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Discrepancy between Attributed Installs and Ad Network Installs / MMP
Discrepancy between Attributed Installs and Ad Network Installs / MMP
Updated over a week ago

At a glance: Learn how to analyse discrepancies between Cost Center's Attributed Installs and MMPs data.

Background

  • "Ad Network Installs" is the number of installs getting from the Ad Network. For Self-attributing Networks aka SANs(Google Ads, ASA, Meta Ads, Tiktok, Snapchat), each ad network calculates the number within their platform. For non-SANs, this calculation uses data provided by the MMP

  • "Attributed Installs" is the number of attributed users who have an ID (GAID for Android, IDFA/IDFV for iOS)

  • For SANs, "Ad Network Installs" are usually higher than "Attributed Installs" because the ad networks tend to attribute more than reality.

  • For non-SANs, "Ad Network Installs" are sometimes higher than "Attributed Installs" for Android because there are users without ID (i.e. users who turn off personalised ad settings). This is less than 1% overall. But some ad networks may acquire much more users like this.

How Cost Center calculates Attribution Installs

  • Cost Center uses "first open" from Firebase to calculate attributed installs, which may differ from MMPs.

  • Cost Center has a new-user verification process. Whenever a new user is reported by MMP, Cost Center will verify if this is a real new user by cross-checking their activities within the last 30 days. If they are not a new user, this user will not be counted, making the "Attributed Installs" different from the MMP.

How to troubleshoot

  • This is a non-issue If the discrepancy between Attributed Installs and MMP is less than 10% because of the reasons stated above.

  • Mintegral tends to acquire more non-ID users than other ad networks. If the discrepancy happens your Mintegral data, it is an expected outcome.

  • If the discrepancy is more than 10%,

    • make sure that you migrate the historical users to the new MMP if you have switched MMP recently;

    • CC might not receive enough raw data from the MMP, which could be the case if you’re using Adjust. Please reach out to [email protected].
      Note: There is no way to backfill data in this case.

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