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AI vs. Human Engagement In Retail – Complementary Solutions To The Human Experience Of Shopping


Recently, I moderated a fascinating discussion on AI and Human Engagement with a dozen of Rethink Retail’s Top Retail Experts. We started with the low hanging fruit of chatbots and ended with the state of AI in Retail itself.
ChatBots Using GenAi
We all were impressed by how Walmart can successfully roll out chatbots to negotiate mission critical supplier contracts, resolving the majority of contract negotiations without human intervention and at a higher satisfaction rate, because vendors got information and responses in real-time.
At the same time, many customer service chatbots are maddeningly frustrating, as Ian Scott hammered home with his regular English gusto. Oliver Banks pointed out there is bad design pervasive in human call centers too.  It’s not just an AI problem, but one of underinvestment in areas that are more categorized as cost centers.   Theo Schweitz pointed out the damage from potential hallucinations, citing an Air Canada chatbot that made up a policy because it didn’t know the answer that the airline then had to adhere to.   Kirat Anand added that any AI is only as good as the model it is trained on.  Gary Newbury pointed out executives need to align with the real human needs of customers and understand the acuity of the customer service pain to properly invest. Too few do.
Thomas Harns was optimistic that with NLP we are just beginning to learn and then be able to train on how people want to ask for things, and as a result the experience will get much better.  Kate Sheldon pointed out how human touch points in service like with Chewy builds an enhanced customer trust level. Ian Scott mentioned he’s increasingly seeing call centers return from offshoring to provide native speakers and better service.
Ultimately we ended up that the key was to lean in on both GenAI and the human touch.  GenAI provides unique opportunities to get to most answers faster and more conveniently, one of the key pieces of feedback from Walmart’s supplier negotiation program, and also highlighted from this telling feature from Klarna, where GenAI completed 2/3rds of call center conversations, the work of 700 employees and did so with higher customer satisfaction and 2 minute resolution times instead of 11 minutes!  This allows you to lean in to the 10% that require a human connection and provide a superlative experience that drives loyalty.
The dual approach leads to convenience and better service, all at a much lower cost that is estimated to improve profits by $40m per year!  Win-win-win.
AI Is Enhancing The In-Store Customer Experience And Leveling Up The Sales Associate
Sharon Lawler kicked us off talking about in-store customer experience singing the praises of new digital tools at Irish sports retailers called SafeSize that would scan feet and make size and shoe longevity recommendations for her teenager.  She noted it was even more powerful when used in coordination with a sales associate.  And then the discussion lit up.
We discussed sales associate tools like RillaVoice (sales management monitoring) and Theatro (sales associate voice first tools) and numerous AI based associate training tools.  AI can also reduce the medial, repetitive tasks so that associates can better serve customers.  And that discussion dovetailed into computer vision.
Computer Vision Increasingly Being Adopted To Understand Physical Retail
Understanding is the key to improvement, and there has been no greater black boxes than brick-and-mortar retail. Our physical spaces have been more art than science for too long.  Computer vision is opening up new data streams to what’s happening in physical retail.  We are seeing a lot of increasing demand at Raydiant on optical sensor data for traffic, audience demographics, and viewing for retail media and digital at the shelf.  We generally are seeing many more RFPs for retail analytics like Pathr and RetailNext with increased investment in store experience.
Computer vision is increasingly being used for loss prevention.   Ian Scott referenced being able to sense changes in body language that precedes theft, and in England, the secret has been not to confront the potential shoplifter, but to “love bomb” them, in other words to shower them with friendly and helpful staff attention.  But be careful of regulations, as Rite Aid found out by illegally using facial recognition without notifying customers.
License Plate Readers (LPRs) such as Flock Safety are widely being deployed to catch criminals at major retail chains and malls by providing data to police departments. Gwen Morrison chimed in that Iterate.ai is using LPRs in drive throughs to automate payments in QSRs.  She also brought up that there is a lot of opportunity with more accurate data streams coming from RFID adoption and visibility to which Marshall Kay jumped on the RFID soapbox and talked about the rapid decrease in RFID sticker prices driving adoption.   New data sources are powering a better understanding of store.
Learning from Wendy’s PR Flub On Dynamic Pricing 
Speaking of QSRs, the Internet was a-frenzy with Wendy’s announcement that it was investing in dynamic pricingKarl Heller criticized their positioning of it, “we’ve had dynamic pricing at bars all the time, we call it Happy Hour and no one gets mad at the concept of Happy Hour.” Richard Hammond mentioned a bar in the US that groups beers together and gamifies prices of the groups up and down to encourage people to try new beers and have fun.  Customers love it! The discussion pointed at the real need to position new technologies appropriately to customers, focused on the benefits or the experience, or shopper will come to their own suspicious and often worst case conclusions.  Retail needs to learn these messaging lessons as we are seeing increasing deployments of Electronic Shelf Labels and inventory intelligence and robots, as Michael Klein pointed out.  Ultimately, humans want to feel in control of their experience, and with AI they can benefit from more options and or savings if they see technology as an enabler, not a manipulator.
So Why Isn’t There More Retail News About AI?
We know AI is being actively deployed behind the scenes in supply chain, predictive analytics, ad optimization and customer data processing.  But our group isn’t hearing (or maybe disclosing) much on the frontlines of AI and human engagement and the shopper experience. How could that be?
Shannon Flanagan added that retail executives over the last decade have been burned repeatedly by the promises of technology and are reluctant to publicize much before success and get burned.  Once bitten and twice shy, or maybe the commonly repeated adage that retailers don’t ever want to be first or third. Gwen Morrison added that Big Tech is not prioritizing investment in retail, because budgets aren’t shifting as rapidly yet.
The reality is that retailers are working feverishly to build out the data infrastructure to take better advantage of AI. They are enhancing product data with descriptive modifiers, correlating online and offline customer data,  These aren’t big sexy launches, but they are the foundations for a future of conversational commerce, augmented reality, and 1:1 shopping personalization that signal the foundational retail shifts that we highly anticipate.  Ehen these technologies are deployed in a way that recognizes our humanity, they reduce friction rather than increase conflict and enhance our human experience rather than detract from it via automation.