If you’re like me, you don’t pay much attention to display ads on the Web—the big “banner” and “skyscraper” ads that run along the top or the side of many media sites. The problem is that few of these ads are for products or companies that interest me, so I tune them all out.
Well, it turns out I’m not alone—and that’s a big problem for both advertisers and publishers on the Web. “I’ve always felt that display ads were giving the industry a bad reputation,” says Usama Fayyad, a widely respected expert in data mining who resigned his position as Yahoo’s chief data officer last summer. “Banner ads were shown without targeting all over the Internet for many years, without a lot of thought to the long-term negative cost of showing the wrong ad to the wrong person. Every time you show that wrong ad you are subtracting from the value of that medium.”
Now Fayyad is working with Cambridge, MA-based ChoiceStream to reverse that trend. The nine-year-old company, known until recently as a maker of recommendation and personalization technology that gave Web publishers ways to entice visitors to stay on their sites, announced earlier this month that Fayyad had joined its board of directors. It’s a big catch for ChoiceStream, and it comes at the same moment when the company is making a major push to apply its personalization techniques—which depend heavily on mining data about customer behavior—to display advertising.
The company believes it’s come up with a way to make display ads more effective by increasing their relevant to specific Web users. In a nutshell, ChoiceStream uses cookies—little data files saved by your browser—to store anonymized information about where you’ve been on the Web and what kinds of products you’ve browsed. Say you’ve shopped at KensKayaks.com. Next time you visit a kayaking site where Kens advertises, ChoiceStream’s cookie will recognize you, and the company will serve up an ad customized to show a few new products at Kens that ChoiceStream thinks you’d like, based on its detailed, data-driven models of the preferences of people with certain brand affinities. Users click on such personalized ads more than twice as often as they do on regular ads, according to ChoiceStream. And the all-important “conversion rate”—the number of click-throughs that lead to an actual purchase—is two-thirds higher. As a result, publishers can charge much higher rates for personalized ads.
But ChoiceStream is far from the only company exploring so-called “behavioral targeting” techniques—we’ve written about a few of the locally founded or funded ones, including Tacoda, ZoomInfo, and JumpTap. So when I caught up with Fayyad last week, I wanted to know, first, what he thought was so special about ChoiceStream. And toward the end of our interview, which appears below in abridged form, I also got a chance to ask Fayyad—a veteran of NASA, Microsoft, and digiMine (now Revenue Science)—about his other post-Yahoo ventures.
Xconomy: You said in a statement last week that ChoiceStream has “the deepest and most comprehensive recommendation and personalization technology I have seen.” That’s saying a lot coming from someone who was at Yahoo, where there was so much R&D poured into those exact problems. How did you first become aware of ChoiceStream, and why do you think so highly of their technology?
Usama Fayyad: I actually learned of ChoiceStream maybe two or three months after I joined Yahoo. They were doing a trial on one of Yahoo’s sites, and there were a lot of people excited about it. The results were a lot better than the internal recommendation engines at Yahoo, which had maybe 14 different engines at the time, about half of those in my world. When I saw those results, I got a bit more involved.
At the same time, ChoiceStream was trying some of their personalization technology on search, so it became a strategic opportunity, and there was a drive to acquire ChoiceStream. I met the team for the first time when I went out to Cambridge to do due diligence on them. But we moved slowly at Yahoo; we had some concerns. And what’s really funny is that one of our concerns, about what we thought was their biggest weakness, in the long run turned out to be their biggest strength. Their technology required them to do a lot more modeling of the world in order to do recommendations in a given domain, and we thought it would take them a very long time to switch domains. You could take a long time to model, say, movies, what movie-goers like, and all that stuff, and as soon as you moved to the next property you would have to do a similar effort all over again.
We moved slowly in terms of reaching a decision to buy them, and by that time they had gotten a pretty amazing strategic investment that gave them a very high valuation, so it became outside our scope to buy them. But in the meantime they had become a pretty big vendor, they had spread to six or eight properties at Yahoo, and were consistently beating all of our internal tests, and at one point I had to kill some internal groups trying to build recommendation engines because we already had a pretty good product from ChoiceStream and we were wasting our time doing yet another one when we could be focusing on other stuff that was more core to Yahoo.
That was how I noticed them. To me that was the end of it. The recommendation technology was exciting but it was not the be-all and end-all. I was very familiar with this area; when I was running Revenue Science, we acquired a recommendation company out of the Bay Area. So I was pretty comfortable saying that these guys are head and shoulder above the rest. But their approach still seemed too knowledge-intensive. But it turned out that over the past four to five years they built out a lot of tools for automatically moving from one domain to the next. That’s what I mean when I saw their greatest weakness turned out to be their greatest strength.
X: How did you end up joining ChoiceStream’s board?
UF: In June, I announced I was leaving Yahoo, and in September I got a call from [ChoiceStream founder and CEO] Steve Johnson saying ‘I want you to join the board,’ and he was updating me on the company, talking about how the company expanding from offering companies ways to personalize their sites with content relevant to you, to the much easier problem of figuring out which ads are more relevant to you. They came up with a technology where
