The Performance Analytics Decoder

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The Performance Analytics Decoder

Analyzes your content performance to identify replicable success patterns and create a predictive model for future content.

Prompt

You are a content forensics expert analyzing for replicable success patterns.

DATA SET:
Top 10 performers: [full text/metrics]
Bottom 10 performers: [full text/metrics]

QUANTITATIVE ANALYSIS:

Performance Metrics:
- Engagement rate calculation
- Virality coefficient (shares/views)
- Comment sentiment analysis
- Save-to-engagement ratio
- Click-through patterns
- Audience quality score

Content Patterns:
- Word count correlation
- Reading time sweet spot
- Hook type effectiveness
- CTA conversion rates
- Format performance (text/visual/video)
- Posting time impact

QUALITATIVE ANALYSIS:

Success DNA:
- Emotional triggers present
- Story arc structure
- Controversy level (1-10)
- Novelty factor
- Authority signals
- Social proof elements

Failure Patterns:
- Assumption mistakes
- Timing misalignment
- Message-market mismatch
- Complexity barriers
- Missing hooks
- Weak value props

COMPETITIVE CONTEXT:
- Industry benchmark comparison
- Trending topic alignment
- Algorithm favorability
- Seasonal factors
- Competition saturation

PREDICTIVE MODEL:

Success Formula:
[Hook type] + [Content structure] + [Emotional trigger] + [CTA type] = Expected performance

Variables that matter most:
1. [Factor]: [XX% impact]
2. [Factor]: [XX% impact]
3. [Factor]: [XX% impact]

NEXT 30 DAYS ACTION PLAN:

Week 1: Double down on [winning element]
Week 2: Test [new angle based on data]
Week 3: Eliminate [losing pattern]
Week 4: Scale [highest ROI activity]

Content Calendar:
- 5 posts replicating top performer structure
- 3 posts testing edge cases
- 2 experimental formats

A/B Testing Framework:
- Variable isolation protocol
- Statistical significance targets
- Decision tree for results
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About the author

Co-founder of Prompt Magic and ThinkingDeeply.ai Career Chief Marketing Officer