Next Step for Ad Tech: Product Data Innovation

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We’ve reached the most granular level in online advertisement targeting technology: an SKU to an impression. So where will the next innovation come from? I’m thinking the next big step in ad tech will be on the product side, helping advertisers pick which SKU to show a particular impression, at a specific bid price.

An impression is more than just the age and gender of the person. It is the person at the exact time and place. It includes the demographic, psychographic, and geographic information, the taste, mood, and everything about who the person is, adjusted for the context of what she is looking at. We probably can’t combine all those data for a given impression yet, but we’ve made a lot of progress in painting a picture of this person at the exact state in time.

What about the SKU side? When an impression shows up on a website, how much should an advertiser bid on this impression and more importantly, which product should he show?
I believe an impression has a fair intrinsic value that is a function of the predicted click through rate, conversion rate, the average order value, and how much % of sales the advertiser is willing to pay, adjusted for risk. In a formula, this looks like this:
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I’ve outlined my thought process in a previous entry, found here.

My question is, of all the advertisers that are bidding on impressions, how many are looking at the product side on a data driven way? By data driven, I don’t mean “this product is designed for single urban males who like cars”. I mean “analyzing all the transaction history involving this product, the calculated CTR & CVR of this impression is X & Y, with standard deviation of Z”. The point is, advertisers are choosing which product to show without the rigorous past purchase analysis that should point them to the optimal SKU to show at the optimal bidding price. If you sell hundreds or thousands or even millions of SKUs how can you be sure that the ad you decide to serve is the best one in your product portfolio? Also if you are not amazon or Walmart do you have enough data to really make an intelligent decision?

The next innovation in ad tech will effectively collect these purchase data across merchants and transform it in a way that is useful to advertisers. With information asymmetry out of the way, advertisers will bid on impressions based on predicted CTR, CVR, and AOV. So what will win an impression when multiple merchants are selling identical products? It is the % of sales the advertiser is willing to give up thus ensuring the publisher will get the maximum $ for the impression. The user who will see the ad will see a calculated, optimized ad, which should match his profile so well that the ad will be less of a distraction and more of a content. Of course the advertiser who was willing to pay the most will get to show the ad, so we have a win-win-win situation between the user, publisher, and the advertiser. Moreover the product side innovation should drive automation even further. Ultimately, a user showing up to a website will trigger a process that will sift through millions of products across advertisers to find the optimal one. That sounds like a more efficient market to me.

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