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Writing Data Reports That Non-Technical People Actually Read

Published 2026-03-20 \u00b7 4 min read

I've written data reports for executives, clients, and board members. The ones that got read had one thing in common: they answered "so what?" in the first paragraph. The ones that got ignored started with methodology.

The Inverted Pyramid for Data Reports

Journalists use the inverted pyramid: most important information first, details later. Data reports should work the same way:

  1. Executive summary (1 paragraph) — The key finding and its implication. "Revenue grew 15% but customer acquisition cost increased 30%, making each new customer less profitable."
  2. Key metrics (1 page) — 3-5 numbers that matter, with context. Charts, not tables.
  3. Analysis (2-3 pages) — What's driving the numbers? What changed? Why?
  4. Recommendations (1 page) — What should we do about it? Be specific.
  5. Appendix — Methodology, raw data, detailed tables. For the people who want to check your work.

The AI Report Generator structures your data into this format. Input your numbers and context, and it generates a report framework with narrative sections.

Writing for Non-Technical Readers

According to Tableau's communication research, the biggest barrier to data-driven decisions isn't data quality — it's communication. Your stakeholders are smart people who don't speak statistics.

Rules for non-technical writing:

Charts That Belong in Reports

Use the Chart Generator for report visuals. Best chart types for reports:

The Data Pipeline

  1. Clean your data with the Data Cleaning Tool
  2. Explore with the Data Visualizer
  3. Generate charts with the Chart Generator
  4. Structure the report with the Report Generator

As HBR emphasizes, the goal of a data report isn't to show how much data you have. It's to drive a decision. Every sentence should move the reader toward that decision.

Turn your data into reports people actually read.

Try the Report Generator →

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