The Imperative of AI in Retail: Finding the Most Value in Decisioning

Prem Kiran, founder and CEO of Hypersonix Inc., joined Brian Kilcourse, managing partner for RSR Research, at Analytics Unite this week to discuss how retailers and brands are successfully leveraging machine learning and AI across their enterprise value chain to drive profitable growth quickly in rapidly changing times.

Retailers want to be able to anticipate consumers going into a retail store so they can anticipate them coming in real time and, according to Kilcourse, retailers were trying to do this before COVID-19 hit the world, “but now we know we want to accelerate it.”

Kiran explained how leveraging AI and data in general all is about making decisions – procurement, promotion, pricing, fulfillment decision, etc. “How can a system adapt to that so that you’re ultimately getting your customer to get the value that their looking for has been a big shift in the industry,” he said.

“Retailers have to be able to now anticipate a behavior from its earliest stages so that they can react accordingly,” said Kilcourse, noting that this is the essence of omnichannel. Examples like this are one of the reasons where artificial intelligence can help.

“At the end of the day, you want to be able to react fast, or anticipate things better than your competition,” said Kiran, so that it drives back loyalty and customer lifetime value, etc. “You need to be able to leverage data fast in order to do that. You need a system of actionable intelligence,” he warned.

Demand signals are not only coming from brick-and-mortar stores anymore, but from a variety of different channels, but you have a fixed amount of inventory to react. Kiran sees AI being able to stitch siloed data together faster, and then apply decision sciences and data sciences in a way that makes sense for a business user to make decisions (in fairly real time).

“And today AI is enabling these capabilities because of advancements in NLP and advancements in compute power and being able to do things at much lower cost,” added Kiran.

“Retail is complex because there’s just so much data. But it’s not too hard to understand – the volume is what drives the complexity,” commented Kilcourse. But, AI is good at looking at huge lakes of data and detecting a pattern. It is also good at producing behavioral models based on the data it’s looking at. This becomes important when you start to think about how it can help retailers respond quickly. Retail is a famously reactive business.

“We’re not talking about putting a man on Mars and getting him back home again safely. We’re talking about selling soap and toilet paper and dresses and shoes,” Kilcourse joked, before making his point that the complexity in retail is driven by the size.

The first thing retailers need to do (which is very COVID-related) is establish an executive team that identifies what they need to respond more quickly to in order to meet the needs of customers, and ultimately be profitable, according to Kilcourse. “And then what’s the information needed to make the right decisions for those things. And how can systems support them?”

This is a cross-functional discussion Kilcourse said, and “my expectations is what happens is the organizations starts to horizontalize (starts to get flat) and AI is the enabler to make that happen.”