Marketing
AI for marketing reports
Export the numbers from your analytics, ad and email tools into one sheet, then ask an AI tool to summarize what changed, flag anomalies and draft the commentary. You check every figure and add the decisions. AI writes the narrative faster, but it should never be the only source of your numbers.
Effort:
Low
Time saved:
Often half a day saved per monthly report (estimate; test it)
The problem today
Monthly marketing reports take a day of copying numbers between Google Analytics, ad platforms and email tools. By the time they are done, nobody has time to ask what the numbers mean.
How it works, in plain words
It is like an analyst who reads your monthly spreadsheet and writes a first draft of the commentary for you to correct.
What goes in: one standardized sheet or Looker Studio export with your 5 to 8 key metrics, with the same columns and date range every month.
What the AI does: it compares this month with last month and with the same month last year, flags big changes and suggests possible reasons to check.
What a person checks: a person checks every figure against the source sheet and replaces guesses with real explanations and decisions.
What comes out: a short monthly report for the owner or the team, with numbers, commentary and next actions.
It can misread or miscalculate numbers, so it should never be the only source of your figures.
How it could work for businesses like yours
Illustrative examples, not client case studies.
A 12-person digital agency in Marousi
Account managers spend the first days of every month writing client reports. They would set one export template per client and use AI to draft the commentary, which they then edit. They would measure hours per report and how often clients come back with follow-up questions.
A 5-person toy e-shop in Komotini
The owner looks at Google Analytics, Meta and email separately and rarely sees the full picture. He would combine eight metrics in one sheet and ask for a summary of what changed plus three questions to discuss. A first target could be a 30-minute monthly review with the decisions written down.
A 60-person courier company in Aspropyrgos
The commercial team reports new leads and campaign spend to management every month. They would export the same metrics from the CRM and ad tools and use AI for the written summary, checked by the team lead. They would track the time it takes to produce the report and whether decisions are recorded each month.
How to do it, step by step
Choose 5–8 metrics that drive decisions, for example sessions, conversion rate, cost per lead or sale, email clicks and revenue by channel.
Standardize the export. Use the same date range, columns and names every month, ideally in one spreadsheet or a Looker Studio dashboard.
Ask for a structured summary: what went up or down and by how much, possible reasons to check, and three questions for the team.
Verify every number. Compare the AI's figures with the source sheet, because language models can misread or miscalculate tables.
Add the decisions yourself. The value of the report is what you will do next, which the AI cannot know.
Pilot for two reporting cycles and compare time spent and the quality of the team discussion.
Tools to consider
Looker Studio: free dashboards that bring Google Analytics, Google Ads and spreadsheets into one view. Caveat: setup takes time, and non-Google sources may need extra connectors.
ChatGPT (data analysis) or Claude: read exported CSV files and draft commentary and simple charts. Caveat: always cross-check the calculations.
Microsoft 365 Copilot: summarizes Excel data and drafts PowerPoint slides from it. Caveat: it works best with clean tables and needs the right licence.
Data protection and GDPR
Marketing reports should rely on aggregated figures, which carry little GDPR risk. Problems start when exports contain user-level data such as email addresses, IP addresses or customer IDs. Remove these columns before using AI tools, or keep the analysis inside tools covered by a data processing agreement. Check that your analytics setup respects cookie consent choices, because reports built on tracking without consent inherit that problem. Treat the AI summary as a draft, since you are accountable for what goes to management or clients. For unclear cases, check with your DPO.
Mistakes to avoid
Pasting raw exports with customer emails or IDs into a chatbot.
Trusting totals or percentages calculated by the AI without checking the source.
Reporting every metric available instead of the few that drive decisions.