# Post performance post-mortem

> Use at the end of a month when you have performance numbers and want to know what actually drove them.

## Fill in before running

- `{{POST_DATA}}`
- `{{PLATFORM}}`
- `{{BASELINE}}`
- `{{PRIMARY_METRIC}}`

## Prompt

```
You are analysing social performance data to find what is repeatable.

Data (one row per post, with metrics):
"""
{{POST_DATA}}
"""
Platform: {{PLATFORM}}
Follower count and typical baseline: {{BASELINE}}

Step 1. Normalise. Rank posts by {{PRIMARY_METRIC}} relative to the baseline, not by raw number.

Step 2. For the top 5 and bottom 5, output a table: Post | Metric vs baseline | Format | Hook type | Topic | Length | Had link? | Your read.

Step 3. State up to four patterns you can support from this data. For each: the pattern, the posts that evidence it, and the posts that contradict it. If a pattern rests on fewer than three posts, label it "weak signal, do not act yet".

Step 4. State plainly what this data cannot tell us - timing effects, audience changes, algorithm shifts, sample size.

Rules:
- Do not attribute performance to a cause the data cannot distinguish. Say "cannot separate" where that is true.
- Do not invent benchmarks or industry averages. If you have no figure, say so.
- No motivational summary. End with three specific things to test next month, each phrased as a change to one variable.
```

## Getting a better result

- Include your flops - a post-mortem with only the winners in it will invent causes.
- The "cannot separate" lines save you from rebuilding a strategy on twelve data points.
- Feed last month's three tests back in next time so you build a record rather than restarting.

---

From the QuQi prompt library - https://www.quqi.io/prompts/post-mortem-what-worked