Abstract
App developers seek to optimize the number, format, placement, and combination of ads to be served a given user. However, they often don’t know which placements, numbers, or formats are the most effective. Running tests to determine optimal ad combinations to a given user is cumbersome and time-consuming.
This disclosure presents analytical techniques to display ads in a variety of formats and measure the efficacy of the ad in terms of, e.g., ad-time vs. app-time; numbers of ads shown; time since last ad; attrition of users; etc. The analytical techniques determine which ads to show based on statistics that optimize the lifetime value of users. Statistics generated by the techniques herein can be used by app developers to drive particular app behavior, e.g., the design of ad units that reduce attrition.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Toksoz, Tuna; Dukellis, John; Weng, Edward; and Guiro, Boubou, "Automated insertion and testing of ads", Technical Disclosure Commons, (December 03, 2018)
https://www.tdcommons.org/dpubs_series/1747