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Calculate baselines for Edits/Unique User in a calendar year
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Description

Background

The Apps team is in the early stages of planning for a Year in Review / Insights feature. This feature hopes to present a personalized wrap up of an app user's 2024, including insights on their editing behavior, and their reading and donation behavior from in-app data.

In order to present insights on a user's editing history for 2024, we may need to use existing APIs like the user contributions API, or Growth's Impact API. The user contributions API can fetch 500 edits at a time, and the Growth's Impact API only pulls data for the most recent 1000 edits. We want to see what the current breakdown of our editors is, to know if we can successfully use either of these APIs at scale.

User story
  • As a maintainer of the User contributions API, I want to know what % of users in the iOS app have more than 5,000 edits (requiring 10 requests to pull their full year of data), vs 1000 edits (requiring only 2 requests), so I can gauge the strain that releasing Year-in-Review to all iOS users would have on the API.
  • As the owner of the Growth Impact API, I want to know what % of users in the iOS app have between 1k and 10K edits, so I can learn if raising the minimum to 10K edits would be helpful for the Apps team.
Task
  • Calculate or estimate the breakdown of unique iOS app users who fall into the following buckets
    • Made fewer than 500 edits (all edits, not just app edits) in the 2023 calendar year
    • Made 500-1000 edits (all edits, not just app edits) in the 2023 calendar year
    • Made 1k-5k edits (all edits, not just app edits) in the 2023 calendar year
    • Made more than 10k edits (all edits, not just app edits) in the 2023 calendar year

If this can't be achieved using media.wiki history, please explore if it could be roughly estimated by calculating an average edit/year for each editor, then bucketing. (Total contributions from User Info API / years active)

Event Timeline

2023 iOS Edits Only Unique Editor Counts (logged in only, unreverted edits)
(Keeping for reference, actual request is for all edits by iOS editors).

Bucket by iOS Edit CountCount Editors
fewer_than_50019334
500_to_100048
1000_to_500046
5000_to_100003
more_than_100006

2024 - 6 months data - iOS Edit Editors bucketed by All platform edit counts (logged in only, unreverted edits)

Bucket by Total Edit CountCount Editors% Distribution
fewer_than_5001254795.0%
500_to_10002421.8%
1000_to_50003132.4%
5000_to_10000490.4%
more_than_10000600.5%

Based on average monthly iOS unique editors ( 7672) and average monthly new unique editors (407) and known distribution of activity buckets we can estimate totals for 12 months of editor bucket data:

Bucket by Total Edit Countestimated_user_count% Distribution
fewer_than_5001486695.0%
500_to_10002871.8%
1000_to_50003712.4%
5000_to_10000580.4%
more_than_10000710.5%
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