A Look Back at Customer Service During the 2019 Holiday Season

The holiday season has only just wrapped, and it was arguably the most important season for any retail customer service organization. When there are issues with holiday orders, you encounter the very real possibility of unhappy customers who are angry and embarrassed by missing or incorrect gifts. Customer expectations are at an all time high, and organization must over-deliver during their greatest times of need. Whether it’s handling simple product questions in real time, proactively alerting customers when there is an issue with their order, or rectifying any subsequent issues upon delivery, customer service during the holiday season could be the difference between a lifelong customer and one lost to the competition.

How Peak Season Customer Service Has Changed

The digital and direct-to-consumer shifts have had a huge impact on retail customer service. While customers now expect instantaneous service on a multitude of channels, they also expect personal and helpful interactions, similar to face-to-face interactions with in-store associates. In fact, according to a recent Kustomer survey, 75% of consumers aged 25-34 said they expected personalized communications from retailers. And that is 15% higher than those 65 and older, meaning personalization is becoming increasingly expected with younger generations.

2019 Holiday Season Developments

Last year there was a drastic increase in multichannel shopping (both online and in-store), and multichannel support inquiries are also on the rise. That means consumers may start an inquiry on one channel, and finish it on another. Whether the channel switch is because they are on the go, or they didn’t get a prompt response on their original channel, multichannel inquiries can cause duplicative work resulting in agent collision as well as the unfortunate need for customers to repeat information. It is important that retailers have a strong omnichannel support solution in place for any peak shopping period. A true omnichannel support solution can integrate your combination of communication channels in order to capture the free flow of conversations across channels and display the data in a single screen. This ensures seamless transitions and consistent experiences from one channel to the next.

Peak Season Challenges

The constant struggle for customer service organizations during peak shopping periods is sheer volume. With more shopping comes more support inquiries, and businesses that don’t have a scalable strategy in place, supported by the right technology, may not be able to deliver on customer expectations. Additionally, many businesses hire “seasonal employees” to help with the busy periods that they must heavily train to ensure they provide a consistent brand experience. With software that does the heavy lifting for them, providing unified customer history in a single screen and delivering standardized responses via dynamic content, the onboarding burden during an already busy time will be lessened.

Additionally, with a high volume of inquiries, customer service organizations often have trouble prioritizing the most urgent or pressing issues, and simply stick everyone in a queue, which is often unbearably long. Retailers can use AI and automation to intelligently route the most pressing issues to the most appropriate agents, or even prioritize loyal customers.

Overwhelmed customer service organizations often fall into the unfortunate habit of delivering bare minimum support in order to complete inquiries as quickly as possible. It’s important to realize that during peak shopping seasons, your customers are also stressed out, and expect retailers to deliver on their usually stellar service just as thoroughly as they would on the slowest day of the year. That means delivering real-time support, on any channel they choose, in a personalized manner.

Overcoming Peak Season Challenges

Whether it’s Cyber Monday, Valentine’s Day or Back to School season, brands should not only have a scalable strategy in place, but also technology that enables them to be more efficient and effective. AI and automation can improve the precision and speed of service by automating repetitive, manual tasks. While there is always fear of losing personalization when using AI and automation, with the right platform, businesses can actually do the opposite. For instance, if a business leverages customer data properly, AI could ask personalized questions based on an individual’s purchase or browsing history. These interventions save time for both the customer and agent, and increase the time spent on the actual issue rather than information gathering and low-level support.

To learn more about the results from the 2019 holiday shopping season, and how to properly prepare for future peak shopping periods, download the full report.

Download the Report


What Does the Future Hold for Contact Centers?

It’s undeniable that customer experience is only becoming more central to business success. But being thought of as an “icon” in the customer service space is challenging. A surefire way to succeed? Prepare for the future now. According to a CCW Digital survey of contact center professionals, the future of customer service is already within grasp. Read on to learn what pros in the industry think, and how to prepare for the future.

Channels of the Future

Just fifteen years ago, the iPhone didn’t exist. Neither did Twitter. In five years, the landscape of customer service channels may be dramatically different. According to the CCW study, the phone will not disappear as a dominant support channel, with only 17% of respondents expecting its relevance to decline, however a digital transformation may come to fruition.

A whopping 84% of respondents believe chat and messaging bots will become more central to support functions in the next five years, showing the importance of AI to the future of customer service. But instant agent channels will also become more popular, with 81% expecting messaging to rise and 76% saying live chat will be imperative. Lastly, social media and connected devices will have a place in the future, with 68% of respondents saying social will become more important, and 60% saying connected devices are on the rise.

The Customer Service Intelligence Challenge

Did you know only 11% of consumers believe that organizations take their feedback seriously? It’s true, and it’s an issue that businesses are trying to solve.

Collecting great insights from customers is the leading contact center objective that companies want to achieve by 2025. Unfortunately, only 1% of organizations currently believe that their customer intelligence strategy is perfect. Why? Almost half (47%) of organizations have data scattered across various systems, showcasing the importance of a unified data environment to gather meaningful and actionable insights.

Other customer intelligence issues reported by businesses were: not collecting enough data (43%), not using data to personalize the experience (43%) and not doing enough to understand customer sentiment (40%). An additional 40% believe that they don’t even HAVE sufficient data to fully understand their customers.

The contact center of the future will have to leverage systems that unify data and give businesses a seamless way to analyze customer intelligence and take action on that intelligence.

Establishing Customer Service Objectives

Many of the “objectives of the future” are the ones we strive to currently measure, but may have difficulty achieving. In order of importance, customer service experts think the following will be the biggest objectives by 2025: reducing effort, consistency across touch points, proactively resolving customer needs, and collecting great insights.

These objectives highlight the importance of a true omnichannel experience, as opposed to a disjointed multichannel experience, and proactive support.

On the other hand, contact center professionals will not be prioritizing some of the traditional success metrics of days past, such as reducing call volume and reducing handle times. Instead agents will be empowered to focus on providing the best possible experience for customers, no matter how much time that interaction takes.

To read the full report, which includes a plethora of additional data, download here.

Download CCW Market Study


What to Look for in a Modern Day Customer Service Software Solution

Consumer expectations are growing. In fact, 66% of consumers aged 25 to 44 believe that the customer is always right, almost 35% higher than those over 65. That means the younger generation is expecting more from the brands they choose to shop with, and companies must keep up. But how do you accomplish that?

Without endless resources, delivering seamless and personalized service, on every channel, can be an intimidating challenge. Luckily, technology can help. But just as consumer expectations have shifted rapidly, so has the way we do business. Finding a software solution that is built for the modern age is of the utmost importance.

Customer-Centric, Not Ticket-Centric

Think of it this way. Just fifteen years ago, the iPhone didn’t exist. Twitter didn’t exist. And customer service software wasn’t built to accommodate the expectations and channels of today’s customers. A modern day customer service solution treats customers like people, not tickets.

Many customer service solutions on the market today are ticket-based, meaning they identify the customer as an attribute of an inbound or outbound message and build the communication around that ticket. These systems prioritize the metric of a “done ticket” over a customer relationship.

In contrast, modern day customer service solutions focus on the customer at the center of each interaction. By tying existing applications, business processes, and performance to the experience of the customer, companies are able to deliver more human interactions, as they know the full context and history of that customer and how they’ve interacted with the brand in the past.

Focusing on the customer may also inspire changes in your business beyond the changes in your CX process. Building a customer-centric mindset increases the chance of evolving your business in response to customer feedback, not theories.

What Makes a Modern Day Customer Service Platform

Holistic Customer View ✓
Every customer has a timeline unique to their history of purchases, omnichannel interactions, orders and returns – combining all internal and external data into one actionable view.

Powerful Automation ✓
AI and machine learning enhances agent productivity and assesses the needs of your customers in real time to deliver the best outcome in the shortest time.

Truly Omnichannel ✓
Agents can seamlessly switch engagement channels in real time within the same conversation, easily toggling between channels.

Understands Sentiment ✓
Know how your customers actually feel and gain actionable insights across every support channel and interaction.

Customizable To Your Business ✓
Fully actionable integrations with any existing system – internal or external. Let your customer service software match your business.

Download Kustomer’s full Buyer’s Guide to learn what you should be looking for in a customer service software solution, how to evaluate potential partners and how to measure success.

Download Buyer’s Guide


Kustomer Introduces KustomerIQ, Bringing Artificial Intelligence and Machine Learning to Enterprise Customer Service

NEW YORK, NY — October 3, 2019 — Kustomer, the SaaS platform that is reimagining enterprise customer service, today introduced KustomerIQ, embedding Artificial Intelligence and Machine Learning across the Kustomer platform to enhance the customer service experience of companies competing in today’s on-demand world. KustomerIQ uniquely integrates Machine Learning models and other advanced AI capabilities with the Kustomer platform’s powerful data, workflow, and rules engines to enable companies to provide smarter, automated customer experiences that are more personalized, efficient, and effortless. The Kustomer platform stands out among customer service solutions for the comprehensiveness of available customer data and its business process automation that is driven by branchable, multi-step workflows and custom business logic.

“In today’s crowded market, excellent customer service is often the differentiator that builds loyalty and trust between one brand to another,” said Brad Birnbaum, Co-Founder and CEO of Kustomer. “With KustomerIQ and the inclusion of Artificial Intelligence and Machine Learning into our omnichannel platform, Kustomer will now go even further in helping brands automate their business processes, while making it easier for their agents to take action on customer information, ultimately developing a stronger and more profitable customer relationship.”

KustomerIQ brings together a wide breadth of Artificial Intelligence methods such as Machine Learning, Natural Language Processing (NLP), Predictive Analytics, Deep Learning, and Multi-dimensional Neural Network Mappings. Companies adopting KustomerIQ use their own data to train the predictive Machine Learning models, automatically customizing them to address their own business needs. With each new interaction and piece of data, these models learn and self-tune increasing their predictive accuracy and improving the decision making of both the models themselves and the customer service organizations using Kustomer.

Through KustomerIQ, companies will be able to automate manual, repetitive tasks and essential processes of their customer service experiences. In addition, KustomerIQ changes the way companies manage knowledge during a service inquiry by surfacing relevant insights and predicting future outcomes to enhance customer self-service, facilitate real time intervention through recommendations, and streamline proactive outreach. By automating everything and providing the right information at the right time, KustomerIQ frees up agents to focus on more complex and emotional customer interactions, resulting in reduced costs and faster resolution of calls.

KustomerIQ is bringing new smart customer service features to the Kustomer platform, including:

  • Automated Conversation Classification: Intelligently categorizes and classifies conversations using Machine Learning and attributes of the conversation and customer. 
  • Queues and Routing: Routes customers to the most appropriate agent using conversation classification, agent skills, and overall team capacity to drive the machine learning model. As a result, KustomerIQ helps companies improve customer satisfaction, increase first call resolution, and reduce wait and handle times.
  • Customer Sentiment Analysis: Using Natural Language Processing, the Kustomer platform can read messages between customers and agents and quantify how a customer feels about a brand in real-time. Seeing customers’ sentiment helps agents empathize with customers in a digital medium, and thus determine the best way to communicate with them. 
  • Automatic Language Detection: Using Natural Language Processing, the Kustomer platform can automatically identify the language being used in a conversation and then route the customer to an agent that speaks the language. In addition, if a company has pre-written responses (shortcuts) set up in multiple languages, those responses will automatically switch to the language used by the customer to ensure a better experience for both customer and agent. 
  • Suggested Agent Shortcuts: Provide recommended pre-written responses to agents based on conversation and customer attributes to help agents immediately access the knowledge they need to resolve customer issues faster.
  • Customer Self-Service: Automatically suggests help articles from a company’s knowledge base providing an immediate answer to a simple customer questions without interacting with an agent, so customers get answers faster and agents can focus time on more complex customer inquiries. By giving a customer more self-service options it also lowers agent volumes and improves resolution and handle times.
  • Workforce Management: Helps to predict future conversation volume and staffing needs based on historical and trend data of items, such as SLA attainment and seasonality. Can also assist in identifying training needs by providing insights into areas where an agent or agents are deficient. 

To further increase its rapid pace of innovation, Kustomer will triple the size of its development team in 2020. The team will focus on ensuring the continuous improvement of KustomerIQ’s machine learning models and further expansion and integration of innovative Artificial Intelligence capabilities throughout the platform.

About Kustomer

Kustomer is the omnichannel SaaS platform reimagining enterprise customer service to deliver standout experiences – not resolve tickets. Built with intelligent automation, Kustomer scales to meet the needs of any contact center and business by unifying data from multiple sources and enabling companies to deliver effortless, consistent and personalized service and support through a single timeline view. Today, Kustomer is the core platform of some of the leading customer service brands like Ring, Rent the Runway, Glossier, Away, Glovo, Slice and UNTUCKit. Headquartered in NYC, Kustomer was founded in 2015 by serial entrepreneurs Brad Birnbaum and Jeremy Suriel, has raised over $113.5M in venture funding, and is backed by leading VCs including: Tiger Global Management, Battery Ventures, Redpoint Ventures, Cisco Investments, Canaan Partners, Boldstart Ventures and Social Leverage.

To learn more about Kustomer visit www.kustomer.com or reach out by email to info@kustomer.com.

Get the Most Out of Your Kustomer Contact Data with PieSync

Cloud-based technology has revolutionized the way small businesses work. Nowadays, entrepreneurs can access top platforms without spending a fortune or hiring a team of developers. Next to the dozens of benefits cloud applications offer, there comes a challenge: Not all apps “talk” to each other.

Most business tools collect valuable customer and prospect information in different stages of a customer’s journey. But when the apps you use across the sales process are not communicating, you’re left with the inevitable data silos.

To prevent this problem, Kustomer offers several integrations with leading applications, including PieSync (who by the way is connected with 180+ other business tools).

What’s PieSync?

PieSync is a contact synchronization solution for business tools that works 2-way and in real time. Wait… What? Let’s break it down: PieSync consolidates contacts from multiple cloud-based applications in sync. The “2-Way” means that whenever you add or modify a contact in one app, that update is synced back to the other app, and vice versa. The value of bidirectional syncing is that your data will be accurate across all your apps.

Translation: no more out-of-date contact data and no more import/export!

PieSync in Action

With PieSync, you can enrich Kustomer to create a 360º view with data from your CRM, Marketing Automation, Payment processing platform, etc. PieSync allows you to automatically translate all types of data attributes into Kustomer, providing you with the most up-to-date information. This data can be used in different ways to automate, personalize and prioritize your Kustomer conversations and keep your ticket management organized.

By enabling seamless access to rich data, PieSync allows you to exponentially increase your customers and lead engagement rates. Thanks to its Intelligent Rules, you are able to set up more intuitive and complex conditions to automatically create and update your best-of-breed cloud applications. PieSync also supports field mapping to help you associate information fields, including custom fields.

 

Kustomer in Action

Many businesses around the world are working with more than one business application. Wouldn’t it be nice to create your own ecosystem of best-in-class applications?

By leveraging valuable data from many different data sources, you can create a highly personalized experience for your current and new customers. Not only will you be able to create a more dynamic user experience, but you will also be able to define more efficient Business Rules, conditional branching and multi-step workflows that will allow your team to be more productive.

Some examples:

  • Assigning conversations to specific users or teams based on CRM ownership
  • Prioritizing customers accordingly based on billing information
  • Assigning conversations to the right agent based on language
  • Sending automated responses based on the Contact Type of the CRM
  • Updating customer attributes based on conversation attributes and syncing them to your other applications

Top syncs for Kustomer users

Accounting Apps:

  • Kustomer and Quickbooks
  • Kustomer and Xero
  • Kustomer and Chargebee

 

CRMs:

  • Kustomer and Salesforce
  • Kustomer and HubSpot
  • Kustomer and Copper
  • Kustomer and Pipedrive

 

VoIP apps:

  • Kustomer and RingCentral

 

Check all the apps you can sync with!

Configure a connection between Kustomer and another app

 

Need help configuring your sync? Visit PieSync’s Support Center!

About the Author:

Claudia Martinez is a Digital Content Marketer at PieSync. This tech-savvy communicator and marketing expert, creates awesome content and shares on social media what’s going on in PieSync.

Keep AI From Feeling Like Sci-Fi With Our Terminology Guide

When the conversation turns to AI, there’s often a Sci-Fi novel’s worth of terminology and jargon that the uninitiated reader has to decode. If you’re looking at using automation for service, then here’s a quick guide to the difference between AI, Machine Learning, and Deep Learning.

Watch Our Webinar with Solvvy here – The Truth About Bots and Intelligent Automation

Artificial Intelligence as a concept has been around since at least the ancient Greeks, who designed some mechanical devices that could be loosely-termed as intelligent. However the term itself is around 60 years old, and the first applicable AI technologies have only just started coming to market in the last few years.

Machine Learning is a more specific subset of AI. It describes machines’ ability to learn from their mistakes and improve over time. A good example of Machine Learning in practice example is the recent Google AI that beat a world champion at Go. The more the AI plays, the better it becomes at spotting patterns and predicting its opponents’ moves.

Deep Learning is a further iteration of machine learning. It describes machine learning algorithms that run on multiple layers, mirroring how our own neurons function. A now common example of deep learning is the way that smart assistants like Alexa or Siri process speech.

Also important is Natural Language Processing. NLP is the ability for a computer program to understand human speech, regardless of slang or dialect. By being able to make sense of written or spoken language in the messy and error-filled ways humans normally express it, AI capabilities become much more applicable to everyday life.

What does this mean for service? Artificial intelligence and intelligent automation can take over existing tasks and create new efficiencies that your organization couldn’t dream of previously. Machine Learning is just one example. By suggesting responses agents can use to common customer queries, a partially-automated system could learn the most effective replies and language for your customer base. Deep learning capabilities should extend to IVR trees, and put an end to the common “Sorry, I didn’t get” response from many systems that currently rely on processing speech. And NLP is crucial for chatbots, and for analytics that look at all of the conversations your agents have across chat, social, and any other text-driven medium.

It’s important to build a solid understanding of these exciting technologies as they become more prevalent and relevant to the service and customer experience sphere. To learn more, listen to our webinar with Solvvy: The Truth About Bots and Intelligent Automation.

To Bot or Not to Bot? Neither, Start with a Strategy

By Mark Kersteen from Kustomer and Maggie Lin from Solvvy.

Customer service automation is the hot topic of conversation these days, and more specifically, how bots fit into the mix. While intelligent automation is core to both Solvvy and Kustomer, we encourage our customers to not simply take an automation-centric or bot-centric approach, but to first take a step back and identify what your key goals are.

We’ve seen companies jump the gun and add a bot because they felt like everyone else was doing it, only to find it delivered sub-optimal/disappointing results.

In reality, not everyone is using a bot—but many are experiencing mixed results. In our recent webinar, 67% of participants shared that they aren’t using any bot technology today and 72% of participants who have tried a bot have experienced issues.

So, what can we take away from this? It’s important to see the big picture and identify where automation can add value, rather than implementing point solutions like bots and hoping they make an impact. We’ve all been there–it’s easy to get swept up into adding a piece of technology just because it’s what everyone else is doing.

In this post, we’ll tackle a key goal we’ve frequently seen from our customers: how do we increase agent productivity to improve our overall customer experience? We’ll share how intelligent automation can effectively support this goal in two ways by 1. increasing efficiency for customers and 2. increasing efficiency for agents.

Increasing Efficiency for Customers

Empowering customers to resolve questions on their own means agents handle less repetitive questions (and less tickets). This translates into getting back to customers faster and focusing on high-value questions that require the human touch. Increasing efficiency doesn’t have to be complicated. Depending on where you are in your support team maturity, ways to improve include investing in content, intelligent self-service, and end-to-end automation.

Content
While it seems obvious, when companies are scaling quickly, a lot of focus is given on agent enablement versus customer enablement. But, at the end of the day, customer enablement helps agents at scale. In an organization where customer interactions are often 1:1, investing in content is 1:many and scales with the business. Taking the time to create help center articles can save your support team hours of copy-pasting a macro that should be public to customers. Publishing content that helps customers find answers on their own frees up your agents to deal with more complex questions.

Intelligent Self-Service
Investing in content is step one. Intelligent self-service is the next step to making it easy for customers to discover this information. With intelligent self-service, it’s important to understand the underlying technology used to determine user intent. A lot of bots fall short here because they are keyword-reliant or rules-based and ultimately aren’t able to understand the context of a question and the relationship of words unique to a specific business. Self-service eases the workload for agents, but if a bot is falling short of expectations, it can create friction when a customer reaches an agent and has to repeat their question.

End-to-End Automation
The ability to fully automate repetitive transactions is a huge opportunity in customer service. These could be questions around order lookups, returns, refunds, and subscription changes. By handling these types of questions without an agent, support teams can direct attention to complex questions and take on proactive initiatives that scale. The interface for end-to-end automation can be guided steps, or it could be a bot in a chat window. Whichever way you deem the best customer experience, it should be clear that it’s not a human and that it is an automated experience.

Increasing Efficiency for Agents

We’ve spoken with agents who have expressed anxiety about chatbots or other technologies taking over their roles. It’s totally natural to be wary of new technology, but our answer has always been clear: We don’t think there’s anything to worry about. In fact, there’s a whole list of ways that bots and automation can assist agents and make their lives easier. Bots can take over the boring, repetitive, and mechanical tasks that drive agents up the wall, freeing up their time to focus on the interpersonal connections and more emotionally complex tasks that likely attracted them to the profession in the first place.

Conversational Forms
Just because it looks like a bot and acts like a bot, doesn’t always mean it’s a bot. Conversational forms are robots in disguise. When a customer opens the chat window, they’ll feel like they’re chatting to an immediately available agent. The conversational form will start asking the customer questions. These include important queries for identification—name, email address, phone number, shipping info, and whatever else is necessary—as well as more quantitative questions, like asking them to describe the issue they’re having. This way the customer gets the instant feedback they expect on chat, and the agent can jump into the conversation with all the info they need.

Suggested Responses
The scariest thing about pursuing a chatbot strategy is the lack of control. Once you switch on that feature, there’s nothing standing in between your customers and an algorithm that may not always provide the best experience. Enter suggested responses. This system works like the suggested text feature on your phone, but just for service. A computer processes the conversation and generates answers, but instead of sending them straight to a customer, the agent gets them first. This speeds up their reply time, and the system can also learn from the agent’s choices to become smarter. The more agents use the system, the better it gets at helping them, so you can be certain that automation is helping your experience, not holding it back.

Further Uses for Automation
There is a whole world of automation-enhanced solutions to everyday problems for your organization—and the majority of them work behind the scenes. Using an automated system to suggest tags, categorization, macros, and helpbase articles for your agents can save tons of time, and can be much simpler to set up and operate than a customer-facing chatbot. Assisting your agents’ everyday workflows and reporting may not be glamorous, but it can have a massive knock-on effect towards streamlining your experience and increasing efficiency. As Peter Johnson, Kustomer’s VP of Product, summarized in our recent webinar: “Automation is not just about helping the customer, it’s about helping your support organization scale, and identifying areas the product team can improve.”

Final Thoughts

If we can leave you with one bit of advice to take away, it’s this: before pursuing a bot or automation strategy, do your homework and consider your options. It’s crucial to have a strategy, and that you don’t just jump right in. As Kaan Ersun, Solvvy’s SVP of Marketing, advised on our webinar: “Number one, define a strategy, and figure out where the bot can be useful to you, where it won’t work, then pursue new opportunities. Start with the big picture, then move towards implementation.”

Look at the data available to you, and use that to define your strategy going forward. Take some time with your reporting, and see what the most common issues are and where customers are asking for support. Once you start spotting patterns, those can dictate where you’ll go next. Maybe something as simple as an updated help page or self-service tool can cut your service volume in half? If your agents are constantly doing the same things over and over again, solve for those issues first. If your goal is to increase efficiency, then you should be focusing on finding the best method, not using chatbots for their own sake. By looking at the patterns within your support organization, you can start identifying issues that are holding back your experience to dictate your strategy, which is great practice as a whole. That’s the best way to figure out how automation will fit in.

With the right groundwork, you can be certain that when you do start to explore and use new technologies, your efforts will be a success—and will make a meaningful difference for your customers.

The Truth About Bots and Intelligent Automation

84% of the attendees of our recent webinar, The Truth About Bots and Intelligent Automation, consider Customer Experience Automation a priority for their strategy going forward. What options are available for the automation-minded company, and will a bot deliver amazing service AND make you breakfast? Well, not quite. We got to the bottom of these questions on air, and you can too from the recap below.

Watch the recording here.

Peter Johnson, Kustomer’s VP of Product, and Kaan Ersun, Solvvy’s SVP of Marketing, are both authorities on bots, automation, and using intelligent technologies for better service and support. They discussed the pros and cons of the solutions out there, and made some suggestions for picking and enabling more intelligent service.

Is Automation a Priority?

To kick things off, we started with a poll to take the temperature of the audience. We asked, “Is adopting a customer experience automation solution, such as bots, a priority for you https://s29093.pcdn.co/ your organization?” The results were surprising—the majority of respondents were actively pursuing an automation strategy. Here’s the breakdown:

Yes, this year: 40%

Yes, next year: 32%

Yes, within 2 years: 12%

Not a priority: 16%

Terms You Need to Know

To level-set, PJ and Kaan laid out an overview of the terminology they’ll be using when discussing this complicated technology.

While “intelligent” technologies have existed since Roman times, the term “Artificial Intelligence” came into use in the 1950s—though truly intelligent products just started becoming widely available over the last handful of years. Machine Learning is a more specific application, referring to the ability of machines to advance their program and “learn” from their mistakes without additional programming. A good example is the recent Google AI that beat a world champion at Go. Deep Learning is an even more advanced subset, describing computers that use algorithms that mimic the neural networks of the human brain—meaning they can learn on multiple levels without human supervision.

Bots—Are They All They’re Cracked Up to Be?

But how are these advancements being used on a practical level today? Bots are already taking on a variety of service and service-adjacent tasks within the enterprise, from Digital Marketing and DIY Service, to use cases involving virtual assistants. However, these experiments are still in their early stages. While they may help scale your service, they require a lot of effort to build, and lack customer understanding and the ability to deliver a quality, memorable experience. When you look at the cost and effort to build one versus the level of experience they provide, the math is a bit off.

As PJ put it:

“You’ve probably contacted or been contacted by a support system that tried to act like a human being, but clearly is not. One of our best practices is not to try to seem human, because it can really hurt your brand image and experience.”

On top of that, they aren’t exactly plug-and-play. Service teams have to create replies for every possible input, and they need to be customized for the relevant terminology and details of your business. Actually integrating them with your existing data systems can be a headache, plus they need ongoing maintenance every time you add a new feature or product.

Who’s Using Bots?

Bots may not be the tech overlords they’ve been billed as (yet), but other applications of automation and intelligent systems can supe up your support. And, it’s probably not too late. In our second poll, we learned that most attendees haven’t started using bots yet:

We asked, “What has been your experience with traditional bot technology in your CX operations?” and these were the results:

We use a bot today and love it: 9%

We use a bot today and have encountered some issues: 12%

We use a bot today and have encountered many issues: 12%

I don’t use any bot technology today: 67%

From Bots to Conversational Experience

Before you start experimenting with bots, it’s good to know your options. As Kaan recommended:

“It’s key to have an overarching, holistic automation strategy first—then you can deploy bots as point solutions.”

Bots are a part of this strategy, but not the only focus. Instead, you can also use automation in conjunction with other integrations and platforms to create a stronger experience. Conversational forms look like a chat, but can be used to gather customer info and issues before handing off to a more capable agent to handle the issue. A system that automatically suggests responses to agents works the same as a bot, but uses the added layer of human oversight to learn the right way to respond by tracking your agents’ decisions. And automation is useful for suggesting tags, categorization, macros, helpbase articles, and assisting workflow and reporting—all things that can speed up your experience and make it more efficient, without directly interacting with customers.

As PJ summarized: “Automation is not just about helping the customer, it’s about helping your support organization scale, and identifying areas the product team can improve.”

Kutomer and Solvvy work together to make conversational experience a reality. If you submit a question to Solvvy and can’t find the answer, you can choose to instantly open up a chat in Kustomer and get the answer. Kustomer’s conversational form then collects your personal information, then connects you with an agent who knows your whole customer history.

Where to Begin?

Where do you start the process of using automation or bots strategy if you haven’t already? Kaan had some advice: “Number one, define a strategy, and figure out where the bot can be useful to you, where it won’t work, then pursue new opportunities. Start with the big picture, then move towards implementation.”

Adding to Kaan’s advice, PJ suggested going straight to the data: “First thing: Look at your reporting, and see where you have the highest level of support volume. Look for patterns, see which questions your customers are asking, and what the most repetitive tasks are for your agents?”

If you’re taking a wide-angle approach and carefully planning your strategy, instead of leaping head first into messing around with a bot, your initiatives are much more likely to be a success.

You can always watch the recording HERE, and for more great insights into service, experience, and technology, follow Solvvy and Kustomer.

Why Companies Are Switching from Ticketing Systems to Kustomer

Ticketing systems have been around for decades. Ticket numbers, formal emails (“don’t reply below this line”), isolated data (“what is your order number?”), have been a part of our lives as customers and customer support professionals. It’s hard to believe a better world is possible. Kustomer, built by industry veterans, was created with a different vision in mind—a customer-centric platform that ties together all the conversations and business information about a customer into a single timeline, together with powerful workflows that enable customer-first companies to execute their customer experience vision. In the past year, a number of customers have successfully migrated from ticket-based solutions to Kustomer. Here are a few items that CX agents and executives who made the switch have highlighted about making the move:

1) From Isolated Tickets to a Single Timeline View of the Customer

How many platforms does your team use to communicate with customers? Is your team in constant need to merge tickets? Because tickets from different channels are often disconnected, it’s easy to run into a customer who is chatting with another agent while you’re in the middle of replying to their email. Or worse, you might reply without knowing that they’re already being helped.

In Kustomer, you can see all the communications with your customer in one place. That means that real omnichannel communication is possible. You can go from emailing with a customer to chatting with them, to calling them on the phone, and see all those records in one conversation. That’s because the customer is the atomic unit of our platform—everything revolves around them.

2) From Disconnected Solutions to Actionable Integrations

How many tabs does your team need to keep open at the same time? When your customer support platform is disconnected from the rest of your platforms, agents need to keep copying and pasting customers’ email addresses into your admin systems to get even basic information about the history of their interactions with your company—past orders, delivery status, etc. Kustomer pulls data from all your platforms and tools and arranges it in a way that makes sense for your business.

With Kustomer’s single timeline view, the customer is the focal point, not individual conversations. Not only does Kustomer merge every interaction into the same conversation automatically, it also integrates with your other systems—like Shopify or JIRA, just to name a few. That means you can see when orders are dispatched and delivered, or previous items that customers have added to their carts or subscribed to on your site. All of this is displayed in that same timeline, so you have a deeper context whenever they reach out. Everything is completely customizable, so it’s easy to create a view that empowers your team to tackle your specific business challenges.

With this level of integration, tasks like returns or reimbursements can be completely automated (as we’ll discuss in the next section). No matter if your business is pizza, shoes, or software, Kustomer can be customized to show your agents everything they need to know in a single window. Orders, shipping info, product or version number, buyer and seller information, and social interactions can all appear beside each customer in bespoke “K Objects”. This makes it easy for agents to get the whole picture and take the next best action, or communicate with the right parties while staying on one platform.

3) From Repetitive Tasks to Intuitive Automation

Kustomer makes it easy to automate commonly-used workflows so that your agents can focus on connecting with customers rather than rote tasks. Don’t be limited by basic workflow functionality that won’t simplify your agents’ day-to-day work. Now you can define intelligent, branched workflows and reports encompassing all customer-related systems in your business.

Because Kustomer integrates with your other platforms, it’s way more powerful than just showing your customer history—it allows you to act on it. These branched, multi-step workflows make it easy to efficiently scale your team and automate simple tasks. Sending instant follow-up emails or processing a return is now only a click away and no longer has to take your agents’ attention away from the customer.

4) From Reactive Support to a Proactive Experience

Proactive service solves for what your customers need. That means it may be something they haven’t even asked for, like a faster delivery to avoid an incoming storm that might cause delays. It’s one of the best ways to build stronger relationships and deliver meaningful experiences. Ticketing systems are inherently reactive, as agents only respond when customers have a problem or a question. Because Kustomer keeps all of your customer information in one place, you can create granular searches for customers around specific behaviors or qualities, all on the same platform. That means your service isn’t just efficient—it’s smart.

If you want to build customer loyalty, you can search for customers that may have bought a product that could give them an issue, then send them all a message proactively. Let’s say your new mascara is mislabeled as “Vegan”—you can look up all the customers who have preordered it, then send them an email letting them know the mistake and offering a free refund or exchange if they don’t want it—all before their orders have arrived. Or if there’s going to be a storm that affects customers in a certain geographic area, you can notify all the customers with orders going to that region with a list of options before their shipment is delayed. With all your customers’ information in one place, it’s easier to surprise and delight them than ever.

When you combine this robust search capability with automated workflows, intelligent and proactive outreach can become a reality.

By putting all the information about your customers in a single view and making it easier than ever to act on it, Kustomer is winning over companies across industries. To try our powerful platform for yourself, schedule your demo today.

3 Examples of Conversational Experience

It’s good to have a conversation with your customers, but talking alone isn’t enough. Encouraging customers to contact you over their preferred channels means you need to be ready to respond just as fast as their closest friends. Often, conversations can go in different directions. Sometimes customers may be trying to make a return when what they really need is an exchange. Or they may decide to buy a new product in the middle of asking about a different one. That means that conversational commerce and conversational service are two sides of the same coin. If you want to engage your customers on a 1-1 basis and in real time, then your entire customer experience needs to be part of the conversation. A truly conversational experience is hard to find, but we’ve shared some examples from Brad Birnbaum’s latest piece in Forbes to give you a better idea:

Example 1: IoT

Problem: Your customer’s smart speakers aren’t connecting to WiFi.

Conversational Solution:

  • Your proprietary app brings up an FAQ article when it detects that your customer is not connecting to WiFi.
  • Your automated customer service platform sends an email with an instructional video and support desk information if it detects that your customer has reset their device three times or more.
  • You assign customers who have had multiple problems with high-priority when they call your customer service number so they connect to an agent quickly.
  • Your agent knows that they’ve already received the FAQ and video because your platform gives them a single view of the customer. With that, they can skip ahead to advanced troubleshooting so the customer doesn’t have to repeat the same steps.

Example 2: Meal Delivery Subscription

Problem: Your customer needs to change their subscription and delivery dates.

Conversational Solution:

  • If the customer has to change their delivery location or date, a chatbot or automated solution should instantly handle these simple tasks.
  • If the request is more logistically complicated, like pausing for a week then delivering to a different location, the request should be elevated to an agent.
  • If the request is more complex than that, like changing dietary requirements, agents should get on the phone and consult with them 1-1 to deliver the best possible experience.

Example 3: Clothing Subscription

Problem: Your customer needs a more consultative experience.

Conversational Solution:

  • If customers are asking for a simple request like changing the date of the delivery, agents should ask questions and get more information.
  • If there is a bigger reason, like they’re getting a new job, then an agent should be empowered to step up and act like a stylist to pick more formal options.
  • This more hands-on experience encourages customers to upgrade to a higher subscription tier in the future.

Read the full Forbes article here.

To see how can deliver a truly conversational experience with Kustomer, request a demo today!

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