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AI agent for newsletter writers

Newsletter Engagement Diagnosis Agent

Explain why an issue under- or over-performed and propose tests for the next one

AnalysisDecisionsMarketingWriters
See how it worksGet access
Newsletter Engagement Diagnosis Agent: what goes in, what the agent does and what you get

What it does

Newsletter writers see a bad open or click rate but rarely know why, so they change the wrong thing. Forty-eight hours after each send, this agent pulls opens, clicks, bounces and unsubscribes for the issue and the last eight. It compares each metric with its normal range and treats a change as real only if it is outside that range. It then tests candidate causes: subject line, send time, link order, new subscribers from one source, or one mailbox provider dropping. When privacy opens exceed half of opens, it leans on clicks. If no cause explains the change, it splits results by segment and signup source and tests again. It flags deliverability if bounces or complaints double. It drafts a note with the likely cause and two tests. The writer picks which test to run. Edge case: privacy-inflated opens lead the agent to rely on clicks.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedNo 1 STARTS WHEN Issue reaches 48 hours after send 2 USES A TOOL Pull opens, clicks, bounces and unsubscribes forthis issue and the last eight 3 DOES Compare each metric with its normal range 4 DOES Test candidate causes: subject, send time, linkorder, new subscribers, mailbox provider 5 CHECKS THE RESULT Does at least one cause explain the change withdata? If not: split results by segment and signup source, thentest causes again. Back to step 4. 6 USES A TOOL Draft a diagnosis note with two tests for the nextissue 7 YOU APPROVE Writer picks which test to run 8 RESULT Diagnosis note and chosen test logged
Read the steps as a list
  1. Issue reaches 48 hours after send
  2. Pull opens, clicks, bounces and unsubscribes for this issue and the last eight
  3. Compare each metric with its normal range
  4. Test candidate causes: subject, send time, link order, new subscribers, mailbox provider
  5. Does at least one cause explain the change with data?If not: split results by segment and signup source, then test causes again. Back to step 4.
  6. Draft a diagnosis note with two tests for the next issue
  7. Writer picks which test to runThe agent waits here for your OK.
  8. Diagnosis note and chosen test logged

How it decides

It only names a cause when the numbers for that cause moved more than the normal week-to-week range; otherwise it says the change is noise.

  • Treat a change as real only if it is outside the last eight issues' range
  • Prefer click rate over open rate when privacy opens exceed half of opens
  • Flag deliverability if bounces or spam complaints double

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Number of past issues used as baseline (default 8)
  • Metric to trust most (clicks or opens)
  • Hours after send to run (default 48)
  • Where the note is saved

What keeps you in control

It always asks you first

  • Choosing the test for the next issue

Hard limits

  • Never changes list settings or sends anything
  • Does not delete subscribers

It stops when

  • Done: diagnosis note saved with a chosen test
  • Stop: fewer than four past issues to compare

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensIssue 112 had a 31% open rate against a usual 38 to 41%. The agent tested subject length and send time and found nothing, so the cause check failed. It split by mailbox provider and found Gmail opens fell from 40% to 22% while others held. It flagged a likely spam-folder problem tied to the new sending domain. The writer chose to test authentication fixes first.

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