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Analysis for email confirmation banner experiment
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Description

Motivation

We want to A/B test the banner presence before a complete rollout to ensure there is no unintended negative impact on the user behavior.

Hypothesis
  • We see an increase in confirmed emails for users who see the banner
Experiment setup
  • Users: Logged-in users with unconfirmed emails
  • Wikis: English, French, German, Polish, Japanese, Hebrew, Wikidata, Commons, Mediawiki, Meta
  • Experiment setup:
    • A/B test
    • Arm A: 50% of users in the experiment see banner version 1
    • Arm B: 50% users in control group
  • Length of experiment: 2 weeks (summary of power analysis)
Metrics
  • Primary metric: Number of accounts with confirmed emails
  • Secondary metric: Banner impressions and Banner clicks
  • Guardrail metric: Number of accounts with emails
Results
  • We observed increase in email confirmations across all projects. On average we saw a 92.6% increase in email confirmations on the projects where we had substantial data.
  • Email removal ranged from 0.15% to 1.9% on the projects. These numbers are low so we don't have a significant statistic to report but it was higher than the control group. Worth noting that about 25% of users who removed their emails went on to confirm them later indicating that they were replacing their old email with a new one.

On the whole, this experiment is considered a success and we will proceed with rolling out the banner to all eligible users on all projects.

Event Timeline

Based on these results, we will move ahead with deploying the banner to all users and probably execute the rollout in small batches.

Core Metric: Email Confirmation Rate Impact

  • The new banner delivered a highly impactful and statistically significant increase in the Email Confirmation Rate across almost all wikis.

Screenshot 2026-05-28 at 11.13.08 AM.png (2,428×1,314 px, 318 KB)

  • SRM Mitigation: Although we encountered a Sample Ratio Mismatch (SRM), probably due to some missing tracking logs in the treatment group. We did a worst-case adjustment to the data, which assumes that every single "missing" user in the treatment group actually entered the test, saw the page, and failed to convert. The results prove that even under the most pessimistic assumptions, the positive impact remains robust. The tracking imbalance does not compromise the trustworthiness of our core conclusion.

Screenshot 2026-06-01 at 1.07.36 AM.png (937×542 px, 89 KB)

Guardrail Metric: Email Removal Rate

  • We observed a slight uptick in the email removal rate within the treatment group.
  • Insight: With further investigation, ~25% of users remove email and confirm again - they might remove an old email and add a new one.
  • Conclusion: Compared to the large increase we see, and the very small email removal rate we would call this a positive result for the treatment.

Screenshot 2026-06-01 at 1.37.00 PM.png (2,642×1,320 px, 337 KB)

Secondary metric: Banner Click Through Rate We can use this metric as references and baselines if we want to run another experiment on banner versions.

Screenshot 2026-06-01 at 1.42.43 PM.png (2,674×1,326 px, 303 KB)