Evan Schuman's StorefrontBacktalk

When Walmart.com announced its new search engine on August 30 and that it had already gone live, the retailer promised the ability to understand “the intent” of a shopper’s search. As a practical matter, though, the new engine simply didn’t. But “in the next couple of months,” version two of the engine will actually consider the shopper’s queries in context, according to the Walmart executive in charge of the program.

To test whether the initial engine was indeed able to factor in a shopper’s intent, we searched for Apple. Understandably, the results were about iPhones, iPads and other hardware from that company. But we then searched for Oranges, Bananas, Pears and then again asked it about Apple, hoping that it would now understand our desire for the Garden of Eden edible type of apple, which Walmart.com does indeed sell. Nope, it didn’t take the hint and continued to display mobile computers. (When we searched for “fruit,” the desired apples did materialize in the results.)

Sri Subramaniam, vice president at WalmartLabs, said that the new search engine—called Polaris—factors in many variables that the earlier engine had not. But for the type of inquiry context where the engine considers all the shopper’s questions and then changes its answers accordingly, that will have to wait for “the next couple of months.” That is when the engine will ramp up its personalization efforts, he said.

That’s understandable, but it’s not what Walmart bragged about in its announcement on August 30, which claimed that the new engine “uses semantic search technology to anticipate the intent of a shopper’s search to deliver highly relevant results for them” and that it “focuses on engagement understanding, which takes into account how a user is behaving with the site to surface the best results for them.”

Right now, the context Polaris uses is based on the fact that the shopper is visiting Walmart.com. Using the apple example, he said, Walmart sells far more iPhones and iPads than whole, sliced or canned apples. As such, it’s reasonable to assume that a Walmart.com visitor’s apple search is for purposes of mobile, not meal.

In short, Walmart instructs its engine to first look at sales reports and to then factor product popularity into its analysis of what answer the user probably is seeking.

Specifically, Polaris decides what results to display based on product popularity (“last seven days of sales and last one year of sales”), the number of shoppers who have clicked or purchased that product, product user-generated ratings, the number of Facebook likes, what searches are popular from specific IP address ranges (suggesting geography) and other factors, Subramaniam said. “There are about 100 signals we use, not just text,” he said. That click analysis is updated every few hours.