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.

Background:
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

• Post a summary on mediawiki. (Either post on on Growth's Positive Reinforcement page, or make sure the summary is linked from that page).