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How to Prepare Revenue Metrics for Due Diligence (Series A-C)

Investors will stress-test your ARR, churn, and cohort data. If your numbers come from a spreadsheet someone manually updates, you'll spend weeks in a data fire drill.

Why Due Diligence Breaks Most Startups' Data

At seed stage, investors trust your word. You say ARR is $500K, they check it roughly matches your bank deposits, and they move on. The bar is low because the bet is on the team, not the metrics.

By Series A, they want receipts.

Here's the typical scenario: You share that ARR is $2.4M in your deck. The investor asks for a cohort breakdown. Your data team pulls the numbers and gets $2.2M from Salesforce. Stripe shows $2.5M in active subscriptions. Your internal spreadsheet says $2.4M because someone manually adjusted for timing.

Now you're spending the next two weeks explaining discrepancies instead of selling your vision.

The Seven Metrics Investors Will Verify

  1. ARR/MRR — Not just the number, but the methodology. Are annual contracts paid monthly included? What about ramped deals? Usage-based components?
  2. Net Revenue Retention (NRR) — By cohort, not just a blended number. They want to see if your earliest customers are still growing.
  3. Gross churn vs. net churn — Gross churn tells you how many customers leave. Net churn accounts for expansion. They'll ask for both.
  4. CAC and payback period — This requires matching spend data to attributed revenue. If marketing and finance use different systems, these won't reconcile.
  5. Cohort revenue curves — Month-over-month revenue by signup cohort. This shows whether customers grow, flatten, or shrink over time.
  6. Contract values vs. recognised revenue — TCV (total contract value), ACV (annual contract value), and recognised revenue are three different numbers. They'll want all three.
  7. Customer count methodology — What counts as a customer? A paying account? A billing entity? A parent company? Different answers give different counts.

The Data Problems That Surface

How to Prepare Before the Process Starts

  1. Pick your source of truth and document it

    Decide: is ARR calculated from Salesforce opportunities, Stripe subscriptions, or your data warehouse? Pick one, document the logic, and make sure it's reproducible.

  2. Reconcile your core systems

    Audit your top 50 customers. Compare what Salesforce says vs. what Stripe says vs. what your warehouse calculates. Fix the discrepancies or document why they exist.

  3. Document your metric definitions

    Create a one-pager that defines each metric, its calculation, its source system, and edge cases. Investors will ask "how do you calculate ARR?" — you need a crisp answer.

  4. Build cohort views in advance

    Don't wait for the data request. Build the cohort analysis now. You should be able to produce NRR by quarterly cohort within 24 hours of being asked.

  5. Create an audit trail

    Every number in your deck should trace back to a query, a system, and a timestamp. If an investor asks "where does this $2.4M come from?" you should be able to show the exact path.

The Due Diligence Data Checklist

Before entering diligence, confirm you can produce each of these within 24 hours:

The Bottom Line

Due diligence doesn't create data problems — it exposes them. The companies that close fastest are the ones that reconciled their numbers before the term sheet, not after.

If you're raising in the next 6-12 months, start the reconciliation now. The cost of delay is weeks of firefighting during your most important sales process.

Eru connects your revenue systems, reconciles the conflicts, and gives you metrics you can defend under diligence.

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