SaaSfit

A SaaS founder opens Stripe and sees that MRR is up.

That should feel reassuring.

But then a few other numbers start telling a different story:

• new customer revenue is slowing;

• most of the growth is coming from existing accounts;

• failed payments are rising;

• churn looks stable, but acquisition is weakening.

Nothing is obviously broken.

The dashboard is not wrong.

But the founder is still left with the hardest question:

What actually deserves my attention now?

That situation is what led me to build SaaSfit.

Most SaaS founders do not lack data. Stripe already shows subscriptions, invoices, customers, payments, refunds, and revenue movement.

What is often missing is a clear explanation of how those signals fit together.

SaaSfit turns Stripe billing data into a prioritized diagnosis:

• what changed;

• what looks risky;

• which issue matters most;

• what to investigate next;

• what not to overreact to.

For example, instead of stopping at:

MRR increased 4%.

SaaSfit may explain:

MRR is still growing, but new customer revenue and new customers are slowing. Growth may be relying too heavily on expansion from existing customers.

That is the difference I am trying to validate: not more analytics, but more confidence about what the evidence means.

I have built an early MVP with sample diagnoses and CSV-based analysis. Direct Stripe connection is still being prepared.

You can review a full sample diagnosis here:

https://saasfit.up.railway.app/reports/scenario_billing_leakage

No signup, Stripe connection, or upload is required.

I would especially value feedback from SaaS founders who use Stripe:

After reading the report, did it make the next area of focus clearer—or did it still feel like another dashboard?

Critical feedback is very welcome.