Our unbiased ad mediation enables you to place complete trust in our machine learning algorithms. 

Firstly, Tapdaq collects data on each user session, including (but not limited to) location, the requested ad format, and the app category.

Using this data, alongside the latest revenue data from each ad network, we analyse and prioritise demand sources based on who we predict will be the highest paying.

We apply machine learning to the data to build powerful predictive models, which continually improve the accuracy of our predictions, and ultimately, your eCPMs.


Waterfall Transparency

As well as prioritising networks based on the above criteria, Tapdaq allocates a small impression budget to test different demand sources in each waterfall position. This ensures every network has a fair chance to compete for all available impressions, and that networks are priced accurately.

You can easily see which networks are winning each impression within your app using Tapdaq's ordinal reporting.


Manual Price Rules

You can also set manual price rules for each network zone in your waterfall. This is only recommended if you have a direct deal with a certain demand source, or if you have configured specific price rules on an ad network's dashboard.

Did this answer your question?