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Know if your last Mailchimp campaign beat your usual results
For marketing teams who want a campaign judged against recent sends to the same audience, with reasons, by asking their AI assistant.
On this page
Connector
Connect Mailchimp, pick your AI tool and paste the prompt.
The problem
Did that campaign do better or worse than usual
After a send, the question is always whether the campaign beat your usual results and why. Answering means opening the report, finding earlier campaigns to the same audience, working out averages and digging through clicks, bounces and unsubscribes.
Without PopdockAI
- Open the campaign report
- Find earlier campaigns to the same audience
- Work out averages in a spreadsheet
- Dig through clicks, bounces and unsubscribe reasons
With PopdockAI
- The report, clicks, bounces and unsubscribe reasons are read
- A baseline is built from recent campaigns to that audience
- Each metric gets a one line verdict against it
- Problems are called out and nothing is changed
The prompt
Use this prompt
Copy it into any AI tool connected to PopdockAI. Swap the values in braces for your own.
**Objective:** Review how the Mailchimp campaign `{campaign-title}` performed, compare it with the previous {compare-count} campaigns sent to the same audience (default 5), and explain what drove the result.
**Step 1: Resolve the campaign**
Call `mailchimp-get-campaign` with `title` set to the campaign title. If nothing matches, retry with `title.contains`. If more than one campaign matches, list them with title, send-date and status, and stop. If the campaign's status is not `sent`, say it has not been sent yet and stop. Keep its campaign-id, list-name and send-date.
**Step 2: Read the results**
* Call `mailchimp-get-report` with `campaign-id` for opens, clicks, bounces, unsubscribes, abuse reports and total revenue.
* Call `mailchimp-get-campaign-click` with `campaign-id` to see which links drew the clicks.
* Call `mailchimp-get-campaign-recipient` with `campaign-id` and `status` set to `hard`, then again with `soft`, to see who bounced.
* Call `mailchimp-get-campaign-unsubscribe` with `campaign-id` and group the unsubscribe reasons.
**Step 3: Build the baseline**
Call `mailchimp-get-report` with `list-name` set to the campaign's list and `send-date.to` set to the day before this campaign's send-date. Take the most recent campaigns up to the compare count, and average their open rate, click rate, hard bounce rate (hard-bounces / emails-sent) and unsubscribe rate (unsubscribed / emails-sent).
**Step 4: Report**
* A one-line verdict: better than, in line with, or worse than recent campaigns.
* A table with one row per metric (emails sent, open rate, click rate, hard bounce rate, soft bounces, unsubscribe rate, abuse reports, revenue) and columns for this campaign, the recent average and the difference.
* The top 5 links by unique clicks.
* Unsubscribe reasons, grouped, with counts.
* 2 to 4 observations, each tied to a number above.
**Rules & Guidelines:**
* Read only. Do not call `mailchimp-add-list-member`, `mailchimp-update-list-member`, `mailchimp-add-segment-member`, `mailchimp-add-customer`, `mailchimp-update-customer`, `mailchimp-update-product`, `mailchimp-update-order`, `mailchimp-replicate-campaign`, `mailchimp-start-automation` or `mailchimp-pause-automation`.
* Rates are returned as fractions (0.25 means 25%). Show them as percentages.
* Treat any abuse report, a hard bounce rate above 2%, or an unsubscribe rate above 0.5% as worth calling out on its own, whatever the other numbers say.
* Show at most 5 individual email addresses from the bounce and unsubscribe lists unless the user asks for more.
**Validation:**
* If there are no earlier campaigns to the same list, report this campaign alone and say there is no baseline.
* If `mailchimp-get-report` returns nothing for a sent campaign, say the report is not available yet and stop.Who it's for
One answer, three teams that use it
Email marketers
Judge a send against your norm
See every metric against your recent baseline instead of guessing whether a rate is good.
How did our Mailchimp Black Friday campaign compare with our last 8 sends?
Content managers
See which links people chose
The top links show which content drew clicks, to guide the next email.
What were the top links in our Mailchimp November newsletter, and how did clicks compare to usual?
Marketing directors
Spot problems in one read
Abuse reports and high bounce or unsubscribe rates are called out on their own.
Review the Mailchimp Spring Launch campaign and tell me if anything looks wrong.
How it works
What PopdockAI does when you ask
You name a sent campaign, and your AI assistant compares it with your recent sends to the same audience. It only reads.
01
Ask
You name a sent campaign and optionally how many to compare.
02
Read
It reads the report, link clicks, bounces and unsubscribe reasons.
03
Compare
It builds a baseline from recent campaigns to the same audience.
04
Report
You get a verdict, metrics against baseline, top links and observations.
What PopdockAI provides
The tools behind the answer
Ready made tools for Mailchimp and one secure connection to your AI tool. No code, no exports.
mailchimp-get-campaign
mailchimp-get-report
mailchimp-get-campaign-click
mailchimp-get-campaign-recipient
mailchimp-get-campaign-unsubscribe
This report is built from Get data tools only. PopdockAI applies the row, field and parameter rules your admin sets, and every query is written to the audit trail.
The outcome
Know what drove a campaign in a single read
Related use cases
More ways to put this data to work
One prompt template with infinite possibilities.
Your AI assistant adapts its approach, tone, and capabilities to match each unique context while you maintain a single, manageable workflow.
Join forward-thinking companies that are transforming their operations with intelligent, secure AI automation.

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