The numbers add up. The story doesn't.

The headline metrics are not wrong.

That is what makes this hard.

A company reports LTV/CAC of 12x. Gross revenue retention at 78%. Both numbers are real. Both came from the actual data.

Neither one describes the business the investor is about to fund.

What aggregate metrics hide

An LTV/CAC ratio is a function of two things: how long customers stay, and how much it cost to acquire them.

In the early months of many startups, sales and marketing spend is near zero. The founders were selling. There was no team, no budget, no campaign.

Those early cohorts have almost no CAC. They anchor the ratio.

When you rebuild the ratio cohort by cohort, the picture shifts. The earliest cohorts carry lifetime values built over three or four years at near-zero acquisition cost. The cohorts from the last two quarters, acquired when there was a real S&M function, have CAC that actually reflects the business today.

A 12x aggregate ratio can still be consistent with recent cohorts performing far below the headline.

That gap is not fraud. It is math. But it is not the math the headline implies, and an investor doing cohort-level underwriting will find it.

What retention headlines smooth over

A 78% aggregate gross revenue retention number can be held up by a small number of large, stable customers.

At the same time, logo retention for the two most recent mature cohorts might be 55%. The revenue headline can still read 78% when the customers that remain are large enough.

The logo-retention curves have not flattened. They have not stabilized. The aggregate revenue number looks durable, but the customers the company is currently acquiring are leaving at a different rate than the ones it acquired two years ago.

An investor comparing cohort curves will ask why the recent cohorts look different. A founder who has only looked at the aggregate number will not have an answer ready.

The question that follows

This is not about catching founders in something. Most of the time they know the headline, and they know it is probably held up by the early base. They just have not had a clean way to see the gap precisely, or to prepare for where the conversation goes when someone asks about it.

Levian rebuilds logo retention and lifetime value by cohort from your transaction history, then reads them alongside aggregate revenue retention and your financials to show where headline metrics and underlying data diverge.

Not to manufacture a problem. To show you exactly where the question is coming from before it gets asked.