Audit beginner Works with: Any AI

Mailchimp Campaign Performance Review and Learning Log

Table output Has example

• 🐵 Mailchimp

Compare campaigns and record what works.

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.

Review email campaign results. Data per campaign: date, subject, audience size, delivered, opens, clicks, unsubscribes, revenue if tracked: [CAMPAIGN_DATA].

Set out a table with delivered, clicks, click rate (clicks divided by delivered), unsubscribes, unsubscribe rate and revenue per email where available, and show one calculation in full: 84 clicks from 2,800 delivered is 3.0 percent. Group campaigns by type and compare the median rather than the best case. Identify patterns by topic, send day and length, noting sample sizes. Open rates can be inflated by privacy features, so lean on clicks and replies [VERIFY]. Avoid claiming causes: write learnings as hypotheses.

Provide a learning log template with columns date, what we tried, what we saw, confidence (low, medium or high based on the sample) and the next test. Say how many campaigns you were given, because fewer than ten is a small sample. List the one test you would run next and the decision rule you would set before running it.

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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.

Invented table. Campaign Spring offer: delivered 2,800, clicks 84 (3.0 percent), unsubscribes 6 (0.21 percent). Campaign Tips: delivered 2,850, clicks 142 (5.0 percent), unsubscribes 2 (0.07 percent). Campaign Webinar: delivered 2,790, clicks 61 (2.2 percent), unsubscribes 5.
Median click rate 3.0 percent. Learning log entry: 'Practical tips earn the highest click rate and fewest unsubscribes (5.0 versus 3.0); confidence medium (three campaigns); next test: tips with an offer at the bottom.' With three campaigns the learning is a hypothesis; confirm with two more sends before changing the content plan.

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