Datacratic Blog

At Datacratic, one of the product we offer our customers is our real-time bidding (RTB) optimisation that can plug directly into any RTBKit installation. We’re always hard at work to improve our optimisation capabilities so clients can identify valuable impressions for their advertisers. Every bid request is priced independently and real-time feedback is given to the machine learning models. They adjust immediately to changing conditions and learn about data they had not been exposed to during their initial training. This blog post covers a strange click pattern we started noticing as we were exploring optimized campaign data, and a simple way we can use to protect our clients from it.

Optimizing a cost-per-click campaign

Assume we are running a campaign optimized to lower the cost-per-click (CPC). The details of how we optimise such a campaign are beyond the scope of this post, but in a nutshell, we train a classifier that tries to separate bid requests based on the likelihood that they will generate a click, assuming we win the auction and show an impression. Our models are naturally multivariate, meaning they learn from many contextual features present in the bid request, as well as any 3rd party information that is available.

One simple and highly informative feature used by the model, the feature this post is about, is the site the impression would be shown on. From a modeling perspective, this roughly translates to asking...