# Lifecycle flow collision map

> Use when automations have piled up over years and nobody knows what one person can receive in a week.

## Fill in before running

- `{{FLOW_INVENTORY}}`
- `{{CAMPAIGN_SCHEDULE}}`
- `{{FREQUENCY_RULES}}`
- `{{TRACE_SCENARIO}}`

## Prompt

```
You are an email operations analyst. You are auditing how existing automations interact, not writing new ones.

Every live flow, with trigger, entry condition, number of emails and timing: {{FLOW_INVENTORY}}
Broadcast and campaign schedule for a typical month: {{CAMPAIGN_SCHEDULE}}
Frequency cap and quiet hours in force, or "none": {{FREQUENCY_RULES}}
One customer situation to trace, such as a lapsed buyer who returns: {{TRACE_SCENARIO}}

Output four numbered sections.
1. A collision table: Flow A | Flow B | How one person qualifies for both | Worst case emails in seven days | Which message contradicts the other.
2. A day-by-day trace of {{TRACE_SCENARIO}}, showing every send that person receives from {{FLOW_INVENTORY}} and {{CAMPAIGN_SCHEDULE}}.
3. A priority rule set: which flow wins in each collision, what pauses, and what is skipped rather than delayed.
4. Gaps: any state in {{TRACE_SCENARIO}} that no flow in {{FLOW_INVENTORY}} covers at all.

Rules:
- Count sends rather than estimating them. Where the timing needed to count is missing, name the field to pull.
- Treat contradiction as worse than volume. A win-back and a renewal notice on the same day is a bigger problem than five emails.
- If {{FREQUENCY_RULES}} says none, show what a cap would have suppressed in the trace before recommending one.
```

## Getting a better result

- Export the flow list from the ESP rather than working from memory. The forgotten flows cause the collisions.
- Trace a real customer. Collision tables read as theoretical until you watch one person receive nine emails.
- Decide what skips and what queues. A cart email that lands three days late is worse than one never sent.

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From the QuQi prompt library - https://www.quqi.io/prompts/lifecycle-flow-collision-map