B2BExecutive agent for founders and leadership

Product-Market Fit Score

Know if your product-market fit is real, and if it will last.

This agent grades your fit against a scorecard you choose, whether that's an AI-era stress test built on what founders and investors look for or Sean Ellis' “how disappointed would your customer be without you” survey. It reads your customer conversations and product usage data, then backs each criterion with hard numbers.

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The problem

Hype can look a lot like product-market fit. Until customers stop coming back.

43%

of failed VC-backed startups cited poor product-market fit as a reason they shut down.

Two-thirds of those fit failures were early-stage companies that never found a market.

Source: CB Insights analysis of 431 VC-backed startups that shut down since 2023 (March 2026)
How it works

Your fit criteria, graded on evidence

Three steps. Pick a scorecard, connect your data, and get a grade on every criterion with the numbers behind it.

Ingest

Your scorecard and the data to grade it

Your scorecard
Help desk
Sales + CS calls
Usage + revenue
Web research
Anything else
Rippit

Analyze

A grade on everything that defines fit, with the proof

One row per criterionAgent adding fields…
CriterionEvidenceWhat moved
Real budget, not experimental62% of revenue in productionUp from 0. Six pilots converted.
Retention curves flatten54% active at month 12Steady. Curves flat since month 7.
Healthy marginsBilling not connectedConnect billing to grade it.
10 of 14 · 3 criteria waiting on data

Act

A read on fit every morning

Morning summaryLeadership, by email

10 of 14, up 2. Real budgets are the weak spot.

Email sent
Scorecard docGoogle Docs or Notion

Every criterion, color-coded, with charts and examples.

Page updated
+ Any connected MCP

Post the score to a leadership Slack channel, or send a red flag to the team that owns it.

See MCP connections →
FAQ

Questions

Which scorecard does it use?

Yours. Upload the criteria you trust, or ask Rippit chat to draft one from what top founders and investors look for, then edit it.

What data does it read?

Customer conversations, from support chats to sales and CS calls, through Rippit’s integrations. Product usage and revenue come through your warehouse, the Ingest API or a CSV. If you already rate conversations for churn risk or product feedback in Rippit, it reuses those ratings. See integrations →

What if we don't have data for a criterion?

It marks it as a gap instead of guessing, leaves it out of the headline score and tells you what to connect, like billing data for margins.

Can we change the criteria?

Yes. Add, drop or reword criteria any time, and the next run grades against the new version. Retention checks use all the history you have, down to month-12 cohorts.

Where do the results go?

A summary email with a link to the full scorecard in Google Docs or Notion. It runs daily by default, or weekly. See MCP connections →

Find out where you stand before your board asks.

Pick a scorecard, connect your data, and get your first read on fit.

Paste in your AI agent

Copy this line into ChatGPT, Claude, Gemini or your coding agent. It takes it from there.

Set me up with rippit.com
Try Rippit free
or request demo