Sramana Mitra: You sold at the right time because after the iPhone and mobile advertising, the whole ad rate world just collapsed.
Yaron Galai: Generally, it did. We sold at a very pretty good time. I do know that just by talking to a friend from AOL that they kept running Quigo as an independent product until last year. Just recently, they sold it to one of the bigger ad platforms. They were extremely happy with the results.
Sramana Mitra: You had a good chunk of ownership in Quigo and you made good money off that transaction?
Yaron Galai: Yes, it was a good outcome.
Sramana Mitra: Did you have to go to work for AOL?
Yaron Galai: No. I stayed through to the last day of acquisition. Towards the end of Quigo, the business was great. The team was fantastic. The thing that was frustrating to me was, over the years, the contextual ads that were were selling were not very interesting to me as a user. That was frustrating to me because going back to the motivation, I really wanted to just put really interesting links in front of people.
I agreed with AOL that I’d leave the day we close the deal. I wanted to just focus on content links. Instead of contextual advertising, I just wanted to recommend links to other bits of content. I thought that would be a step up in terms of finding interesting things.
Sramana Mitra: Let’s talk about that beginning of Outbrain and the market’s appetite. I’m very familiar with Outbrain. We’ve been your customer at different points. We know how you place links. One of our case studies earlier has been one of your top competitors. That’s Taboola.
We’re familiar with the space but I’m curious about one thing. In 2007 time frame, this notion of recommending content and placing content was relatively nascent. It wasn’t really monetizing well at that point. What was your journey? Take us through your journey of how you built Outbrain in a little more granular way.
Yaron Galai: The seeds were planted in 2000. That’s where I really tried to provide recommendations on content. With Outbrain, I said, “Let’s make all those links point to content.” In terms of how we wanted to recommend content and the business model, what we set out to do in 2007 is basically what we’re doing today. It’s both how we do it and how all the companies in the space that we inspired.
I think there were a few pivots along the way of things that we didn’t get right. For example, I thought where people are going to consume content is not going to be on publisher’s sites. Our first iteration of the content recommendation were within our readers. That turned out to not be true so we pivoted away from that. Although if you look at it now, the contents have moved to Facebook and Twitter.
Sramana Mitra: Twitter is the most dominant content-consuming engine right now. Let’s go back to 2007 when you just started. What did you launch with?
Yaron Galai: It was going to be a recommendation engine for RSS readers. We didn’t have any data and to make recommendations, you really need to have access to have a lot of data. We needed a stepping stone to get to the actual recommendations. We started with just the ratings. Five star ratings are the early Like buttons before Facebook existed.
We distributed that through RSS readers and bloggers eventually. We, internally, look at the pages with recommendations opened. For audience outside our office, they only have the rating. We’d get all the data reported to our system. Once the recommendations looked good internally, we’d turn them on externally as well. The first thing that we made available outside of the office was this reading functionality to drive data back to us.