Facebook has been selling itself as an ideal venue for brand advertising for several years now. That’s not just because there’s a lot of money in brand ads; it’s also because Facebook has long seemed like a relatively poor environment for direct-response ads. People who go to Facebook do not have high purchase intent—they’re going there to catch up with their friends, not to search for something to buy. Of course, that’s true of TV, too—no one sits down to the tube expecting to find new stuff to buy. Usually we just want to goof off. There’s another way in which our Facebook use resembles how we watch TV: We spend a lot of time there. People spend about 7 hours a month on Facebook, more than on any other site. One of the only things we do more often than waste time on Facebook is watch TV. We do that a lot more often, clocking in an average of about 5 hours a day in the United States.
But demand-generating advertising has been a relatively tough sell for Facebook. That’s because the online ad business is structured around measurement—around advertisers’ ability to precisely track how people are responding to their ads—and brand advertising is notoriously difficult to measure. The lack of measurement explains why some advertisers have been so skeptical of Facebook—see General Motors’ very public denunciation of the site last year.
Again, though, it’s useful to compare Facebook with television. In its early days, TV also had a problem with measurement. No one knew how to tell whether commercials were really working. But in the 1970s and ’80s, advertisers and analytics firms like Nielsen came up with a variety of ways to analyze ads on the tube. Among other things, they instituted standardized measurements to compare TV to other media—like “gross ratings points”—and, after surveying consumers’ purchases, they figured out how people’s TV viewing affected their buying habits. Today, thanks to a practice known as “mix modeling,” the return on TV advertising is exquisitely measurable. Large advertisers like Procter & Gamble know exactly how much they’re getting out of it—and that’s why, despite all the many other devices that now intrude our lives, TV advertising rates remain as high as ever.
Now Facebook is trying to bring to the Web same rigorous metrics that have ruled brand advertising on television. “We’re trying to create industry standards around how people advertise online,” says Brad Smallwood, the Facebook vice president in charge of its measurement and insights team. At the core of this work is Facebook’s partnership with Datalogix, though given Facebook users’ (justifiable) squeamishness about how the site uses their data, Facebook and Datalogix had to perform their analysis very carefully.
What they came up with was a Rube Goldbergian system that strips out personally identifiable information from the databases at Facebook, Datalogix, and the major retailers while still matching people and their purchases. The system works by creating three separate data sets. First, Datalogix “hashes” its database—that is, it turns the names, addresses and other personally identifiable data for each person in its logs into long strings of numbers. Facebook and retailers do the same thing to their data. Then, Datalogix compares its hashed data with Facebook’s to find matches. Each match indicates a potential test subject—someone on Facebook who is also part of Datalogix’s database. Datalogix runs a similar process with retailers’ transaction data. At the end of it all, Datalogix can compare the Facebook data and the retail data, but, importantly, none of the databases will include any personally identifiable data—so Facebook will never find out whether and when you, personally, purchased Tide, and Procter & Gamble and Kroger will never find out your Facebook profile.
Then, each time a major campaign runs on Facebook, the company can see how people’s purchases were affected by ads. What’s most important is that Datalogix gives Facebook extremely large data sets, which allows for enough statistical power to draw fundamental lessons about how people respond to ads. “If 40 million people were exposed to an ad campaign, you could end up with a very high percentage of them available for the analysis,” Bruich says. “You could begin to answer questions like, ‘For this type of product, what is the optimal frequency for the campaign—how many times should people see the ad?’ And does it differ for people who buy a lot of the product versus a little? And should you show a different number to heavy users of Facebook versus other users?”
Facebook has already begun to improve the effectiveness of ads on its site. One of its findings, for instance, is that for particular brands and product types, there is a “sweet spot” for ad impressions—an optimal number of times to show an ad to a user before the message becomes ineffective. By homing in on that optimal rate, Facebook was able to improve the return on investment of some campaigns by 40 percent. It also found that by customizing the frequency of an ad based on factors like how often a user purchased a certain brand or product category, the company could improve return on investment by 22 percent.
Certainly that’s good for Facebook and for advertisers. But it’s also not terrible—and might be even good—for users. If Facebook’s research shows that companies were wasting money by serving some people the same ad too many times, that could mean you’ll be subjected to that kind of thing less often in the future. As Facebook’s measurement systems improve, you might even see better ads—one of the eventual goals the system, Bruich says, is to figure out what kinds of ads appeal to what kinds of users, so over time you’ll be presented with ads that are less likely to annoy you. And if, as you insist, ads really don’t work on you—that you never buy things because of marketing you see on Facebook—it’s theoretically possible that Facebook’s system would be able to figure that out, too, and maybe the site won’t show you any messages.
But that’s unlikely. You may not love the ads you see—and you’ll still never click on them. But unbeknownst to you, Facebook ads still work on you. Resistance is futile.