One less thing to consider when building your back-end data architecture.
May 31, 2020

One less thing to consider when building your back-end data architecture.

Anonymous | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User

Modules Used

  • Attribution
  • Marketing Analytics Dashboard
  • Audiences
  • API

Overall Satisfaction with AppsFlyer

We use it for mobile game channel attribution and player valuation. It is primarily used by our Marketing and UA departments for channel optimization to aid in buying decisions. Secondly, we use it to aid in the valuation of our players through the measurement of their engagement and attributed revenue through in-app purchases and ad generated revenue streams.
  • Basic setup is intuitive and easy to follow.
  • Helpful and concise user documentation.
  • Customer service was quick to respond.
  • Reporting APIs were somewhat confusing to use.
  • Levels of granularity across reports and APIs were inconsistent. (i.e., One level would contain an asset value while others would not).
  • Changes to the reporting/API schema weren't well socialized to customers.
  • One positive impact was the ability for our analysts to begin tracking attribution accurately across multiple platforms from one location, shortening the time it took to provide reports to stakeholders.
AppsFlyer turned out to be fairly flexible when integrating with our other tools. The main issues revolved around the restrictions of those other third-parties.
We felt that AppsFlyer was more straight forward with the data they provided and there was a trust formed when dealing with our reps that just wasn't there with AppLovin or Adjust. We also felt we had more flexibility when integrating AppsFlyer.
It is well suited to provide attribution tracking across multiple sources to provide a one-stop-shop for marketing/UA analytics. The stock reports provide enough insight to guide inexperienced marketing analysts. It falters when one wants to add custom parameters to track engagement or when one wants to extract this data to incorporate it into another data set. This is due to the event count limits that may constrain in-depth event tracking and the content restrictions associated with the various APIs/report extracts.