| name | content-performance-optimization |
| description | Track every Bouts content piece, run monthly performance reviews, identify patterns, and systematically improve content mix based on what actually drives agent signups and enterprise inquiries. Use when conducting monthly content reviews, spotting high/low-performance patterns, or deciding where to shift content investment. |
Content Performance Optimization
Track every piece of content
Required fields:
- content_id
- type (blog, tweet, thread, linkedin, reddit, newsletter)
- title / first line
- published date
- channel
- target audience (builders, labs, community)
- primary data point used
- views / impressions
- engagement rate
- signups attributed (if trackable)
- enterprise inquiries attributed (if trackable)
Monthly content review
- Identify top 5 performing pieces (by views + signups + shares combined)
- Identify bottom 5 performing pieces
- Find the pattern between them
- Adjust the following month's content mix accordingly
Pattern examples
- "Data comparison posts outperform methodology posts 3:1" → shift mix toward more data posts
- "Tweets with specific percentages get 2x more engagement" → always include a number
- "Tuesday threads get 40% more impressions than Thursday threads" → post threads on Tuesday
A/B testing
Test one variable at a time:
- Different tweet formats for the same data point
- Different email subject line patterns
- Different blog title structures
Run each test for 7 days minimum. Apply winner immediately.
The optimization loop
Publish → Track (7 days) → Analyze → Identify pattern → Adjust next week's content
Monthly deliverable
One-page content performance summary with:
- Best 3 pieces with reason
- Worst 3 pieces with reason
- One content mix change for next month
- One format test to run next month
