By default, the system will continuously minimize bid CPM levels without sacrificing delivery targets. As more and more sellers switch to first price auction models, this protects the buyer from paying unnecessarily much for an impression.
If "Bid Optimization" is set in a filter, the system will optimize bid CPM levels towards the set campaign KPI. A filter can be used on specific bid strategies, or as campaign wide default.
Bid Optimization - Don't Sacrifice Pace: Will optimize without sacrificing campaign delivery goals
Bid Optimization - Strict: Will optimize fully even if it risks sacrificing campaign delivery goals.
Cost Per Click
Adjusts bid proportional to likelihood of impression being clicked
Cost Per Viewable Impression
Adjusts bid proportional to likelihood of impression being viewable
Click Through Rate
Adjusts bid proportional to likelihood of impression being clicked. Only bids on high likelihoods.
Things to think about when using Bid Optimization
Using bid optimization will on average lower you eCPM with 30%. This means that you should set a higher max CPM than your wanted average CPM, to facilitate buying the most valuable impressions.
Also, keep in mind that the optimization does not exclude poor performance completely, but rather places lower bids, making you pay less per unit of performance.
When using Click Through Rate or Quality Click Through Rate KPI's, use Strict optimization for best performance. This is because we want to not bid at all for low scoring impression opportunities, rather than pay less for them.
No Minimization or Optimization
When selected, the system will always bid with your set max CPM. This may be useful e.g. when targeting deals that have a fixed floor price.
How does bid optimization work?
Machine learning models are used to predict the effect of bid opportunities on some common campaign KPI's. The models are trained from known effect of previously bought ad impressions. The machine learning algorithms used to train the models consider attributes such as when (weekday, time of day), where (site, category, ...), what (ad size, category, ...) and who (device type, previously clicked ads, ...)
When running, the ML model will score how well a given bid opportunity fits the campaign KPI. The score between 0 and 1 will be multiplied with the set max CPM bid, to get the final bid CPM.
Advertisers with more than 1 million impressions per week will get models trained specifically with their own buying performance data. Models are trained and updated once each day.