Using AI to Power the Next Decade of Customer Experience

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Join Kate Leggett, VP and Principal Analyst at Forrester Research and Mahesh Ram in an exclusive webinar, “Investing in the Future of CX” on Wed, Mar 14 at 11:00am PST. We will discuss how CX will become faster, smarter—and yet, more human with AI.

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Jeff Bezos once famously noted: “The best customer service is if the customer doesn’t need to call you, doesn’t need to talk to you. It just works.” 

Bezos was foreshadowing what today’s consumers now expect from business—speed, accuracy and consistency—across every interaction channel and especially for support. Omni-channel contact capabilities and the rise of conversational interfaces have raised the bar further for businesses to compete for consumer attention in the digital on-demand economy. Failing to meet this bar results in lost opportunity.

But racing to meet these rising expectations can incur massive costs for business without thoughtful planning and strategy. For example, if organizations try to meet these users’ rising expectations merely through increased staffing, it would be incredibly inefficient and expensive—and worse, the quality of service would greatly vary. It’s simply not scalable to throw labor at the problem. Yet if the fundamental goal of any business is to get closer to customers, what can companies do to deliver a superior customer experience that is both elegant and profitable?

Fortunately the answer is emerging before our very eyes. A recent study by Aspect found that nearly 3 out of 4 consumers prefer to solve their customer service issues on their own if presented with the right tools to do so. Personalized and intelligent automation, with artificial intelligence at its core, can be combined with time-honored principles of human-centered  service. Intelligent self-service solutions, powered by machine learning, can liberate companies to focus more on optimizing customer journeys and delighting consumers.

Moving from Defense to Offense

AI is becoming the new competitive battleground for delivering a superior customer service experience (CX). It is helping companies work smarter and transition from defense to offense, from heavy dependence on labor to intelligent automation. The leading brands are increasing their investment on customer-facing knowledge and education knowing that this knowledge “has wings” to “fly” to all consumer touchpoints and be instantly available to end-users on the device, browser and channel of their choice.

Today’s connected consumers demand much higher levels of choice and control: they want to choose the customer service experience that best suits their needs at that moment. They are trained to express themselves conversationally on any channel. They want their questions understood and resolved within the context of previous interactions. They want to seamlessly switch between different contact channels as it suits their busy lifestyles.

Companies are turning to AI for delivering this consistency and speed across all support channels.

AI helps businesses move from defense to offense

Improved self-service creates a slew of secondary benefits for companies and their employees.  As intelligent automation enables self-service for many (if not most) Tier 1 and Tier 2 tickets, agents become more empowered as well. They can handle more complex interactions that require more attention and greater personalization. Their engagement level goes up and their attrition rates go down. They go from being ‘agents’ to becoming ‘guides’ or ‘concierges’, which in turn ensure high CSAT ratings.

Intent to Resolution: An AI Journey

AI allows organizations to take in consumer issues via completely natural language, make sense of their actual intent (i.e., categorize them properly), and determine the user intent in real time. But understanding the intent of the ticket is only one part of the complex puzzle.  Self-service resolution requires deep AI and machine learning science that identifies the most relevant resolution from the vast repository of knowledge and serves it up in real time. If the question is not self-serviceable, AI must automatically detect this and redirect the question to a human agent minimizing user friction.

The AI algorithms are able to deliver intelligent automation at speed and scale. Understanding the question involves using natural language understanding that can handle complex utterances and go beyond mere keyword dependencies. This is a hard problem but once solved, it creates a miraculous experience. Once issues are aptly understood in context, supervised and unsupervised learning methodologies allow classification of the incoming user questions into relevant tags or categories. This is a multi-step process that involves sorting, optimizing and creating tags.

For instance, an ecommerce company might get frequent questions around pricing, discounts, shipping, refunds, returns and exchanges which might fall under more than one category.

A question may fall under multiple categories, as depicted in the graph above

The ability to automatically categorize tickets as they come in greatly improves the accuracy, quality and speed of providing resolutions that match the issue intent. Categorization also creates the ability for companies to have a deeper understanding of product issue trends, key defects, or gaps in knowledge.

AI and machine learning applications for customer experience are hard to build and design. When done well however, the use of AI empowers organizations to create delightful end-to-end customer journeys by providing instant resolutions in minutes as opposed to hours, or even days!

Moving from Tactical to Strategic

Artificial intelligence also employs sophisticated machine learning capabilities that leverage existing algorithms to learn from data, in order to build generalizable models that give accurate predictions, find unknown patterns and offer deep insights.

Companies are able to take the learnings from their customer interactions, build on them and then intelligently apply them to improve customer journeys across the board by taking into account the variable operating conditions. User journeys often vary depending on where they are is in the lifecycle of a product or a process, nature of their support issue, whether they are a first-time user or not, their demographic profile and other factors.

As systems continue to evolve and become more sophisticated over time, AI enables companies to be more strategic and targeted about who they serve, what channels they employ, and where they allocate their resources. As a result, they are able to achieve the magic equation where the key support metrics go up on the one hand and costs come down on the other.

Machine learning capabilities lend a competitive advantage to businesses. 

With technology on their side, organizations are in a position to make informed business decisions to achieve a sustainable ROI while creating a frictionless customer experience.

Conclusion

With customer service becoming a brand differentiator, organizations are using AI technology as an enabler to transition from individual silos and disjointed experiences to integrated and consistent experiences. Organizations are moving from defense to offense, and from tactical to strategic. Most importantly, end-users or consumers are happier and spend more money with these leading companies. As CX leaders, there has never been a better opportunity to build a leadership position for our brands that deliver an intelligent and effortless customer experience!

Join Kate Leggett, VP and Principal Analyst at Forrester Research and me in an exclusive webinar, “Investing in the Future of CX” on Wed, Mar 14 at 11:00am PST. We will discuss how CX will become faster, smarter—and yet, more human with AI.