For Email Marketing Specialists ·
What you'll accomplish
You'll have a repeatable process for transforming raw ESP metric exports into polished, client-ready performance summaries — complete with an executive overview, what drove results, what underperformed, and 3 specific recommendations. What used to take 90 minutes now takes 20.
What you'll need
In Klaviyo: Go to Analytics → Campaigns → Export (the download icon). Select your date range and export as CSV. In Mailchimp: Go to Reports → Campaign Reports → Export as CSV. Open the CSV and identify the columns you want to include in the report.
What you should see: A CSV file with one row per campaign, columns for open rate, click rate, revenue (if tracked), unsubscribes, and list size.
Troubleshooting: If revenue attribution isn't in the export, note that separately — it may need to come from Google Analytics or your e-commerce platform.
Don't paste the full CSV — create a clean summary table. In the CSV, filter to the reporting period (e.g., last month) and copy the relevant rows. Or simply type out the key metrics as a list:
March Campaign Stats:
- Campaign 1: "Spring Drop" (Mar 3) — Open: 34.2%, CTR: 2.8%, Revenue: $4,200, Unsub: 0.18%
- Campaign 2: "Bestseller Restock" (Mar 10) — Open: 41.6%, CTR: 4.1%, Revenue: $6,800, Unsub: 0.09%
- Campaign 3: "Member Exclusive" (Mar 17) — Open: 52.3%, CTR: 5.9%, Revenue: $9,100, Unsub: 0.05%
- Campaign 4: "Flash Sale 48hr" (Mar 24) — Open: 38.1%, CTR: 3.2%, Revenue: $5,400, Unsub: 0.22%
Monthly totals: 4 campaigns, 46,000 sends, $25,500 total revenue, avg open 41.5%
Open ChatGPT and start a new conversation. Paste:
I'm an email marketing specialist preparing a monthly performance report for a [brand type] client. Here are my campaign stats for [month]:
[paste your data table]
Write me a client-ready performance report with:
1. Executive summary (3 sentences — what happened overall)
2. What performed well and why (2-3 observations)
3. What underperformed and likely root causes (1-2 observations)
4. 3 specific, actionable recommendations for next month
5. One forward-looking note (seasonal trend, upcoming opportunity)
Tone: professional, data-confident, but accessible to a non-technical client. Avoid jargon. Don't just describe the numbers — explain what they mean.
What you should see: A 4-5 paragraph report draft ready for review.
ChatGPT doesn't know your client's business context, so add:
Edit directly in ChatGPT's output or copy it to Google Docs and edit there.
If you need different formats, follow up with:
1. Full monthly report:
Write a monthly email performance report for a [brand type] client using this data: [paste stats]. Include: executive summary, wins, underperformers, 3 recommendations, and one forward-looking note.
2. Single campaign wrap-up:
This campaign performed: open [%], CTR [%], revenue [$]. Context: [any relevant info]. Write a 3-sentence wrap-up I can add to our internal campaign log.
3. Year-over-year summary:
Compare these two periods: [last year stats] vs [this year stats]. What changed? What explains the difference? Write a brief analysis for a client review meeting.
4. Recommendation memo:
Based on these 3 months of email data: [paste]. Write a 5-point strategic recommendations memo for Q2. Focus on what we should change, not just what's working.