larsen: (05:15)
Do you feel like on that kind of understanding your current state, is there different methodologies, tools, best practices you’ve found to actually capture that? Is it mostly interviews? I mean, you kind of mentioned that, is that the way to best do that? Or how do you go about getting that?
Sami Nuwar: (05:33)
Yeah. The mode of collecting, it really depends on what you’re trying to achieve and your timeframe. You know, there’s a need to balance. You have to balance the need for relevant information and the timeframe that you’re working within. And in a lot of cases, especially in a business environment, you don’t have all day, you definitely don’t have all year. And so you’ve got the budget, the data collection need and the need for significance and relevancy with the need for time, and time costs money. So, find that balance that works for you and then choose the mode that works for you as well. So for me, what’s worked is a combination of quantitative techniques and qualitative techniques. Surveys are a great way to manage that balance of data relevancy and time because you can get a massive amount of information quantitatively by doing simple surveys. But that typically isn’t enough because surveys just gives you an indication of what the problem is. And maybe some indication of how big the problem is, which you also need to get is the why. And that really comes from qualitative information. So interviews, video is the new up and coming technology that people tend to use a lot of these days. We have a technology called LivingLens, which is really cool. It lets people submit video feedback or audio feedback and then it gets analyzed behind the scenes by the system. So those are all qualitative techniques –
Gabe Larsen: (07:14)
All different ways you can kind of capture it. Got it. Interesting. Once you get this data, you and I chatted a little bit about this before, but I thought it was such a great point. It’s, not all data is good, not all data is the same value. Some data is, I mean, the world is now capturing so much data, we’re having a hard time making sense of the data, getting the validity. How do you kind of walk through or make sure that you’re not being misled when it comes to some of this data you’re capturing?
Sami Nuwar: (07:41)
Yeah, that’s a key point. I mean, one of the other signals that, I mean, I mentioned techniques to collect data from people quantitatively and qualitatively, but the other, and I think overlooked channel for data, is the internal knowledge base within the business, the operational data. We all have systems and machines that capture data from our interactions with customers and our daily business. And that is typically a treasure trove of information and what, it’s difficult to gather because it’s typically incomplete or hasn’t been cleansed enough to be relevant. And so it’s in a state that’s pretty rough. But if we can take that data and test it to make sure that it’s relevant and then marry it with the feedback that you could get from talking with customers and whatever message you choose, then it becomes, it turns that data into information because you’ve added context. The experience feedback that you’re getting on top of the operational data that you’re already collecting and probably under-utilizing, marry the two pieces together and they become relevant pieces of information. But at the end of the day, the first thing you got to do is, whether you’re collecting data from customers or collecting data from internal systems, you’ve got to test its validity. If you fail to test the validity of that data and you make decisions based on the data without verifying that it’s true, you’re risking making bad decisions in setting the wrong course for your business.
Gabe Larsen: (09:22)
I love that. What are some of the data points you’ve found to be most important operationally speaking that you know you’d say, look to the audience, “Guys, these are probably some data points that if you really want to get operationally sound, a couple pieces of feedback would maybe be this metric, that metric.” Anything come to mind on that?
Sami Nuwar: (09:39)
Yeah. I mean, just going back to my telecom roots and this is actually, the example I’ll give you is pretty agnostic. It’s a telecom, it’s a problem, it’s always going to be there, it’s always been there, but it’s pretty much a universal problem regardless of industry and it’s one of time, right? We can never be fast enough. And anybody who’s ever subscribed to a cable, TV, or internet service or a phone service, any kind of service that requires some provisioning or some monkeying, some wrench turning behind the scenes to be done, there’s always an expectation of time of when it’s going to be done, right? When can I expect the technician to arrive? When could I expect some work to be done by you that you’ve promised me?
Sami Nuwar: (10:32)
And a metric that is typical in the telecom space is customer desire due date. That’s an internal, very nuts and bolts metric that is based, it’s based on a time expectation, right? The clock starts ticking and then the clock stops ticking at a certain point and an image of the difference between that, and that’s a metric that’s kept internal, and that’s how they measure their performance among their teams. And the analogous time metric from a customer’s point of view and in a question that you would typically ask them in a survey, for example is, “Did this thing occur within your expected amount of time? Yes or no?” And if not then here’s the follow up question, right? And then they tell you what it is. And so when the customer responds to a survey, they’re giving you their perception of how long it took something to get done.
Sami Nuwar: (11:28)
And so what’s incumbent upon us is to take the two pieces of information, their perceived experience coupled with what the business believes happened, and now we look for matches or mismatches in the data. And what I found at Verizon were huge mismatches. And typically that’s because of the measurement time post, right? So the moment in which we would start the clock and then stop the clock and measure that time was not the same moment in the customer’s mind, right? So they’re a customer, the clock starts ticking at the moment of the handshake and then in the telecom company’s perspective, the clock doesn’t start ticking until you sign that contract and that could be a difference of a few days or a couple of weeks.
Gabe Larsen: (12:21)
That’s so powerful. I love that. I just think those are the types of insights I think leaders need to figure out. It’s the tactical advice that really kind of moves them from one place to the other. Last question then is, once you found this and you got the currency, you found the data, then you got to kind of move into the next phase, the change, right? Where do you go from here and kind of, how do you wrap up?
Sami Nuwar: (12:42)
Yeah, you have got to get that data or that information into the hands of the people that you know are going to drive that change and that’s really where the continuous improvement people, the people that are the lean practitioners, the six sigma practitioners, or the people that are purposed, are driving some sort of operational process improvement in the business. We’ve got to get that into the hands of those people and it’s got to be specific enough that tells them what the nature of the problem is, how big that problem is and who’s impacted by it. Ideally dollar signs, if you can attach some sort of financial component to the problem that really gets people’s attention and makes them act on it. And then hopefully they take some sort of action, but it’s incumbent upon us to make sure either to help them take that action or to ensure that they take that action and hold them accountable to it. And lastly, once the action has been taken, right, and you can see the notice in the change and you’re measuring that change, or you’re tracking it over time because that’s part of what we do, it’s also incumbent upon us to tell people about the change, because if you don’t, then no one’s going to know about it other than you and maybe that other person in that other department. So you’ve got to advertise, you’ve got to promote.
Gabe Larsen: (14:00)
I love that. I love that. Sami, that’s such great advice. And I love kind of the tactical-ness of it. As you, as we kind of wrap here, any quick advice that you’d leave behind for the audience as they try to get operationally excellent in their different support experience teams?
Sami Nuwar: (14:15)
Yeah. I would say that last part that I just mentioned is probably the most important part. We talked about collecting signals and collating it in a way that people can comprehend and then holding them accountable to some sort of action, but at the end of the day, you’ve got to tell people about the change. And I consider that the most important component that’s often overlooked. But if it’s done right, what will happen is it’ll create a reinforcing loop. But people that did not jump into your bandwagon initially, because there’s always somebody who’s not going to jump on board, they eventually do jump onboard later down the line because they see their peers performing because you’ve advertised. You’ve shown that this discipline works and here’s the changes that’s come from it. And those dissenters initially, they didn’t jump on board will eventually jump on board and everybody will sing to the same sheet of music.
Gabe Larsen: (15:07)
I love it. I love it. You got to find those insights. The insights and then the sale. You don’t get it out there, nobody knows about it, it obviously doesn’t, you can’t end up changing anything. Well Sami, we really appreciate you jumping on. It’s fun to have a little more of a true practitioner. Sami is an operational kind of ninja, so it’s fun to hear how you’ve experienced some of that both in your current life and then in your previous life. If someone wants to get ahold of you or learn a little bit more about Medallia, what’s the best way to do that, Sami?
Sami Nuwar: (15:33)
Oh, you can send me a LinkedIn request. I’m on LinkedIn, pretty active on there. So I’ll be happy to connect with you guys and help out wherever I can.
Gabe Larsen: (15:43)
Awesome. Awesome. Well again, hey, really appreciate your time and for the audience, have a fantastic day.
Sami Nuwar: (15:48)
Great. Thanks for having me.
Exit Voice: (15:54)
Thank you for listening. Make sure you’re subscribed to hear more Customer Service Secrets.
Data. The buzzword we can’t escape. The subject of many a podcast, workshop, TEDTalk — you get it. By now, most organizations understand the impact of acquiring, analyzing, and modeling data to drive business decisions. And while many like to wax poetic about how data is changing the world of customer service forever, there’s not much talk about actionable ways to architect or use your data. The phrase “data modeling” might feel like PhD material, but it really just refers to a process for using data to help you predict business performance (even if you’re just working from pivot tables in a Google Sheet).
When you want to use data to address a business challenge, it’s important to ensure that you fully understand the problem at hand. This concept might feel like a no-brainer, but I often find that companies don’t spend enough time trying to understand the issue. As a CX Director or team lead, you may feel like you have a solid grasp on the problem, but that problem may be understood differently by your agents — or even your customers! Lean into this step to fully understand all facets of the issue as you begin to sort through existing data and identify gaps in the data that need to be filled.
As a Customer Success Manager at Kustomer, I have the privilege of seeing firsthand how companies big and small are integrating data-centric strategies into their operations. Below are some of the most recent use cases that inspire me.
Using Data To Understand International vs. Domestic Performance
One of my clients wanted to explore how their business performed internationally, and how that performance compared to their work in the United States. They have always gathered contact reasons for each of their conversations. They also possessed the country info for each of their customers (primarily gathered through their shipping addresses). Segmenting customers into international vs domestic audiences — and breaking down the count of unique contact reasons within these segments — yielded interesting conclusions for their CX team. It’s probably not a huge surprise that “where is my order” topped the list of contact reasons for each segment, but there was a clear divergence in the data after that. Their team was able to dive deeper into these reasons to build a more tailored content strategy for their international customers and improve international sentiment.
Using Data To Understand Which Products Are Most Likely To Be Damaged During Shipping
Another client wanted to examine which of their products were most likely to be reported as damaged in transit to the customer. While they collected whether a customer reported a damaged item through the conversation’s contact reason, they did not collect the product SKU that was associated with each of those “damaged” contact reasons. The business began training their agents to fill out SKUs for specific contact reasons, and they reinforced that training by building logic into the Kustomer Platform that required the SKU to be provided when the “damaged” contact reason was selected for a conversation. As they’ve begun collecting this data, they’ve been able to determine which of their specific products are damaged at higher rates, and adjust their shipping and packing strategies to better protect those items. Not only does this work increase sentiment and trust for their customers, but it also helps the business to save money spent on replacements and refunds.
Using Data To Understand How Sales Team Consults Contribute To Revenue
One of my clients has a sales team that helps customers navigate the company’s inventory and acts as consultants through the buying process. However, that sales team is not involved in every experience — they’re simply present if the customer wants or needs their expertise. My client wanted to understand how these consults were contributing to the company’s revenue; what was the ROI for these consults? In order to get this insight, the company began to automatically tag customers as “sales influenced” for 24 hours after a consult was completed with their sales staff. If that customer places an order in that 24-hour window, then the sale is attributed to the sales team’s efforts. This process allows the business to better understand how effective these consults are, and whether to update the process or continue forward.
Interested in learning how the Kustomer Platform can uncover more data-driven insights for your business? Schedule a demo here.
In this episode of the Customer Service Secrets Podcast, Gabe Larsen is joined by Steven Maskell, Vice President of Customer Experience at Zones, to discuss how to create a personalized, data-driven customer experience. Learn how Steven does so by listening to the podcast below.
Creating a Data-Driven Customer Experience
Steven Maskell has successfully led service teams for nearly 30 years. Throughout his time in the CX industry, he has figured out how to integrate data into providing the most excellent customer service possible. He says, “I see the people have a very high expectation and a short fuse. And so what that means is that they will give you the data or they accept that you’re going to take the data, but by golly, you had better make it worthwhile.” In discussing tips in which data can be attained, Steven mentions knowing your customer, who they are, what they’re doing, and how they interact with the brand have all proven to be greatly effective when building brand loyalty and curating to the customer persona.
Data can also be used as a helpful tool when advertising to the customer. Customer data shows shopping interests and purchases. Based on this, the company can decide how to advertise to the customer in the most effective way. Rather than advertising the product a customer has already purchased, a brand could advertise a warranty on that product, ideas for how to use that product, etc. Proactively using data to shape the customer experience can ultimately lead to brand loyalty.
Starting Small Makes a Big Impact
The next step to personalizing the customer experience after finding the data is figuring out an infrastructure to store that data and to organize it to be more useful. Steven knows that it can be overwhelming and difficult for companies to change their current methodologies to becoming more data driven. He mentions, “I wouldn’t say start an Excel spreadsheet, but start somewhere small where you can just get the literal basics structured. There’s great relational databases out there. There are some really good tools out there. As I mentioned, there’s off the shelf sort of relationship management products that are out there.” The easiest way to implement this change is to start small and to invest into the basic essentials of data storage and framework. Starting small to get the basics structured into a system is highly recommended by Steven to allow for more structural growth as new data is added. Once the company figures out what they really want to gain from each customer interaction, they will be better able to configure their databases to become more data driven for a more personalized experience.
Integration of AI into CX Operations
Artificial intelligence has become somewhat of a controversial topic in the CX realm. Becoming more normalized, AI can be found in a lot of customer service organizations as an implemented aspect of daily customer interaction. On this topic, Steven notes:
You’ve got to be very flexible in my opinion about how you react to the data and what you have and really what you’re trying to achieve. So… have very realistic expectations. Please don’t think you’re going to double the company’s revenue because you’ve done AI implementations or some nonsense like that. But please know that you can have a significant impact on it.
AI, while certainly helpful, is not without flaws. At its current state of development, AI is not a perfect system, nor is it a valid replacement for human intelligence. AI can be helpful in guiding customers to finding answers to their simple questions, similarly to questions answered on FAQ pages. However, nothing can replace the genuine human connection between a customer and a CX agent. It’s this connection that ultimately builds a sense of trust between the customer and the brand.
Steven urges CX leaders to take an honest look at themselves and to reevaluate how they amplify their brand and its products. He believes that in doing so, leaders will produce better CX outcomes.
To learn more about the secrets to personalizing the customer experience, check out the Customer Service Secrets podcast episode below, and be sure to subscribe for new episodes each Thursday.
You can also listen and subscribe to our podcast here:
Full Episode Transcript:
Using Data to Personalize the Customer Experience | Steven Maskell
Intro Voice: (00:04)
You’re listening to the Customer Service Secrets Podcast by Kustomer.
Gabe Larsen: (00:11)
Welcome everybody. We’re excited to get going today. We’re going to be talking about how you can take the customer experience, personalize it, all using data to do that. And got a special guest, Steven Maskell. He’s joining us as the Vice President Customer Experience from Zone. Steven, thanks for joining. How the heck are ya?
Steven Maskell: (00:32)
Absolutely wonderful to be here. Happy days to everyone so it’s a joy to be here.
Gabe Larsen: (00:37)
We just got Steven before he’s going on vacation so I appreciate him jumping on and doing it quick before he jumps on the week long vacation. Before we jump in Steven, can you tell us a little bit about yourself, maybe your background? Give us that quick overview.
Steven Maskell: (00:53)
Background is that I’ve been in the customer experience space for about 25 to 30 years and have spent a lot of time both on the research side, on the consulting side, and now on the implementation side. So I’ve spent my career both learning what customers want and then helping other organizations better understand how to deliver on that. Then actually being a consultant and helping organizations implement that. And now as the Vice President of Customer Experience, I am on the complete opposite end of the spectrum. Designing, building, implementing and measuring against KPIs.
Gabe Larsen: (01:27)
Yeah, such a fun background. I think it’ll be a fun talk track today. So let’s dive in, big picture as you think about this. Personalization is obviously an important word that people are using a lot more. Data is something that I think people want to use more. AI is a buzz word that people haven’t figured out. How do you start this journey? How do you start to think about using data to personalize? Because I think we all want it, but we don’t know how to do it.
Steven Maskell: (01:54)
Yeah. It’s a great place to actually start this conversation. Here’s the thing about personalization and about customer experiences as a data-driven methodology or practice, you have to, first of all, have the data. You have to know who that person is. You have to be capturing the data. You need to be in a place that they want to give you their data because there’s value in giving it to them, by giving it to you. So, where do you all start with it is what do you know about your customer? Are you able to actually see how they are interacting with you or is it anonymized? Are they sharing with you information that’s important that you can use? We can talk a lot about that in a little bit, but all of us are doing our level best to understand how to really drive a customer experience and make their lives a whole lot easier. And customers are doing their level best to say, “I don’t want you to know too much about me.” So it’s balancing that and making sure that they understand what they’re giving up and what they’re getting, but then you also have to have a robust set of data so that you don’t recommend the completely wrong product service, a path to someone just because you’re trying to put them in a persona that doesn’t make any sense.
Gabe Larsen: (03:05)
But this collision, right? Where do you typically stand? Do you feel like people are more open to give you more data nowadays, or you feel like you’re seeing kind of this tightening up where people are saying, “I don’t even care if you give me value, I don’t want to get the data to you?” What’s the trend you’re kind of seeing there?
Steven Maskell: (03:25)
I see the people have a very high expectation and a short fuse. And so what that means is that they will give you the data or they accept that you’re going to take the data, but by golly, you had better make it worthwhile.
Gabe Larsen: (03:42)
I love that.
Steven Maskell: (03:42)
If you go on a website, you do something and then you start seeing an advertisement for the item that you were looking for. Yeah, I kind of expect that. But then you show that to me six months later, no. I’ve moved on. You look really, really ridiculous. Or the next step on that will be, let’s say there’s a product that you purchased and really, stop advertising it. Start telling me what a warranty is or how to use it, or really taking it to the next step. You’re using my data, make it worthwhile. Inspire me. I bought something, now give me a recipe to make with this unusual ingredient that I might’ve purchased off of an obscure website. So people have a short fuse and then if you don’t do it right once, they can be bothered with you. You’ve lost credibility pretty quickly.
Gabe Larsen: (04:33)
Isn’t that true? I can’t argue that point. And maybe I’m acting the same way. I just, short view’s a good way to say it. It’s like people don’t, we just don’t tolerate. It’s that effort word? I just don’t deal with high effort anymore. You’ve got one chance and if it was hard, I’ll go to somewhere else. I don’t care if you’re a big brand name like Nike, I’ll go somewhere else to get my shoes. When you look at the different data sources and trying to create a customer experience that does matter, are there certain things you feel like they’re either the basics or they’re the must haves? It’s kind of like, look, if you’re going to start to take advantage of that one opportunity, that short fuse, it’s this or that type of data to really start to build that personalized experience.
Steven Maskell: (05:21)
Yeah. There’s a lot that goes into it and they fall into, I would start with two large buckets. Bucket number one is who is the person? And bucket number two is what are they doing? What’s the intersectionality of those two things? So is this person a procurement person? Are they a legal professional? Where do they sit within their profession? Where do they, who are they overall? We’re not talking about highly granular, but if you have a procurement person they’re looking for X. Generally, they’re looking to get the best deal and the best whatever. If they might be a lawyer, they might have something specific, a highly unique need that they want. So now you have an understanding of who they are a little bit about what their drivers are. The second would be then, what are they actually doing? How are they actually purchasing things? How are they actually interacting with your brand? Are they looking at your advertising? Are they responding to your blog posts? Are they actually making purchases? Are they open to conversations? What are their actual behaviors so that you can start building a good understanding of who they are? So you also want to keep testing your hypothesis. This person is A, and so this is what’s important. Their data suggests that that’s what they’re going down. That then would drive you as a deliverer of consumer or customer experience to follow that path. But the second you start seeing them doing something different, now’s the time that you have to pivot. You have to understand what’s going on. And so the two areas where I would say the best understanding is, is frame it around, who are they? And then what are they doing? And then how are they influencing each other?
Gabe Larsen: (07:01)
Yeah, I think those are great big buckets that you can kind of build around. I think as soon as you start talking about data though, the word technology kind of comes into play and you start to think about, “Okay, that makes sense.” Behavior, who they are. I don’t know how to store that stuff. I don’t know where to store it, or it’s stored in so many disparate systems that I don’t think I can bring it together to make a difference. I don’t necessarily want you to be, sell some technology with this question but, quick thoughts on building that infrastructure to actually do something with it or capture it from a technology standpoint? Because it seems like once you know what data to get then you’re going to say, “Well, how do I get it? Where do I store it?”
Steven Maskell: (07:48)
Let’s just take a deep breath on that one, because there’s so much that happens. There’s some great off the shelf products. There are bespoke products. There’s custom work that people do. The thing that is most intimidating is there’s just so much data. And it comes down to a point of taking a deep breath, in my opinion, and saying, “What do I really want to drive with this? There’s so much that I can and so many interactions.” Well, there’s these silly things like, how do you eat an elephant? One bite at a time. You boil it, you can’t boil there. So we all have these things. The exact same thing applies. You know, I wouldn’t say start an Excel spreadsheet, but start somewhere small where you can just get the literal basics structured. There’s great relational databases out there. There are some really good tools out there. As I mentioned, there’s off the shelf sort of relationship management products that are out there. But once you start actually figuring out what it is that you want to learn about, someone build that and feed it and keep it going. Then something will come along where you want to add a new entity or a new attribute, or something that’s a little bit different that’s associated about that person. Grow with them and only them, don’t try and build this behemoth of, “I want to know everything about everyone and everything.” You’re never going to succeed. Rather, just get the basics. Who are my top customers? Why are they my top customers? What do my top customers look like? What do my top customers buy? What do my top customers not buy? That’s enough. That really is enough because now you can start saying, “Okay, these seem to be my large product central services. Now I can look at my other customers that look like my top customers, maybe from two years ago, are these the same things that I should be sending to them? Should I be nurturing them in the exact same way?” Let me tell you something, that’s more than enough.
Gabe Larsen: (09:38)
Yeah. Yeah. I really appreciate the crawl, walk, run strategy. I’ve often referred to it as it does get overwhelming fast and narrow it down to some of those key points and to start to manually capture. I’ve always found if I can build it and get it in an Excel spreadsheet first, or you’d mentioned that, that’s just, I got it. I’ve kind of felt it. I’ve tasted it. I’ve touched it and may only be three data points then it’s like, “Okay, how do we automate this?” And then pretty soon I’m moving on to kind of phase two. I think that’s really important. So you kind of frame that, but I’m curious as people go down this journey, what are some of the other gotchas? We know it intuitively the data, we need it. Personalization, do it. We’re not, a lot of us aren’t doing it very successfully. Is there a couple of gotchas that, and maybe one of them is, it’s that crawl, walk, run, you don’t try to boil the ocean to start with the day. Anything else you’re seeing where people are kind of stumbling on this journey?
Steven Maskell: (10:36)
That’s like a two year podcast to have conversations around that. And I’ll just hold –
Gabe Larsen: (10:43)
Of course you’re going on a vacation tomorrow, so we don’t have to –
Steven Maskell: (10:47)
Yeah. Look, there’s so much that the people botch. I think some of the things are expectations and it’s having very realistic expectations. We hear a lot of mumbo-jumbo around machine learning and AI and all these sorts of things. And it took IBM a really long time to build Watson and Watson still screws up. And what I would say is this, don’t expect that it’s going to solve everything. Really what it’s going to do is it’s going to help you understand a little bit better, a little bit better. That’s what you’re trying to do each and every time. There’s also going to be some gotchas especially in a B2B sort of environment where the user or the person you’re trying to interact with is anonymized. And so you then have to switch your mindset around, “Okay. I was trying to do a one-on-one between me and you, Mary the buyer, or Jane the seller, but now it’s just a buyer. And how do I understand that?” That’s a bit of like, “Oh wow, I can’t succeed.” Actually, you really can. You’ve got to understand that someone’s making a purchase, and you have to switch your mindset. You’ve got to be very flexible in my opinion about how you react to the data and what you have and really what you’re trying to achieve. So the gotchas would be, have very realistic expectations. Please don’t think you’re going to double the company’s revenue because you’ve done AI implementations or some nonsense like that. But please know that you can have a significant impact on it. Two is also making sure that you have a lot of people on board with you on this data amalgamation and centralization and then pushing out of insights and, or next steps is fantastic. Yay. But really what it comes down to is you’ve got to have everybody understanding how to use that. How are you actual sellers? What is your salesforce using this information for? The wisdom for them, you’re going to make more money by knowing more about your customer, which means you have to get more so that I can help you and all that sort of thing, would be some of the other things to really consider in the entire equation. And it is an equation where one plus one plus one, there’s a lot that goes into the chain versus, “Okay, pull a lever and then suddenly something will happen,” but that’s human interaction. And my data also may suggest something, but then I’m having a bad day and I completely throw a fly net on them. So I would just keep the realistic expectations. Know that you’re not always going to get the data and that you also need to make sure that everyone’s, there are a lot of people are on board with the entire process of getting it. And please don’t think that AI is going to be the solution. Please don’t think that machine learning is going to be the solution. We’re a ways off on that. There’s some great stuff that’s being done, but it’s not perfect. And it’s never going to get rid of, never’s a strong word. It’s never going to get rid of people actually understanding someone else.
Gabe Larsen: (13:45)
Yeah. I mean, I’m guilty. I actually was one of those people who was like, “Oh, I’ll just deploy a chat bot and it’ll run itself.” And it didn’t require a full-time person to program and integrate. So I’m smiling you bring up kind of like the AI thing. So I’m guilty on that one. You’ve talked about it a lot. We hit a bunch of different topics on the data front. If you had to kind of simple it down and just mentioned starting on this journey, where or how would you recommend a CX or CX leader start?
Steven Maskell: (14:25)
When would I start? When would I recommend the CX leaders start? I would recommend that a steep CX leader needs to have a good, honest assessment of where they’re at. The function that I had the delight of being in is the result of that assessment. Where there was a goal, there was a big, hairy, audacious goal. And the bottom line is the infrastructure, the platform, the knowledge, it just wasn’t there. And that’s okay. And you know, so the first thing is the CX leader is what’s there, is there a CRM solution in place? Is there a, is there some way that it’s being fed? Is there a mechanism to better understand, are we engaging with customers? Do we have a way of solutioning and being standardized and how we try and solve for things? It’s looking at your landscape and wondering like, “Okay, what do I know about my customers?” And if it’s sitting on the backs of napkins at the end of the long night of drinking, then it’s not going to do a whole lot of good. But if it’s codified and solidified, and if I use the right nomenclature and no matter how many times I say a certain word, everyone understands exactly what that word means, now that we’re heading in the right direction. And so those would be the things that that would happen. I would also argue that you have to understand that a business, the CX leader is in a place to amplify what a business is doing well. So businesses are the results of delivering of services, goods, and products and they do that really well. So please don’t think that customer experience is going to change your product. You have to remember what your product is and you’re there to amplify it. So, I’m not going to change how airlines fly. I am going to make the whole process of engaging with, in this case an airline, as delightful as possible. I’m going to leave the wings and all that to them. And so that would be the other thing as a CX leader is I am responsible for amplifying what my business does and understanding you also have to be able to really, this is one of the hard things, you got to be able to suck it up when someone says you suck. And understand that they’re right.
Gabe Larsen: (16:37)
Yeah, yeah, yeah, yeah. Sometimes those are hard words to swallow. Sometimes those are hard words to swallow, but well said. Well Steven, appreciate you taking the time. I know you got fun stuff coming up ahead over the next couple of days. If someone wants to get in touch with you or continue the dialogue, what’s the best way to do that?
Steven Maskell: (16:56)
Find me on LinkedIn. Steven Maskell. Happy to have a conversation.
Gabe Larsen: (17:01)
Awesome. Awesome. Well again, Steven, really appreciate the time. Fun talk track on thinking through how to use data to personalize that customer experience. So thank you again and for the audience, have a fantastic day.
Exit Voice: (17:18)
Thank you for listening. Make sure you subscribe to hear more Customer Service Secrets.
In this episode of the Customer Service Secrets Podcast, Gabe Larsen is joined by Derek Hixon to talk about his lessons learned after providing over 15 years of exceptional customer support. Listen to Derek’s fun and invigorating life lessons in the podcast below.
Fostering Relationships Leads to Better CX
Derek Hixon, Director of Customer Support and Implementation at WordStream, proudly leads his team of reputable customer service agents. Having over 15 years of customer service experience, he has learned the best methods of garnering customer loyalty and agent happiness, starting with fostering relationships in the workplace. Derek believes that the best customer service experiences start with a happy team of CX agents. To present this idea, he states, “Everything starts with the team that you have working for you and if they’re not happy with you or with the role, nothing’s going to work. So that’s where your primary focus has to be initially. You always got to stoke that flame to make sure that they’re happy and cool with you.”
Derek finds that when his team is happy, their positivity trickles down and reflects in their work. They are able to have more productive conversations, find the best solutions to their customer’s needs, and have better overall CX scoring. When those genuine daily interactions take place, the work environment becomes more comfortable and interactive, ultimately resulting in the best customer service experiences.
Utilizing Data as a Tool
Data is a driving force in innovation. It presents the information needed to push internal growth and to modify methods and tools to better suit the needs of the customer. When customers use a product and don’t understand how to use it, Derek finds that is the right opportunity to learn from their data and to innovate that product as well as alter their CX approach. He says, “Data is key. It’s not the only thing, but you need solid data to make informed decisions.” Using data to gauge what your customer expects from a product has proven to be extremely useful with Derek’s CX process. Data can give the information needed to build internal tools that assist customers, or remove the need for internal CX tools all together by creating an effortless experience. Having a high-level view and taking the small but necessary steps to creating the ultimate satisfactory customer experience through using data can be very beneficial to companies.
Building on Each Other’s Strengths
Something all companies would benefit from is employing each team member’s strengths to work together and create a cohesive CX team mindset. Early on in his career, Derek found that each person offers specialized skills for their job and that utilizing that specific knowledge has proven to be advantageous to the company. He explains, “I think when you’re working with people with different expertise and skill sets, that’s where true innovation really can happen. That’s where you can really have the biggest impact on the business and the customer experience.” He notes that unearthing each team member’s strengths takes patience because oftentimes, they are used to completing tasks in specific ways, and their specialized knowledge gets buried under the day-to-day cycle. Breaking that cycle can be done through engaging with the team, learning from the team and pulling from their skill set. CX teams would be wise to learn from each other and to use their specialized knowledge to build on each other’s strengths.
To learn more insightful life lessons, check out the Customer Service Secrets podcast episode below, and be sure to subscribe for new episodes each Thursday.
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Full Episode Transcript:
Great CX Starts With Happy Agents | Derek Hixon
Intro Voice: (00:04)
You’re listening to the Customer Service Secrets podcast by Kustomer.
Gabe Larsen: (00:11)
Hi, welcome everybody. We’re excited to get going. Today we’re going to be talking about lessons learned from running 15 years of successful support operations, and to do that, we brought on Derek Hixon, who’s currently the Director of Customer Support and Implementation at WordStream. Derek, how the heck are you?
Derek Hixon: (00:30)
I’m doing great. How are you doing Gabe?
Gabe Larsen: (00:32)
Yeah, pretty good. Well, I’m pretty good, man. We had an interesting morning. But I got to ask, man, it sounds like you’ve got a fun hobby on the side, is that true? You’re a DJ by night, by day, by, what is it?
Derek Hixon: (00:45)
I’ve been trying to retire for years, but I can’t get out of the game, I guess. I do DJ around Boston, specifically a place called State Park in Cambridge that I really like and I also make some music on the side and actually I think being creative is very important to me. And I think what I learned outside of the walls of work really helps me inside them as well. So –
Gabe Larsen: (01:07)
That’s awesome, man. Been doing it for years? As long as you’ve been doing support or not really?
Derek Hixon: (01:12)
Oh, I’ve been messing with music since I could walk, so yeah, long, long time.
Gabe Larsen: (01:17)
Love it, man. That’s fun. I’m just getting my boy into guitar lessons. I always wanted to be a jammer, but I just never had the guts to stick with it. So we won’t make you say your DJ name, but if you want to know that you’ll have to ping Derek on LinkedIn. So outside of DJ, give us your quick background real quick.
Derek Hixon: (01:40)
So, I’ve been working within technical support organizations for the past 15 plus years now. Before that I was working within a company called Pearson and, sorry, I’m just going to take a beat for a second. I can’t even talk about myself. So I’ve been working in technical support organizations for the past 15 years and I have a pretty diverse background in media as well. I’ve worked within print production. I’ve worked within the education sphere. I’ve worked within big media and video and I have a fairly diverse background in communications and I’m also in media.
Gabe Larsen: (02:32)
Awesome, man. Well, it definitely sounds like you’ve got a robust background. Want to see if we can pull out some of that today, as we talk about just lessons learned. I mean, you’ve been at different companies, you’ve been in different industries. What are some of those things that just stand out as, “Man, as I’ve looked back at my career, these things have been kind of the make or break things that have made me more successful?” Start at the top. What comes to mind?
Derek Hixon: (02:57)
Oh, it’s funny. I think I’ve fallen into a technical support role and leadership role kind of by accident, but that’s kind of life too. I think life’s very non-linear and you kind of got to go with the waves and fight against them or you’ll drown. And I was working in publishing many moons ago and it was a big publishing company and I was rising up the ranks well, and I had a pretty big team and across multiple cities, but I just wasn’t feeling the culture or just the industry, so to speak. So I was looking for my next new big challenge and I heard of a company called Brightcove at the time. And what excited me about them is that they combined two of my loves, technology and also video. And this is back in 2008, 2007, and YouTube was only a year old. Having video on the internet was the wild, wild West. It was exciting, new, and hard. Which all of it really intrigued me. I had a friend who recently joined there and all they had open at the time was a single contributor support role. And I’ve debated in my head because I had this good career path. I had a good bonus. I liked the people I worked with at the time, but I wasn’t really challenged in ways I wanted to be. Way back in the day I went to school for video and I was going to be the next great Steven Spielberg or something like that. So it was a way for me to still kind of plug into that world as well. So I kind of rolled the dice and I interviewed for a position. I got the single contributor position and this is 2008 and it was about two weeks after I accepted that the whole economy fell through the floor. And I thought, I remember one day specifically, I was going up the elevator and I thought it was gonna be going right back down it. We had to do some layoffs. They were a startup at the time and I was able to survive it thankfully. And the thing I realized real quickly at Brightcove that was different than at the previous company I was at was, and some of this may be due to me at the time, me being in my mid to early twenties, but I thought I knew everything. And I always felt like I was the smartest guy in the room and real quickly at Brightcove, I realized I was not the smartest guy in the room. I was far from it. And it was very intimidating at first for me. I had a lot of fakers syndrome. I was like, “Why did they hire me? Like this was a mistake. Like I shouldn’t be in the room.” But what that really did for me is it threw me into survival mode and I’m like, “Okay. Well, if I’m not going to be the smartest guy at the table,” like I was literally, ActionScript was a thing back then. Rest in peace Flash. I like literally, the guy who was sitting across the table from me, wrote the book I learned from and I was just like, “This is ridiculous, I can’t compete with this level of knowledge.” So what it instilled in me was, I’m like, “Okay, if I can’t be, if I’m not going to be the smartest guy in the room or at the table, I’m going to be the most prepared. I’m going to be the hardest working.” Really what I started doing, the seeds I started lying just to survive, ended up being very helpful for me throughout my career as I grew in different leadership positions in technical support organizations. And what I’d really tried to do initially was I had brilliant coworkers, but they had all this brilliant knowledge trapped inside their heads. So I was just always pinging and poking at them to try and learn from them. And then I was trying to transfer all that down to paper or Google Docs or whatever it was or Confluence or whatever it was at the time, and create my, and it was really a selfish way for me to do documentation. And so I had the knowledge, so I could do my job better. But by getting that mindset, it’s really helped pave a path for me to where I am today.
Gabe Larsen: (07:10)
I love that man. That’s powerful. So one of the big keys was, it sounds like you kind of thought a little high, got yourself in the deep water, neck deep, but you were able to figure it out. And one of the keys was just being able to kind of, sit with that team, really spend some time and pull stuff from them and not just do the conversations, but actually translated into a document or something that could be shared with others or shared with yourself so that you could actually say, “Hey, this is what this process looks like. Or this is what this function, or actual detail looks like,” is that correct?
Derek Hixon: (07:49)
Yeah, that’s exactly right. And that’s something I’ve noticed from my early experiences at my first technical support experiences at Brightcove all through the last few roles I’ve had is I’ve been really blessed throughout my career to work with really brilliant people. And sometimes it’s just helping organize the really good knowledge that they have. Like everyone has very specialized knowledge for wherever they work, but sometimes it’s trapped within and like trying to really get hive mentality and spread the love with what they have.
Gabe Larsen: (08:23)
How [Inaudible] I mean, I think most of us know that intuitively, but it’s always hard to kind of pull it out of people and then get it into, again, a format that’s digestible. You just take, is it just about taking the time? Is it about the right questions? What’s kind of the secret to getting that richness out of people and into a place that can be digested?
Derek Hixon: (08:43)
Yeah. It’s a lot. It’s a bunch of things you have to be patient with. I’m like old school at heart. I like to DJ. I DJ with vinyl only. I don’t like DJ out digitally. If I cook I’m grilling with charcoal, I don’t want a gas grill. It’s just kind of my nature. I just think things are better if they’re done right and slowly, and usually you benefit from it in the long-term. You can always get short-term success with things, but if you have the luxury of time, which you don’t always have obviously, you can do really great things. And I also think just keeping it real with people and being transparent can really get you a lot of credit with people to get trust within you. To kind of pull things out, but it takes time. And where it really starts is, it’s process, right? Process is what everyone’s chasing in a leadership role. They want people to do things in a similar manner. I don’t necessarily want everyone on my teams to do things exact. And I compare, I like sports as well. And when I talk to my team, I’m really, really good at bad analogies. And I like to equate how they do their job, like a golfer and a golf swing, or a baseball player in their batting stance. It doesn’t have to be the same exact stance or swing for everyone, but we’re all trying to get the same results. You’re trying to drive the ball straight and far down the middle, or you’re trying to get a base hit or a home run. When I’m sitting with people, you really have to sift the team, you have to take the time. You have to stroke the coals, you have to prepare for a DJ set, like you have to really understand, “Okay, what’s their day-to-day like?” And that goes through shadowing. Okay. And like I always say, cliques kill. You can do things to simplify your team’s job, you’re getting quick wins and you’re making their lives easier, which is going to filter right down to the customer. And so that’s where you start. And also people like talking like, hey, I’m doing it right now. People like talking about themselves. People like showing off the things they know and it also gives people a chance to feel empowered and talk about the hard work they’ve put in and how they do it.
Gabe Larsen: (11:02)
I like that. Then through all of these interviews you’ve done and different stakeholder discussions, et cetera, any quick things you’ve found that ultimately changed the way you look at support, ideas around simplicity, or people making it harder than they maybe need to sometimes, but different things like that?
Derek Hixon: (11:24)
Yeah. I think that it’s hard to see the forest through the trees type of thing, fully applies when it comes to support. And I think support at times traditionally can have a bit of a stigma. It’s literally at the end of the big funnel from sales to marketing, through products; we’re at the very end. But also, we’re at the end of one part of the process where we’re at the tip of the spear for the customer part of the process of how they’re using a product and where they’re running into things. And I think that it’s just really important to, I’m sorry, what was the exact question? I kind of went off there a little bit.
Gabe Larsen: (12:05)
No, no. It’s totally fine. I missed some of the lessons learned as you interview some of these people and, just curious if there’s general findings. What did you find [inaudible] people ‘complexify’ stuff or –
Derek Hixon: (12:20)
Yeah. Yeah. I think sometimes, and this is the, I find this especially when I first join an organization is I really lean into it when I hire somebody new as well. New blood is invaluable, new perspectives, just new angles on looking at things. Sometimes people live with a certain way of doing things for so long or someone told them to do it a certain way. So they just will do it a certain way. And that’s just the way they’re going to do it forever. And it goes back like, I have a saying that I always tell my team is like cliques kill. And like, if we can simplify the amount of things like tools needed to accomplish a task or ways to assist someone, that’s where it helps. And also I think the other hard thing, a thing I’ve seen across the, when I’m working with people to try and figure it out and simplify the job is, a lot of times, people are afraid to take a short-term hit to get a long-term gain. And I kind of almost look at it like preventative medicine or it’s like if sometimes teams are really scared to take some steps back and look at, “How do I do my job? Well, what are the steps I need?” instead of actually just taking the cases and doing them because like, “Oh, if I’m doing all this stuff and I’m not taking the cases, are cues going to really grow?” And I’m like, well take that short-term hit because it’s going to like, if you take time on this one case it’s going to help, or if you write an article on this one type of case and we post it, it’s going to help hundreds of people down the line and it’s forever going to be evergreen and all that jazz. So it’s helping the pulp. I think that’s, really it’s the benefit I have in the positions I’m in now. I used to be in the trenches, just like the people on my team, taking the cases and doing the calls. You don’t always have the luxury to pull yourself above the clouds and look down at everything. But to be able to do that with the team and allow them that freedom really helps them to help the customer experience better, how the team works better, and also helps them get a different perspective on things and potentially, like I think when people talk about support and customer success so much, they’re always just talking about the customer, but the customer experience is going to suck if the people on the team supporting them aren’t happy, or don’t what they’re doing, or don’t feel like they’re growing. Not everyone’s going to be a support lifer, and that’s cool. I’m sure yourself, you’ve had many different turns throughout your career. But when people are on my team and they’re working with me, I want to know what their goals and aspirations are. And I want to figure out how, when they’re in the current role they’re in with me and my team, how can I help grow skill sets that will help them accomplish larger goals while also helping the immediate goals with what the team has now? So, I really think it’s hard. I think the biggest secret is pulling people out at times and understanding what their path can be and the results will filter out throughout to the customer, the data will start pointing in the directions you want, and you’ll just create a really good working environment where people enjoy being, and working, and pushing and pulling in the same direction with each other.
Gabe Larsen: (15:46)
I like that. So, one big thing is just understanding your team, what they’re doing, learning from some of those findings. The second thing that we touched a little bit about was this idea of case analysis and what do customers really need help with? Talk about how that’s been a lesson that you’ve learned and how that applies to kind of transforming service organization.
Derek Hixon: (16:10)
Yeah. Data is key. It’s not the only thing, but you need solid data to make informed decisions. And so it goes back. And so in the very beginning, if I’m shadowing, it’s like if I got a new job at CompanyWide tomorrow to run their global customer support organization, the first thing I would do would be sit down with the team and understand what their day-to-day is like. And it’s not just to make sure their to-kill cliques and to make their day-to-day more simple, but I want to understand what the cases are and what the questions are that they’re answering and asking. I’ve done this primarily, this is nothing new, but I do this primarily through using case-reasons and sub-reasons at the case level. That means like, if it’s a billing question, that would be the case reasoning. And then from there, the sub-reason could be, “When’s my next bill due? I want to cancel. Where do I find?” Once you can bucket out what the customers are writing in about into different reasons and sub-reasons, then you can really start building a map of what people are actually asking the team about. Really, I don’t look at support, I always kind of looked at as support as a secret part of product because that’s what the, people are using a product.
Gabe Larsen: (17:38)
Derek Hixon: (17:38)
We’re all consumers and we’re all going to have questions on things at some point in time. So I love working as support just because I think it’s good karma. When people are putting their heads against something, and they have a question, it’s because they’re using the product and it’s not working, or they don’t know how to, or they don’t want to figure out how to, because they still have time to sit down and figure out all the things. So really understanding what the people are asking about and then once you understand what they’re asking about, the real proof in the pudding is what action are you taking on the data, and who are you sharing that data with? It’s always easiest initially, to affect things internally, meaning within the support organization, but when you really start developing at my level relationships with peers across the aisle, and in marketing, in products, in engineering and development, that’s when you can really, really, really start doing some great stuff with the data such as creating internal tools. So you can do better work for the customer, or even better, make those tools available for the customer, or make it so the tool is not even needed because the thing just happens. Oftentimes, just from analyzing product usage data, a lot of places where customers might butt their heads against the wall, aren’t going to show up because they’re going to support those sort of things.
Gabe Larsen: (19:07)
I like that. I mean, sometimes the devil’s in the detail, man. It’s finding that, I love the idea of this case-reason and really being able to figure out what’s working, what’s not working, can be, I mean, it just opens up so much insight as to where you potentially need to go. I liked that one. And then number three, you talked a little about this idea of working in a box. Jump into that for a minute. How does that apply to kind of lessons learned?
Derek Hixon: (19:30)
Yeah. My favorite thing about working within a technical support organization is that, when I’m working at a software company, you work with and you talk to everyone within the company. Like then that goes from a tier one associate on my team to me. We’re talking to account managers, we’re talking to marketers, we’re talking to sales guys, we’re talking to product, we’re talking to engineers. And it’s really nice to have like our tentacles throughout the company that way. And like, what really gets me off is cross-collaboration. I think when you’re working with people with different expertise and skill sets, that’s where true innovation really can happen. That’s where you can really have the biggest impact on the business and the customer experience. So, I try and really foster relationships there. It’s not easy. It can be really hard at times because all the different segments have different goals, and different OKRs that they’re pushing towards. Hopefully everything will roll up to the greater good, but it’s hard for all of it to cross over exactly. And just being realistic with where support lies within the totem pole of things at times, if you can learn how to work within other teams, cross-functional OKRs, and whatnot, you’ll have better success with what you’re trying to do instead of trying to jam a square through a circle hole. I’ve tried to jam a lot of squares through circles, so I’ve learned through a lot of failure, and I’ve been far from perfect. But hopefully I’m getting a little bit of wisdom with age, but to be determined.
Gabe Larsen: (21:14)
Wow. Well, I totally understand where you’re coming from. It seems like I get smarter with age, but then I look at myself and I look at my life and I’m like, “No. I’m not.”
Derek Hixon: (21:27)
Gabe Larsen: (21:29)
BS’ed my way through everything. Well, we covered a lot today, Derek. As you think about other service support leaders out there trying to win, what’s kind of a summary takeaway that you’d leave with the audience based on some of the stuff we’ve chatted about today? Any quick kind of quick summary comment?
Derek Hixon: (21:50)
Yeah. I would just say, know your team and then use the data as a tool. Everything’s a tool. Like, there’s a phrase, “Death by a thousand paper cuts,” and I like to apply life by a thousand paper cuts. We’re always, and like the real big phrase that I say to my teams is, “Green grows and ripe rots.” Meaning like, as soon as you think you’re good and you know everything and you start being stagnant, you’re screwed. And like, I try and have a mindset of always wanting to grow and learn and understand, and we’re always tweaking things, but we’re never making this huge, big, crazy change, but we’re always making series of changes based on the data we’re getting and through just keeping a really open communication within the team. And from there, there’s no whiplash had by the team by all these big changes, but if all of a sudden we look back six months, we’re like, “Oh wow, we did a lot. We used to do things this way? That was crazy.” So I think just really having a high-level view of things and I’m not trying to boil the ocean, but always trying to slowly innovate, push, and move forward. But like, everything starts with the team that you have working for you and if they’re not happy with you or with the role, nothing’s going to work. So that’s where your primary focus has to be initially. You always got to stoke that flame to make sure that they’re happy and cool with you.
Gabe Larsen: (23:15)
I love it, man. Alrighty. Well, a lot to cover. Definitely a lot of experience coming out. I can hear the wisdom in your voice. I’ll have to join you in Boston sometime when things calm down with all that’s going on with the COVID, et cetera. It’d be fun to hear you DJ, man. So anyways, thanks for joining and for the audience, have a fantastic day.
Exit Voice: (23:40)
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“Unprecedented times” feels like such an overplayed phrase at this point, but it’s true. As a Customer Success Manager at Kustomer, I’ve had a front-row seat to how the pandemic has impacted (and still impacts) the businesses that are under my care. Some are struggling, some are booming. As I collaborate with my clients in building out business strategies, examining year-over-year performance trends is a tricky endeavor. It’s a bit like trying to judge the size of a hurricane when you’re sitting in the eye of the storm. 2019 feels like aeons ago at this point, and what does it really tell us if a business’ first response time increased by 30 seconds from 2019 to 2020?
As a personal project, I began studying the performance of our clients from March 2020 to August 2020. Many companies have been focused on this window of time as it relates to their performance in a post-COVID world. While there are several metrics that I could have focused on for this project, I chose to spotlight two: First Resolution Time and Average Handle Time. In my opinion, these metrics are some of the most impactful when it comes to judging your team’s performance.
First, I gathered the Average Handle Time (AHT) and First Resolution Time (FRT) metrics for each of our clients. Then, I defined the industry category of each organization. I used the following overarching categories:
Once I had the data, I first explored it by sorting clients by their industry categories. I built a pivot table and gathered the minimum value, maximum value, mean, and median of those respective categories. Then, I explored the data without pre-emptively sorting them into industries – this is important because I didn’t want my industry sorting from the first exercise to lead me to any false conclusions. For the second exercise, I re-sorted the data into ranges of values for both Average Handle Time and First Resolution Time metrics without grouping by industry. I then took note of how industries aligned or did not align to my first analysis. Finally, I documented the correlations I observed.
As I began analyzing the data, I approached my research with a central hypothesis: Average Handle Times will be higher for clients in our Marketplace and Service industries and lower for clients in our Delivery and Retail industries. Additionally, First Resolution Times will be higher for Marketplace and Service clients and lower for Delivery and Retail clients. At a high-level, I found that my hypotheses were supported.
There is a wide spread of data for Average Handle Time and First Resolution Time across all of our clients. There are organizations that operate at opposite extremes within the same industry, ultimately skewing the data. A quick example: the retail category of clients has a minimum value of 0.82 minutes for Average Handle Time but a maximum value of 46.6 minutes for the same metric. To circumvent this skewing, I used the median values of these metrics as they are better indicators for general benchmarks.
I developed the following recommendations for client benchmarks as they relate to Average Handle Time and First Resolution Time:
Delivery: 4.45 minutes AHT | 10.2 hours FRT
Marketplace: 7.5 minutes AHT | 106.8 hours FRT
Retail: 6.25 minutes AHT | 9.15 hours FRT
Services: 8.7 minutes AHT | 22.2 hours FRT
To supplement my research, I also read about academic studies on benchmarking (and how to successfully apply them to improve team performance). A fascinating read that I uncovered was a study completed by Peter Dickson that examines the competitive advantage businesses gain by implementing customer improvement practices. Benchmarking is considered to be a customer improvement practice, and it was enlightening to learn more about how this particular project could lead to more successful outcomes for our clients. Dickson writes the following: “Both management and evolutionary economics describe a behavioral theory of the firm where an organization’s routines determine its competitiveness. Higher-order search and learning processes improve organization routines that are defined as ‘ways of doing things that show strong elements of continuity.’ According to these theories, the long-term survival, evolution, and growth of organizations in competitive markets depends, in large part, on the superiority of an organization’s routine process improvement practices”.
While I don’t believe that using these benchmarks will make or break the future success of an organization, it is important to consider the implications of encouraging customer service teams to think about improvements. These improvements promote successful businesses, and giving your agents pursuable goals builds accountability and ownership.
Something important to consider: There may be times when an organization willfully ignores benchmarking – particularly if they are implementing a cost-saving strategy. Always consider what’s best for your brand and your team.
As COVID-19 cases began to spike in February and March of 2020, the economy slowed. Many companies were faced with the difficult decision to layoff or furlough a percentage of their workforce to stay afloat. As we move into the summer months, there have been modest gains in economic activity and employment growth. Reuters reports that approximately 25% of private-sector jobs have since been recovered out of those lost in March and April. Still, recovery has been slow as many contemplate future waves of the virus.
Considering the uneven terrain of our current economy, workforce management has become even more critical to maintaining profitability. It also promotes the health of your customer service team. If you’re running a skeleton crew and looking for ways to justify an increase in headcount for your team, read on.
How Kustomer Data Can Help
There are a handful of important metrics within the Kustomer platform that can help you understand whether your team is over- or under-staffed: inbound messages, average handle time, and agent capacity. For the purposes of this exercise, we’ll focus primarily on a single channel: chat.
Here is the major question to consider: what does the data tell us about staffing needs and restrictions? Additionally, how many agents do we need to staff so that all chat customers are served immediately?
Let’s say that you’re an up-and-coming retailer in the Atlanta area. You currently have a 10-person team that handles all of the incoming chat conversations on your website. Each of these agents is trained to handle five chat conversations at a time. Collectively, their average handle time is five minutes.
Every agent works an eight-hour shift. They take multiple breaks throughout the day that add up to approximately one hour; they work for approximately seven hours per day. Thus, every agent is capable of performing approximately 420 minutes per shift (seven hours is equal to 420 minutes). Sixty minutes divided by an average handle time of five minutes means that each agent could theoretically complete 12 conversations per hour (if not multitasking). If we multiply that number by agent capacity (five, in this case), we can speculate that an agent can handle 60 conversations per hour.
If an agent can resolve 60 conversations per hour, and each of those conversations has a collective average handle time of five minutes, then an agent is capable of performing 300 minutes of work in an hour (in the eyes of our reporting). Finally, when thinking through the amount of work an agent can handle in a shift, that number is 2,100 minutes of chat work (300 minutes multiplied by seven hours).
As the lead of this team, you begin by pulling the average inbound messages per hour within the Conversations tab of your Standard Reports. Break up the data by day of the week. You notice that Mondays, on average, see a typical volume of 6,000 inbound chat messages. Again, if we multiply the total number of messages by our average handle time (five), this represents 30,000 minutes of chat work that needs to be completed on each Monday. If we divide those 30,000 minutes of chat work by the 2,100 minutes that an agent is capable of completing each shift, we can guess that we need approximately 14 agents working on Mondays to serve all of the chat customers as they arrive.
You can replicate this process across all days of the week, or certain seasonal spikes, and even apply this method to other channels. With further calculation, you could provide an hourly view of necessary coverage for inbound chats as well.
One final disclaimer: the important thing to remember here is that we are using past performance to forecast the future. Thus, it will not always be a perfect predictor of future staffing needs. It’s important to regularly monitor the ebb and flow of inbound messages to ensure that your team is adequately staffed.
Today, businesses thrive when they can provide a convenient, personalized customer experience. That entails answering questions specific to a customer’s concerns and addressing wants and needs of a particular patron, all within a short amount of time.
Certainly, businesses can help customers and provide top-notch customer service when taking on such tasks, but customer service agents can also be a valuable resource when they go above and beyond and reach out to the customer first. We refer to this as proactive support, and it can be a secret weapon to improve the reputation — and bottom line — of your company.
In the world of customer service, timing is everything. According to the Customer Service Barometer study fielded by American Express, 40% of customers agree that they would be pleased by customer service agents taking care of their needs faster. This means companies have to be forward-thinking about their customers’ wants and needs, to get ahead of the curve. With proactive customer service, this goal is highly attainable.
In this article, we’ll take a look at proactive vs. reactive customer service, dive into the importance of proactive support, and discuss the five different ways you can transition from reactive to proactive customer service:
What is Proactive Customer Service?
Software Advice Inc., a partner of Gartner, defines proactive customer support as the strategy used by a company to anticipate potential concerns of the customer. Essentially, it’s enabling customer service agents to reach out to consumers before they are pinged, in an effort to offer a solution or suggestion without being prompted.
Proactive live chat, for example, can be used by agents to address anticipated concerns based on various factors, such as the amount of time a customer spends on a page or a continuous return to a certain page. Online behavior, as well as browsing reoccurrences, are critical bits of information that can allow your customer service team to dive into the immediate needs of customers and address underlying issues they may be experiencing, but are unsure if they should bring to your attention.
What is Reactive Customer Service?
Reactive customer service may be known as the more common type of response. This is the type of support that’s offered once the customer brings the problem to the surface. As HubSpot explained, it’s like using medication — just as one would take medicine to combat symptoms and treat the body to get rid of the impact that has already occurred, customer service agents can use reactive support to address customer concerns after learning about them.
Five Ways to Make the Transition From Reactive to Proactive Customer Support
How can you prepare your service organization to anticipate your customers’ desires and to deliver an experience that defies their expectations? In our CEO and Co-Founder Brad Birnbaum’s Forbes piece, he took a deep dive into the theory and practice of proactive service. Below, we’ve outlined the five most important steps you can take now to upgrade your experience and delight your customers with forward-thinking support:
1. Train Your Customer Support Team
Proactive customer support isn’t just about analytics, it requires an equal amount of human insight. Before investing in tech, make sure you have a team of engaged agents that are already thinking about your customers’ needs. For example, Outdoor Voices’ agents are able to collaborate more easily because of comprehensive training, amplified by Kustomer’s intuitive interface. Great service starts with great people.
2. Equip Your Team with the Right Knowledge: Prioritize and Invest in Analytics
By combining human insight with powerful analytics, reporting, and a record of every customer’s history, you can equip your team with everything they need to know about your stakeholders. Just ask Glossier, who works with Kustomer and Looker to get rich insights into customer behavior. If you don’t have all the data in a single customer view, it’s almost impossible to be proactive.
3. Protect and Secure Your Data
Beyond having all the necessary data at your fingertips, that data needs to be in one safe, central location or network of locations. This can be a system you’ve created in-house, or a third-party CRM—the important thing is security and usability. Read more about our commitment to security here.
4. Help Customers Search and Find What They’re Looking For
When you have all of your customer information in one system, across all of your platforms and integrations, you can create the kind of granular searches for customers that account for their specific behaviors or needs. Once you’re able to identify customers by their last order, their location, their sentiment, and more, surprising and delighting them is a snap.
5. Don’t Get Lost in the Weeds: Track the Right Metrics
You need a way to capture how your customers are feeling. That requires a combination of several things. You should be measuring sentiment within customer communications and on social media, using surveys that capture metrics like CSAT, NPS, and CES, and tracking behavior across every channel of interaction. For a brand like LOLA, having all the relevant information at agents’ fingertips when customers have a question about their subscriptions is crucial to great service.
To be smart, personal, proactive, and timely requires a lot of moving parts to come together, but doing so is the hallmark of a standout customer experience. Once you can gather and store all relevant customer information, you can act on it with a combination of well-trained employees and specific features within your software platform. When you can connect with individual customers over their preferred channel with the right personalized message, your experience can become a true revenue driver and differentiator for your organization.
Getting there isn’t as simple as completing a checklist — it’s a complex process, unique to every business. However, when all of these threads come together, your customers will see and feel the difference in every interaction. Check out Brad’s Forbes article to learn more.
How Kustomer Can Help You Prioritize Proactive Support
Kustomer’s robust customer service CRM is designed to help your customer service team meet the wants and needs of consumers, all while getting ahead of their common queries and concerns.
Instead of waiting for a customer to ping you, agents can send instant messages to target audiences based on various factors, such as:
Time spent on the page.
Last page visited.
Attributes based on log-in information.
Are you looking to make the transition to proactive customer service? Learn more about what Kustomer has to offer by requesting a demo today.
Until now, the omnichannel, cloud-based, 360-degree customer view-enabled contact center was mostly a pipe dream, touted by technology vendors and thought leaders, with a majority of businesses falling short of this gold standard. Most customers still expect to fight their way through a dead-end IVR, endure multiple transfers, and repeat their information to agents who have zero context on who they are or why they’re calling.
As technology grows more robust, however, more and more businesses are starting to overcome these bottlenecks, more of which are related to a lack of data transparency. Businesses are using AI and machine learning-enabled platforms to unify their data across the organization, route customers based not only on queues but context, and design self-service platforms that facilitate end-to-end support.
Treat Every Customer Touchpoint as a Potential Data Source
For many businesses, their website is the seat of personalization. By collecting data on customer’s viewing history and purchasing habits, they can provide personalized recommendations and proactive support based on context, such as offering help through web chat to a customer who’s having trouble completing an online purchase. But a truly omnichannel experience is one where personalization follows the customer, whether they’re on the phone with an agent, shopping online or visiting in-store.
This means that data you collect from your website must be reconciled with the customer’s activity in all other channels to build a complete 360-degree view of each individual customer. When an agent interacts with a customer, regardless of channel, they should be able to see the customer’s buying history, sentiment and previous interactions (across every channel), status of their orders and customer’s preferred channel.
Says Kustomer CEO Brad Birnbaum, “Imagine having a conversation with a friend but not being able to remember anything about that friend, or any interactions you’ve had with them previously. It would be difficult to have a truly personal or meaningful conversation. That’s how traditional retailers have historically interacted with their customers, with a large blind spot around customer preferences and history.”
Optimize Human to AI Interactions
“Agents for complex issues, AI for simple ones” is an oft-repeated principle for successful human-AI interactions in the contact center. However, customers still find themselves calling when a chatbot does not function as anticipated. For this reason and others, the contact center is often still considered a cost center rather than a revenue driver. Once businesses learn how to optimize their self-service channels, while giving customers recourse to contact a live agent if needed, agents will automatically become the go-to touchpoint for complex issues and expert recommendations, and thereby come to be perceived as subject matter experts.
Without the burden of responding to repetitive inquiries, agents can focus on building a relationship with the customer. As Birnbaum says, “It will become the customer service agent’s job to reflect the company’s mission and values, and act as a trusted partner. The changing expectations of consumers means that customers want to do business with companies they believe in, feeling as though they are a part of the brand. Customer service agents can help do just that, through both proactive and reactive support.
Unfortunately, many tactics that once served an organization well in engendering a customer-first culture simply fail to keep up with the enormous increase in both customer data, and use of connected devices. Two and a half quintillion bytes of data are created each day at current pace, and Gartner predicts there will be more than six connected devices per person as early as 2020. This device proliferation and increase in data results in an overwhelming number of touchpoints that must be tracked and connected to the customer’s buying journey. It’s a tall order, but the organizations who will win are those who can use all of this data to scale the customer experience quickly, efficiently, and effectively, and all on the customer’s terms. It’s not just enough to collect data: it needs to be the right data that can be acted on in the moment.
Working with the customer where they’re comfortable
The digital age has changed where, when, and how customers interact with a brand. What was once a simple cycle of seeing an ad, making a purchase, and repeating, has shifted into a looping journey with the potential for numerous friction points that can turn a customer away from a brand all too quickly. McKinsey describes this journey through four critical areas: consideration, evaluation, purchase, and post-purchase experience. Instead of assuming a consumer will immediately be faithful to the previous brand purchased, McKinsey states that today’s buyer continues to consider new brands available to them. McKinsey adds the element of the Loyalty Loop, which fast tracks future purchases, but in order for a brand to effectively qualify for this shortcut, they must have fostered lasting loyalty with the customer. And 95% of consumers say customer service is important in their choice of brand loyalty. In other words, helping a customer find the answer they need quickly is a significant indicator of whether or not a brand has continued ownership of that customer’s wallet share.
An additional complication is the increase in possible touchpoint locations: digital searches, email, social media, website, and more. In fact, 31% of millennial customers looking for help reach out to a company via Twitter. It’s important for an organization to connect all relevant touchpoints to a unified customer profile in the event of a customer service interaction, or they run the risk of further fracturing the experience and the relationship.
Brands must be willing to look critically at their existing systems to evaluate if they’re truly prepared to handle the significant amounts of data, devices, touchpoints, and the unified view necessary to provide a seamless customer experience. Tools driven by AI and machine learning are the only way to ensure a business can scale to keep pace.
The expectations for customer agents have never been higher; below are ways that AI magnifies data to bolster a support team so they can create optimal customer experiences.
Automate processes and tasks
KPMG has estimated that the service cost reduction with Robotic Process Automation (RPA) is as great as 75%. With the average cost of service centers continuing to rise — voice is $12 per contact, and live chat is $5 per contact — shifting resources to self-service through automation and a knowledge base can result in huge savings. Automation tools can decrease costs to just 10¢ per contact.
It isn’t simply the dollars and cents saved, however, that make automation so impactful to an organization. In one use case, automation can vastly improve worldwide organizations needing to route certain language speakers to agents who can communicate in that language. Additionally, by routing common questions and needs to a self-service portal or base that can both quickly and effectively solve a customer’s problems, agents are freed up to more quickly take on the more complex, nuanced issues that customers face.
While skeptics might be concerned about customers valuing human interaction above all else, according to this report from Statista, 88% of US consumers expect an online self-service portal. In fact, bringing numerous types of customer data touchpoints into one place — and from any resource — creates a more seamless, personalized experience for that customer. This method allows for both speed and a personalized approach to be achieved, and on the customer’s terms.
Augment existing agent support
When a customer dials into a service call center, provides significant information regarding who they are and why they’re calling, and is then directed to an agent for further assistance, the worst possible scenario is that customer then having to repeat all of that information…again. When considering a customer may have also reached out through email and even social media, it becomes even more crucial to use data in the right way. Much like being retargeted by an ad for a product you purchased yesterday, today’s customers are smart and expect organizations to be intelligent with their data. If, after interacting with a chatbot and providing all relevant data, a customer’s issue is escalated to a human agent, the customer expects an agent to already have the necessary context to properly manage the issue. That context should include relevant information like shipping number, previous conversations from both online and offline sources, and previous purchases made, combined into a unified customer profile.
Not only does the full customer data view aid with escalating issues directly, it can even be used to provide recommendations to the agents before even interacting with the customer. Through AI technology, an agent can be given an automated recommendation for how to best handle the customer’s request, eliminating both time and mismanagement; thereby improving the quality, time, and ease of service for both the customer and the agent.
When AI is used to capture data for context, the technology and the human agent become critical partners in providing the right customer experience. It empowers an agent to be a true specialist, who can change the customer’s outcome in a way automation cannot. The marriage between the two is what elevates the customer experience to a level that promotes long-term loyalty.
Proactively boost future outcomes
As a part of the new expectations customers have for service-related interactions, customers expect their preferred brands to be proactive in handling potential issues. For an organization this can be as simple as customer communication that informs of impending weather that will impact a shipment, or as sophisticated as predicting volume needed quarters in advance based on real-time interactions. In order to accomplish this, however, all relevant data must be gathered in a location where it can be acted upon quickly.
One use case could even enable leads and managers to get ahead of issues in-the-moment. For example, as a call is happening, the voices can be translated into text, then analyzed and graded in real time to measure key indicators that identify a call going south. Instead of arbitrarily choosing which calls to QA, or to QA all calls after-the-fact (and risk missing the ones requiring assistance), AI and machine learning can alert a team lead exactly when to jump in and improve the customer interaction as it occurs.
Antiquated technology looks reactively at improvement; the best customer experience requires proactive use of data as the touchpoint interaction occurs, rolling it into the most personalized experience possible.
Connecting all the data to relevant touchpoints and driving a hyper-personalized experience will change how your customers experience you and your product. Tune into our webinar with guest speaker from Forrester where we break down how you can create an elevated customer experience.
Growing your business is hard enough—but growing your service organization alongside it comes with its own challenges. More agents customers mean more complexity. To help make sense of your growing CX team, we’ve listed some common stumbling blocks and some intuitive solutions to get around them.
Tickets coming in from multiple channels makes it hard to separate out who owns what. When a customer gets annoyed with wait times, they will often start reaching out over several different channels with the same problem. Agents working in these different channels then have no way of seeing that it’s the same person, and the customer ends up getting a response from more than one team member on chat, email, and wherever else they reach out.
The solution to this problem sounds easy, but is a huge shift in service philosophy. Give your agents ownership over the customer relationship, so that they are responsible for satisfying individual customers over many channels, instead of all the customers in one channel. By making your service omnichannel, agents are aware of every conversation happening with each customer.
Disconnected Data, Disconnected Systems
As your business expands, so too do the places and ways you store customer data. If you don’t rein these in, then agents end up wasting time switching between applications and hunting for information in back-end systems.
If agents have to go into multiple systems—ordering, shipping, customer information, and more—to see all the information about the customer, then copy that information and paste it into another screen, their workflow grinds to a halt.
To overcome this obstacle you need to be able to have all of your data in one place, with systems that integrate with one another, and a way to turn that insight into action. When agents don’t have to spend time hunting in separate systems for information they need, that makes everything in your service organization easier to scale—because your agents are more efficient and productive than ever before. Just the ten seconds agents save from not having to switch applications can translate to days of work saved in one month alone.
From Reactive to Proactive Service
When you scale your business, you do everything you can to keep up with your customers. However, all the effort it takes to simply respond to and stay on top of their queries leaves no time for any forward-thinking, proactive engagement.
You soon won’t have the luxury to pick up the phone and call every customer who gave you a low CSAT score. You need to be prepared to deliver that same level of 1-1 service, but on a much greater scale.
Automation is going to go a long way towards freeing up your agents’ time. Anything you can do to learn more about your customers and their needs before they’re transferred to an agent is going to massively increase your efficiency. Chatbots that ask a few simple questions about the issue a customer is having can simplify the experience for customer and agent alike. Smart segmentation that makes it easier to determine the right actions based on informed personas will save even more time and effort. Proactive outreach can inform an agent to send an email, or even automatically send an SMS, if an item is going to be delayed, giving customers options for how to proceed.
Team Reporting and Monitoring
As your team grows, so too does your need for detailed reports and insights. However, these reports are often in separate products for different channels, forcing you to spend a prohibitive amount of time creating and combining separate customer reports. To make matters worse, these reports are often delayed by hours or even days, meaning you can’t really see what your team is doing in real time. Many businesses that are scaling quickly also tend to start using more remote agents and teams to work faster. You are going to need a way to effectively monitor them in order to provide proper coaching.
The answer to your reporting problems is to be able to query, segment, and display reports through custom dashboards in real time. If your current solution doesn’t have these features built-in, they aren’t going to spring up overnight. And without proper reporting, you won’t be able to fully understand what’s happening in your growing team.
It can be difficult to successfully scale your support team—we know. Without a modern platform for customer experience, it might feel nearly impossible. Learn more about how Kustomer can help you avoid the common pitfalls of efficiently scaling your team here.
You get the most out of Kustomer once you’ve connected all of your customer information and data. As an official technology partner, our Magento integration allows you to personalize your support based on your Magento customer profiles, including your customers’ online behavior, their purchases, and their return history.
Now your support team can see all the purchases made by every customer, set up searches based on Magento information, provide proactive service using workflows, and more. For example, you can create a search for customers with Magento orders worth more than $200 who have made a purchase more than once a month, then assign them to a higher-tiered support level and send a bulk message with a coupon thanking them for their loyalty.
Integrations should be more than delayed, view-only glimpses. As part of this integration, we’ve added a real-time shopping cart card, which lets you easily see the contents of your customers’ shopping carts while you provide support. Your team will have all the necessary information to quickly resolve your customers’ issues, decreasing shopping cart abandonment.
Our integration will sync standard objects out of the box such as customers, orders, and more. You can also easily send your own custom events (like items in cart) and have them populated as custom objects. As with all custom objects, you can create reports to gain deeper insight into how your shopping is connected to customer support and service.
I am unique. You are unique. We differ in many ways, including how we behave, shop, engage, talk, and react.
We are also creatures of habit and prefer to leverage a trusted vendor who has provided us with a consistent, good experience. For example, most people have a favorite local barista at the cofee shop we buy our large coffee from on the way to work. When we have consistent, good experiences, we return to the same trusted vendors or brands that serve our diverse daily needs like clothes, cosmetics, jewelry, housing items, pet food, travel and food.
These businesses also have an identity of their own, a unique approach and well defined processes for treating and serving special customers like me and you. However, there is often a disconnect between businesses’ approach to the customer experience and customer expectations.
The chasm between the needs of today’s customers and what experience brands truly provide, is referred to as the CX Expectations Gap. Meeting these needs requires a lot of work: time, money, effort, and resources.
There are places and companies who have been successful at addressing specific expectation and personalization needs. They are usually local vendors who have intimate knowledge and recurring facetime with their customer base. You interact with these local vendors every day, from your regular bar’s bartender, local diner manager, barista at the coffee shop on your way to work, or my local fruit vendor. They are all different in many ways but have one critical aspect in common. A process that helps them know everything about every customer.
My local fruit vendor works hard. He recognizes me and knows my preferences. If there are great, slightly green bananas and it’s Monday he knows to save me these as I pick up fruit on way back from work. When he gets an order of figs (one of my favorites) and sees me exit the subway, he lets me know. He knows I like the extra hard cucumbers and the plums my kids make me buy everytime they come with me to buy fruit.He offers these as upsell and perhaps caters to people like me with a special offer.
He knows there is another vendor three blocks away, so after a bad experience with sour, bad grapes, he immediately refunded me and offered fresh grapes. And he now knows that everyone who bought these batches of grapes that day may have experienced the same displeasure and are at risk of moving to another vendor, risking a loss of repeat business and clientele. So he asks those he remembers if the grapes were ok and offers similar replacements.
But does this process scale? What if it could? What if you could make every customer a priority, just like my local fruit vendor, by knowing everything about them?
For that you need to ensure every system, app, and data point is integrated the right way as to portray your unique business processes, focusing on driving superior CX and enabling you to drive the right, informed action by agent, marketing, automation and knowledge workers in the company.
This requires the following:
Incorporating every customer’s entire buying history, from self service, online, offline and every relevant action into as single repository that drives the right action for the appropriate customer facing employee.
Understanding your customer’s engagement preferences, to be able to respond to them when needed and proactively reach out when appropriate.
Analyzing sentiment changes, trends, and patterns, as to drive informed decisions for a segment of customers, who may have received the wrong or damaged product.
Enabling inventory demand vs supply shifts to notify the right person through their preferred channel of interaction and to offer alternate products now vs waiting for the restock.
Automating your business processes to drive great CX, enabling a full view of every customer’s unique story, and knowing everything about every customer as to drive informed actions — that’s the vision and future we all dream about.
About Alon Waks: Alon Waks is the VP of Marketing at Kustomer. Previously Alon was VP of Marketing at 8×8, leading segment and demand globally, including all Go-to-market, content and sales development. Alon has a vast experience in B2B Marketing, Product Management, GTM and consulting. Prior to 8×8, Alon was VP, Global Head of Marketing at LivePerson, where he led all content, demand generation, field marketing and global operations, and also served as the head of product marketing for many years. Prior to that, Alon led Product Go-To-Market for Avaya. He has a rich background in IT consulting, Business Intelligence, Product and working worldwide with enterprise customer’s Line of Business, IT and marketing. Alon holds a dual degree from Tel Aviv University and a MBA from Duke University.
Customer Support is playing an increasingly strategic role in companies. Today, we are excited to unveil a new powerful solution that uncovers valuable insights and trends about your customers. We have partnered with Looker to create a solution that enables companies to integrate their support team’s data into broader, company-wide insights and analysis.
Kustomer helps Support teams get a complete view of their customers and treat them like people instead of transactions. Companies using Kustomer can easily create a real-time data export stream of this Support activity into their data warehouse.
The Kustomer & Looker Block
Kustomer and Looker are a perfect match: Kustomer gives you one place to view all of your customer support data and Looker is a great way to help you share, combine, and analyze that information at an operational level for your whole company.
To make it even easier to get started with your analysis, we’ve created a Looker Block for Support Analytics by Kustomer. Looker Blocks make it easy for companies to quickly deploy expertly built, tailored solutions specific to each business unit or data source. They are also a great way for partners like us to make the data we’re replicating into your data warehouse immediately actionable.
The Looker Block for Kustomer allows you to easily explore your customers, conversations, and teams data to provide a comprehensive view of Customer Support team operations. Some example metrics include:
Key statistics for support team members, including average time to first completion
Average time to first response and average number of messages in conversations
Conversation status and volume by channel
The Complete View of your Customer
So, why is using Looker on Kustomer data valuable? Kustomer gives you the context of the customer beyond an individual transaction and in Looker you can link this data with other operational data in your data warehouse, including application data and home-grown systems.
This union of customer data enables you to perform the analysis that can result in actions that increase loyalty, improve customer lifetime value, and help customers get what they need. You can use Looker to uncover intelligent insights not only in your customer data but in your enterprise data too.