Audit advanced Works with: Any AI

Sender Reputation and Spam Complaint Audit

Table output Has example

Audit sender reputation and spam complaints to find what is hurting inbox placement, with fixes ranked by impact.

The Open buttons send the prompt text as currently shown below to that site only when you click. Fill in the placeholders first.

[VERIFY] is an editorial flag, not a blank to fill. Wherever the prompt shows [VERIFY], check that item against a reliable source before you use it.

Audit my email sender reputation. Sending volumes, bounce, complaint and unsubscribe rates by campaign: [SENDING_STATS]. Where the list came from: [LIST_SOURCES]. Recent changes in frequency or content: [RECENT_CHANGES].

Identify likely causes of poor placement: old or purchased addresses, no confirmation, high complaints on certain segments, sudden volume jumps, unclear sender names, and misleading subject lines. Rank them by likelihood from the evidence and say what would confirm each.

Return a table with Signal, Reading, Concern and Action, a score from 1 to 10 for list health, content, consistency and technical setup, and a 30-day recovery plan. Consent and anti-spam rules are [VERIFY] for [JURISDICTION].

Also add a weekly monitoring list of the five numbers to watch, thresholds I should set based on my history, and a decision rule for pausing a segment. Describe how to warm up sending when volume must rise.

Then write a recovery and prevention plan covering 90 days. Week by week, specify which segments to mail, the sending volumes, content restrictions, and the metrics to review before each increase. Include a rule for pausing when complaints exceed a threshold I set from my own history. Provide a re-permission message of under 100 words for uncertain segments and a policy for list sources, forbidding purchased lists and requiring documented consent. Create a dashboard layout with the five numbers to watch and their normal ranges based on my data. Add guidance for working with the email provider's support, such as what evidence to gather. Include a short staff guide on collecting addresses honestly at events and on forms. Consent and anti-spam rules are [VERIFY] for [JURISDICTION], and results cannot be guaranteed.

Add a reminder to keep a dated record of every change made to sending practices, so that cause and effect can be understood when results change weeks later.

Remove personal data from anything I paste, and tell me if you notice customer information. Tag consent, tracking and data-sharing rules [VERIFY] for [JURISDICTION] before any change is made.

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Optional: type your details and the prompt above updates. Nothing is saved or sent.

Replace each bracketed placeholder with your own details, then paste into Any AI or another assistant.

Signals (invented, 30 days)
Sends 62,000; bounces 3.8% (hard 2.9%); complaints 0.31%; unsubscribes 0.7%.
Segments: "Event leads 2021" 9,400 addresses, bounce 11%, complaints 0.9%. Red.
Frequency jumped from 1 to 4 sends a week in week 3. Amber.
Subject lines: two start with "Re:" though they are not replies. Red.
Likely causes ranked: old list segment, frequency jump, misleading subjects.
Plan: pause event leads, send a re-permission message to uncertain contacts, return to weekly sends for two weeks, review complaint rate before raising volume.
Consent rules [VERIFY]; no result is guaranteed.

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