One of the biggest shifts over the past few years? A digital-first mindset. While phone support isn’t going anywhere, when you force consumers to switch platforms in order to get their questions answered, you give them a reason to abandon their purchase or generate negative feelings. The less effort, the better — and with the digital-first consumer, chat is often better.
In an effort to understand how brands are currently using live chat for business, why some have not yet done so, and whether there is a disconnect between customer needs and brand expectations, Kustomer went out and surveyed over 100 CX professionals and compared these findings with our recent consumer research.
What is Live Chat for Business?
Live chat is a customer service widget that allows your questions to be answered effortlessly within the web browser. Live chat allows customers to effortlessly communicate with customer service representatives in real time, without having to leave the platform they are already doing business on. The live chat allows customers to communicate with customer service at stores or brands in real time without having to talk with a customer service representative.
Why Consumers Love Chat
Think about the online shopping experience. You find the perfect Christmas present for your son, but have a question about whether batteries are included. So, instead of picking up the phone or searching for an e-mail address to contact the business, there is a chat window right there on the page that can allow your questions to be answered effortlessly. While switching channels may not sound like a deal breaker, the data says otherwise.
According to recent consumer research conducted by Kustomer, 79% of consumers get frustrated when they can’t contact customer service on their preferred medium or platform, and 81% of consumers would abandon a purchase due to a poor service experience.
Chat, as well as social media messaging, allows you to instantly meet your customers where they are, whether that is browsing online for products, checking their shipping status, or perusing your social channels. Research from Matt Dixon revealed that only 9% of customers who have low effort experiences display any kind of disloyal attitude or behavior, compared to 96% of those customers with high effort, difficult experiences. And chat does a great job of delivering this effortless quality customer service experience.
The Business Disconnect
Curiously, businesses are not aligned with these consumer preferences and wants. Only 25% of surveyed customer service organizations are currently using chat, and 18% report they currently use chatbots. When taking into consideration the effortless, fast service that modern customers demand, the vast majority of businesses are missing a huge opportunity and leaving themselves open to competitors.
The top two reasons that companies have not yet adopted chat software, speak to a lack of time, resources or strategy internally: the organization does not know where to start, or they have staffing constraints when it comes to managing more channels. However, the third most popular reason speaks to the massive disconnect between CX organizations and consumers: businesses report that they don’t think their customers want or like it. However, according to Kustomer’s recent consumer research, customers rank live chat as the second most popular channel or tactic for contacting customer service, right below phone.
Top Reasons CX Organizations Haven’t Adopted Chat
Don’t know where to start
Customers don’t want / like it
Lack of customizable solutions
Lack of executive buy-in
Additionally, many organizations report that they are prevented from adopting chat because of the lack of customizable solutions. Seventy-five percent of CX teams say that matching the chat experience to the overall brand experience is important, so slapping any old chat widget on your site just won’t do. Make sure that your customer service CRM can allow your business to build or integrate chat widgets seamlessly, ensuring that all customer data and history is integrated within the chat experience, while maintaining brand guidelines.
When it comes to chatbots, the reasons for lack of adoption differ slightly from live chat:
Top Reasons CX Organizations Haven’t Adopted Chatbots
Not sure of the benefits
Lack of resources to manage chatbots
Customers don’t want / like it
Tried, isn’t effective
Lack of executive buy-in
As chatbots are quite new, and often involve buying a pricey solution or building one with an internal team, the top reasons for lack of adoption make sense. But 61% of the younger generation prefer self-service over talking to a company representative, meaning that the benefits are clear: your customers now expect chatbots as an option.
Additionally, chatbots free up agent time for more complex and proactive support. They can be used to collect initial information, provide responses to simple questions, and even complete standard tasks like initiating a return or answering an order status question. 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, chatbots 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.
Look for a platform that leverages chatbots and AI-enabled deflection to act as a first line of defense, optimizing a customer’s ability to self-serve so agents can focus on the most important cases and deliver the highest impact.
Want the complete findings from our research on chat? Download the report here.
Conversational automation is crucial to great customer support. An effective customer service chatbot can communicate with customers and answer important questions, streamlining the customer support process.
How to Understand Your Metrics When Building a Customer Service Chatbot
Containment rate, or its alternative name, “deflection rate,” is the percentage of total conversations fully handled by a chatbot, and is a key metric to track when trying to figure out how well your chatbot is performing. Customer satisfaction is also important. Keep in mind how the introduction of a chatbot could alter existing performance indicators. For example, will the average handle time increase now that agents are only handling more complex inquiries? Ultimately, a well-defined customer service chatbot program will be able to communicate increased agent efficiency and customer satisfaction, which equals a reduction in the cost of care.
Learn how to build a chatbot that makes communication easy with these six chatbot tips, and watch customer satisfaction skyrocket! Now, let’s explore how to build an effective customer service chatbot program.
1. Start With Hello
Your first customer service chatbot does not need to be elaborate. In fact, we recommend against it. When you are first getting started, pick one or two simple (but useful) use cases to automate. Then, you can learn and iterate as you discover how your customers prefer to interact with a chatbot. No one gets it perfect right out of the gate, so avoid wasting time by trying to build something “perfect”.
2. Leverage the Agent
We have seen countless customer service chatbot programs fail to engage the existing front-line customer service team when designing an automated conversational experience. It’s great to learn from data and prevailing customer experience research, but your customer service agents are the ones who know how your customers are interacting with the chatbot. Treat the bot like another agent: when you need performance feedback, use its peers.
3. Templates, Rules, and Machine Learning
Not all customer service chatbots are “conversational AI”, because not all use cases require machine learning. Very effective bots can leverage rules and simple conditional logic — it all depends on the use case. Similarly, natural language processing is great when you have a customer service chatbot with many different skills and a large corpus of knowledge.
Why make your customers trudge through structured flows when they can ask the question directly? In both cases, we recommend leveraging buttons, quick replies, and other conversational templates that help the user move through the conversation quickly and efficiently.
4. Know When to Handover
A customer service chatbot is not a replacement for a human agent. Often, you need to give the user a way to bail out of tough conversations and difficult questions, and that’s alright. Chatbots are excellent at fully resolving low-level queries because they often suit the modern customer’s habits of utilizing mobile technology to solve simple issues. However, just because an issue is complicated does not mean a chatbot cannot be helpful. Consider how you can use the bot for information gathering and light triage before routing to the right agent. In these cases, the customer service chatbot helps reduce handle time and expedites the customer’s support request.
5. Automation Happens Elsewhere, Too
Customer service chatbots get a lot of attention when it comes to automation. Often it’s the mental model in our heads for intelligent customer service. Consider other ways you can streamline the customer support experience with a chatbot, and leverage additional intelligent services: automatic tagging, routing, and prioritization for the agent (just to name a few).
6. Be Customer-Centric
At the end of the day, the success of your customer service chatbot comes down to how well it fits into the customer support journey and cadence strategy you have outlined for your customers. Consider different segments of customers that might prefer automation to “direct human” connection. Perhaps automation can be more helpful at the end of a live chat interaction than at the beginning. Take a good look at your customers, and we’ll help you find out the right size that fits. In doing so, you will improve your customer experience and customer satisfaction metrics. Discover Kustomer’s intelligent chatbot solutions today.
Since the dawn of the computer age, engineers and designers have had to consider how humans can, and should, interact with new technology. They designed and implemented interfaces that altered our mental models for exchanging information and we had to learn novel symbols, workflows and behaviors in order to interact with these new platforms. Basically, we conformed to the computer, not the other way around. Yet over the last few years, a new service has emerged that represents a departure from this norm: the chatbot, a digital experience that replicates and automates the medium of human conversation.
What Are Chatbots?
If you’ve interacted with an online chat popup, there is a high probability you messaged with a chatbot first, and conversed with a human second. Conversational chatbots are not as complex as you might think. These digital customer service assistants can tap into customer data and knowledge bases stored in their database to help answer common user questions based on the user’s needs or inquiries.
For example, if a customer wants to know what the store operating hours are, they can reap some of the customer service chatbot benefits by getting an automated response with your store’s intelligent chatbot and human customer service agents are now free to focus on more high-level or specific inquiries, conducted through live chat, that might be a bit too complex or nuanced for the chatbot to answer.
The Three Customer Service Chatbot Benefits You Need to Know
Text-based support and conversations are the new interface, but it can get repetitive and it’s difficult to scale a one-to-one communication operation. This is where conversational chatbots come into the picture. Smart businesses use automation to help support more customers who prefer digital communication.
As automated interactions, conversational AI chatbots can essentially exist wherever human-to-human dialogue is used to change information and accomplish an assignment. The best way to experience the benefits of this kind of automation is to focus on the conversations that you are already having with your customers. Here is where you’ll see an immediate impact:
Faster Response Times: Chat and messaging work best when someone can immediately respond, not when customers are waiting in a queue because agents are tied up. With a chatbot, each message is seen and responded to, and your most common questions are quickly addressed. Further, by allowing chatbots to handle initial information gathering, agents are able to join and resolve conversations faster if escalation is needed.
Better Agent Utilization: No one wants to answer the same question over and over again. Chatbots remove basic, low-level questions from the workload. By reducing the number of messages your agents receive, you will increase the efficiency of your support operations and be able to focus on the more complicated questions and tasks.
Data on What Customers Need: Chatbots automatically collect and analyze your customers’ questions and issues. Instead of manually reviewing conversations or asking agents for anecdotal insights, you can review organized and aggregated intent data.
Implementing a Chatbot for Superior Customer Service
Five to Ten One-Touch FAQ Answers: Focus on supporting your most common questions that can be addressed with one response. You can direct customers to an FAQ article, or deliver a conversational answer directly.
One Common Workflow: Similar to the above, there are certainly interactions that require authentication or simple lookups from another data source; these aren’t hard to tackle, just usually require manual attention. Verify, authenticate, and pull in data to automate simple workflows. If you’re an e-commerce business, “Where is My Order” or “Return Status” are great, universal examples.
Easy Agent Takeover with Routing: Once a chatbot cannot answer a question or resolve an issue, make the handover process to human support quick and painless. Better yet, ask a few questions just prior to the handover to give agents context for the conversation and route to specialized teams.
Natural Language Processing: Natural language processing and machine learning — the “AI” of conversational AI — make it possible for your bot to understand and respond to customer intent, not specific keywords. This allows the bot to keep up with the way each customer thinks, communicates, and switches topics, ultimately leading to higher understanding and better resolution rates across all conversations.
Want to learn more about how chatbots can transform your customer experience? Check out how Kustomer powers intelligent self-service here.
If the events of this year taught those of us in the customer experience world anything, it’s that we can never stop innovating to be more customer-centric. We can’t hope that we will “get by” just a little longer with legacy CRMs and support tickets. We must embrace change and adapt quickly to meet today’s consumer expectations for a smart, omnichannel experience powered by a modern CRM—the key to scaling CX, meeting explosive growth, and adapting to change.
Some argue that 2020 has signaled the decline of ticket-based support systems. Why has the pandemic emerged as the straw that finally broke the legacy CRM camel’s back? The data tells the tale. Recent analysis of e-commerce trends shows a staggering 10 years of growth in just 3 months at the beginning of 2020. And that was just the early stages of lockdown. As chaos and uncertainty took hold, CX teams were inundated with customer calls and support tickets as they struggled to keep up with questions, changing plans, requests for assistance, and the demands of going direct-to-consumer.
But that’s only where the challenges begin. 2020 also forced organizations to accelerate digital transformation by 6 years to adapt to the “new normal” of stay at home orders, remote workforces, supply chain disruptions, shipping delays, and the economic slowdown. Along with this digital transformation, many CX leaders are realizing they need to follow the lead of the direct-to-consumer disruptor brands that are differentiating themselves, and thriving, by delivering a modern consumer experience.
The DTC Disruptor’s Secret Weapon: Intelligent CX Focused on the Whole Customer
As the pandemic took hold, most direct-to-consumer innovators were many steps ahead and better prepared to deal with the curveballs 2020 delivered. These businesses started with the right culture, philosophy, and customer-centric CRM platform. They built their business to connect with customers at scale. A great example of this is The Farmer’s Dog, a company dedicated to delivering safe and healthy pet food, who totally nailed the customer-first approach. Their customer service agents connect on an emotional level with their buyers using whatever channel the buyer selects to educate and foster authentic relationships. This takes a level of insight tickets can’t provide.
UNTUCKit is another great example of a customer-centric brand. They ensure their stellar shopping experience is supported across every customer touchpoint, especially support. Team members have a virtually seamless process for seeing customer history, gathering the right data points, and resolving customer inquiries.
What Makes a Modern CRM?
If tickets aren’t the ticket, what is the secret to direct-to-consumer success today?
Visibility to Care for the Whole Customer
Now more than ever, customers feel they’ve lost control and trust. Zappos and Amazon have set the bar high with proactive, rapid, data-driven customer experiences. Modern CRMs can help brands rebuild that trust through data-driven conversations informed by a view of the whole customer. Agents must have complete visibility across systems to understand the consumer and their entire situation. But with a plethora of data, and a growing number of channels to monitor, we need AI to unlock these insights. Efficiency is the name of the game in customer service, and AI is a true force multiplier, enabling customer service teams to work more efficiently and focus on the customers who need the most help. Contact centers using ticket-based systems, while relying on siloed customer data, simply cannot deliver the type of experience customers demand today.
Omnichannel Customer Experience
Omnichannel support means a customer can connect with your business anywhere, anytime, and with any method—or even with multiple methods or channels. If a customer wants to reach out via email and then switch to chat, so be it! It’s the experience a new generation of consumers expect. This requires companies to break down silos and integrate their data for a picture of the whole customer across channels. Consumers must be able to switch channels mid-conversation and leverage the best channel for each conversation’s purpose. Our research shows that nearly 90% of customers are frustrated when they can’t contact a company on the channel they prefer. That shouldn’t be a surprise—we all know customers want what they want.
Omnipresent, Guided Self-Service
Just as customers expect more tailored and personal communications, they also demand self-service options for immediate resolution. As our new AI e-book explains, AI is being rapidly adopted in contact centers to act as the first line of defense, amplify performance, and create strong efficiencies. The volume, velocity, and variety of customer data today overwhelm organizations without the technology, processes, and operational capabilities to integrate siloed data and personalize communications. AI is transforming customer experiences, and for good reasons.
Happy Agents, Happy Customers
Research shows companies with excellent CX have employees that are 1.5X more engaged than employees at companies with less satisfactory CX; additionally, companies with highly engaged employees outperform their competitors by 147%. AI is also vastly improving agent productivity and reducing churn for contact center leaders. AI can have a dramatic impact on the customer experience and satisfaction, which in turn makes the employee experience far more interesting and exciting.
AI makes jobs more meaningful and less frustrating by deflecting much of the grunt work and alleviating manual and repetitive tasks agents hate. Agents don’t need to waste time transferring and redirecting customers. Rather, conversations can be automatically classified and routed to the appropriate agent for a speedy and personalized resolution. Not only will this reduce wait and handle times, but it will also maximize team capacity by directing real-time conversation traffic to the right person at the right time.
Realizing the Intelligent Customer Experience
You need a modern CRM to help you execute your digitally advanced, customer-first approach. Leading contact centers have indicated that integrated platforms and data analytics are important in gathering insights into the customer journey. Enter the Intelligent Customer Experience, a culmination of all of the improvements we just discussed.
Intelligent CX means leveraging a modern customer-centric approach and advanced AI to create a smarter, faster, and more enjoyable customer experience. It’s about delivering results fast using the power of AI and data from all channels, whether that be via a call, chat, email, tweet, or all of the above. Your customer service agents will feel more informed since you’ll be empowering them to provide real value, not just closing a ticket or processing a transaction. AI uses context and conversations to make it easy for customers to get help, while allowing agents to provide more personalized service at scale.
We’ve seen dramatic changes since March of this year that have accelerated every aspect of digital transformation. We recently launched Kustomer IQ for omnichannel deflection, sentiment analysis, and intelligent routing. Check out more details here.
Customer Care Delivered in a Remote Environment
The pandemic has certainly upended the notion of the traditional 9-5 office. Companies are racing to adapt to a distributed work model, and technology is the biggest driver in adjusting to operating remotely. The next generation of customer service CRM does more than just manage support conversations. It enables the delivery of the customer experience from anywhere, through remote work orchestration and oversight. Taming the CX frankenstack is another step toward easing the remote transition. Modern CRMs must allow organizations to streamline integration of platforms, data sources, and channels to make remote work.
Collaboration is key to delivering an exceptional experience, so the modern CRM should provide a platform for customer service representatives to work together, to deliver service and support more efficiently and effectively. Collaboration between agents enhances the quality of answers provided to the customer by leveraging subject matter experts. At Kustomer, we believe the collective knowledge of experts makes your customer service organization stronger overall. In fact, we’ve embraced the use of Collaborators, users from other teams outside of support that can view conversations, customer history, and searches. By setting up Collaborators, other team members or departments can help you solve customer questions with internal notes and @mentions, see customer feedback, and more.
The Demise of the Dreaded Ticket
2020 will be the beginning of the end for legacy CRMs and transactional ticketing systems that were built to manage cases, not customers. Personalized support has been a key tenet of the business-and-buyer relationship from day one. Every customer wants to feel like they are known, respected, appreciated, and well-served. They certainly don’t want to be insulted by an interrogation. Traditional ticketing systems will be left behind, as customers expect more and the world continues to converge quickly.
Intelligent, modern CRMs enable true connections to be made with customers in their greatest times of need, by making it easy for agents to come from a place of understanding and context, consistently. This requires unlocking the value of data shared between different teams (such as marketing and customer service), creating new roles to act on the data, and leveraging new and modern technology.
Download the AI for CX e-book to learn more, and take a look at how Kustomer can provide the tools you need for exceptional DTC customer service.
Every consumer has a different expectation as to how they believe they should be treated by organizations they do business with. Perhaps I wouldn’t hesitate to ask for a full refund and an apology when I feel I’ve been wronged, whereas you wouldn’t be caught dead being so demanding.
But while we all have our minute differences, it is also true that consumer expectations generally shift with the times, and have clear generational differences. This past year has brought a significant amount of changes, and businesses may feel more in the dark about what their consumers are demanding. We wanted to pull back that curtain.
Kustomer surveyed over 550 US-based consumers to better understand what they expect from the customer experience, where organizations are falling short, and how expectations have shifted across generations. According to our research, 79% of consumers say customer service is extremely important when deciding where to shop, and many consumers are more picky with where they spend their money than ever before. Read on for the findings from our research, and for strategies to deliver on consumers’ growing demands. You can download the full report here.
We Must Treat Customers as Humans
If 2020 has taught us anything, it is that empathy is of the utmost importance when dealing with customers. As the world has drastically changed, and individuals feel more stress and anxiety than ever before, the potential to brighten someone’s day with a simple support interaction is hugely impactful.
According to our survey, 69% of consumers expect an organization to prioritize their problem if they are upset. Through a combination of sentiment analysis and intelligent routing, your customer service platform should be able to move upset or loyal customers to the front of the line and immediately get them help from the most appropriate agent.
Additionally, 53% of consumers expect a business to know about them and personalize how they interact. To create these meaningful relationships, companies need to adopt technology that allows them to see customer history, issues and behavior in context, no matter the platform. According to Amy Coleman, Director of CX at Lulus.com, the humanity of customer service is often lost in call center environments. “I think that one of the downfalls to old school ticketing systems is that it’s no longer about people. It almost becomes like data entry for those agents that are working on the same thing. It’s how many tickets there are,” said Coleman. “We were never thinking of it in terms of the human beings that are on the receiving end. And I think that’s what Kustomer has really done for us, it’s allowed us to spend the time with the human beings that are on the other line and spend more time developing our team.”
One thing is clear across the board: consumers expect retailers to know how they’ve interacted in the past, what issues they’ve encountered, and they want organizations to actively make amends. A whopping 76% of consumers expect companies to proactively follow-up and reach out to them if there is a problem. Whether it is a winter storm delaying a shipment, a new safety policy, or a fulfillment issue, proactive outreach is not only a nice benefit, it is now an expectation. Proactive communication can provide even more value when you use it for actions like reengaging unhappy or complacent customers, and building brand loyalty with targeted offers. Make sure your platform can power bulk messaging, targeting specific customer segments based on your unique data, like orders, location, or CSAT. In no time your customer service team will turn from a cost center into a profit center.
The Need for Speed in CX
We’ve all been there. Too much to do, too little time. This turn of phrase is even more pertinent for customer service organizations. Delivering real-time service is inherently difficult without endless resources, especially during peak shopping periods. But it is truly what your customers expect.
Seventy-one percent of consumers believe their problem should be solved immediately upon contacting customer service, but 52% report that they’ve experienced hold times longer than fifteen minutes. That’s a massive amount of consumers whose expectations are not being met.
Luckily, thanks to automation and artificial intelligence (AI), businesses now have the opportunity to provide more self-service options, freeing up agent time for complex and proactive support. In fact, 53% of consumers prefer self-service over talking to a company representative, meaning AI-powered experiences fulfill their needs. Tools like chatbots are growing in popularity with both businesses and consumers, with 53% of consumers saying that chatbots improve the customer experience. They can be used to collect initial information, answer simple questions, and direct customers to a help center if human intervention is not needed.
These tools 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. Additionally, 42% of consumers reported that they would be willing to buy a product or service from a chatbot. This transforms AI-powered chatbots from a deflection tool into a revenue generator, with the ability to suggest similar products, or answer questions consumers need clarification on before buying.
To read the full report, including industry and demographic data, click here.
In case you missed it, last week Kustomer hosted a series of events all around switching from traditional ticketing systems to a modern CRM for customer service. The week was action-packed, filled to the brim with insights from Kustomer executives and customer-centric brands like Lulus and Ritual.
It’s not too late to gather insights from the week. Below you can find four key takeaways from #MakeTheSwitch week, and what they mean for your brand.
1. Treat Customers Like Humans, Not Tickets
Many companies are still relying on the old model of customer service, where they treat each new interaction as a separate event handled by different people across a variety of siloed platforms. To personalize a customer’s experience, you have to know the customer—and that requires data. A platform that brings all the data about a customer into one place helps customer service agents understand the context of a customer’s conversations and helps them deliver more efficient, proactive and relevant service.
Amy Coleman, Director of CX at Lulus.com, thinks that the humanity of customer service is often lost in call center environments. “I think that one of the downfalls to old school ticketing systems is that it’s no longer about people. It almost becomes like data entry for those agents that are working on the same thing. It’s how many tickets there are,” said Coleman during a Thursday afternoon webinar. “We were never thinking in terms of the human beings that are on the receiving end. And I think that’s what Kustomer has really done for us, it’s allowed us to spend the time with the human beings that are on the other line and spend more time developing our team.”
Eric Choi, Community Support Manager at Zwift, said during a Friday afternoon LinkedIn Live that he made the switch to Kustomer because his team was looking for a platform that was more human, and allowed them to interact with their members in a more organic way. “The old ticketing system made me feel… like a deli counter. You pull a ticket, you get answered, you throw the ticket away and then you move on.”
When all customer information is available at the click of a button, agents are able to personalize the customer’s experience by giving fine-tuned advice, addressing problems proactively, and suggesting other products or services the customer might enjoy. The result? An efficient but personal interaction that builds a lifelong customer relationship.
2. Unlock the Power of Data Through a Customer Service CRM
As Kustomer CEO Brad Birnbaum said in his Tuesday afternoon LinkedIn Live, an effective CRM should allow you to fully understand the relationship that your business has with each and every customer, and leverage data in order to do that. Legacy CRMs were built to manage cases, not customers. And you shouldn’t have to pay more for operational solutions AND modern communication tools in order to provide effective support.
Coleman agrees that e-commerce companies “absolutely have to be able to access data around what your customers are contacting you” about. Before making the switch to Kustomer, Lulus didn’t have any data because their platforms weren’t talking to each other, and that was a big issue. A modern customer service CRM should be designed to connect seamlessly with your other data sources and business intelligence tools, while taking the place of your support platform, contact center routing software, and process management solution.
3. Cut Down on Tickets With an Omnichannel Approach
In a multichannel support environment, each channel lives in its own silo with its own dedicated team of agents, with limited communication or sharing of information between channels. As a result of this fragmented experience, customers will have to take the time to repeat to the second agent what they told the first agent. In addition, multichannel support leads companies to focus on resolving tickets, rather than building stronger customer relationships, because agents lack a holistic view of each customer.
After switching to Kustomer, Coleman truly realized how many omnichannel conversations were taking place within Lulus’ customer base. With a truly omnichannel customer service CRM, Lulus “ended up merging or cutting [their] tickets down significantly.” Agent collision never occurs when communication channels are integrated, because agents can view the conversation and maintain context even as customers engage through multiple channels.
Michelle McCombs, Vice President of Safety and Support at HopSkipDrive, has now structured her team so they are all omnichannel. With Kustomer’s timeline view, and intelligent queues and routing, her team doesn’t have to go and find what they need to do next. All of her agents “live right there in their one space and… and get to work.”
4. Make the Agent Experience Effortless and Fulfilling
Ultimately, agent happiness directly translates to customer happiness. The more information that agents have at their fingertips, and the more they are able to focus on quality instead of quantity, the happier they will be, and the happier they will make your customer base.
Andrew Rickards, Director of Customer Experience at Ritual, has experienced this first hand. “It goes without saying customer service can be a thankless job and even … the best spirited individual can find those tougher days. So for me, it’s looking at the agent’s experience and understanding what the points of friction are and removing them, so what is already a tough job doesn’t have to be any tougher,” said Rickards. “When I talk about agent happiness, if you look at the internal surveys we do, to see just how people are on a quarterly basis, a lot of the questions that would indicate day-to-day stressors…we improved on those results post-Kustomer switch.”
Coleman agrees, and sees how making the switch to a more effortless platform can impact agent development. “I do feel that we’ve had less turnover due to the fact that the platform is easier, to the point where we’ve been able to actually focus our leadership on actual leading instead of micro managing,” says Coleman. “And what I feel is the most honorable and noble career, which is the service of helping other people, it gets lost in the abyss of really complicated workflows. And so Kustomer has given us, has given me as a leader, so much value, because I’m actually able to lead people for who they are based on their individual strengths and opportunities.”
Click here to learn more about how making the switch could be a gamechanger for your team.
In this episode of Customer Service Secrets, Gabe is joined by Aarde Cosseboom and Vikas Bhambri to discuss how to use AI in contact centers. Aarde is the Senior Director of Technology and Product for Global Member Services at TechStyle. He’s spent the last decade working in e-commerce and is the author of the book Enable Better Service. Vikas, a familiar guest on the show, is the SVP of Sales and CX at Kustomer and a 20-year CRM / contact center veteran. Both Aarde and Vikas have extensive knowledge on the use of AI in customer service and they have come together to discuss how other businesses can optimize with the help of AI.
“Omnibot”, The Omnichannel Bot
Customer expectations have changed significantly over the last few months, and companies are starting to feel the strain— especially in regards to their AI. While autobots have a reputation for dehumanizing companies, we are starting to rely on them heavily as customer needs increase. To ensure chatbots have a positive impact, Vikas and Aarde focus on making sure they are used as an omnichannel tool. Aarde states, “You can’t just have a chatbot on your website anymore, and it only be in your chat profile. It’s gotta be across all of the different channels that you use to support your members.” As customers switch channels, the bot needs to be available to support your customer on their preferred channel. Gabe, Vikas, and Aarde called this adaptable bot an “omnibot.”
Knowing the need for effective AI, and bots that function on multiple channels, Vikas and Aarde discuss who should build the bots and how they should be built. Because coding and creating AI can be taxing, they recommend finding a good partner to help, as it will be a better use of resources. As for how an omnibot should be built, Vikas notes the need for authenticity to the brand. He states, “If you’re a fun hip brand, you want to keep it relative to that. If you’re maybe a more mature brand, you want to keep it in tune with your … general reputation and what your customers expect of you.” In other words, make sure that the bot matches your brand. And, as an additional note, let customers know they’re talking to a bot. Customers don’t like to question whether they’re talking to a person or not.
How to Humanize a Customer’s AI Experience
One of the main concerns with using chatbots, even ones that are authentically built to the brand, is that consumers lose the human touch of customer service. This is a valid point, but Vikas and Aarde explain ways to overcome that while still increasing efficiency. To humanize a bot experience, have a good team behind it. In regards to AI Vikas states, “You still need people that will go and optimize the program behind it.” It is a team effort to optimize a chatbot, and constant evaluative measures will ensure that it grows and changes with the needs of the customer. Good AI is not meant to replace people in customer service, but to aid those committed to helping customers. In fact, Aarde mentions optimization tactics that fix AI and help the customer at the same time. He says, “When we feed the transcripts to our agents, our agents are actually reading through and seeing where things fail and then they escalate that to the bot architects, the engineers in the background. So they could change those bugs.”
Best Practices and Final Advice on How to Optimize AI
Transcribing bot conversations and having the bots follow the customer across multiple channels helps with the overall customer experience. Additionally, not being hesitant to transfer someone to a live agent is a good tactic. If people are saying “Operator”, pressing zero, or yelling, don’t use the bot to fix the problem, have a person step in and do their job. Aarde’s final piece of advice, or best practice, is to not tackle the hardest type of AI first. Don’t try for voice AI from the beginning. “I recommend trying,” he states, “but trying it slowly. So testing with maybe a low volume channel first, just doing a small portion, maybe 10% of volume, see its success rate and then roll it out to the greater population.” Add AI to your company’s customer service department one step at a time. Agreeing with Aarde, Vikas adds, “Look at your FAQ. What are the articles that people most often go to that resolve their issue?” He also suggests, “[Talk] to your agents or even [look] at the analytics in your CRM ticketing tool to look at, ‘What are the macros they most often use?’” While investing in AI can be an intimidating venture, bots can provide increased efficiency to your company, and successful self-service to your customers.
To learn more about how to leverage AI in your customer service department, 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:
Leveraging AI to Power Your Contact Center With Aarde Cosseboom and 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 broadcast. We’re excited to get going here. We’re going to be talking about one of these really relevant and interesting conversations, leveraging AI and self-service to really power your contact center. To do that we brought on two special guests. We’ll let them introduce themselves. Aarde, why don’t we start with you?
Aarde Cosseboom: (00:31)
Sure. Thanks again Gabe and Vikas for having me and Kustomer, of course, for hosting. I’m Aarde Cosseboom. I’m the Senior Director of Technology and Product for GMS, which is Global Member Services for a company called TechStyle. And we’re an e-commerce retail company.
Gabe Larsen: (00:47)
Awesome. Vikas, over to you.
Vikas Bhambri: (00:49)
Vikas Bhambri, SVP Sales and CX here at Kustomer, 20 years CRM Contact Center Lifer, looking forward to the conversation with Aarde and Gabe.
Gabe Larsen: (00:57)
Yeah, this is exciting. And you know, myself, I run growth over here at Kustomer. So let’s get in and let’s talk about this. Aarde, let’s start with the big picture. What do AI and self-service bots even solve?
Aarde Cosseboom: (01:11)
Yeah, this is a great question and really hard to answer specifics because every business is slightly different, but I’ll try to stay as high level as possible. Really it helps with self service, it’s in the title, but deflection, reducing contact. There’s a lot of automation that happens as well, too. So not only automating for your customer, but also automating a lot of the agent processes like creation of tickets and then auto dispositions as well too. And then one of the things that’s kind of hidden that most people don’t think about, and it’s actually one of the things that we don’t really measure that well in the industry in this area, is customer experience as well, too. So as millennials and gen X are expecting these types of tools, it creates a better experience for those people who are expecting it.
Gabe Larsen: (02:01)
Vikas, maybe you can add onto that. I mean, why do you think this is such an important conversation more so now than it was even just a couple months ago? Give us kind of that thought process.
Vikas Bhambri: (02:11)
Sure. I think what we’re running into right now is folks like Aarde are really seeing a tremendous surge of inquiries into their contact center. And the reason they’re seeing that is there’s the heightened level of anxiety and expectation for consumers. Most of what they’re shopping for, they want now and it doesn’t matter what it is. In fact, I was talking to a friend of mine who’s in the middle of buying a bike. Now, normally you buy a bike and you’re good. Whenever it shows up, it shows up. But because of the quarantine, he is literally like, “I need a bike so that I can have something to do with my kids.” So when he placed an order for the bike and wasn’t immediately notified when his bike was going to be available, he got extremely concerned and started pinging the bike shop. So I think it’s really interesting to see that behavior, particularly in these times, the ticket surge and putting pressure on people like Aarde and his peers to be able to respond.
Gabe Larsen: (03:20)
It feels like, again, there’s just more need for it than ever before. How do you think about chatbots versus social versus some of these other channels? Do you feel like they’re just different times to use them, is it different companies, is it different industries? Aarde, what’s your thought on kind of the mix of channels that are out there, why people would use one versus the other, et cetera?
Aarde Cosseboom: (03:42)
Yeah. And it goes back to expectations. So your customers expect a lot from you. And as we grow in channels in the customer service realm, growing the social and then direct social, which is things like WhatsApp and Apple business chat, direct SMS, and MMS. Those are all areas that we need to grow into and when we do grow into, we need to create an omnichannel experience. So you can’t just have a chatbot on your website anymore, and it only be in your chat profile. It’s gotta be across all of the different channels that you use to support your members. And as a member switches, as they do the channel switch, maybe they start in chat online and then they say, “You know what, I’m going to pause the conversation. And now I’m going to go to Facebook messenger.” You need to follow that with your AI so they don’t have to start all over from scratch with that automation tool.
Gabe Larsen: (04:36)
I like that. Vikas, how would you add to that?
Vikas Bhambri: (04:38)
I think Aarde nailed it. The term chatbot is so yesterday, right? Your bot needs to be omnichannel, your bot needs to be available, not just via chat as a channel, but you know Aarde mentioned Facebook messenger, WhatsApp, SMS email, right? So when we think about automation and bots here at Kustomer, we think about it regardless of channel, I mean, even email, right? Why is it that somebody sends an email and somebody actually has to enter a response? Why wouldn’t you send some responses that will allow that customer to self service, even by email, which is obviously one of the older, more mature channels. So that’s how we think about bots here at Kustomer.
Gabe Larsen: (05:23)
Well, look, I’m as guilty as anybody; the chatbot I’m so used to thinking chatbot and it’s something on the website. Is there a different term? Is there, I mean, obviously as you guys kind of pointed out, it’s better to think about it, maybe in an omnichannel approach, but Aarde, I’m looking for you on this one, man. How come you haven’t invented a term that is an omnichannel chatbot? What is that term, what is it?
Aarde Cosseboom: (05:49)
I haven’t invented it, but it is out there. It’s IVA which stands for Intelligent Virtual Assistant and really it’s the omnichannel bot experience, doesn’t matter how you use it, but that’s how you deliver it. So Virtual Assistant or Intelligent Virtual Assistant,
Vikas Bhambri: (06:07)
Gabe, I’m not the marketer on this call, but I’m going to give you a lay up here and you can give me credit. And if our friends at Zendesk are listening, they’ll probably copy it as they always do, but Omnibot.
Gabe Larsen: (06:19)
Omnibot! Oh my goodness! Oh, stolen.
Aarde Cosseboom: (06:22)
I like it.
Vikas Bhambri: (06:22)
I’m a transformers kid. I grew up, I’m a transformers generation. So that just sounds super cool to me.
Gabe Larsen: (06:29)
Honestly that sounds like —
Aarde Cosseboom: (06:31)
Gabe Larsen: (06:31)
Omnibot does sound like one of those transformers. What’s the main transformer? What’s the old guy?
Vikas Bhambri: (06:36)
Gabe Larsen: (06:38)
Optimus Prime. Optimus Prime, meet Omnibot.
Aarde Cosseboom: (06:43)
That’s a great name for a bot too. We could brand it.
Gabe Larsen: (06:47)
It totally works. That probably is good for this question you guys. I consider myself a programmer. I wanted to build my own bot. My kids are doing little things with programming. It seems like a lot of people are building bots these days. Should someone just build a bot? Should you buy a bot? And excuse me, an Interactive Virtual Assistant. Aarde, let’s start with you man. You’re out there in the market, talking to people, can companies just build these things? Is that easy or should you buy it? I’m confused.
Aarde Cosseboom: (07:19)
Yep. Great question. There’s a lot of controversy here and lots of different companies are doing their own little flavor. As technology grows and changes, it’s enabling companies to be able to build their own. Things like Amazon Lex or Google dialogue flow, it’s getting a lot easier than it was a year ago or even five years ago. But in the current market and we assess this here at TechStyle every six months, we recommend to buy or partner, is what we like to call it, partner with an actual partner that has the technology in place. You get a couple benefits from it, ease of use, and you’ll get to market faster. You won’t have to do that long implementation, have to have those developers and experts build something from scratch. You’ll be able to lean on the expertise of your partner to help you with that. And then the other thing that’s really beneficial that most people don’t think about is, when you’re partnering with a technology partner, they’re going to be leveraging all of the AI and machine learning that they have across all of their other customers and bring all of that to you and your bot. So if there’s a best practice in your space, we’re in retail, for example, and we use a partner and they have a best practice for another retail customer, they’re going to knock on our door and give us that easy flow without us having to do all the legwork. So I recommend buy for now and partner with a dedicated partner that has it in that ecosystem.
Gabe Larsen: (08:45)
Yeah. Look, it’s becoming, I mean, there’s just, there’s enough out there. You guys, I think you can get it for a good enough price that I don’t know if you need to dedicate a whole engineering team to kind of build your own automation, roles and bots, and things like that. So I don’t think I’d disagree with Aarde. Vikas, this one just came through on LinkedIn, this is from Keith, this question, and I meant to throw this in here and so I want to throw it in now. He said, “Hey, look, we’re trying to humanize our bots. So we designed them to help people not be viewed as an application. But it still comes — begs the question of how do you think about these bots? I’m thinking more on the website at the moment. Do you name it the bot, do you put a human there? Do you — how do you balance that? Have you seen best practices on that?
Vikas Bhambri: (09:26)
Yeah, the first thing that I recommend to customers is you got to keep it authentic to your brand.
Gabe Larsen: (09:32)
Vikas Bhambri: (09:33)
That’s number one. If you’re a fun hip brand, you want to keep it relative to that. If you’re maybe a more mature brand, you want to keep it in tune with your just general reputation and what your customers expect of you. The other thing is, I think in the early days, and most companies have gone away from this, I remember there was a brand in the UK that had announced a bot, but they branded it Lucy. Ask Lucy. And customers cannot really tell whether they were speaking to a human being or a bot. And they actually got very negative feedback because people were just asking questions and the bot at that time, you can imagine almost seven, eight years ago, wasn’t trained. It couldn’t answer half their questions. So I think the more that you let your customer know, “Look, you’re dealing with a bot” and that allows them to give some flexibility and some leeway to you to understand that look at some point, this bot may not be able to answer my question; to know that you can always escalate to a live human agent, right? So you can still give it a name, right? But making sure it’s authentic to what it is. And if the point comes where it can not resolve the customer’s inquiry, that they know there’s a handoff, a seamless transition. That’s another thing a lot of people get wrong. Right? So now I connect to the human agent, don’t make me ask the five, six, seven questions that I just went through with the bot. The agent should pick up the conversation fluidly from where I left off. Aarde what do you think?
Gabe Larsen: (11:09)
Yeah Aarde, I want to talk — do you agree because I think you might disagree?
Aarde Cosseboom: (11:15)
No, I do agree. There’s a little bit of uncanny Valley; gotta be careful about not tricking your customer into thinking they’re talking to a human. So I totally agree that you have to upfront tell them that it’s a bot. I like to brand it as giving it kind of a bot accent. So if it’s a voice bot giving it a little bit of a mechanical accent, so they know that it’s a bot or, not having a hundred percent of a fluid conversation fragmented a little bit more so they know that they’re talking. Also, you could declare it at the beginning of a chat or social conversation saying that “You’re engaging with an AI tool at this time.” And then, another key point here is you’re right, try to do it on brand. So we have 95% of our customers are females. So we have a female voice. If you’re selling golf clubs online, you may want a male voice because there may be a higher percentage of males that are listening to or engaging with your bot. So think about voice, tone, accent, especially accents, U.S. accents. So if you’re on the East Coast, don’t put words in there like “cool” or “hip” or things like that. Make sure that it’s localized to your customers and brands.
Gabe Larsen: (12:29)
Yeah, don’t use one of those weird Utah accents like you hear coming in all, all “Here y’all.”
Vikas Bhambri: (12:36)
One other thing to Keith’s question, right? And this whole concept of an application; look, it goes back to back in the day and chat, we started out with what we called a pre chat survey, which was literally, “Here are the five questions you need to answer so that we know who to route you to, who you are,” et cetera. Then it became a bit more where people were doing authentication. And so they had some data. Then we moved to this concept of conversational form, which was still a bot, but it asked the question in a humanized way. So it wasn’t just “Fill out these five questions.” It would ask you the question one at a time and maybe there was a variability where if you said you were a buyer versus a seller, the next question would change. Now Keith, where we want to take it is the bot can gather so much data about the customer before they even type in one word. So a lot of that is now picking up with the information that is now unknown to you so that you can then either answer the inquiry or then route it to the agent. So it should necessarily have that kind of predetermined, almost process flow. You can be much more mature about how you even go about using natural language processing for people to just key in things and it doesn’t have to be hard coded, right? So I think there’s a lot that you can do there now.
Gabe Larsen: (14:00)
I like that. This is, I think, one of the questions that comes up often, this is such a cool feature look at this. I can just throw this in here, right here. Look at that. Are you guys seeing that?
Aarde Cosseboom: (14:11)
Vikas Bhambri: (14:11)
Gabe Larsen: (14:12)
Geez louise, man, look at this technology. Scott Mark, little shout out to Scott Mark. What are best practices around the handoff from a bot so we stop dropping the ball? I think that’s — we wanted to get actually into some best practices. Maybe we start it now. That’s just a big debate. It’s when you handoff, how do you hand off, how many questions do you ask? It’s just, it never feels right. Thoughts? Aarde let’s start with you on that one.
Aarde Cosseboom: (14:38)
Yeah, absolutely. And you have to think of one thing first, which we call the IVR prison or the chatbot prison. You’ve got to allow people to get out of that prison. So if you get the same question twice and it’s not — you can’t recognize the right answer like, “What is your email address?” and can’t recognize, ask again, can’t recognize, fail it out to a live agent. That’s a good best practice. Also if they say the word operator or press the zero key on their phone, or if they start cursing, definitely fail them out of the IVR. Don’t keep them in prison. Always allow them a way out of that IVR. But then when you go over into the agent experience and that handoff, even for the experiences where someone engaged with the bot for a very long time, and there’s a long transcript, maybe there is actions that were done like they updated their credit card information with the bot, they updated their billing information, their name, profile; all of that you want to transfer to an agent, screen pop not only the member profile, start to fill out the case or tickets so the agent doesn’t have to do it. And then also, feed them the transcripts so that if the customer or member says, “Hey, I talked to the bot, it updated my billing address, but I think it didn’t do it right. It didn’t do the right street address, the right number. Can you go back and check and see if it did that?” The agent should be able to scroll up through that transcript and see exactly where it failed and then fix that, that failure.
Gabe Larsen: (16:11)
Yeah. Vikas, what would you add to that?
Vikas Bhambri: (16:13)
I think the biggest, so Aarde nailed it, right? So, your initial implementation, those are all the best practices. I think the challenge for most brands is you’ve got to treat this like a program management, just like a marketer would if they were doing a promotion on their website or doing a campaign. Constantly revisiting and optimizing, right? So one, your bot is going to get smarter if you’re investing in the right technology. But two, if you’re finding that customers are constantly getting challenged, that process in your step, go and see what do you need to do to modify it, to smooth that out, right? So where are people cursing, where are people hitting zero? Where are people saying, “Get me to a live human agent?” How do we further optimize that piece before we do it? So I think that’s the biggest thing I see is where people will roll these things out and then forget about them and then six months later, they’ll say, “You know what, this isn’t working and we just have to pull it off the site.” And that to me —
Gabe Larsen: (17:16)
Why do you have to call me out like that? Why do you have to call me out like that? I mean, geez louise. In all truthfulness, that was my first experience with a bot. I mean, it’s been a few years back, but I don’t know. I thought you could throw it on the website and it would maybe like, I don’t know, do its things, some sort of magic or something. And three months later, I’m like, “This thing’s a piece of garbage.” I totally, I mean, I came to the heart of the conclusion that like anything else, it has to be iterative and optimized. I love that one.
Vikas Bhambri: (17:45)
No, I think Gabe, this is an interesting thing, right? Because people keep talking about AI just on a broad macro level. And you know, people will say, look, “AI is going to put everybody out of a job. We won’t need salespeople. We won’t need marketers. We won’t need customer service people.” No, because the role will change because the technology is great, but you still need people that will go and optimize the program behind it. Right? So I think, I think that’s an interesting nuance just as we think about AI generally.
Aarde Cosseboom: (18:11)
Yeah. And talking a little bit about supervised learning; so when we feed the transcripts to our agents, our agents are actually reading through and seeing where things fail and then they escalate that to the bot architects, the engineers in the background. So they could change those bugs. So your team members, your agents are now a part of a QA or quality assurance process on your technology, which is huge. And it kinda levels up the agent as well, too. They’re no longer just answering chats and emails and phone calls. They’re now, they now feel a part of the organization because they have a higher role in reporting this information back.
Gabe Larsen: (18:49)
I’ve been hearing more about this kind of bot, almost like a role, like a bot architect. I love the idea of getting the frontline people in front of it. Guys, give me a couple other nuggets. I think that’s where people want to go with this because I think people are getting onto the idea that they need to have these assistants or bots on their sites, et cetera. I don’t know if people know some of the best practices, lessons learned from deployment, where they get started. Our time’s a little bit short, but give us a quick rundown. Aarde let’s start with you then Vikas, we will go back.
Aarde Cosseboom: (19:18)
Yeah, absolutely. I’ll make it super short, but, it’s a huge chasm to cross from having nothing to having something. That’s why I recommend trying, but trying it slowly. So testing with maybe a low volume channel first, just doing a small portion, maybe 10% of volume, see its success rate and then roll it out to the greater population. So try to do the easier channels first. So online web chat is probably the easiest or a social chat or an SMS bot. Don’t tackle voice first. That’s going to be your hardest heaviest lift and you’re going to be sidetracked.
Gabe Larsen: (19:54)
Vikas what do you think man?
Vikas Bhambri: (19:54)
Yeah, I agree with Aarde. Look, you have to look at this as a crawl, walk, run, right? If you try to bite off more than you can chew, you’re going to end up pretty miserable. So for me, number one is, look at your FAQ. What are the articles that people most often go to that resolve their issue? Maybe that’s something you want to be more proactive serving up. The second is talking to your agents or even looking at the analytics in your CRM ticketing tool to look at what are the macros they most often use, right? Because if somebody is just cutting and pasting, we’re hitting hashtag time after time, again, that means those are probably some, that’s some low hanging fruit that you could front end via a bot, the omnibot, for them to resolve themselves. So those are some things that you could look at. Query the data you have, and then just think about, “How do you want to be proactive and thoughtful about putting some of these things in front of your customers?”
Gabe Larsen: (20:54)
I think that’s spot on you guys. I mean, my biggest takeaway from today, I’m going to trademark Omnibot. That’s what I’m doing. That’s — I could barely listen to you guys. I was thinking so much about money I’m going to be making on Omnibot here. No, I’m teasing. Aarde, really appreciate you joining. Vikas, as always, great to have you on. For the audience, hope you guys have a fantastic day.
Vikas Bhambri: (21:19)
Have a great weekend.
Aarde Cosseboom: (21:20)
Exit Voice: (21:27)
Thank you for listening. Make sure you’re subscribed to hear more customer service secrets.
Many of us look forward to the holidays. We get excited about the prospect of parties, family gatherings, holiday cheer and presents galore. But the holiday season also brings a big lump of coal: an increase in needy customers reaching out to your team in need of immediate support.
According to Kustomer data, inbound customer service inquiries increased by almost 120% during the holiday season in 2019, with particularly dramatic spike in activity on Instagram, e-mail, voice and chat.
Many businesses struggle to maintain a high level of support during spikes in activity. They may need to hire a flurry of seasonal employees who have a short training period. Last year, $284 billion dollars were spent between Thanksgiving and Cyber Monday alone, so the stakes are high. The question becomes, how do you handle the seasonal rush without breaking the bank or disappointing customers? Read on to learn what customers expect, and how to deliver with smart strategies and smarter technology.
Customer Expectations During the Holiday Season
Spending isn’t the only thing skyrocketing during the holiday season — so too are customer expectations. Here is what consumers expect from brands during the upcoming holiday season.
During the holiday season, the turn of phrase “too much to do, too little time” hits a lot closer to home. Between normal day-to-day life, holiday celebrations, traveling and gift buying, consumers don’t want more of their time taken up by customer service.
According to recent Kustomer research, 77% of customers expect their problem to be solved immediately upon contacting customer service. Customers demand that you respect their time, especially during the busy holiday rush, and if you don’t, they are willing to leave for another retailer. In fact, 70% of consumers would not shop with a retailer again if they had to leave a chat before being helped, and 71% would do the same if they waited so long on hold that they hung up.
Available on Any Platform
Especially during the peak shopping season – Thanksgiving to Christmas — consumers are on the go. They may be traveling to spend time with family, taking a much needed vacation, or multitasking during the work day. What does this all mean? Customers are more willing and able to reach out on new platforms that are most convenient for them.
While 88% of consumers get frustrated when they can’t contact a company on the channel they prefer, availability on multiple platforms isn’t enough. Eighty-six percent of customers said they get frustrated when they have to repeat information to customer service agents. This means that if customers switch channels or need to be transferred, they don’t want the context of their previous interactions lost.
Most of the time, when a customer contacts a company, the team manning that channel will create a ticket. If the customer then contacts the company through a different channel about the same issue, a second ticket will be created with each team working their respective tickets. This results in a fragmented experience and the unfortunate need to repeat information.
How to Wow Your Customers During the Holiday Season (Without Breaking the Bank)
The typical strategies businesses use to please customers have one thing in common: they cost money, and aren’t scalable. What are some strategies and technology tools that you can put in place to wow your customers WITHOUT breaking the bank?
There’s something to be said about beating your competition to the punch. According to research by Digital Commerce 360, 56% of customers chose where to shop during last year’s holiday season based on past experiences. In addition to common seasonal marketing strategies, delivering a stellar experience NOW can help you drive business in the future.
The companies that are practically synonymous with brand love, and have customers that are loyal to the death, have one thing in common: they have prioritized customer experience since their inception. In fact, customer experience is becoming more important than price and product when it comes to loyalty. Ensure that during busy seasons, when your inquiries and orders quadruple, you can continue to make customers feel just as valued as on the slowest day of the year. By preparing early, you can put the right tools, staff and strategies in place to not only deliver the perfect holiday gift, but also the perfect holiday customer experience.
Get a Little Help From Your Robot Friends
When resources are thin, technology can make a huge impact on your team’s efficiency. Oftentimes the most tedious tasks on an agent’s plate are manual and repetitive, and may not require human intervention. Luckily AI can handle simple tasks like tagging and routing conversations to the most appropriate agent. And consider the power of chatbots during peak shopping periods. They are growing in popularity with both businesses and consumers. In fact, 67% of consumers prefer self-service over talking to a company representative.
Chatbots can be used to collect initial information, provide responses to simple questions, and even complete standard tasks like changing a booking or answering an order status question. 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, chatbots 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.
Be Available Wherever Your Customers Are
Omnichannel support shifts perspective from ticket resolution to customer relationship building, which is incredibly valuable during the holiday season, when companies have the opportunity to attract an entirely new cohort of customers. Individuals have the freedom to move between channels throughout their engagement, and are guaranteed consistency, so each conversation starts where the last ended. Agent collision never occurs when communication channels are integrated, because agents can view the conversation and maintain context even as customers engage through multiple channels. If executed properly, omnichannel support provides a consistent experience for customers at every touchpoint after acquisition.
Ensure you have the right technology in place to integrate your combination of communication channels in order to capture the free flow of conversations across platforms and display the data in a single screen. A best-in-class solution should create a unified home for all your customer data, regardless of the source, not only the data generated from customer conversations.
Artificial intelligence is making a major impact on customer service and shows no sign of stopping. The increased interest is warranted — Forbes contributor Kathleen Walch of Cognitive World said AI is a useful tool that’s improving customer service, enhancing customer loyalty, enabling better brand reputations and allowing customer service agents to focus on tasks of greater value that can bring companies more business.
While all of these benefits are highly advantageous for businesses, making sure customer service staff are satisfied is a critical initial step in the process. Here are four simple ways that AI chatbots can improve work-life for your customer service agents and better streamline agent experience and expectations:
1. Improved Work Efficiencies
One of the many benefits of utilizing chatbots is the ability to shift work expectations of customer service agents. As Chatbots Magazine stated, chatbots are truly the future of engagement. There are many direct questions that can be handled by way of automation, giving customer service staff the freedom to take on the more meaningful conversations within a short period of time.
2. Better Conversations With Customers
When customer service staff can focus on more important cases instead of the simple questions that AI chatbots can handle, agents have a strong role in driving business and loyalty for the company.
3. Enhanced Job Satisfaction
When customer service agents have more time to focus on complex queries and enhance the connection between customers and your company, they may find greater overall satisfaction in their work. With AI chatbots, you also have the opportunity to introduce steady, more enjoyable working hours that create work-life balance. AI-powered bots can handle the low-level inquiries during the traditional “after hours” time frame, which means you don’t have to worry about keeping staff on the clock at all hours of the day. Not only can this help with workplace satisfaction, but it can also reduce overhead costs.
4. Increased Capacity
Realistically, customer service staff can only talk to one customer at a time, making it difficult to handle more than one issue simultaneously. When AI chatbots are introduced, you can alleviate the pressure that customer service agents once felt about long queues. While this is beneficial for agents in terms of streamlined expectations, your company can still meet bottom-line goals and continue servicing all customers that contact you.
Working With Kustomer
Kustomer’s customer service CRM platform is built to meet the expectations of the customers and agents of today. With our solution, you can better manage customer inquiries and high support volume to streamline staff and company expectations. Request a demo today to learn more about our process and services.
Customer service agents provide immense value to any business. Not only are they highly knowledgeable resources that consumers can rely on to solve their issues, they also play a role in influencing purchasing decisions and building community.
The digital age, however, has made it easier for companies to rely less on human agents to answer easy questions and instead utilize artificial intelligence to get the job done, and many significant companies like LinkedIn, Starbucks and eBay are on board. The general interest in the AI chatbot is only anticipated to grow, as Business Insider reported that the market size is projected to increase from $2.6 billion in 2019 to $9.4 billion by 2024.
The Power of the AI Chatbot
Enabling automated, low-level service via an AI chatbot allows your business to take these smaller inquiries off the hands of your agents, so they don’t have to work around the clock. They are able to focus on the most important cases, playing an invaluable role that drives business and loyalty.
Today’s consumers love convenient interactions. AI chatbots allow for quick resolution without impacting the quality of the experience.
Questions that are simple are ones chatbots can easily handle. CXL Institute refers to these as “Tier 1” questions, which can be interpreted easily by a machine that’s loaded with information in a database. Queries regarding size availability, time and rescheduling for travel booking, as well as specific order numbers can be easily answered by chatbots.
“What time is my flight?”
“When will my package arrive?”
“How much is a ticket to the Monday show at 5 p.m.?”
Queries regarding information that can be found on your company website are also great for an intelligent virtual agent to tackle, saving customer service agents time and energy that would otherwise seem wasted.
“Where is the nearest ATM?”
“When does your store close?”
Chatbots have the ability to ask fact-based questions, pulling customer information into your internal knowledge base that is built in part by the customer queries. Some examples include:
“Which day do you want to go to the event?”
“How many people are attending?”
“What color are you looking for?”
Questions for Live Agents
Live chat is unmatched for some consumers. When it comes to the complex questions, we agree. For example, if a customer is interested in a certain product but wants more information and guidance down the sales funnel, an agent can address doubts, answer these specific questions and help customers make decisions.
Questions that can turn into bigger issues based on communication limitations don’t work well for chatbots; customer service agents can provide sincerity in the form of understanding and humility, for example, which can improve the reputation of your business. Some examples:
“Why can’t you process my credit card?”
“How can I get credit for this coupon?”
“I can’t decide between the small speaker and the big speaker. Can you help?”
“I used to wear this perfume, but I can’t find it anymore. Do you make something similar?”
AI chatbots allow you to scale your customer service and rely both on artificial intelligence and human agents to provide a quality experience for consumers.
Learn more about how Kustomer can improve your customer service strategy today by requesting a demo.
In this episode of Customer Service Secrets, Omar Pera, CEO at Reply AI, joins Gabe Larsen to discuss how to use artificial intelligence to make customer service faster and smarter. Omar’s background is in solar engineering. His first job in customer service was at CERN, a physics lab in Switzerland, where he deployed the internal customer service tool for 2000 employees. Later on, Omar moved to New York to work with Big Civil, a tech startup. On nights and weekends Omar worked with his brother, Pablo Pera, developing some indie apps that became really successful with more than 50 million downloads in different markets. Fast forward to 2015, Omar wanted to know the penalty fee for a flight change, and after a terrible customer experience Reply AI was born as an easy way to automate conversations. Omar has extensive knowledge in the technology sphere and provides valuable insights on how technology and artificial intelligence can help create an exceptional customer service experience. Listen to the full podcast episode below.
Instantaneous is the Expectation of the Customer
Every customer service team knows that the customer wants their issues resolved, quickly. Customer experience is becoming more important than price and product when it comes to loyalty. Businesses who prioritize customer experience are the ones succeeding and the ones with more engaged customers. Omar shared a story about being on hold for 45 minutes and waiting 7 days for an email just to find the answer to his question about a flight change fee. This experience motivated him to build a platform that would help automate the most common question businesses receive. Customers want instantaneous solutions to their problems and they want to do it themselves. Omar states, “67% of customers prefer self-service over talking to an agent. … I believe that companies should be focusing on self-serve.” Intelligent automation as part of the customer service strategy not only keeps your customers happier, it also improves the efficiency of your agents.
Chatbots and Other Efficient AI Applications
Chatbots are typically the first platform thought of when it comes to customer service, and for good reason. Almost every business uses charbots to reduce unnecessary engagements with agents. Simple problems and questions can be answered much faster with chatbots. However, Omar points out that there are some other good examples of how to use AI in customer service: agent assistants, automatic categorization of tickets, smart routing or deflection. Omar summarizes:
“Everyone thinks that chatbots can solve everything. Not at all. Really, you can use a chatbot just to gather information and then hand over to an agent. That’s already helping your agents to be more efficient and the customer doesn’t need to wait for that initial “hello” from the agent to start solving their issue. Or, going a little further, you can do some API calls, integrate with your backend, and fully resolve issues”
There are so many different ways to use AI that companies are missing out on because they are only focusing on using chatbots to answer questions. The positive customer experience of the future has AI integrated into several stages of the customer journey.
How to Start Integrating AI into Your Company
Starting the AI journey is no easy task. There are so many things that can be automated, which is intimidating. Omar understands how hard it is and shares, “Start with one, one automation at a time. Focus only on that one… If you have live chat for example, why not understand which topic has the most volume and start gathering information about that today. Maybe a chatbot that answers “Where is my order?”. Ask the customer what is their order number and then hand it over to an agent. Once you control that, move to the next step: integrate with your backend so that later we can give them the tracking code… Start small. Start today.” After doing an audit of your company and the processes that should be automated, pick one, and get started. It will be a gradual process but Omar assures that it will be well worth it in the end. Good customer experience should revolve around making sure the customers get their answers with little friction and in a timely manner.
To learn more about AI and automation in customer service and how to integrate it into your company, check out the Customer Service Secrets podcast episode, and be sure to subscribe for new episodes each Thursday.
You can also listen and subscribe to our podcast here:
Full Episode Transcript:
Making Customer Service Faster and Smarter With AI with Omar Pera
Intro Voice: (00:04)
You’re listening to the Customer Service Secrets Podcast by Kustomer.
Gabe Larsen: (00:10)
Alright, welcome everybody. We’re excited to get going today. We’re going to be talking about artificial intelligence. We’re going to be talking about some recent news that happened here at Kustomer. We acquired a company called Reply.ai and they bring a wealth of information in the bot deflection and artificial intelligence category. And so we brought on Omar Pera, who’s currently the CEO and founder of Reply.ai and is taking on a Director of Product Position at Kustomer. And we want to dive into this idea of chat bots, AI, and how companies are using these different tools to be more efficient and more effective. So Omar, I appreciate you joining. How are you?
Omar Pera: (00:56)
Thanks for having me.
Gabe Larsen: (00:58)
Yeah, I think this will be exciting and congratulations on the big announcement.
Omar Pera: (01:03)
Thanks so much. This being the most exciting two days of pretty much my life except my wedding, so it’s been pretty good.
Gabe Larsen: (01:11)
I love it. Well, yeah, tell us just real quick. I mean, it’s obviously been a busy couple of weeks. Well, we probably better start a little higher. I wanted to jump right in the announcement, but maybe let’s start with just a little bit about you and Reply. Can you tell us a little bit about what Reply does and a little bit about your background?
Omar Pera: (01:31)
Yeah. So, my background is in solar engineering actually. I started my career in bioinformatics, then moved to CERN, which is a very famous physics lab in Switzerland. And actually my first job in customer service was at CERN. It was a physics lab that I deployed the internal customer service tool for 2000 employees there. And then after that I moved to New York, to work in a tech startup. And then on the nights and weekends, Pablo Pera, which is my brother too and co-founder of Reply, myself and a small team, we created some indie apps that got very successful in the markets. And then after that I jumped, diving into Reply.
Gabe Larsen: (02:15)
I love it. What was the reason to move to New York? Was it just wanting to — I mean, obviously, originally, Spain is home, correct?
Omar Pera: (02:24)
Well it is home today. I’ve been around eight years outside Spain. I went to first UK, then Germany, then Switzerland for CERN, and then I moved to New York–
Gabe Larsen: (02:38)
Oh yeah because CERN would’ve been in Switzerland. Yeah that’s right
Omar Pera: (02:38)
And then I moved to New York, to be working with Big Civil, which is a company that got acquired for a bunch of dollars. It was a pretty exciting moment there. Then later that’s when I started Reply.
Gabe Larsen: (02:58)
Okay so that makes more sense. So you’ve bounced there, so you’re quite the international traveler, it sounds like.
Omar Pera: (03:03)
I am. But I still have a funny accent. I cannot deal with that.
Gabe Larsen: (03:08)
It just depends on where you are if the accent is funny or not. You know, I lived a couple of years in the Middle East, a couple of years in Germany and my accent was weird to them there as well. So, no harm, no foul. It sounded like you did when you mentioned you had successful Indie apps, it was very successful. I mean to the tune of millions of downloads, is that correct?
Omar Pera: (03:29)
Yeah. We deployed around 10 or 12 apps to the markets, on many different verticals. It was just our own ideas and some of them actually got into the order of millions to a total of 50 million downloads.
Gabe Larsen: (03:44)
Oh wow. Wow. Hopefully you were charging a couple bucks per download on those.
Omar Pera: (03:47)
No, I know. I wish. I wish, but no, it was a combination of advertising and other things.
Gabe Larsen: (03:55)
If it was, we probably wouldn’t be talking right now. Right. If you’re doing five dollar– So I’m glad you didn’t. I’m glad you didn’t do that. Well let’s get into Reply then. I mean you kind of walked us through the background and then you ended saying, we then started Reply. So what was the story behind that? How did it start? Why Reply?
Omar Pera: (04:16)
Yeah, so it was funny because one of the apps, [inaudible]. So from five emails, we got into 50 emails and then 100 emails per day. So we could not keep up. We actually hired on a freelancer or other services there, some contractors, but really we could not keep that momentum. And then actually one day, this was 2015 one day I wanted to know the price of the penalty for a flight change. So I called an airline, and waited on hold for 45 minutes and then the phone disconnected and it was super annoying. And then I sent an email and waited for seven days to respond. So I really knew that that was a bad experience.
Gabe Larsen: (05:01)
It was seven days, huh?
Omar Pera: (05:03)
Seven days to respond just to understand it was 70 bucks of the penalty fee. So we really knew that that was a very bad customer experience. We also knew that from being a customer. So we hate to wait, like everyone hates to wait. So we had a look at the market and said I don’t think there is a platform out there today that makes it very easy to automate conversations. So that was the beginning of Reply. We now are a customer service automation platform now integrating to Kustomer. We help companies to resolve their most common questions without any agent in the region.
Gabe Larsen: (05:42)
Oh my goodness. So important. I just feel like — it’s funny because I’ve often debated this kind of bot versus, deflection bot versus human interaction. That’s been a conversation for a while. But man, in the last couple of months, the amount of energy and the amount of focus that companies are putting on doing more with less kind of to use your line to eliminate that agent. It just seems like it got — it was important, don’t get me wrong, but now it’s like, wow, it’s really important. Right? It’s just kind of the times have changed. So, one more followup to that. I think you’ve kind of hit on this, but I want to just double click it and that is, what then really was the core thing you were trying to solve for Reply?
Omar Pera: (06:35)
Yeah. So we experienced both sides of the problem, right? As a company, as business owners and as myself as a customer. So these gave us unique insights, how to fix the problem because first, for any company of the planet who is growing, it’s very, very hard to scale customer service. That’s pretty much a fact. So we sit down to set ourselves to solve that problem. And the ultimate goal is pretty much to have a great customer experience and make customer service faster and smarter. That’s what we really want to do. So we started doing that on Reply by providing a do it yourself tabled platform. And then we quickly realized that there was more than just chat. So we’ve expanded our offering to provide self-serve on all channels, including chat, email and your contact form. And I think to date, which I believe is going to be around 1 million and a half consumers have gotten any answer from us without waiting.
Gabe Larsen: (07:41)
Wow. Wow. Okay. So those are the number of answers or deflections or self service inquiries that have been solved.
Omar Pera: (07:47)
Yeah, the number of customers who have been touched with our automation and being helped.
Gabe Larsen: (07:53)
So over a million is where you’re currently standing. And the great thing is it isn’t just, that last point you mentioned, it isn’t just the bot, it’s actually email you said and what was the last one?
Omar Pera: (08:05)
So we can replace the contact form by using your FAQ. So the FAQ is usually the most creative piece of self-serve that any company has. So we try to make use of it so that whenever you are submitting a contact form, we provide you with suggestions for that contact form. So they don’t need to wait.
Gabe Larsen: (08:25)
Fascinating. And again, just so timely and maybe I’ll follow that up with that. I mean, why do you think it is so timely? Why is it so important now that people start to think about these types of tools, these types of technologies?
Omar Pera: (08:41)
Well, COVID is one of the causes, which is very sad, but at the same time, it has caused that customer service is totally overwhelmed. And the reality is that people still expect that you solve the issues fast.
Gabe Larsen: (08:57)
Omar Pera: (08:57)
They are used to one day delivery. So maybe now with a three day delivery, they’re going to find that not with a one week delivery. Right. So I will say that today for even any business consumer company, if you have a contact form or an email and you have three to seven days response time, you know that you have a problem. Right? So I think it is — every company has learned to do social very well, but usually customer service has been a call center right in the background of every company. So I think now more than ever, customer service is also part of your brand and the only, not the only, there are many solutions out there, but, AI and better self serve can really help get your company in a very good position to have a good customer experience.
Gabe Larsen: (09:48)
Hmm. Interesting. I mean, it does seem like there was some good — and maybe you have those off the top of your head, but there’s some good stats out there that really highlight the need for this new age world, which is people do want answers more quickly. They expect it. To your point, it’s a little more part of your brand. You have a couple of those off the top of your head.
Omar Pera: (10:11)
I have one which is the most funny one is that consumers would rather go to the dentist than contacting a company by phone. That is hilarious. And then you mix that with I think it’s 67% customers prefer self-serve over talking to an agent. So I think you put those two together and you have everything that every company is struggling to maintain that level of productivity. I believe that companies should be focusing on self-serve.
Gabe Larsen: (10:47)
Wow. Yeah. That idea that 67% of consumers would prefer to do self service. Why do you think that? I mean, truthfully, I believe that. I’m a consumer, we’re all consumers ourselves. And I think I have my own reasons. But what was the why behind that? Just in your own opinion, why do you think people want that?
Omar Pera: (11:09)
So I believe today we are very impatient and we want answers as fast as possible. Even the rise of messaging. Everyone is texting, is doing texts these days, right? With WhatsApp or Telegram, all those messaging apps that are popping up, they have even more traffic than social today. So I think that instantaneous communication, you want that translated into the brands that you love.
Gabe Larsen: (11:43)
Yeah, yeah. I mean we all — that instant, I love that word. It’s instant gratification. Sometimes it’s used in a negative context, but truthfully, I want it, I want it now and some of the current environment I don’t think has helped that. So let’s see if we can get into a couple examples here. I love the idea — I mean, you’ve got a strong background in artificial intelligence, machine learning. AI is definitely a big talk track in customer service today. Obviously it fits into some of the things we’ve talked about doing more with less. What are a few examples of using AI in customer service? Let’s see if we can click down there.
Omar Pera: (12:21)
Yeah. So today when you say AI in customer service, everyone is thinking about chatbots correct? But I think we should not end there and maybe we should not even start there. So we will have that. But they believe that there are many, many good examples of AI including chatbots that you can apply to your company. So one of them could be like agent assistant, right? You have an assistant who is helping your agents to be more efficient by suggesting answers on real time and it can even learn from past behaviors. So it’s really helping you out. Another one, very simple is to categorize your tickets automatically. Like how many companies do have one or two people categorizing those tickets in order to get to the right person or even later for insights. The most typical one today who has been a big one in the phone space has been smart routing, who to direct this issue to based on what you know. That is a big one.
Omar Pera: (13:33)
So we’ve already gone through three and then the fourth is usually chat bots. Correct. Everyone thinks of chatbots as a chatbot that can solve everything. Not at all. Really, you can use a chatbot just to gather information and then hand over to an agent. That’s already helping your agents to be more efficient and the customer actually to not need to wait for that initial hello from the agent or you can actually go a little bit further and do some API calls, integrate with your backend and fully resolve issues. I think the last piece, which I believe is the one where on Reply, we’ve been focusing the latest, which is deflection with your FAQ. Everyone has an FAQ today and you can really provide recommended suggested articles in a very smart way and try to really provide that paragraph that really works and resonates with the customer asking a question so that they can get resolved that issue faster.
Gabe Larsen: (14:32)
Got it. Okay. So we got agent assists, we’ve got, categorization of conversations, routing, chatbots and some of the deflection I think is what you talked about. Couple of follow ups on that. One is, that is a lot. So if you were going to start, if you were going to recommend for someone to start somewhere on their AI journey, which one of those initiatives would you maybe start them on?
Omar Pera: (14:55)
So I will say that usually the biggest problem is that you have too much volume, right? So the simplest way to set up something is usually deflection because you already have an FAQ, right? So that’s usually the first step that I will suggest. And then if we move into — if you have live chat, that usually depends on the channels. If you have live chat, why not understand which is your one topic that you have more volume on and start gathering information for that topic today. Just a little chat bot that says, Hey, maybe it is “Where is my order?” questions are your top one. So let’s just do a chatbot that’s only that. Ask the customer what is their order number and then hand it over to an agent. You can do that in a day, today. Later, okay, let’s integrate with your backend so that later we can give them the tracking code. Okay, good. Next step, we can get the tracking code, we can call the shipping provider and we can get them the exact day that it’s going to be delivered. So it’s an iterative process and there is no risk. So I think that’s important. But the biggest piece of advice that I usually give to every single company is to start very small and start today.
Gabe Larsen: (16:19)
I liked that iterative process, right? Because I don’t know if there is a way you can just — I think truthfully that’s maybe one of the mistakes I did when I first was playing around. I’ll use the chat bot just as an example. I thought, you know what, I can just throw it up on my website and be done. That was a mistake. You kind of needed to go through what you were talking about; build, measure, repeat. I learned that the hard way, but I think that’s a great principle to live by. Let’s see if we can continue down that journey. So as we think about getting AI into CX, I love your iterative process, but you were also saying, Gabe, as we’ve worked with companies, I like this idea of starting small and starting today. I want to continue down that journey. What are some, what do you mean by that?
Omar Pera: (17:03)
So this means that for someone, one of our customers, you saw a large marketplace and they have many, many different types of issues. From, where’s my order to scheduling issues, to refunds, change orders. So there is a lot. So what we need is just to start with one, start with one, one automation at a time. Focus on that one. Don’t focus on any other topic. You can focus on two or three. Okay. But it is even better to just do one and then — but the most important part is if you do one you do that very well and everything else reduces that friction to the customer. So that’s very important. For example, when I mean they could start today and start small; do you have an FAQ contact form? Okay. Start today with an FAQ deflection. What are you waiting for? You can remove even 40% of your questions with that. Or do you have live chat?
Gabe Larsen: (17:58)
40% of your questions? Oh, so they wouldn’t put them in the form, they could just get answers via the deflection.
Omar Pera: (18:04)
Suggested articles. Yeah. If you have a good knowledge base, you can get suggested articles and usually customers are not browsing anymore a lot of knowledge spaces because usually they are tired of searching and not finding anything. Right. So if you bring AI to bring the answer to the question at the right moment, they are going to pay attention.
Gabe Larsen: (18:24)
Hmm. Got it. Got it. Okay. So start small. Start today. I love some of those examples, whether it’s contact form or live chat, you can get something that resolves your order or deflect something. Okay. Where do you go next? What’s kind of — after you start small, start today, what’s your next principle to get people up and going here?
Omar Pera: (18:40)
So the concept I would say is pretty simple. Make it very easy to find answers. Make it very easy. That means that you have a knowledge base, open it, very visible, not in the footer.
Omar Pera: (18:55)
Their knowledge base. They write all these great articles. No one ever uses it, right?
Omar Pera: (18:59)
Correct. And they have the contact us page on one side and their knowledge base on the other like put your contact page, inside your knowledge base. Make your articles short and sweet. Simplify it. Cutting to short sentences. This is not marketing, this is more about really going to the point to solve that question and I think it’s very important. These are common mistakes where I see like the knowledge base is a structure from the point of view of the company. I think flip that. Flip the navigation of your knowledge base into the point of view of the customer and the common problems that they are going to have.
Gabe Larsen: (19:33)
Yes. Yeah, it is interesting. It does feel like — you’ve mentioned a few other things but it does seem like often the knowledge base is hidden. It’s kind of back in the middle of nowhere. Sometimes I have a hard time figuring out where the knowledge base is and the thing that I love that you guys do or that you’ve talked to me a little about is just bringing that knowledge base to the customer. That may mean some of the deflection capabilities, but you know now I don’t have to go search. I may be chatting with a bot and the bot is actually bringing that knowledge base from the back to the front to me rather than having me go find it. I love that idea. I just think that’s so easy. It’s to your point, it’s getting answers easy and reducing friction. Okay, so we’ve got one, two, three. What is, what’s the next one? Where do you go next when you coach people on this journey?
Omar Pera: (20:17)
So I believe this one could also be one of the most important parts if you don’t want to damage your brand, which is don’t frustrate your customers. This is such a simple idea. And everyone usually will say that they are not trying, but if you do any automation, you need to be not careful. You need to have a good process. If you do any automation today, like dude, never pretend that you’re a human ever.
Gabe Larsen: (20:45)
Omar Pera: (20:46)
Yeah, that’s, that’s my point of view. There are many others who believe in a different way, but I have a strong point of view on that. Another strong point of view which I’ve also seen in the market quite a lot is the, “Sorry, I don’t understand” message right? Chatbots have been a little bit controversial in the past few years going in ups and downs because I believe it is not about the technology was not there, not like if you improve it has improved a lot, the technology. But I think the process is very important. So the process to create a nice conversation design brings that maybe you don’t need that “Sorry, I don’t understand” message. Forget that. Get out of the way. Automation, get out of the way very fast. Go to an agent directly. If you don’t understand a question, reduce the friction. So I think that is very important. And then just to put a concrete example, remember the chatbot about “Where is my order?” that I mentioned before? If the customer says absolutely anything that is not related to “Where is my order?” you go to an agent directly without waiting, without doing anything, without rephrasing, just go to an agent. Maybe ask their name and email and go for it right away.
Gabe Larsen: (22:03)
Wow. Yeah. So you are, don’t mess with the bot, get to the agent faster. Don’t mess with it so much is what I’m hearing you say there. Wow. All right, well, last question before I let you go and then I would love to hear maybe a quick summary. But, again, congratulations on the news. I’ve never had a company acquired. I’m sure you’re kind of on cloud nine. Can you give us, from your perspective, it’s been a busy couple of weeks the last two weeks, but how did it all kind of go down and, are you excited about the result? Are you excited about the next step and joining Kustomer? Give us kind of your quick take on the last couple of weeks here.
Omar Pera: (22:49)
Yeah, so I actually told my brother last year in a Slack message that I just saw a demo with Kustomer and I was so amazed, so amazed about the product that I believe that they will pretty much eat the whole market share of digital customer service with a powerful CRM. So, I’m actually — I think most interpreters usually say that you are going to feel kind of sad in a way. It feels sad. But I think I have more excitement about the future. So I believe now it’s like I’m in this new adventure. It’s like starting on day one with the same excitement as if I started Reply on day one. So I am very, very, very happy of this.
Gabe Larsen: (23:39)
Good man. Well again, congratulations. I know everybody here at the Kustomer Crew is excited to have you join. So talked about a lot; the acquisition, best practices with using AI, a lot about bots and different AI capabilities. Summarize kind of the conversation for us as we think about customer service leaders trying to win and take today’s challenging times.
Omar Pera: (24:01)
So I would say any customer service leader knows that it’s very hard to keep satisfaction high while you are growing. That is very hard. So I would say make self-serve a priority in your company. Start very small, make it very easy to find answers and that, you bring that together with a customer service tool that is very good. Put in the context of a contact in the same screen such as Kustomer. I believe it’s actually the key to success. So my last point will be, really the technology is there. There’s no need for one year plans. You just need to start a small start today and really don’t wait, just implement these broadly and the benefits will come over time.
Gabe Larsen: (24:45)
Yeah. Yeah. By small and simple things great things come to pass, a wise man once told me that. So Omar, really appreciate your time. If someone wants to get in touch with you or learn a little bit more about some of the things you’re doing, what’s the best way to do that? Like LinkedIn maybe or?
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.
Here at Kustomer, we believe artificial intelligence plays an essential role in helping companies scale customer service and efficiently deliver exceptional results. And we aren’t alone. Gartner predicts that 72% of customer interactions will involve technology such as machine learning and chatbots by 2022. That’s why we are excited to share that Kustomer is acquiring Reply.ai to deliver even deeper intelligent self-service and agent assistance to our customers.
As a long-time partner of Kustomer, Reply is able to seamlessly integrate their tools into the Kustomer platform and help brands efficiently scale without compromising quality of service. The partnership furthers our commitment to integrating Kustomer IQ, our artificial intelligence engine, throughout the customer journey, while providing some powerful benefits to businesses and customers.
Reply is ranked as one of Forrester’s Top 10 AI Providers for Customer Service Automation, leveraging sophisticated machine learning models to power incredibly accurate self-service chatbots and deflection tools. With an astounding 40% average deflection rate, Reply, now a part of Kustomer IQ, can successfully resolve nearly half of all initial customer communications without the need for live interaction with a service agent. And with 67% of customers preferring self-service over talking to a company representative, deflection tools are not only a win for businesses, but also for customers.
With Reply now a part of Kustomer IQ, our customers will save thousands of hours spent answering simple questions, so they can focus on the most important cases that have a much larger impact on business and loyalty. At a time when customer service teams are being asked to do more with less, our suite of AI tools can tackle your growing queue of inquiries around the clock, while drastically minimizing costs.
We are so excited to welcome co-founders Omar and Pablo Pera, and the entire Reply team of world class data scientists and engineers to the Kustomer Krew. With Reply’s engineering offices in Madrid, this acquisition will also expand our presence in Europe and accelerate our growth in the region.
It goes without saying that we’ve always been committed to revolutionizing customer service. Today’s acquisition of Reply marks one more step in that journey.
What Customers Can Now Expect From Kustomer IQ
Built within Reply’s natural language processing engine, these best-in-class chatbots feature visual flow builders and templates for easy one-time creation and deployment across multiple channels and languages, providing effortless experiences by connecting customers to the right information.
Knowledge Base Deflection
An enhanced deflection widget can be embedded in forms, email, and chat, and features a powerful information retrieval system in which a semantic search engine and answer extractor not only provide relevant articles and content, but the exact answer to a question.
The platform can plug into third-party APIs to leverage a company’s most critical customer data points when deflecting. For example: a chatbot can answer the question “where is my order” or “when does my policy expire”.
Relevant answers and subsequent actions can be suggested to agents based on historical behavior, user text and conversation context. Actions include routing or auto-tagging conversations, as well as responding with relevant templated content.
Deflection success rates are measured and chatbot behavior can be evaluated, with functionality to support custom events, set conversion goals and segment audiences.
Reply is the first acquisition for Kustomer, reinforcing Kustomer’s commitment to AI and machine learning capabilities throughout the customer journey. With Reply, Kustomer will now offer enhanced chatbot and deflection capabilities through its customer service platform.
New York, NY – May 14, 2020 — Kustomer, the omnichannel SaaS platform reimagining enterprise customer service to deliver standout experiences, announced today it has signed an agreement to acquire Reply.ai, a customer service automation company founded in 2016 that helps companies scale intelligent customer service without compromising experience. Reply leverages artificial intelligence and machine learning models to improve agent efficiency through self-service chatbot and deflection capabilities. This announcement comes on the heels of the expanded roll-out of Kustomer IQ, the artificial intelligence engine embedded across Kustomer’s CRM platform. With Reply, Kustomer can provide even deeper intelligent self-service and assistance via Natural Language Processing (NLP) based chatbots, enhanced omnichannel customer deflection and machine learning based response suggestions. Madrid based Reply will also accelerate Kustomer’s European growth by significantly increasing its presence in the region.
“We believe artificial intelligence is essential to helping today’s enterprises scale customer service and efficiently deliver exceptional results. We recently rolled out Kustomer IQ to meet the growing need for companies to have access to the power of AI, and with today’s acquisition, we continue our investment in bringing self-service tools and intelligence capabilities to our clients,” said Brad Birnbaum, CEO and Co-Founder of Kustomer. “Reply has built deflection and self-service chatbots that help companies effectively deflect initial customer communications at an astounding rate of 40 percent. This means that almost half of all initial customer communications can be successfully resolved without requiring live interaction with a service agent, bringing greater efficiency to the entire customer service function. We are excited to welcome co-founders Omar and Pablo Pera and the entire Reply team of world class data scientists and engineers to the Kustomer Krew.”
The Reply suite of tools include deflection capabilities that look at historical and contextual data, continuously improving over time, as well as deflection widgets that can be embedded in forms and email, and features a powerful information retrieval system that extracts relevant answers to customer questions from a company knowledge base. Reply also features a platform to build chatbots that can be deployed across multiple channels and languages, and agent-assist tools that suggest relevant answers to messages and subsequent actions, such as routing or auto-tagging conversations.
“We are excited for Reply to join Kustomer and share its mission to make customer service more efficient, effective and personalized. As a long-time partner of Kustomer, we are able to seamlessly integrate our deflection and chatbots technologies into Kustomer’s platform and help brands more cost-effectively increase efficiency. We look forward to working with Brad and the entire team,” said Omar Pera, Co-Founder of Reply.
“By leveraging advanced AI capabilities and Kustomer’s robust CRM platform, combined with self-service deflection tools, Kustomer is uniquely built for the needs of today’s enterprise companies,” adds Birnbaum. “Since 2015, we have been committed to revolutionizing customer service and today’s acquisition of Reply marks one more step in our journey.”
Kustomer is the omnichannel SaaS CRM platform reimagining enterprise customer service to deliver standout experiences. 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, Glovo, Glossier and Sweetgreen. Headquartered in NYC, Kustomer was founded in 2015 by serial entrepreneurs Brad Birnbaum and Jeremy Suriel, has raised over $174M in venture funding, and is backed by leading VCs including: Coatue, Tiger Global Management, Battery Ventures, Redpoint Ventures, Cisco Investments, Canaan Partners, Boldstart Ventures and Social Leverage.
Reply.ai helps brands scale customer service by providing AI-powered solutions that instantly resolve common customer questions on chat and ticketing channels. The two core products, Deflect for Ticketing and Deflect for Chat, reduce consumer frustration and deliver 24/7 personalized service, ultimately increasing self-service effectiveness and support team capacity. Reply’s customers, like The Cosmopolitan Of Las Vegas, Vail Resorts, Honeywell, Glovo and Paula’s Choice, rely on Reply for innovative and industry-focused solutions to customer service problems. Reply was founded in 2016 by former Google and CERN engineers and is headquartered in New York City and Madrid, Spain.
Life has become a series of trade-offs and workarounds in light of the pandemic. Curbside pick-ups are my new norm. My inbox is a litany of order confirmations and estimated delivery times. Last weekend, I drove to a local hardware store and found the following handwritten message on a sign at their front door: “Know what you want. Get in and get out.” At times, my interactions with people feel purely transactional.
The world has changed, and customer service is changing right along with it. Businesses are being challenged with a paradoxical conundrum: how do we retain our humanness? How do we maintain trust in a time of uncertainty? Below are three ways customer service teams must adjust in light of the global pandemic.
Empathy Is #1.
Companies who approach customer service with a deeper level of empathy are more likely to maintain loyalty and win new business. This concept is not a newfound revelation. In fact, The Empathy Business has studied the efficacy of empathy in business for years. And what have they found? Organizations that focus on the “emotional impact” they have on employees, customers, and society are valued higher and earn more than their counterparts.
In the world of COVID-19, empathy is even more desperately needed. Quarantine measures and social isolation mean a rise in loneliness and other mental health issues. Think about it this way: what if your organization delivers the only social interaction an individual will experience for a full day? Armed with that information, how should you change your customer journey?
Start small. Use your data. Study the way your customers use your tools and services. Where are they running into roadblocks? Where are you making your customers’ lives easier? Take note and adjust. Document your FAQs in an accessible location, like a Knowledge Base. Have the patience to clearly explain the nuances of your business and policies. Above all else, practice kindness in all of your communication.
“One-Size-Fits-All” Won’t Succeed.
As the pandemic spreads, we’ve seen a spike in conversations for many of our clients. And according to a recent survey by Kustomer, there has been a 17% increase in inquiries across industries. With this influx in communication, it no longer makes sense to force every customer to call the same number to contact your company. Instead, it’s time to get smart about the channels you employ to manage customer interactions, and it’s time to invest in a fully-fledged omnichannel experience.
But beware: you should avoid blindly adding new service channels without a strategy in place. Dig deep into your customer personas and understand their respective beliefs and behaviors. McKinsey notes that “not all customers are the same, and it’s how they differ in their behavior and preferences—particularly on digital—that should have an outsize influence on how service journeys are designed.” Keep this in mind, too: a small percentage of customers — classified as the “offline society” -— may suddenly be forced into adopting digital communication in light of shelter-in-place orders. Take these different customers into account when adapting your customer service strategies.
Automation Is a Necessity, Not a Luxury.
As we’ve seen an increase in the number of inquiries, we’ve also seen an increase in the need for artificial intelligence and machine learning technologies. Agents can become easily overwhelmed by an onslaught of new messages. AI can automate some of the more tedious tasks that those agents might encounter, thereby freeing their time for more important work.
Consider how you can deflect commonly asked questions and save your agents valuable time. Let’s say you’re an airline in today’s world. With the rise of the pandemic, you’re being flooded with requests for information about your refund policy. Instead of directing your team to answer each inquiry individually, you could use automation to serve up pre-written articles that align with the inquiry’s keywords. Not only do you protect your team’s time, but you also deliver a better customer experience as customers receive near-instant answers to their questions. Beyond that, unsuccessful deflections can provide a treasure trove of data to guide your future content.
Those who adapt and adjust their strategies now can influence their fate in the post-pandemic world. The opportunity is there. We have to be good stewards of our time and resources to capitalize on it.
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.
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.
Customers have high expectations when it comes to the level of service they demand from brands. While the American Express Customer Service Barometer found that Americans are willing to spend up to 17% more on businesses with excellent customer service, the top reason most customers switch products or services is because they feel unappreciated by the brand. In fact, 33% of Americans are inclined to switch to a different company after a bad experience.
Unfortunately for companies, the cost of human support is high. Introducing artificial intelligence (AI) into operations is one way companies can control costs while improving their service abilities and maintaining the human touch that makes customers feel appreciated and valued.
What Is AI Customer Service?
While AI and machine learning may at first appear to threaten the customer service industry, they actually have the power to make customer service agents’ jobs less time-consuming and more fulfilling.
Integrated AI can instantaneously retrieve the data an agent needs, while the agent or support team deals directly with the human side of customer service. This eliminates the need for human agents to run multiple systems simultaneously to address customer inquiries. Rather than employ agents to work 24/7 in a call center, AI can be used to field and classify calls and messages so human agents are then able to work more reasonable shifts with increased efficiency and reduced physical and mental stress.
Through intuitive machine learning that constantly works to improve itself, AI allows companies to be present to the very best of their abilities along every step of the customer journey.
How Are AI and Machine Learning Being Used in Customer Service?
There are plenty of reasons why AI and automation should be loved, especially when it comes to customer service capabilities. Here are a few ways the technology is already being used:
Everyone has had the experience of needing a simple question answered by a brand, only to dread having to jump through customer service hoops just to get someone on the phone who may or may not have the answer. Conversational chatbots can make these conversations more seamless. Not only do conversational platforms help cut costs, they also can help your customer service scale and enable your agents to have more meaningful and productive conversations. By using chatbots to aid your live chat operations, your business will be able to engage customers in real time without the need for an around-the-clock staff.
Amazon, for instance, uses chatbots that leverage the data the company collects on all of its customers and their past orders. By allowing chatbots to access information about the customer’s past preferences, you can have the chatbot interact with customers up to the point where an agent is needed. Once the conversation is transferred to an agent, they can pick up where the chatbot left off.
Eventually, you can train your chatbot to not only acquire customer information, but also recommend the actions customers and agents should take next. If a customer simply needs a common question answered about a product they already purchased, the chatbot can direct them to a FAQ rather than contact an agent. This saves the human agent’s time and allows them to make better use of it dealing with more complex customer queries. All chatbot interactions can be automatically tagged in your AI system so they’re easy to track and reference, and can be used to improve future recommendations.
Robotic Process Automation
Robotic process automation (RPA) can be used to handle the necessary, but routine tasks that keep support agents from interacting with customers in meaningful ways. By taking care of low-priority, mundane tasks, RPA helps customer service agents reclaim time in their days that would be better spent handling high-value customers or fully addressing complex questions without feeling rushed.
RPA works across multiple systems to track user actions within an application to complete and perform tasks ranging from automatically replying to emails to routing conversations. The improved efficiency from saved time on menial tasks also saves companies money. Aside from cutting costs, RPA has the power to increase revenue by speeding up the rate at which customers are able to make purchases through your company.
In the past, automated phone systems performed data dips, moving customers through a phone tree where they were asked to “press 1 for a current reservation,” “press 2 for reception,” “press 3 to make a new appointment” or something similar. The flaw in this system is that the information collected was never handed off to the agent, and the customer would have to repeat themself once they were connected with a human. AI eliminates this unnecessary process — if a customer is calling about a product that’s discontinued, for example, there might not be a need for a human agent to talk to the customer only to relay that same information. This saves time for both parties by supporting your human customer service agent and saving the customer from exasperation.
Using AI to capture information about the customers and pass along only the absolutely necessary parts of that information allows agents to have more meaningful conversations and become more knowledgeable about the areas of the business that matter.
If a customer still wants to talk to a human even after discovering their product is discontinued, the agent can immediately begin the conversation by offering recommendations for other products the customer may like. AI doesn’t eliminate the need for humans, as many people incorrectly assume when they hear talk of using AI in customer service. Instead, it augments the human team and allows them to be better at their jobs.
Monitor Support Operations
When you use AI to monitor support operations, you can predict when conversations may start to turn from positive to negative. This insight allows managers to intercede accordingly, and no longer requires them to randomly audit customer service calls to regulate quality.
AI can also help monitor which responses result in reopened tickets. If response A, for instance, tends to resolve inquiries quickly, but response B results in the ticket repeatedly being opened, the system can recommend you eliminate response B in order to set your agents up for success. Managers and executives can use the data generated by AI to oversee customer service operations in a more clear, efficient way, improving day to day operations for everyone involved.
What Are the Advantages of Automated Customer Service?
Customer satisfaction is directly linked to the service experience, and so it’s important to make sure the customer journey is as seamless as possible. Integrating AI into your customer service isn’t about replacing humans. Rather, it is about arming your customer service agents with the information they need to have purposeful conversations with your customers, and using data to personalize your customers’ experience with your brand.
Incorporating AI customer service not only improves your relationships with your customers, it builds trust and increases brand loyalty. This means more repeat customers, and more word of mouth referrals for your business.
When you build an incremental strategy to roll out AI in your organization and optimize according to data collected, success is sure to follow. Using AI to build a more complete view of a customer’s relationship with the brand helps companies meet high expectations for exemplary service, and come across as anything but artificial.
Kustomer Offers AI Business Solutions
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. Kustomer IQ is a groundbreaking new service that 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, more personalized, automated customer experiences with increased efficiency.
Kustomer IQ integrates machine learning, natural language processing, predictive analytics, deep learning and multi-dimensional neural network mappings as a part of its AI suite. Natural language processing involves the interactions between computer and human language, and dictates the extent to which computers are able to process and analyze large amounts of natural language data. Natural language processing is used along with text analysis, computational linguistics, and biometrics in sentiment analysis, also known as opinion mining, which helps companies keep a finger on the pulse of their target audience’s interests and values.
Companies that employ the AI suite are then able to use their own data to train Kustomer IQ’s 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 Kustomer IQ, companies will be able to automate manual, repetitive tasks and essential processes of their customer service experiences. In addition, Kustomer IQ 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, Kustomer IQ frees up agents to focus on more complex and emotional customer interactions, resulting in reduced costs and faster resolution of calls.
Features of Kustomer IQ include automated conversation classification, queues and routing, customer sentiment analysis, automatic language detection, suggested agent shortcuts, customer self-service, conversation deflection and workforce management. If you’re interested in learning more about Kustomer IQ and how it can help elevate your business’s customer service capabilities, download our ebook, explore our website and get in touch today.
Kustomer offers real-time, actionable views of customers, continuous omnichannel conversations, and intelligence that automates repetitive, manual tasks to make personalized, efficient and effortless customer service a reality.
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.
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.
There are a lot of buzzwords gaining traction as we settle into 2018, but probably none are bigger than “Bot”. Particularly in the customer support arena, as companies look to further reduce the cost of serving customers. This has resulted in the rise of chatbots. However, no matter how good the technology, bots aren’t going to be able to resolve every situation or interaction anytime soon. That means that transferring from bot to agent will remain a crucial part of the chatbot experience. What do agents and customers expect when the time comes for them to be connected?
Chatbots are undoubtedly improving and becoming better at seeming human while collecting crucial customer information—their name, address, and description of the problem—and based on that they may be able to produce some initial solutions.
However, the risk companies face is that they give their customers flashbacks to the 90’s. That means an experience that’s identical to the Interactive Voice Response phone trees that end up connecting them to an agent who needs to ask all the same questions over again. How can brands prevent this? Here are a few suggestions:
Put Agents in the Driver’s Seat: Empower agents to select the right channel to engage with the customer and best resolve the issue.
Deliver Complete Context: The agent of the future will be a critical thinker. If you provide them with all the information they need about the customer story so they are well-informed of their profile and history, agents can craft some of their own dialogue based off of talking points from reference scripts. While this creates a more natural customer interaction, it also means that agents must be able to think on their feet and deal with possibly tense situations. Adapting to every situation and keeping calm and focused under fire is thus crucial for great customer service.
Give Agents a Heads-Up: Automate agent alerts based on changes to the customer’s status, order updates, or snoozes so they’re always aware and ready to connect.
Enable Empathy: It’s always great for agents to show empathy, but empathy is hard for any human being to deliver if they don’t understand the gravity of the situation. Brands can use tools like NLP (Natural Language Processing) to provide some insight into how the customer is feeling at the time of engagement, and know whether their outlook is positive, negative, or neutral.
Streamline Connectivity: Efficiency is still critical at the point of contact, but not at the detriment of communication skills. Create personalized shortcuts that don’t just display simplistic customer information like name and email, but provide details of their relationship such as recent items they’ve viewed, their current sentiment, their order’s delivery status, etc.
For brands to be successful in the future, the hand-off between bot and human needs to promote a differentiated experience. If your customers have to start the process all over again when they switch to an agent, then they’re better off just connecting with one in the first place.
However, if your customer can go from speaking with a bot to an informed and empowered agent, that’s a game-changer. If your agents are equipped with all the context and transaction information they need, then they’re well-placed to deliver a meaningful experience. Combining chatbots, automation, sentiment analysis, and a full view of the customer is what it takes to turn your agents into heroes and deliver next-level service. Instead of going from a bot to a human who’s asking mundane questions, doesn’t know anything about the customer, and is powerless to make a decision, they can be connected to a CX superhero.
Vikas Bhambri is Kustomer’s VP of Global Sales and Customer Success