The pitch meeting went beautifully. The partner leaned forward. They asked thoughtful questions. At the end, they said the magic words: “We’d like to move forward with due diligence.”
For most founders, this feels like the finish line. It’s not. It’s the starting line of a process that kills more deals than bad pitches ever do.
Within 48 hours, you receive a due diligence questionnaire. It’s 47 questions long. Half of them require data you don’t have in the format they want it. Your model, which looked so polished in the meeting, suddenly needs to reconcile with your actual books. Your unit economics, which you quoted confidently from memory, need to be demonstrated in a worksheet. Your cap table, which exists as a rough understanding in your head, needs to be a fully detailed spreadsheet.
I’ve watched deals fall apart at this stage more times than I can count. Not because the business was bad, but because the founder couldn’t produce the supporting evidence fast enough, accurately enough, or in a format that gave the investor confidence.
One of my co-founders, Lisa Hirschbeck, has written a high-level overview of how to prepare for financial due diligence as a founder on the blog previously. Today, I'm covering the areas where due diligence most commonly destroys deals, and how to prepare for each.
The Financial Reconciliation Test
This is the first thing most investors check, and it’s the one that catches founders off guard most often. The test is simple: do the historical numbers in your financial model match your actual financial statements?
It sounds obvious, but in practice, the model and the books almost always diverge. The model was built three months ago and hasn’t been updated with actuals. Revenue recognition in the model doesn’t match the accounting treatment. Expenses are categorised differently. The model uses calendar months while the books use a different fiscal year.
When an investor finds a discrepancy between your model and your books, they don’t know if it’s a harmless timing difference or a sign that the model is fundamentally disconnected from reality. Either way, it erodes trust. And once trust is lost in due diligence, it’s almost impossible to recover.
The fix: before starting any fundraise, ensure your model’s historical period ties to your financial statements exactly. Every dollar of revenue, every line of expense, every cash balance. If there are legitimate differences (like accrual adjustments), document them with a clear reconciliation note. The goal is to make the investor’s job easy. If they have to work to verify your numbers, they’ll assume the worst.
Unit Economics Deep Dive
In the pitch, you mentioned that your LTV:CAC ratio is 5:1. In due diligence, the investor wants to see the calculation. Not a summary — the actual workings.
This means showing:
LTV calculation: Average revenue per customer, by period. Churn rate, by cohort if possible. Gross margin applied to revenue. The resulting lifetime value, shown as a range if your dataset is small.
CAC calculation: Total acquisition costs by channel. Customer counts by channel. Blended and channel-specific CAC. Fully loaded (including founder time).
Payback period: How many months until a customer’s cumulative gross margin covers their acquisition cost. Shown monthly, not just as a single number.
Cohort retention: How each monthly cohort retains over time. Are retention curves flattening (good) or continuing to decline (concerning)?
The investors asking these questions are looking for two things: whether the numbers are real, and whether the founder understands them deeply enough to improve them. A founder who can walk through their cohort retention curves and explain what’s driving month-over-month changes signals operational sophistication. A founder who says “I’ll get back to you” signals that the numbers are decorative.
Revenue Quality Analysis
Not all revenue is created equal, and sophisticated investors will dig into the quality of yours. The key questions:
Customer concentration: What percentage of your revenue comes from your top 3 customers? If the answer is more than 30–40%, investors will worry about the risk of a single customer churning and taking a material portion of revenue with them.
Contract structure: Are customers on monthly contracts (easy to churn) or annual (more committed)? Is there auto-renewal? What are the cancellation terms?
Revenue recognition: Are you recognising revenue upfront from annual contracts or spreading it monthly? This matters because it affects both your P&L presentation and your cash flow.
Expansion vs new: What portion of your growth comes from existing customers expanding versus new customer acquisition? High net revenue retention (120%+ is excellent) suggests product-market fit and pricing power.
Burn Rate and Runway
Investors will dissect your spending to understand whether your burn is productive or unproductive. Productive burn drives growth: sales hires that generate pipeline, engineering that ships product, marketing that acquires customers. Unproductive burn is overhead that doesn’t contribute to key metrics: excess office space, over-staffed back-office functions, tools and subscriptions that nobody uses.
The specific metrics they’ll calculate: gross burn (total monthly spending), net burn (spending minus revenue), burn multiple (how much you’re spending to generate each dollar of new ARR), and implied runway (cash on hand divided by net burn). If your burn multiple is above 3x, expect hard questions about capital efficiency. Below 1.5x is excellent.
The “What Happens If” Series
Some of the most revealing due diligence questions are hypothetical:
What happens if your largest customer churns?
What happens if fundraising takes 6 months longer than expected?
What happens if a well-funded competitor enters your space?
What happens if your key technical hire leaves?
These aren’t trick questions. They’re testing whether you’ve thought about resilience. Founders who can pull up a scenario model and show the impact of each scenario — and the contingency plans they’d activate — demonstrate maturity. Founders who freeze demonstrate that they’ve only considered the happy path.
Cap Table and Dilution
This is the area founders most often leave underprepared. Investors will ask about your current ownership structure, option pool allocation, previous round terms and preferences, and how the proposed round affects everyone’s ownership.
A clean, detailed cap table isn’t optional at this stage. It should show every class of shares, every option grant with vesting schedule, every convertible note or SAFE with its conversion terms, and the pro forma impact of the proposed round including any option pool refresh.
If your cap table is a rough calculation in a spreadsheet that hasn’t been updated in months, you’re not ready for due diligence.
The Due Diligence Readiness Checklist
Before entering any fundraising process, work through this self-assessment:
Does my model’s historical period match my actual financial statements exactly?
Can I produce a detailed unit economics worksheet within 24 hours?
Do I have cohort retention data that’s current?
Can I show my burn rate is productive and my runway is realistic?
Do I have scenario models for key risks?
Is my cap table complete and up to date?
Can I reconcile any number in my model to a source document?
If you can’t answer yes to each of these, you’re not ready to start due diligence. And starting a fundraise only to stall in due diligence is far more damaging than waiting an extra month to get your house in order.
Radley Finance generates several due diligence-ready supporting assets alongside your actual model: an assumptions deck, a demo script, an investor Q&A prep guide that anticipates the exact questions in this blog, and a sanity report.
The entire process takes about an hour from first question to finished outputs. When the due diligence questions arrive from potential investors, you’re not scrambling — your answers are already prepared.
Get prepared for due diligence with Radley Finance
This post is the third installment in a series on fundraising and investment for founders. So far we've covered the 7 key assumptions VCs attack first, and how to build revenue projections that survive investor scrutiny. Up next, we'll be covering the potential risks associated with DIY financial models.
