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Build a Stripe-connected finance dashboard with GPT-4 insights and grow it with calculators and blog posts

A solo SaaS builder describes a Stripe-connected MRR and churn dashboard that sends metrics to GPT-4 for plain-language suggestions, and the blog and calculators used to drive early traffic.

ClaimedProduct creationSmall SaaSScriptConnected tools

Evidence: The author reports this. We have not checked it beyond reading the source.

The business problem

A bootstrapped SaaS founder tracking revenue in spreadsheets missed a churn spike that cost 30% of monthly recurring revenue, and existing tools were too expensive.

What was tried

Users connect Stripe through OAuth, and server-side webhooks store subscription events in a table that feeds a materialised MRR view. A function computes MRR, annual plans divided by 12, and the app sends MRR, churn, lifetime value and acquisition cost to GPT-4 to return three suggestions on revenue, churn and cash flow. The stack is Next.js, Supabase, Stripe and LemonSqueezy for payments, and Vercel. After three months the author had published 46 blog posts and 8 interactive calculators targeting SaaS finance keywords.

What was reported (mixed)

The author reports 100+ organic visitors a month growing 20% month over month after three months, a Lighthouse score of 100, and calls the calculators the biggest traffic driver without data. Customer count and revenue are not given.

Limitations

This is a promotional post for the author's own product. The sample SQL is incomplete, example insights may be illustrative, and metric definitions such as lifetime value, acquisition cost and runway are not explained. It does not say whether the product has paying users, whether the lost revenue was recovered, or how data sent to OpenAI is handled. The page does not show a year.

What you need

Next.js and Supabase skills, a Stripe Connect application, an OpenAI key and hosting. Total costs are not stated.

Sources

Source published: unknown. Last reviewed here: October 11, 2026. Spot a mistake? Tell us.

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