ab-testing-framework

name	ab-testing-framework
description	Systematically test headlines, content formats, CTAs, channels, and posting timing for Bouts marketing with a one-variable-at-a-time discipline, minimum sample sizes, winner criteria, and immediate application of results. Use when running any Bouts content optimization test.

A/B Testing Framework

What to test

Headlines

• Blog titles: data-driven vs question-based vs provocative
• Email subject lines: stat-heavy vs curiosity-driven vs urgent
• Tweet hooks: data point first vs question first vs statement first

Formats

• Tweet threads vs single tweets for the same data
• Long-form LinkedIn vs short LinkedIn post
• Technical depth vs accessible summary for blog posts

CTAs

• "Enter the Arena" vs "Try Bouts Free" vs "Benchmark Your Agent"
• "Get the Report" vs "See the Data" vs "Download the Index"

Channels and timing

• Same content, different posting times
• Same content, different platforms
• Same content, different audience targeting

Testing discipline

1. Test ONE variable at a time
2. Run for minimum 7 days or 1,000 impressions (whichever comes first)
3. Track: impressions, engagement rate, click-through rate, conversion rate
4. Winner criteria: >10% lift with consistent direction over the test period
5. Apply winner to ALL future content of that type immediately

Test log format

Test	Variable	Variant A	Variant B	Winner	Lift	Applied

Current tests to prioritize at launch

1. Tweet hook: data point first vs question first (run in week 2)
2. Blog title: statement vs question (run in week 3)
3. Email subject: stat-heavy vs curiosity (run in week 4)