SheetDuck QuickCohorts

Who it's for

Product managers and PM-led growth/ops at startups who today copy data into Google Sheets or run one-off queries in BigQuery/Redash/Metabase or ask engineers for CSVs as the substitute.

The problem

Time and opportunity cost: PMs waste hours waiting for engineers or crafting buggy spreadsheet joins; decisions are delayed and experiments mis-specified (time hurt).

How to build it

Single-page web app: OAuth connect to Google Sheets + file upload CSV; ephemeral per-project DuckDB instance in the browser or server; UI shows 5 canned cohort queries with parameter sliders, resulting table, and 1-click shareable permalink + CSV/PNG export.

How it makes money

Freemium: free for single-sheet & 5 queries; $12/mo seat for unlimited sheets, team links, and scheduled refresh; startups pay because it saves 2-6 hours/week per PM (time=$) and is faster than hiring data help — can't use free options because Google Sheets + manual joins fail at scale and self-hosted DuckDB tooling lacks PM-facing UX and sharing features.

Why it doesn't exist yet

Incumbent BI/analytics products are built for data teams, heavy to set up, and revenue-charged at org scale; spreadsheet add-ons are brittle and slow in large CSVs. DuckDB client-side + WASM plus simple canned PM queries are a new technical sweet spot an indie can stitch quickly; incumbents skip it because it’s too low-ARPU and undercuts their enterprise positioning.

First users

Early adopters: PMs at YC/seed startups who currently email CSVs to Slack, growth PMs doing weekly cohort asks, analytics freelancers, product consultants, and meetup/networks (5-minute demos convert) — they get instant answers and shareable links for reporting.

Build size

1-2 people × 8–10 weeks. Includes: OAuth Google Sheets connector, browser DuckDB via WASM + fallback server DuckDB, 5 prebuilt cohort queries (retention, conversion funnel, LTV by cohort, churn curve, active users), shareable permalinks and exports, basic auth/team billing. Excludes: long-term data warehouse connectors (Snowflake/BigQuery) and complex transformation pipelines.

Biggest risk

A major analytics provider (e.g., Metabase/Looker/GrowthBook) ships an identical 'one-click CSV to cohorts' feature or Google adds a first-party Sheets -> exploration UX that removes the need for a tiny PM-focused layer.

Conditions for a hit (all 3 required)

• Given a CSV or Google Sheet with timestamped events and user-id column, produce a 7-,14-,30-day retention table (cohort start on signup) and downloadable CSV within 10s for up to 200k rows.
• Given same input, produce a funnel conversion rate table (step counts, conversion %) and a plotted funnel PNG export within 5s for 50k rows.
• Produce a shareable permalink that reproduces the exact dataset + query parameters and loads the results (table + chart) for another user in under 3s without requiring backend data access; link expires optionally after N days.

How it's judged (in 6 months)

Product Hunt daily top 5 or GitHub 1,000 stars (either qualifies)(judgment date 2027-02-18)

AI self-confidence 55/100 — self-reported likelihood of meeting the criterion, not a business success rate