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Community Update Module: Experiment Analysis
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Description

User story & summary:

As the Growth team, I want to measure the impact of this new feature, so that I can determine if our experiment is successful.
As the Growth team PM, I want to measure the impact of this new feature, so that I can determine if we should make further improvements to this feature or rollback and end this experiment.

The plan is due by the end of Q1 FY 24-25 (Sept 30th) so that we can begin the experiment in Q2.

Background & research:

https://www.mediawiki.org/wiki/Growth/Community_Updates

The Growth team will create a new module on the Newcomer homepage that can be used by communities to highlight important community events and initiatives. This Community Updates module will be Community Configurable, so communities can decide to highlight specific events, projects, campaigns, and initiatives, that are set by admins using Community Configuration.

Metrics to evaluate:

What we will measure as part of the A/B test (T365889):

QuestionMetricEvent to be tracked
Awareness - How many account holders visited their Homepage while this feature was visible?Number of users who visited the Homepage during the experimentHomepage pageview
Consideration - What is the click-through-rate (CTR) of the module?Number of impressions of the Community Updates module & Click Through Rate (CTR) of Community Updates moduleModule impression & Module click
Conversion - Do more newcomers sign up for the WikiProject or Campaign when they are exposed to the Community Updates Call To Action (CTA) on the Homepage?Number of users who signed up for a campaign during the experimentCampaign signup

Instrumentation: No new schemas will be created for this as we’re using the Metrics Platform Instrumentation and will be relying on the core schema. We will use the HomepageVisit schema to track pageviews of the Newcomer Homepage. We also plan to mirror the Community Updates module instrumentation using the existing HomepageModule schema, as that enables us to learn about possible differences between the two approaches.

Data retention plan: We do not plan to retain any data for longer than the standard 90 day data retention policy.

Acceptance Criteria

Event Timeline

KStoller-WMF renamed this task from Newcomer Homepage: Experiment Analysis to Community Update Module: Experiment Analysis.Nov 5 2024, 5:40 PM
KStoller-WMF moved this task from Inbox to Backlog on the Growth-Team board.
KStoller-WMF moved this task from Incoming to Doing on the Growth-Team (Current Sprint) board.

This analysis has been completed. We found no significant difference between the group of users who saw the Community Updates module and the control group. The primary reason for this is that the number of users who registered on Spanish Wikipedia during the experiment and signed up for a campaign is too low.

The Community Updates module experiment ran on four wikis: the Arabic, Czech, French, and Spanish Wikipedias. For the purposes of analysis, we consider 2024-11-01 (at midnight) as the deployment time and examine activity on those wikis during the month of November. During that time, two of the wikis ran updates that had limitations on who could see the update: the Arabic and French Wikipedia required at least 10 edits. On Czech and Spanish Wikipedia there was no limitation.

Another limiting factor in understanding the effect of the module is that the purpose of the updates were different from wiki to wiki. For example, on Spanish Wikipedia that Community Updates module linked to Wikipedia Asia Month 2024, while on Czech Wikipedia it linked to information about their weekly online wiki advice sessions.

The analysis was limited to the Spanish Wikipedia because of the time available to perform this analysis, the wiki's size, that there was no limit who could see the module, and that the module linked to a campaign that required users to sign up (meaning that we could track who signed up).

During the experiment period, the module was shown to about 3,500 users who signed up during the experiment, and about 1,000 users who had signed up previously. We limited our analysis to the former group as the Growth team focuses on the newcomer experience, and also because the impression and click-through counts for that group were substantially higher.

The per-user click-through rate of the module during the campaign was 1.7%. There was very little difference between the desktop and mobile web platforms when it comes to this rate. This rate is low but similar to baselines we gathered prior to the experiment for the "banner module", a previous feature on the Newcomer Homepage that worked similarly to the Community Updates module.

The sign-up rate for users after they clicked on the link in the Community Updates module, less than 5%, was substantially lower than baselines from other experiments. This led to an overall Campaign Sign-Up Rate, the key metric of the experiment that was also substantially lower than expected. When combined with the fact that the sign-up rate in the control group was also small but not zero, we end up with overall results that are not statistically significant.

What should we do based on this results? Conclude the experiment and release the feature to all users? If so, should we add anything to our KPIs dashboards, eg: impressions and CTR. cc @KStoller-WMF

I've been putting this off as we finished other projects and then completed our Engineering Maintenance sprint, but I think it's time to release more widely!
T384406: Community Updates module: Release to all Wikipedias with GrowthExperiments

Let's chat about that task next sprint. And I'll check in with Benoît about community outreach.

should we add anything to our KPIs dashboards, eg: impressions and CTR.

I know we have this data in Superset, but I imagine it would be more visible if we had it in Grafana... is that what you are thinking?

Thanks for the updates.

should we add anything to our KPIs dashboards, eg: impressions and CTR.

I know we have this data in Superset, but I imagine it would be more visible if we had it in Grafana... is that what you are thinking?

I had forgot about that Superset dashboard, I believe that could work as well, maybe with some tuning like showing a different line per wiki or update.