A lightweight semantic layer that sits between Google Sheets and any BI or dashboard tool, letting non-technical HR and ops analysts define metrics once and push them live to Looker Studio, Notion, or

Millions of SMB and ops teams run their business in Sheets but the path to a shareable dashboard is still embarrassingly painful

Built for HR analysts, data teams, and business operations managers who regularly build custom dashboards for company metrics and KPIs..

The angle

Owning the Google Sheets to dashboard handoff that no serious BI vendor bothers to polish because enterprise customers dont use Sheets

“I have an experienced working in ... how it looks like. I also know how to use spreadsheets and excel. Please let me know if I can help you. Hope to hear from y…”

The receipts — real demand

“I have an experienced working in ... how it looks like. I also know how to use spreadsheets and excel. Please let me know if I can help you. Hope to hear from you soon ... Hi! I am Aulia Putri Maharani, and i am currently work as HR Data Analyst, which i usually work with google spreadsheet and also google data studio, i also regularly making dashboard for every data automation that my company ...”

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Full dossier

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Every corroborating quote, the source receipts, and the community echo. One email, no payment.

5 / 10 · idea quality

demand score 6.5 — the receipts are below

Pain 7

Willingness to pay 6

Feasibility 7

Specificity 8

Audience 8

Competition 8

Why this is a gap

Surfaced from a high-intensity complaint with clear willingness to pay and a specific, reachable audience.

The market

HR analysts and ops managers build custom dashboards for KPIs. No search volume data means demand is uncertain; crowded competition (7/10) suggests the market exists but buyers may default to existing tools.

Competition & the opening

Wedge play crowded — win on a narrow angle Moat 3/10 · thin angle Market 6/10 · a real vertical

Category giants · 8/10 vs Cube (cube.dev) — headless semantic layer with Sheets/BI connectors, funded ~$50M+dbt Semantic Layer (MetricFlow) — OSS + hosted, defines metrics once, pushes to any downstream toolLooker (Google) — native LookML semantic layer baked into the BI tool the product targets as a destinationOmni Analytics — semantic layer + BI, Google Sheets sync, non-technical-friendly, Series B fundedMetabase — free/OSS BI with its own metric definitions that reads Google Sheets nativelySupermetrics / Coefficient — Google Sheets data connectors with lightweight metric push to Looker Studio

Google Data Studio, Metabase, Looker, and Sheets-native pivot tables already cover low-code dashboard building. The gap would be seamless Sheets-to-visual with less friction than Data Studio's steep learning curve.

real pricing Looker from $60/user/month; Looker Studio Pro $9/user/month; enterprise starts $66,600/year

What's hard to build

Tight, bidirectional sync with Sheets API and Data Studio APIs while handling real-time updates, permission inheritance, and nested data structures. Feasibility is high-friction (7/10) because API rate limits, schema validation, and maintaining data consistency across platforms are non-trivial.

Why now

Business intelligence democratization is accelerating; self-service dashboard automation bridges the gap between raw data and polished reporting.

How you'd monetize

$49/mo SaaS with usage-based pricing or per-dashboard tiers

A lightweight semantic layer that sits between Google Sheets and any BI or dashboard tool, letting non-technical HR and ops analysts define metrics once and push them live to Looker Studio, Notion, or

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