Thought Leaders in Big Data: Interview with Andy Nibley, CEO of Yieldex (Part 3)

Sramana Mitra: Let me clarify one thing: Where does e-commerce come into this? Are we still talking about publishers? Are you talking about an e-commerce advertiser?

Andy Nibley: E-commerce firms have realized they can also be publishers. Even though they are listing products on their pages, they can also sell ad impressions on these pages. If you have a list of music you can buy, it may turn out that one of the artists or labels wants to advertise on that page to highlight their artist over the other artists that are also listed. So they buy a banner ad. That is a new revenue stream for e-commerce publishers that they didn’t know they had. The margins on advertising are much higher than they are on e-commerce. They are not going to sell as much advertising as they are selling their own products, but it is still a high margin and new source of revenue. They also have a ton of first-party data that helps them target people. What they don’t have is a forecasting vehicle like Yieldex that tells them how much inventory they have to sell against those targets.

SM: I would like to learn how you would apply your technology to a video site, for instance.

AN: We have a lot of publishers who have display, video and mobile [ads]. One of the advantages we offer is the ability to have a unified look at that inventory. Most publishers have an ad server like DoubleClick, a video ad server like FreeWheel, and a mobile ad server like AdMarvel, for example. But what they want to get a handle on is how much money is all their ad inventory making and how they can get a unified look at all that inventory. That is what we do. We hook into all these ad servers that a publisher has, their order management systems, and third-party data sources they have. That gives them a unified and universal look into their inventory.

SM: Is there another use case you would like to mention?

AN: I would like to mention one more thing. The main verticals we have are automotive, healthcare or weather, for example. One in particular we helped with the sales department to get a better view on how sales were doing, particularly for individual salespeople. It turned out, when we looked at their data, that their number one salesperson was bringing in x amount of money per year and that person was being compensated based on this figure, but they didn’t have a handle on how much that particular salesperson was discounting. One of the things we provided was a view into not only the number of impressions a salesperson has sold and the amount of revenue he or she brought in, but also how much that person is discounting. That sales person who brought in $2 million this year should have actually brought in $4 million if you change the discounting policy.

We also helped with sell through. If you are selling through month after month after month, it may be time to raise your prices for that product. We provide visibility into that as well. Ultimately, you need a historical view of pricing so you can determine if it is a good deal to take, if you should get a higher price for it, or if you are undercutting your pricing structure if you take a particular deal.

SM: How do you price? When you are selling this technology to your customer, what is your pricing model?

AN: We have two components. The first is implementation. It takes us a few months to integrate with a publisher’s ad server, order management system, and third-party data systems. We charge an implementation fee that allows us to recuperate our costs for doing that. Once the publisher is hooked up, we start charging a monthly fee based on the number of impressions the publisher has. If we are going to process every impression, there is a cost attached to that. The more impressions a publisher has, the more they pay us.

This segment is part 3 in the series : Thought Leaders in Big Data: Interview with Andy Nibley, CEO of Yieldex
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