What if a retailer could all but read shoppers' minds before they can say a word in store or get into a complicated search online?

That day is coming sooner than you think, says Michael Haydock, retail analytics leader for IBM Global Business Services, who spoke to Portfolio.com about how technology is already altering the retail industry and how its future includes the possibility of customer service aided by artificial intelligence, à la the IBM supercomputer Watson.

The Price Is Right

It’s notoriously difficult for retailers to price items so that they hit profit margins and move quickly. But, increasingly, major retailers are relying on pricing optimization data—instant analysis of supply and demand—to get the right price.

“Most retailers of any decent size are already doing something in the price optimization area,” Haydock says. “One flavor is everyday prices; there’s another price scenario where you want something off the shelf and you have to ask yourself ‘What rate is the optimal markdown strategy?'”

Pricing merchandise attractively is increasingly going to be a matter of survival, with shoppers now entering brick-and-mortar stores equipped with smartphones and tablets that let them do price comparisons.

“A sharp consumer with a smartphone is really dangerous,”Haydock says. “But I think it’s all about getting the right product at the right price point for that particular consumer.”

As more services that offer price comparison pop up, “Maybe it’s the retailer who should be [showing those comparisons], making it easier for the customer,” Haydock says. While they might pay more for a trusted retailer, Haydock says, they won’t pay that much more, which means retailers will have to differentiate with unique goods and customer service.

Knowing Your Customer

Haydock says retailers will increasingly have to understand their customers better than their competitors. To do so will require watching the data and making an educated guess on what a particular consumer is after, either based on historical personal data or based upon data that details what a “cohort group” of similar consumers goes after.

That sounds like it may be easier to do online rather than in-store, but not so fast.

Haydock sees the in-store experience increasingly meshing with and mimicking what happens online and a time when customers will be given incentives to identify themselves the moment they step in the store through some type of technology. One current example of this is the shopping app Shopkick, through which smartphone-carrying shoppers who have the app loaded onto their phones earn points at that specific retailer upon checking into the store.

Such systems give customers reason to let retailers know they’re on the premises.

“It’s like you would never fly without giving someone your frequent-flyer number,” Haydock says. “You want to get the points.”