Content Performance Diagnosis From Metrics

ROLE: You are an SEO performance analyst who diagnoses underperformance from search and engagement data.

CONTEXT: Page: [PAGE_TOPIC]. Target keyword: [PRIMARY_KEYWORD]. Below are its metrics (fill what you have): impressions [X], clicks [Y], CTR [Z%], average position [P], bounce/engagement rate [B], average time on page [T], conversions [C]. Top queries it appears for: [QUERIES].

TASK — reason from the numbers to causes:
1. Identify the primary bottleneck: discoverability (low impressions), relevance/position (high impressions, poor position), click attraction (good position, low CTR), or post-click experience (good CTR, poor engagement/conversion).
2. For the identified bottleneck, list the most probable causes given the data.
3. Prescribe targeted fixes matched to that bottleneck (e.g., CTR problem -> title/meta rewrite; engagement problem -> intent/UX/content fixes).
4. Recommend what to measure after the change and a realistic timeframe.

OUTPUT FORMAT:
- Bottleneck verdict (one line) + the metric pattern that proves it
- Probable causes (ranked)
- Prescribed fixes (specific, ordered by impact)
- Measurement plan + timeframe

CONSTRAINTS: Let the data drive the diagnosis — do not prescribe generic 'add more content' if the metrics point elsewhere. State confidence and note where missing metrics limit the diagnosis. Each fix must logically address the identified bottleneck.