Three Informed Projects
The root cause analysis, based on combined user behavior and survey insights, sets the tone for H1 23 roadmapping of reducing 'Advertiser Friction'. This page displays detailed artifacts of the solutions created and their achieved impact measured through AB Test experimentations.
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Note: Some UI elements have changed since the initial iteration.
1. Budget & Apply Learning Guidance
Pain point: Advanced users think A/B Testing is expensive because they are spending more than enough budget in the initial test.
Solution:
1. Guide advertisers to set reasonable budgets.
2. Educate advertisers to apply learnings once test results are available. (Advertisers previously exposed to the budget warnings will get an additional in-app message leading to the action page.)
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Impact:
- ✅ [Top-line] Active Advertisers +3%
- ✅ Studies Created +5%
- ✅ Report viewed +15%
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2. Post Test Actions
Pain point: Users need guidance on best practices for applying learnings.
Solution:
1. Provide direct post-action options for tests with a winner. eg. Run winner, duplicate and edit, create another A/B test.
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2. Offer direct post-action choices for cases without a winner, eg. create another A/B test, extend the current test, etc.
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Impact:
- ✅ [Top-line] Incremental Revenue +2%
- ✅ [Top-line] Active Advertisers +2.5%
- ✅ High CTA
3. Winner Result Content Update
Pain point: Users need guidance on understanding the value proposition of A/B Testing product.
Solution:
1. Provide clear communication on the cost-saving aspects of the product. (Note: The current UI has been updated since implementing this change. An example of the original change is ' There's a 84% chance you'll save on cost per click if you continue to run the winner' )
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Impact:
- ✅ Positive Actions +17%
- ✅ Success Actions +10%
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