22. Exporting and Sharing Your Analysis
22.4 One-Page Insight Write-Up Template
Why. Files without words get misread. A short write-up answers: what changed, why it might matter, what to do Monday.
What. Use a fixed skeleton so every analyst on the team sounds clear.
How.
Fill the template every share
- Scope — dates, cities, status filter, fictional or live.
- Headline number — one median or GMV, not ten.
- Comparison — vs yesterday / vs other city / vs last week.
- Driver — top city or top SKU hypothesis (careful language).
- Risk — cancel rate, late minutes, data quality issue.
- Ask — decision you need from the manager.
- Links / files — names of CSV / PNG attached.
Worked example A — Filled template (fictional 22 Oct 2026).
Scope: Fictional Blinkit/Amazon Now sample, 22-10-2026, six Maharashtra cities, all statuses in sheet; GMV quotes use Delivered only.
Headline: Delivered GMV ₹1,114 across 7 delivered orders in this tiny sample (classroom scale).
Comparison: Pune leads delivered GMV in the sample; Solapur and Kolhapur follow. Nashik two delivered orders are small baskets (₹95, ₹88).
Driver: One Sambhaji Nagar delivered order at ₹340 lifts that city in the ranking — check whether festival gift SKUs repeated.
Risk: One Pune cancel (₹90) and one Nagpur return (₹150). Do not treat cancel % as stable from n=9.
Ask: Should we pull a full-week extract next for Diwali planning, same grain (order line)?
Files: outputs/city_status.xlsx, figures/city_gmv.png
Worked example B — Bad write-up (avoid).
“Data attached. Looks fine. Pune good.” — no scope, no number, no ask.
Worked example C — WhatsApp short form.
Fictional sample 22-10-2026 | Delivered GMV ₹1,114 (7 orders)
Pune leads in this file | 1 cancel Pune, 1 return Nagpur
PNG + Excel attached | Need full week extract? — Ruhi
Practice task
Rewrite the template for Nashik-only delivered rows. Keep under 90 words. Attach imaginary file names.