As a reader on Wikipedia for intrinsic learning, I want to satisfy my curiosity by navigating to recommended articles.
Hypothesis: displaying links to articles in the empty state of search on wikipedia.org and article pages will increase internal referrals on both desktop and mobile Wikipedia.
Requirements:
* Use the Codex [[ https://doc.wikimedia.org/codex/main/components/demos/typeahead-search.html | TypeaheadSearch component ]] in both Vector and Minerva== Background
* Allow one or more recommendation APIs to contribute to the recommendations list at the same time.This epic will center around designing and running experiment around testing recommendations within the empty state of search. It will contain all tickets related to the investigation and running of these tests. The epic will be completed once the experiment is done and next steps are determined for the ideas experimented on.
* As soon as a user starts typing, remove recommendations and display results for their query
Experiment parameters:== User story
TBDAs a reader on Wikipedia for intrinsic learning, I want to satisfy my curiosity by navigating to recommended articles.
== Requirements
- An experiment is run that allows us to test the hypothesis: "People who open the search bar and see the recommendations will have more internal referrals for that page that people who do not open the search bar"
Qualitative testing-- Other variables will also be measured depending on the experiment chosen
Potential metrics: of interest:
- internal referrals
- time to query abandonment
- clickthrough rate
- session depth (time x number of articles, i.e. does this promote rabbit hole reading?)
UI component of T370211
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