To paraphrase author and customer relationship pioneer Martha Rogers, your customers are the most valuable asset your company has. Without them, you don’t have a business. You have a hobby.
That observation, first made in the late 1980s, has only grown in its veracity over time. No technology, intellectual property or any other asset is more important than the customer, and companies spend billions of dollars a year trying to track their needs and preferences.
With the advent of artificial intelligence, the science of measuring the customer journey and the customer experience has grown more precise, with companies like Adobe, NICE, IBM and Medallia giving marketers more data and behavioral cues than they’ve ever had.
AI can inform each customer-facing decision to create more value for customers, employees and shareholders, according to a Harvard Business Review article published in August. Results from researchers at Stanford University and Massachusetts Institute of Technology showed positive effects from the rollout of an AI-based conversational assistant tool to 5,200 customer support agents in several countries. The tool raised agent productivity by 14% on average, the AI-assisted interactions had higher average net promoter scores, and monthly agent attrition dropped by 9%.
Not that AI-driven customer experience management is about contact centers. As Medallia SVP, Executive Advisor Bill Staikos described his company’s value proposition, AI can sharpen almost every tool in the shed from simple surveys to pitching the “right offer, right time” to the customer who still has unconverted items in his or her shopping cart.
With more than 20 years in business and a roster of more than 2,000 employees, Medallia has been using AI since 2008, Staikos said. The company pitches itself as a platform that captures billions of experience signals across interactions, including all voice, video, digital, IoT, social media and corporate messaging tools. It then uses proprietary AI and machine learning technology to produce predictive insights that drive desired business actions and outcomes.
Medallia’s customers reduce churn, turn detractors into promoters and buyers, and create in-the-moment cross-sell and up-sell opportunities, Staikos said. Last August, it surpassed 1 million weekly unique users on its platform. One of its goals is to dynamically change the customer experience in real time and within the user’s context.
“From a marketing standpoint, I think everyone’s still coming up [with] the current right use cases,” Staikos said. “I think AI has the opportunity to expand the surface area of more humanized experiences, and part of that will be seen in greater personalization. As the next couple of years start to unfold, you’ll see greater personalization, understanding of your specific needs, and how that translates into the brands you buy from. You’ll see highly tailored recommendations for different experiences that affect the brands you buy from, the products they offer, and even the way [you] search for information on the brand’s website.”
For Medallia, AI shows up in its text analytics capabilities, sentiment analysis, contact transcription, and generally by giving structure to the unstructured data that comes from various customer touchpoints. Its Athena solution is an AI technology layer that helps turn customer, employee and product journey data across a multitude of channels into a 360-degree view that drives action to improve experiences by aggregating data from video, image, audio, survey or any other signal. Its insights are characterized by emotion, effort, sentiment and intent detection.
AI has driven several of the company’s recent use cases. For example, Dick’s Sporting Goods worked with Medallia to capture digital customer insights to understand sentiments at important points in its eCommerce journey platform, including what is needed to turn shopping carts into completed purchases.
Voice of the customer insights from Medallia are tied into Adobe Analytics, enabling the retailer to make decisions that will drive click-through rates and future revenue. Dick’s was able to decrease bounce rates by 50 basis points, increase conversions, and improve its ability to respond to the voice of the customer.
Staikos said he interacts frequently with companies that have more anecdotal evidence about AI’s effect on the platform. For example, he recently spoke with a company whose contact center agents were using sentiment analysis to score calls in real time to inform customer satisfaction levels. He’s also seeing a lot of activity around journey orchestration, hyper-personalization and employee engagement.
“We work with brands across every vertical, even in the public sector,” he said. “For example, right now the conversation across almost every business that we speak with is centered around generative AI. … I think that every industry is going to be impacted by these capabilities. Even traditionally where you might have seen an organization that was very survey-driven, now they’re shifting to measuring customer signals, whether that’s from observed behavior or financial or operational data. What we focus on is bringing all this unstructured and structured data together to analyze it to make more informed decisions around the customer as well as the employee.”
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