AI is transforming retail customer experience from a cost center into a revenue engine, says Talkdesk’s Michael Klein, as brands rethink automation and loyalty.
For years, AI in retail was framed as an efficiency play: better inventory forecasting, smarter demand planning, faster ticket resolution. It was about reducing costs, shaving seconds off handle times, and streamlining back-end systems.
That era is over.
Today, AI sits much closer to the revenue engine. It influences how customers discover products, how they interact with brands, how issues are resolved, and, increasingly, whether they return. In retail, travel, and hospitality, where loyalty is fragile and competition is relentless, customer experience is no longer a support function; it is a core function. It is a strategy.
Few executives have observed that shift from both the operational and technological sides as closely as Michael Klein, Director of Retail, Travel & Hospitality Product Marketing at Talkdesk. Before moving into enterprise CX technology, Klein spent more than three decades in retail merchandising and leadership roles, including time with Adobe and Williams-Sonoma.
That background, he says, fundamentally shapes how he evaluates enterprise software.
“I’ve spent more than three decades in retail,” Klein said. “My background in retail merchandising keeps me focused on how technology actually improves the customer experience and drives real business outcomes. It’s never been about leveraging technology just for the sake of it.”
In merchandising, every decision — from assortment planning to store layout — is tied to measurable results. Klein brings that same lens to AI.
“AI is a strong example,” he said. “When applied well, it helps increase average order value, drive repeat purchases and improve retention.”
In other words, the question is not whether AI is impressive. It is whether it sells more sweaters, books more rooms, or deepens loyalty.
“At Talkdesk, we’re focused on using it where it truly makes a difference for retailers and their customers,” he added.
The Persistent Myth of the Demographic Customer
Retailers have more customer data than ever before. Yet, paradoxically, many still design experiences around broad assumptions.
“One of the biggest misconceptions is that everyone in a demographic bucket behaves the same way,” Klein said. “That Gen X shops one way, Millennials another, and Baby Boomers another.”
The reality, he argues, is messier.
“If it were that clean, personalization would be easy,” he said. “But I’ve seen plenty of Baby Boomers who are perfectly comfortable booking travel online and plenty of younger customers who want to speak to a person when something goes wrong.”
The mistake, he suggests, is building customer journeys around stereotypes rather than behavior. Digital-first consumers are not defined by age alone; they are defined by context, urgency, and preference at any given moment.
Designing around assumptions creates friction. Designing around actual signals creates loyalty.
From Cost Center to Growth Engine
Perhaps the most profound shift underway is the redefinition of the contact center.
For decades, contact centers were treated as overhead — necessary to resolve complaints, but disconnected from growth. AI is changing that calculus.
“From a customer standpoint, AI makes it easier to self-service when they want to,” Klein said. “That convenience drives satisfaction — and satisfied customers tend to spend more.”
Self-service is not about removing human interaction; it is about giving customers control. When done well, automation reduces frustration and accelerates resolution.
For brands, the internal impact is just as significant.
“AI frees up contact center teams to focus on higher-value work,” Klein said. “Whether that’s helping design a room, building a wardrobe, or solving a complex issue. Those are real revenue-driving conversations.”
By removing friction in knowledge access, documentation, and agent training, AI shifts human effort toward consultative interactions — the kinds of conversations that build trust and increase basket size.
At its best, automation does not replace people. It elevates them.
Why So Much “AI-Powered CX” Falls Flat
In a market saturated with “AI-powered” claims, differentiation often dissolves into jargon. Klein has spent years translating complex enterprise technology into language retailers actually understand — and he is blunt about what works.
“Great marketing and complex jargon just don’t mix,” he said. “Instead of relying on technical words that only developers or product managers use, brands should drop the IT acronyms and language that’s too deep in the weeds.”
Retailers do not buy platforms. They buy outcomes.
Plain language, he argues, forces vendors to clarify their value proposition. If a product cannot be explained without abstraction, it likely lacks practical grounding.
Separating Real AI From Marketing Noise
Klein is equally pragmatic about the current AI moment. Not all AI is new — and not all of it is transformative.
“We first need to be clear about which AI we’re talking about,” he said.
Retailers have long used predictive models to forecast inventory, optimize distribution, and manage replenishment. Those systems quietly shape customer satisfaction by ensuring products are in stock.
“That has a direct impact on product availability and customer satisfaction,” Klein noted.
More recently, generative and agentic AI have begun to deliver tangible value in marketing and service environments — drafting content, assisting agent,s and streamlining workflows.
Where the narrative drifts into hype, he says, is in the idea of full automation.
“We’re a long way from AI taking over everything,” Klein said. “Human oversight still matters, and consumers will want the choice between automation and a real person depending on the situation.”
The future, in his view, is hybrid — not robotic.
The Context Problem
If there is one area where brands consistently misstep, it is context.
With so much data available, companies often mistake volume for insight.
“The key to designing better experiences is relying on context signals, like timing and intent, coupled with history and preference,” Klein said.
Without context, personalization becomes misdirection. A customer who once purchased a gift for a relative may be permanently misclassified, leading to irrelevant recommendations.
“Imagine you visit a store for the first time to buy a present for your grandmother,” he said. “If the retailer caters your experience based only on your first visit, your experience won’t serve your current needs.”
The difference between intelligent personalization and awkward irrelevance often comes down to whether brands understand why a purchase occurred — not just that it did.
The Hardest Part of Modernization
Enterprise modernization is rarely blocked by technology alone.
“The biggest hurdle brands encounter is not doing anything for fear of disrupting operations,” Klein said.
Legacy systems may be aging, but they are stable. Change introduces uncertainty.
“The next hurdle is weeding out bad data,” he added. “And the third is dealing with people who are stuck in their old ways or too protective of their territory.”
Transformation demands both technical cleanup and cultural shift. It requires encouraging teams to experiment, test openly, and share ownership across departments.
Without that alignment, even the best technology stalls.
The Metrics That Will Matter Next
As AI becomes embedded in CX systems, traditional metrics such as handle time and surface-level satisfaction scores may lose their primacy.
“In the next few years, customer lifetime value, recency, and frequency will become key metrics to monitor,” Klein said, particularly in retail and hospitality.
Those measures capture relationship strength rather than transaction speed. They reflect whether AI is driving durable loyalty rather than short-term efficiency.
In that sense, the next phase of AI in customer experience is not about the volume of automation or technological sophistication. It is about commercial impact.
For Klein, that is the through line connecting his merchandising past to his product marketing present. Technology is not the hero of the story. The customer is.
And in a competitive landscape where switching costs are low and expectations are high, the brands that treat customer experience as a growth lever—not a service line item—will be the ones that endure.
