The problem

An e-commerce founder spends every Sunday evening assembling numbers from the store back-office, ad platforms and delivery sheets into one report. It takes three hours, arrives late, and nobody reads the raw tables anyway.

The solution, step by step

  1. Connect the data sources to Google Sheets: store orders export, ad spend export, delivery/return log — one tab each, refreshed automatically.
  2. An n8n workflow runs every Monday at 8:30 and consolidates the week: revenue, orders, average basket, top 5 products, return rate, ad cost per order.
  3. Compare each metric to the previous week and to the 4-week average — the deltas matter more than the numbers.
  4. Send the consolidated table to ChatGPT for a five-line commentary in plain language: what improved, what degraded, the one thing to investigate this week.
  5. Update a Looker Studio dashboard for the visual view, and send the commentary plus key numbers to the team channel.
  6. Keep every weekly snapshot in an archive tab — the history becomes your best decision tool.
  7. Result and estimated gains

    • Three hours of Sunday work eliminated every single week.
    • Problems surface 7 days earlier on average: a rising return rate or an expensive campaign is flagged the Monday after.
    • The whole team reads the same numbers, in words everyone understands.