Marketing Reports People Actually Read
Turn platform exports into short reports that lead with the answer and survive scrutiny
A taste of a lesson
I asked AI to summarise my CSV and it said leads grew 45 percent. Can I just paste that into the report?
Check it first. Language models can misread columns or do arithmetic wrongly, and a confident 45 percent might be wrong. Calculate the change yourself in the spreadsheet: this month's leads minus last month's, divided by last month's. If it matches, great. Also show the absolute numbers, because 20 to 29 leads reads differently from 2,000 to 2,900. A better habit is to compute first, then give the assistant your results to draft the narrative. Try it: what were your actual lead counts for the two months?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Structure a report that leads with what happened, why and what happens next
- Choose a few decision metrics and give each the context that makes it meaningful
- Use AI to summarise data and draft narrative while verifying every number
- Explain attribution differences and avoid causal claims without evidence
- Produce a one page report template your readers can act on
Lesson plan
- 1 Reports exist to inform decisions Identify your readers and the decisions your report should support. Start
- 2 Lead with the answer Write a short summary that tells readers what happened and what comes next. Start
- 3 Metrics with context Choose a few metrics tied to goals and show them against meaningful comparisons. Start
- 4 AI for summaries, not arithmetic Use AI to draft and spot patterns while keeping calculations verifiable. Start
- 5 Attribution and cause Explain why channels disagree and avoid claiming cause without a test. Start
- 6 Your one page template Build a reusable report template and use it on a real month. Start
Try asking
About this tutor
For marketers, agency account managers and small business owners who produce monthly or campaign reports that get skimmed or ignored. You will learn to start with what happened, why and what you will do next, choose a handful of metrics tied to goals, add the context that makes numbers meaningful, and state caveats honestly. AI helps summarise exports, find anomalies and draft the narrative, while you keep calculations in a spreadsheet and check every figure against the source. The course also covers attribution disagreements and the trap of treating correlation as cause. You leave with a one page report template.
Reviews
4.3
3 ratingsSample
- Esther N.Sample
My director now reads the first five lines and replies with decisions. Leading with the answer was the whole fix. The template took ten minutes to adapt.
- Kenji T.Sample
The attribution lesson explained why our ad platforms claimed more sales than we made. I now state the data source next to each number. Good, practical course.
- Olumide A.Sample
Learned the hard way that AI got a percentage wrong in a client report. The 'compute first, then draft' habit is now non negotiable for me.
About the teacher
Marketing with AI that still sounds like you: research, messaging, content and testing
9 tutors 478 lessons taught Sample
I teach marketers how to use AI for the slow parts of the job without letting it flatten the brand. My background is in content and brand marketing for small and mid sized companies, where budgets were tight and every campaign had to earn its place. I teach by working on your actual material: your audience notes, your last newsletter,...
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