Reading/Web/projects/Read more

About
Read more is an experiment that will be carried out by the Reading team on desktop and mobile web, in order to further engage readers and increase their browsing time. The concept already exists on apps, where you can check the performance report here

How it works?
A user who gets to the bottom of an article on either mobile or desktop web is shown a list of other articles that are related to the one they just finished. The notion is that if the reader has gotten to the bottom of the article, they might be looking to read more about the topic and surfacing articles that are similar might be exactly what they are looking for. This has been release on apps and saw a 16% click-through (For users who saw it). Additionally, 25% of the users who saw read more results clicked through at least 1x in a __ period (I can't tell from the query here: https://docs.google.com/spreadsheets/d/1iyNqWgC8lNWk3ckSQJS_ACrfeW1UrBHOf58L97oeNqM/edit?ts=560ae622#gid=1184183009)

Rationale
If readers are offered suggestions that are similar to the topic they are reading about, this will further engage their reading session time, it will further educate them about the topic they are looking for, and supports a richer reading experience for those who are just randomly browsing topics.

Prototyping
This will be tested in beta first.

MVP
A user reaching the bottom of an article is shown the title and lead image for 3 articles that relate to the article they just finished. We are able to measure the engagement clicks/impressions with this feature.

User Stories
A user reaching the bottom of an article is shown the title and lead image for 3 articles that relate to the article they just finished so that they can continue reading about that topic.Someone editing a wikipedia article can manually change the article suggestions using wikitext so that they can correct any erroneous or sub-optimal suggestions. An project stakeholder (such as PM or data analysit) is able to measure the engagement clicks/impressions with this feature so they can determine if it is adding user value.

Metrics Implementation
We will want to track:
 * Impressions of read more suggestions (the lump--not each item suggested)
 * Clicks to read a suggested article
 * The position of article (1,2,3). Ideally: whether or not article was edited manually
 * Ideally: a)overall referrals from a page with read more, b)overall referrals from same page without read more

Timeline Estimate

 * 1)     build read more according to mobile web specs
 * 2)     launch on mobile web beta
 * 3)     measure impact using event logs CTR (referral data won't be helpful at these numbers)
 * 4)     discuss with community
 * 5)     launch on mobile
 * 6)     build for desktop
 * 7)     launch on desktop (open discussion about whether we launch in beta first and/or do progressive rollout)
 * 8)     Delivery Estimate: End of December on desktop?