Ebony Nicole Simone
4 月 20, 2020
We are very ecstatic to share our latest discussion with MoPub on impression-level data (ILRD) and never before seen use-cases of MoPub ILRD with Tenjin’s DataVault.
Tenjin built the Basic ad revenue LTV model in 2017, and the Advanced ad revenue model was launched in 2018. In 2019, Tenjin released our Pro ad revenue model using MoPub ILRD with granular impression-level data. We teamed up with our friends from MoPub to discuss the evolution of ad revenue data reporting and the role impression-level data plays in informing important monetisation strategy decisions. We discussed a few use-cases, and Tenjin offered training for ILRD in the webinar. It’s hosted by Senior Product Manager at MoPub, David Gregson, and Tenjin Platform Director Matthaus Krzykowski.
So, what the hell is ILRD, anyway? Basically, it allows publishers to see an estimation of how much money they’ve earned from each served impression. Impression-level revenue data, as described by MoPub, enables full-platform publishers to leverage data to better understand their users by adhering to three principles: access, clarity, and flexibility.
It’s all about accurate and granular data, and what this data can do for publishers with the new use-cases is continually being discovered. MoPub’s ILRD, combined with Tenjin’s DataVault, is a game-changer.
We discuss one use-case, showing the optimal number of ads with Tenjin Data Exporter (Training #211, Tenjin). This training is one of the three use-cases discussed in the webinar and one that Tenjin Data Scientist, Mei-Han Weng, presented at PGC London 2020. Matthaus and David discuss retention rate and its importance to in-app game impressions.
Other Tenjin training highlighted in the webinar are:
- #701 Tenjin MoPub ILRD LTV Calculation
- #705 eCPM Decay Curve Analysis
- #711 Ad Revenue A/B Testing
You can request the training listed above here.
Lastly, we discuss four predictions on the future of ad revenue tracking. Do we agree on most, all, or none? Additionally, where do you agree or disagree? Let us know on Twitter!
