ENTRIES TAGGED "consumer data analytics"
Revealing shopper behavior, retail battles web with experience and service, and Starbucks' struggles with Square.
Snooping on shoppers pays off
Liz Gannes took a look this week at how online retailers’ desires to track consumers’ shopping habits are resulting in emerging startups offering services to track various behaviors on behalf of retailers. In a post at All Things Digital, she highlights newly launched startup Sift Science, which tracks online shopper behaviors to uncover fraudulent activity, and Commerce Sciences, a startup in beta that offers online retailers a Personal Bar for their websites that uses behavioral science to increase online sales.
Gannes outlines a few interesting insights each company has gleaned from aggregating consumer shopping data. For instance, Sift Science has found that a shopper who types her last name in all caps is 5.6 times more likely to be a fraudster, and shoppers who don’t sign in with a Facebook log-in are four times more likely to be fraudsters. Early findings from Commerce Sciences include using the word “free” — as in “you have won a free coupon” as opposed to “you have won a coupon” — increases sales by 15%, and social influences from displaying what a user’s friends liked and bought had zero effect during the day but resulted in 49% more sales in the evening. You can read Gannes’ report at All Things Digital.
In related news, it turns out Facebook ads are strongly influencing the platform’s users’ buying habits, even if they’ve never ever clicked on an ad in Facebook. Farhad Manjoo reports at Slate on in-depth studies conducted by Facebook showing that ad clicks don’t matter. He reports:
“‘On average, if you look at people who saw an ad on Facebook and later bought a product, [fewer than] 1 percent had clicked on the ad,’ [Sean Bruich, Facebook's head of measurement platforms and standards,] says. In other words, the click doesn’t matter; people who click on ads aren’t necessarily buying, and people who are buying are almost certainly not clicking.”
More notable, however, might be the way Facebook is managing to gather this data. Manjoo notes that last year, Facebook partnered with consumer data aggregator Datalogix, which tracks the purchasing behavior of more than 100 million U.S. households by tying consumer identities to their purchases through store loyalty cards. Manjoo writes:
“Over the past few months, Facebook and Datalogix figured out a way to match their respective data sets in a manner that maintains people’s privacy … Facebook can now tie its users to the stuff they buy at supermarkets. Armed with this data, Facebook began running a series of analyses into the effects of advertising campaigns on its site. If, say, Procter & Gamble ran a Facebook ad for Tide, Facebook could look at Datalogix’s data to see whether people who were exposed to the ad tended to purchase more Tide in the weeks after the campaign.”
Manjoo looks at the differences between direct-response and demand-generation marketing, and compares Facebook’s ad practices with TV advertising. You can read his report at Slate — it’s this week’s recommended read.