Growth/Analytics updates/Help Panel experiment plan

The goal of the help panel is to provide users with easier ways to get help without them having to leave the editing context. This can then enable them to complete their tasks while potentially also meeting the Wikipedia community through questions and answers at the community’s help desk. Helping users complete their tasks can lead to an increase editor activation (the proportion of new users who make edits), and potentially also editor retention (the proportion of new users who return to edit a second time), the latter being the Growth Team's overarching goal.

In order to understand the help panel's impact on editor activation and retention, we propose a six month A/B test. During that test, 50% of new registrations on target wikis will have the help panel enabled by default, and 50% will have it disabled. We are likely to be running other experiments on the target wikis at the same time, for example testing variants of our welcome survey. If those experiments require stratified sampling, we will make sure our sampling strategies are modified accordingly.

Variants
During those six months we also envision testing variants of the help panel to understand how specific interface elements positively affect behaviors inside the workflow of seeking help. We will remember that the stronger our hypothesis that an altered interface will affect activation or retention, the more a test on that interface confounds our longer term experiment on activation and retention.

We will need to prioritize which of the variants to test first, because we will only test one at a time. We will also not run any of the variants until about a month of the larger experiment has run without any of these smaller ones nested inside. This is so that we can learn clearly whether the help panel itself has an effect on new user activation rate.

Leading indicators and plans of action
The duration of the A/B test is six months because it is impossible to detect changes to new editor retention on mid-size wikis in less time than that (unless we drastically impact retention, but we see that as somewhat unlikely). While we wait for our results we want to be able to take action if we suspect that something is amiss. Below, we sketch out a set of scenarios based on the data described in the instrumentation strategy above. For each scenario, we propose a plan of action to take to remedy the situation.