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Leveling up: suggested edit task completion analysis
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User Story:
As a Product Manager, I want to make data-driven decisions about Leveling Up.

Leveling Up is part of Growth's Positive Reinforcement project.

Newcomers receive "easy" suggested edits when they first create an account, and we want to know when we should suggest newcomers "level up" to different task types.

To set this "level up" suggestion at a time when it will be both impactful and relevant, the Growth team wants to better understand how many of each task type newcomers generally complete.

Acceptance Criteria:

Provide a data visualization to show how many suggested edits are completed for each task type:

  • "Add a link" structured task
  • "Add an image" structured task
  • Copyedit (fix spelling, grammar, and tone)
  • Add links between articles
  • Find references (sources for existing articles)
  • Update articles (bring existing articles up-to-date)
  • Expand short articles

Event Timeline

KStoller-WMF created this task.

Moving to "In Progress" as @nettrom_WMF has the initial analysis done. As soon as an update is added to mediawiki we can consider this resolved.

This analysis is largely complete. We have an internal googledoc report, and I've gone ahead and created this on-wiki summary that goes through the main findings and has a couple of graphs to support it.

@KStoller-WMF : can you read through the on-wiki report and make any copy edits you think are meaningful? Then feel free to resolve this task.

Looks great! I made a few minor edits. I'll now update the Personalize praise project page.