Unsubscribe driver audit

Use when unsubscribe rates are climbing and you want to know which sends and habits are causing it.

unsubscribe-driver-audit.md

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You are an email program analyst. Work out what is driving unsubscribes and what to change.

Send data, one row per send with subject, segment, send date, list size, open rate, click rate, unsubscribe rate, spam complaint rate:
{{SEND_DATA}}
Current sending frequency: {{FREQUENCY}}
What subscribers were told they would receive at signup: {{SIGNUP_PROMISE}}
Preference options I currently offer: {{PREFERENCE_OPTIONS}}

Do this:
1. Rank the sends by unsubscribe rate and by complaint rate separately. Note where the two disagree and what that suggests.
2. Test each of these against the data and say supported, contradicted, or not testable with what I gave you: frequency, mismatch with the signup promise, segment fatigue, one bad send, offer heaviness, poor list source.
3. For the three worst sends, name the specific likely cause from the subject and segment, and the change you would make.
4. Recommend a preference center change and a frequency change, each with the trade-off spelled out.

Rules:
- Do not estimate any figure not present in the data. If a conclusion needs data I did not give you, say which field to pull.
- Do not recommend hiding or delaying the unsubscribe link. Suggest preference options instead.
- Give the output as short sections with headings, no long prose.

Fill in before running

Replace each placeholder with your own detail. The more specific you are, the less the model invents.

{{SEND_DATA}}
{{FREQUENCY}}
{{SIGNUP_PROMISE}}
{{PREFERENCE_OPTIONS}}

Getting a better result

Look at spam complaints separately. A high unsubscribe with low complaints is a healthy list correcting itself.
Check the signup promise against what you actually send. Most unsubscribe spikes are a mismatch, not a copy problem.
A frequency choice in the preference center usually saves more subscribers than any wording change.

Questions about this prompt

When is an audit better than rewriting the emails people left on?

When the rate is climbing across sends rather than spiking on one. Rewriting assumes the wording caused it. Sustained unsubscribe growth usually traces to frequency or a mismatch between what people were promised at signup and what they now receive, and no rewrite touches either.

What data does the audit need?

A send-level export with subject, segment, date, list size, open, click, unsubscribe and complaint rates, plus your current frequency, the signup promise and the preference options you offer today. The signup promise is the input nobody can find, and it is the one the analysis tests against.

What does the analysis return?

Separate rankings by unsubscribe and by complaint rate with a note where they disagree, six candidate causes marked supported, contradicted or not testable, the three worst sends diagnosed, and preference and frequency recommendations with trade-offs. The disagreement between the two rankings is the most informative line in it.

How do people misread the result?

By treating a high unsubscribe rate as failure. A list correcting itself while complaints stay low is healthier than one where people quietly mark you as spam. The move that genuinely costs you is making the unsubscribe harder to reach, which converts unsubscribes into complaints.