As a product manager for Structured Data, I want to understand how the image suggestions notifications feature is being used and how it relates to other notifications behavior, so that I can make decisions about how to build and/or make changes to the feature going forward, and determine its success.
Ideally we can create a dashboard with this information.
The high level questions we want to answer are:
1. Is our communication about our suggestions effective?
2. Do Editors include adding suggested images in their current behavior flow?
3. Are the suggestions themselves good (this tickets informs how do we define good)?
Specific analytics questions to answer/acceptance criteria:
[] How many notifications does a user get today? (We are starting with 2 notifications max per week; but this information will help us decide if we should increase or decrease that number in the future). (Covered in T291403)
[] How many articles is a user typically watching? (We may increase the number of notifications in the future based on this number; and may also let us know if we need a landing page or tool where users can interact with suggestions in the future if users would see lots of notifications/suggestions). (Covered in T291403)
[] How many images on average are added by a user per month? (To understand what the current behavior is today and how people engage with images; would help us know if engagement increases based on our work).
[] Number of notifications sent (To get a sense of the scope of our work and whether we should increase or decrease)
[] Number of opt-outs (To see whether users are annoyed by our notifications or not interested in them, etc)
[] Number of images suggested that are added to the matched article within a month of receiving the notification (To see whether the notifications are successful) (Covered in T299667)
[] Number of suggested images not reverted from their matched article (low revert rate to show that the matches are good) (Covered in T299667)