There is an intrusive buzz that is impossible to ignore, it’s an incessant drone that has captured every executive’s attention: the paradigm-shifting nature of artificial intelligence. For retail leaders, the question is not whether we should engage but how.

It’s time to come clean and admit that we regularly yell at chatbots. The current state of automated customer care centers is abysmal. When consumers engage, they often are greeted by an inept chatbot. As the engagement continues, the chatbot’s inability to meet customer needs then escalates to clients demanding human intervention after having already reached peak levels of frustration. This unnecessary consumer angst represents a brand blind spot. 

AI Innovation Theater

Navigating toward an answer is tricky as AI applications multiply, the underlying technology continues to evolve, and pressure to exploit the available applications rises. Rather than chasing the hype, now is the time for brands and retailers to identify goals and priorities as the first step toward developing a long-term AI strategy with the flexibility to capture the transformative benefits the evolving technology is likely to present.

Before transformation though, we should pause to relish the ultimate expression of AI hype, Coca-Cola’s “co-created,” limited-edition Y-3000 (year 3000) cola. The brand claims that customer-inspired AI insights co-piloted the taste profile. We can only speculate on the taste, which the brand describes as the “Flavor of Tomorrow.” This is AI innovation theater at its all-time worst. Buyer beware.

Full-Spectrum AI Customer Insights

We may soon live in a world where AI-inspired flavors actually matter, but basic, good-old AI-fueled retail personalization is already commonplace.

• Amazon’s AI-powered recommendations are a clunky, early application that annoyed customers at first, but as the technology has improved expect a more persuasive and welcome upsell.
• In 2019, Nike purchased the AI predictive analytics company Celect to optimize product offerings, inventory management, and distribution. It is challenging to parse Celect’s analytics from Nike’s larger technology stack, but a recent post by the digital creative agency DigitalSilk suggests that the Celect acquisition was part of Nike’s direct-to-consumer strategy, and key to the utility of Nike’s SNKRS app. The company relies on the SNKRS app to analyze identifiable consumer behavior and apply that information to personalized marketing, future retail locations, product development, and distribution.
• Poshmark is doubling down on personalization according to Chief Data Officer Barbara Saxena. As customers spend time in the Postmark feed, the company collects data that is fed back in real time or used for future targeting.
• The Harvard Business Review reports that brands are working with technology partners or supporting internal teams charged with developing artificial intelligence-fueled customer experience engines to track and influence behavior. Recent tech breakthroughs support a 360° customer profile generated from sales data and trackable engagement that can be applied to hyper-personalization initiatives.

First-Party Data Is the New Espresso Shot

While companies increasingly rely on AI for insights, the applications are only as effective as the data they are trained on. The (now over-used) analogy “data is the new oil” applies but another analogy, “garbage in garbage out” is a better mantra. Limits on purchasing personalized consumer data lead to anemic personalization efforts. While no federal online privacy standards have yet been codified, individual states and E.U. regulations already constrain access to anything beyond first-party data. Consumer privacy regulation compounds the recent data dearth spurred on by Apple’s tracking transparency limitations. While AI software marketing materials hail both contextual and cohort data groupings as a personalization bonanza, de-identified targeting data is a decaffeinated version of first-party data.

If we update the analogy “data is the new oil” to “first-party data is the new espresso shot” for brand/retail personalization, prioritizing the collection of first-party data should be a strategic goal in any long-term AI strategy. The New York Times recently reported on Lily AI, pioneered by entrepreneurs Purva Gupta and Sowmiya Narayanan. Their AI-powered ingenious retail search engine translates search product descriptions that would confound a standard search engine. NYT cited Madewell.com as a use-case example of Lily AI embedded in its search engine. The system uses the customer’s voice to identify key product descriptors. So instead of the typical utilitarian search terms, wide-leg jeans or crop cardigans, Lily AI directs consumers to specific inventory by responding to natural language and situational prompts such as quiet luxury, study hall, and boho chic.

While the engine’s interpretive mastery is a breakthrough that reportedly resulted in a three percent increase in online conversions in less than three months according to the Times, it would be useless without customer engagement on the site. Driving customers to initiate a product search on branded sites, rather than via social or aggregated shopping platforms creates the opportunity for increased conversion as responsive, dynamic first-party data feeds the agile search engine.

Skincare and beauty brands are also keen to harness first-party data-driven personalization If Madewell saw a three percent jump in sales after leveraging real-time customer data, a recent Bolt survey reports that 75 percent of online beauty product shoppers would pay at least 10 percent more for personalized products. To capitalize on this trend, legacy beauty and skincare giant Estee Lauder is partnering with Google to better understand consumer sentiment, inform research and development, and drive sales. Lauder is not only deploying AI to respond dynamically to search queries; it is activating all consumer engagement channels, including social channels and customer care centers, to generate robust, first-party consumer data profiles.

Chatbots as Stealth Heroes

It’s time to come clean and admit that we regularly yell at chatbots. The current state of automated customer care centers is abysmal. When consumers engage, they often are greeted by an inept chatbot. As the engagement continues, the chatbot’s inability to meet customer needs then escalates to clients demanding human intervention after having already reached peak levels of frustration. This unnecessary consumer angst represents a brand blind spot.

Customer care centers enhanced with the latest technology are a stealth hero of retail, the key to a cache of consumer sentiment and first-party data from already engaged customers. Why waste the intelligence opportunity? The moniker CCaaS (Customer Care as a Service) is new to me but demonstrates that startups and technology platforms are building the technology to meet current and future automated customer service demands.

The next time you find yourself in a chatbot cycle of doom, understand that the company you are dealing with is not prioritizing your consumer experience. Vastly improved chatbot applications are available as integrations from the leading CRM and technology platforms and specialized startups. AI-enhanced chatbots now respond dynamically in different languages and are free of bias or emotion, responding with human-like responses while analyzing consumer sentiment and facilitating a smooth handoff to a human when it best serves the customer. Simply put, advanced chatbot technology is a CX opportunity for brands and retailers.

Emerging Clarity

The path to effective, not-too-creepy personalization initiatives is taking shape. A successful long-term approach requires quality first-party data and an agile technology partner. With this in mind, leaders should examine both obvious and overlooked areas of consumer engagement with customer experience as a north star. Then, the company should invest accordingly. Recognizing and serving engaged customers in a manner designed to deliver personalized satisfaction is on the near horizon. Ignore the hype and build with foresight for results.