Read! boosts ad ARPU and ARPDAU by 50% with BidMachine Mediation

Read! boosts ad ARPU and ARPDAU by 50% with BidMachine Mediation

Read! is an e-book platform from LitRes Group, the leading seller of licensed e-books in Eastern Europe. The app passed 10 million downloads, but its monetization wasn't keeping pace with that audience. With BidMachine Mediation, Read! grew ad revenue by 45% and lifted ad ARPU and ARPDAU by 50%.

More competition for the same impressions

The target the team set was to increase auction competition, improve ad delivery and add 10% to revenue and ARPDAU. The reading experience set the boundary, so whatever was gained had to come from the price of each ad rather than from showing more of them, and every change was judged by its effect on readers as much as on revenue.

Price floors by ML, delivery by segment 

Read! brought in BidMachine to test its mediation and get more out of the existing setup. The plan came down to four moves:

  • Automating price floor optimization with ML to maximize yield
  • Tailoring the mediation to user segments and geographies
  • Rolling out a mix of rewarded, interstitial, native and banner ad formats
  • Monitoring performance and adjusting the setup as data came in

Five times the target

The new mediation strategy delivered results well beyond the team's original goals. Key outcomes included:

  • 50% lift in ad ARPU and ARPDAU 
  • 45% more ad revenue

The results demonstrate how increasing auction competition and continuously refining a mediation strategy can unlock significantly more value from every impression.

What came next

Following the success of Read!, LitRes Group expanded its partnership with BidMachine to scale monetization for LiveLib, its book recommendation platform.

What other publishers can take from this

Nothing here required rebuilding the monetization stack. The gains came from two simple changes: automatically adjusting price floors based on demand instead of setting them manually, and tailoring the mediation setup to different markets and audience segments instead of using the same settings for everyone.

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