I was a co-founder and CTO of NetGravity back in 1995, and I spent a lot of years building ad servers. So I can say this from experience: ad servers are hard to build. There’s a lot of expertise that goes into delivering the right ad to the right person where response times are measured in milliseconds and uptimes are measured with five nines. Now it’s been almost four years since I co-founded Yieldex, and I can say another thing from experience: predictive analytic systems are also hard to build. Moving, managing and processing terabytes of data every day to enable accurate forecasting, rapid querying, and sophisticated reporting takes a lot of expertise. And, as it turns out, it’s very different from ad server expertise.
When I ran an ad server team, all we wanted to work on was the server. We delighted in finding ways to make the servers faster, more efficient, more scalable, and more reliable. We focused on selection algorithms, and real-time order updates, handling malformed URLs and all kinds of crazy stuff. Our customers were IT folks and ad traffickers who needed to make sure the ads got delivered. The reporting part was always an afterthought, a necessary evil, something given to the new guy to work on until someone else came along.
Contrast that with the team I have now, where we obsess over integrating multiple data sources, forecasting accurately, and clearly presenting incredibly complex overlapping inventory spaces in ways that mere humans can understand and make decisions about. Reporting is not an afterthought for us, it’s our reason for being. Our success critera are around accuracy, response time, and ease of getting questions answered through ad-hoc queries. Our customers are much more analytical: inventory managers, sales planners, finance people, and anyone else in the organization working to maximize overall ad revenue.
These teams have completely different DNA, so it’s not surprising that a team good at one of them might not be so great at the other. This is why so many publishers are unhappy with the quality of the forecasts they get from their ad server vendor, and one of the reasons so many are signing up with Yieldex. Good predictive analytics are hard to build, and nobody has built the right team, and spent the time and effort to get them right for the digital ad business. Until now.