Turn last week's email numbers into next week's send plan
Turn your email performance data into a specific send schedule that responds to what actually worked last week.
How it works today.
You export last week's email report, scan the open rates, and feel either pleased or worried. The subject lines that bombed sit next to the ones that crushed it, but you never dig into why. You plan next week's sends based on what feels right, not what the numbers tell you.
Your email calendar stays the same week after week. Tuesday newsletter, Thursday promotion, maybe a Friday follow-up if you remember. The data that could reshape your strategy sits in a downloaded CSV that you glance at once and forget.
Before you start.
All of it has to be true, or step one fails in a way that is annoying to debug.
- Access to export campaign performance data from your email platform (opens, clicks, unsubscribes by send)
- A list of your standard email types and their usual send days
- Write access to your email platform's scheduling system or calendar
- Your brand voice guidelines and content themes for reference
The steps.
Export your last 7 days of email performance data
Download the campaign report that shows opens, clicks, and unsubscribes for each send. Most platforms call this 'Campaign Performance' or 'Email Analytics' in the Reports section. Make sure the export includes subject lines, send times, and audience segments if you use them.
Upload the performance data to your analysis agent
Feed the CSV or data export to a generalist agent that can analyze spreadsheets. Check that it can read all columns correctly, especially dates and percentage fields that sometimes import as text.
Paste thisAnalyze this email performance data from last week. Identify the 3 highest and 3 lowest performing emails by open rate. For each, note the subject line, send day, send time, and any patterns in content type or audience segment. Present this as a simple table.
Identify your content themes and usual schedule
List your typical email types (newsletter, product updates, promotions) and when you usually send them. Note any seasonal campaigns or recurring content you plan to continue. This gives the agent context for realistic scheduling suggestions.
Paste thisBased on this performance analysis and my usual email types [list your standard content types and current send schedule], what patterns do you see? Which content types and send times performed best? What should I test or change next week?
Generate next week's send recommendations
Ask for a specific weekly schedule that builds on what worked and tests improvements for what didn't. The agent should suggest actual send days, times, and content approaches based on your data, not generic best practices.
Paste thisCreate a specific email schedule for next week. For each recommended send, include: day and time, content type, suggested subject line approach based on what worked, and one small test to try (timing, audience, or messaging). Keep my usual [X emails per week] frequency but optimize based on the performance data.
Review the recommended schedule against your content capacity
Check if the suggested send times and content types match what you can actually produce. If the agent recommends Tuesday at 6am but you batch-write on Sundays, flag the timing issue. Make sure you have content planned for each suggested slot.
Adjust timing recommendations for your workflow
Modify any suggested send times that don't work with your content creation schedule. The performance data matters, but you need to be able to execute consistently. Note which timing tests you'll try first versus which you'll save for later.
Set up the approved sends in your email platform
Schedule each email you've decided to send using the recommended times and subject line approaches. If your platform doesn't allow scheduling that far ahead, set calendar reminders for the send times. Do not let the agent access your email platform directly.
Create next week's performance tracking plan
Set a reminder to export next week's data on the same day you did this analysis. Note which tests you're running so you can measure if the changes actually improved performance. This creates a weekly feedback loop instead of random schedule adjustments.
What you keep.
Automating the typing does not move the accountability. These stay with a person.
- Deciding which emails actually get sent and when
- Writing and approving all subject lines and email content
- Scheduling sends in your email platform
- Determining your overall email frequency and strategy
Once it works.
The first run is the demo. These are where the time actually comes back.
Run this analysis every Monday morning to turn last week's data into this week's optimized schedule.
Set up automatic data exports from your email platform to feed the analysis without manual downloads.
Expand the analysis to include seasonal trends and subscriber behavior patterns across multiple weeks.
Create template schedules for different performance scenarios so you can quickly adapt when campaigns underperform.
Run this next.
One workflow is a tip. Chained, they are how a week actually changes shape.
The work this replaces.
These are the O*NET work activities this workflow covers, and the categories of tool that address them.
