Google exec: Analysis goes deeper, cheaper

Shoppers today expect the brands and retailers that win their business to be faster, more convenient and more surprising than ever before, but those changes only signal the beginnings of how technology will influence shopping in the future, Kevin Hartman, Google’s head of analytics, said Wednesday in a presentation at Western Michigan University’s Food Marketing Conference in Grand Rapids, Mich.

“We haven’t even begun to experience what technology is going to do,” Hartman said. “That can be frightening. But it can also be motivating.”

Hartman’s presentation put into perspective how the cost of analysis and data collection has declined as its volume continues to mount, providing technology companies like Google opportunities to continuously improve its understanding of the consumer, and pass that information to marketers through technology in stores and online.

For example, he said, Google today can read, analyze and sort all the digital volumes in the Library of Congress in a tenth of a second — a processing speed the equivalent of moving 30 million miles an hour. The cost of processing data has fallen in the meantime: The same data analysis that cost $1 million in 2000, cost about $10 last year. This has subsequently reduced the risk for companies to act on data driven insights and the technologies built around them, he said.

“Simplicity is a big theme of technology and it’s helping marketers reach more shoppers,” Hartman said. “As marketers you live in a complex world — you’re dealing in keywords and bids and on top of that you have your own CRM systems and in your marketplace there’s even more going on. That’s a very complicated and sophisticated place to be.“

Technology can simplify that through advances enabled by the “deep learning” of Google, he said. For example, returning search results relevant to the context of the search — its time and place — that tend to indicate different need states; assigning values and analysis to stops along the path to purchase; and by segmenting audiences based on “people who are your best customers — and those who act like they're your best customers.”

Stores can benefit from deep learning through technologies like smart signs, engagement tracking, video intelligence and immersive experiences. Smart signs are digital signboards that can display messages relevant to particular shoppers and provide “real time” interaction. Engagement tracking can detect when consumers are interacting with particular products, and can signal messaging from smart signs or a visit from a sales rep, Hartman said.

Video intelligence uses facial recognition to analyze a shopper’s emotional reaction to displays or products. Immersive experiences can be enabled through inexpensive virtual reality devices that can, for example, allow stores to view displays before they are built.

Expectations have already been altered by technologies employed by retailers and services resulting in shoppers that expect to be served quickly, conveniently, and personally, Hartman noted, citing apps like Geico providing insurance quotes in minutes; the restaurant chain Chik-fil-A’s app allowing online ordering for pickup; and the men’s virtual apparel retailer MTailor, which uses images of the shopper himself to size and show its inventories.