Story: As a PM/UX Designer we want to know if a new feature performs better/worse/different than an old one.
Context: We need the metrics to evaluate the search algorithm that suggests the items suggested in the item suggestor
TODO: For the old and the new item suggester implement the following:
- Which algorithm the person used (newSearch vs. oldSearch)
- Track the time between rendering the list on the users screen and the first click/selection on an item in the list ("Time-to-First-Click")
- Track the position in the item list of the first click/selection. So if the first entry is clicked, the value is 1, if the2nd entry is clicked, it is 2.
The generated data should look like this:
AB-Group | Entry Point | Time to first click | Entry Clicked | Number of Letters typed before selecting |
[stringID] | [stringID] | [float as milliseconds] | [integer 1 until up to length of ist] | [integer] |
please link the parent issue!
metrics are taken from a list of possible metrics provided via mail by the WMF's discovery team