At the end of 2019, the future of customer experience (CX) is at stake. Customer experience has emerged as the most powerful competitive difference, trumping cost and convenience as the make-it-or-break-it decision factor for buyers. Customers make decisions based on the value of their experiences, and as Forrester points out, the unprecedented volume of technology transformation has created an upheaval in the way consumers interact with brands.
It's also had a dramatic impact on consumer behavior and consumer expectations. Today's customers, steeped in a world where convenience comes at the click of a button instantly, are demanding to be met on their own terms, and to stay competitive, companies need to deliver.
The good news is that CX initiatives can potentially double revenue within 36 months. Companies that earn $1 billion annually can expect to earn an average of $700 million more within three years, while SaaS companies can expect to increase revenue by $1 billion.
Which means it's time to invest up front in the AI-powered customer engagement platforms that can deliver at every point of the customer journey. The technology has evolved to unlock capabilities from round-the-clock accessibility and user-friendly decision-support systems to sophisticated chat conversations and tools that enable live customer service agents to seamlessly deliver satisfaction.
The need to deliver industry-leading customer service experiences will gain momentum in 2020. Companies need to keep that strategic point of view firmly front and center, and AI-powered conversational solutions will be key to winning. Some big CX technology trends have emerged in the past year, and they'll be influencing how customer service and experience strategies evolve throughout 2020 and beyond.
Here's a look at some of the most important lessons of 2019, and how companies can enter 2020 prepared for the future of customer experience.
The biggest, and arguably the most important customer service trend: Engage the customer where the customer wants to be engaged.
"We’re continuing to see more and more customers expecting companies to come to them," says Ryan Lester, Director, Customer Engagement Technologies at LogMein. "People don’t want to pick up a phone and have to call you or be kept on hold; they want you to engage in the messaging channels, social channels, and apps they use, and they want a consistent experience across the board."
But that's not a synonym for "omnichannel." It's been a buzzword for some time now, especially as the number of channels have proliferated and matured. Platforms like WhatsApp are offering more sophisticated ways to engage with customers, with photo carousels, videos, and more, while integrating with backend APIs and adding keywords and metadata has become easier than ever. These platforms tend to have a low cost of entry too, making it tempting for companies to simply stack up the next and the next as they emerge, without considering the endgame.
But there are some things that a service like WhatsApp, or a chatbot, or email is good for, and then some things that a channel simply can't deliver, Lester says. More important than a rush to be fully omnichannel is the need to look at how customers are actually engaging and where. This will lead to a decline, or a mass exodus, from isolated, single-purpose bots and a move toward connected backend systems that use AI to develop a synthesized picture of customer wants and needs.
"Be where your customer is, but don’t build more silos," he explains. "You have to take a broader, more deliberate approach around how you build an infrastructure that can support more than one channel."
Whatever channels and technology you use, be consistent in your messaging, and offer a continuous thread and seamless experience wherever you find them.
Employee experience will remain one of the top influences on customer experience, and in 2020, investing in employees will pay off in big ways. A happier workforce is clearly associated with companies’ ability to deliver better customer satisfaction — particularly in industries with the closest contact between workers and customers, including retail, tourism, food service, health care, and financial services. And enabling those employees to do their job more easily with better results builds on that happiness quotient significantly.
Customers have shown a strong interest in self-serve options, empowering them to find answers to a wide range of questions fast. But that means the employee's role in customer service has matured significantly, and customer agents are now freer to tackle the more advanced customer inquiries. That's where employee-facing AI comes in, equipping customer service employees with the information needed to ensure customer satisfaction, even when things get complex.
It could be an agent in a contact center relying on their AI-powered tool to surface answers fast or joining in as the bot listens to a conversation to provide recommendations to the agent. It could also be a chatbot that faces an employee in a physical store, so that rather than having to call an internal support center, wait on hold, get an answer while the customer waits, they have the info needed at their fingertips.
"You get the best of AI and the bot, and you get the best of the agent," Lester says. "Bringing those two parties together in a much tighter way leads to a better customer experience."
Large banks have deployed these tools and have seen great results, Lester adds. One, they start with a single use case, maybe around policy information. But then they expand to others, like branch information or seasonal information around taxes, other things related to different times throughout the year. Employees have felt increasingly empowered, resulting in swift adoption. They have better access to information, and they can focus more on the customer rather than trying to find information.
To extend that to a retail store, think about the turnover in retail, or the number of temporary seasonal employees that drop in and out. These tools empower employees in-store with immediate, accurate answers that keep customer service seamless.
Both use cases also result in broader insights from your AI, with access to all the questions asked across different stores, or an unexpected signal in the market – perhaps an item in one store that should be carried in all your stores, for instance.
Self-service solutions and sophisticated chatbots can also vastly improve employee experience, solving the most basic, repetitive questions without having to involve human oversight. It removes the burden of these tedious, repetitive tasks from employees who naturally want more satisfying, engaging work.
The demand for self-service solutions is actually increasing as customers are less and less willing to spend time waiting on hold to talk to an employee or an agent. Fortunately, not every online customer support case requires human interaction. Knowledge bases and chatbots powered by AI and natural language processing can answer basic questions, with complex issues shuffled to live support as necessary.
There’s a great opportunity to use AI to take a new approach to developing, managing, and improving workflows related to self-service content as well.
"AI gives us a really good opportunity to be more deliberate about what content we’re creating, how often we update it, how impactful it is," Lester says. AI has breathed new life into the way content creation and knowledge base management is thought about. “Companies tend to prioritize customer-related metrics and agent metrics, but making your content a first-class citizen, and using AI-driven data to improve that content, will have a huge impact.”
That’s because knowledge bases are a cornerstone of self-service, and companies need to take a data-driven approach to developing and keeping them updated. Did an article cause a customer to channel shift, or escalate? Was there a follow-on to that answer, and does it mean the answer was satisfactory, or that they left in a huff? Follow-on questions are leading indicators that the content is not fulfilling the person’s need.
However, just updating the content isn't sufficient -- the workflow around the questions is key.
AI analytics allow you to effectively anticipate what follow-on questions are typical, so that you effectively move the customer forward toward getting them to the outcome they desire.
“If a customer says, where’s the closest branch, you may offer content that says, here’s the address in that branch, and you pull that from a third-party system,” explains Lester, “but then the customer says, how do I get there? Is it open?”
There's also an emerging trend around natural language generation, or AI generating content for the user. Companies need to think about how disparate sources of information can be fed into the AI so it creates tailored, customized, targeted content that might be a better outcome for that user.
However the content is generated, it’s critical to provide a seamless transfer between bot and human agent, which means these agents are taking on a new role, training and supervising the automated experiences these bots are creating.
"We won't simply 'flip the switch' and replace our human agent force any time soon," Lester says. "Humans are still required to connect with customers when they need us the most. Humans are also the only way these tools will be developed and designed in ways that truly put the customer first."
Delivering an optimized experience means organizations must access personal and confidential customer information – but once that box is cracked open, they're also at risk of mishandling that data, and exposing it via a breach or unauthorized access.
Customers are more vigilant than ever about their privacy and security, and any breach is a breach of their trust and immediate hit to a company's reputation and revenue. A company might even face major regulatory fines. In other words, security is increasingly taking center stage as customers get more savvy about protecting themselves, and will not hesitate to call out a company that missteps.
It's time to proactively deal with any security vulnerabilities, before they are exploited. Defensive and preventative strategies are the first step to ensure that threats are detected and contained before they cause any damage to your customers. It requires a holistic approach that involves getting all stakeholders on board to evaluate gaps.
And it's an ongoing process to tackle, now, through 2020 and beyond. Policies and procedures should be improved every year, including staff training, customer education around protecting themselves, and vetting any new vendors, no matter how exciting their AI offerings might be.
"You want to make sure you do your due diligence about what you’re having your customers interact with," Lester says. "One, make sure your own house is in order, but also ensure the folks you work with, platforms or business application vendors, are up to speed on newer and evolving sets of standards."
Scarlet Johanssen is not going to be in our ears any time soon, Lester says referring to the movie “Her”, but developments in next-generation AI will create exciting new opportunities.
For instance, 2020 will be where we really start to see a post-app world. Not to say that native apps are going to go away completely, but with trends in responsive browser-based experiences, companies have the opportunity to think about creating engaging experiences that include things like AI and chatbots and conversational experiences that don’t require building a full native app. There are obvious examples like the big on-demand services – Uber, Lyft, Airbnb – that will still require the completeness of a native app to fully leverage the hardware in a phone, but more and more, mobile web is going to become on par with the native app experience.
"Next year will start this tipping point of a post-app world, where things like Apple Messaging and improvements in the browser are going to drive more capabilities," Lester says. "Whether a user is on a desktop, a tablet, or a mobile device, you can start to have really immersive, engaging experiences without having to invest in a mobile app."
Another major future trend is about creating a much deeper extension of your employee with the customer. For example, things like guiding the customer and seeing what they see through co-browsing. For instance, if you're a company that sells mortgages and the application process is complicated, the technology has evolved to the point where an agent can look at the customer’s device — and it doesn’t matter what the device is, so long as they’re in a browser — and see what they’re looking at, so that they can walk a customer through an experience, and do things like AR for annotation in a variety of use cases.
"It starts to really blur the line, in any device, between the employee, the company, the brand, and the customer in the overall experience," Lester says. "That’s exciting, and the capabilities that are coming down the pike will open up some exciting opportunities."
AI is only going to become better and better at offering outreach, support, better outcomes, and more.