← Back to articles

The 30 Investor Diligence Questions You Will Get. Here Are the Answers.



Why Pre-Building Diligence Answers Closes Rounds Faster

Investor diligence is not an exam you pass or fail. It is a conversation about whether the investor understands your business well enough to commit capital. The founder's job in that conversation is to reduce uncertainty efficiently.

Founders who walk in with pre-built answers to the likely questions move faster, inspire more confidence, and often create the impression of a better business simply because they demonstrate preparation. Here are the 30 questions that appear, in some form, in virtually every VC diligence process.

Category 1: The Market (Questions 1-6)

Q1: What is your TAM, SAM, and SOM?

Best answer: A bottom-up SAM calculation derived from the number of real potential customers times the contract value per customer. Not a top-down TAM from a market research report divided by an assumed share. Q2: Why is this market large enough for venture returns?

Best answer: An explicit path from current size to a $100M+ revenue business, with the market dynamics that make it possible.

Q3: Who are the incumbents and why have they not solved this? Best answer: Specific reasons rooted in their business model constraints (not "they are slow" or "they are not innovative").

Q4: What changes in the market have created this opportunity now? Best answer: A specific recent change (regulatory, technological, behavioural) that makes this possible today but not five years ago. Q5: How do you define your target customer?

Best answer: A specific firmographic and behavioural description, not "SMEs" or "enterprise."

Q6: What are the market adjacencies after you win the core? Best answer: A specific sequence of adjacent markets that logically follow from the core offering, not a theoretical TAM expansion.

Category 2: The Business Model (Questions 7-12)

Q7: How do you make money?

Best answer: The pricing model, who pays, when they pay, and how that scales.

Q8: What is your gross margin and why?

Best answer: The actual figure, what drives it, how it compares to sector benchmarks, and the trajectory.

Q9: What is your CAC by channel?

Best answer: Actual CAC data from real campaigns, broken down by channel, not a blended estimate.

Q10: What is your LTV and how do you calculate it?

Best answer: Monthly ARPU times gross margin divided by monthly churn, with a cohort chart showing retention over time.

Q11: What is your CAC payback period?

Best answer: The actual calculation plus the trend line and what you expect it to do as you scale.

Q12: What does the unit look like at scale?

Best answer: A specific scenario where volume is 10x current and the unit economics per customer at that point.

Category 3: The Model (Questions 13-18)

Q13: What are your key revenue drivers?

Best answer: The 2-3 variables that most directly determine revenue, with current actuals and assumptions for each.

Q14: What assumptions are you least confident in?

Best answer: An honest answer identifying the 1-2 highest-risk assumptions and the evidence that would change them.

Q15: What does conservative look like?

Best answer: A specific scenario at 60-70% of base case with the resulting cash position shown month by month.

Q16: When do you break even?

Best answer: The specific month in the model, the assumptions that determine it, and what changes if those assumptions shift. Q17: How did you size the raise?

Best answer: The specific milestones the capital funds, with each milestone mapped to a line item in the model.

Q18: What are the key milestones this raise funds?

Best answer: 3-5 specific, measurable milestones with the month each is expected to be reached.

Category 4: Traction and Evidence (Questions 19-22)

Q19: What traction do you have?

Best answer: Current revenue or users, growth rate over the last three months, and the most important leading indicator.

Q20: What do your best customers say about the product?

Best answer: Direct quotes or NPS data, plus the pattern in why customers stay.

Q21: What is your churn rate and why do customers leave?

Best answer: The actual monthly or annual churn figure, cohort retention chart, and the two most common reasons for churn.

Q22: What is your NRR (net revenue retention)?

Best answer: The calculation, how it compares to benchmarks for your stage and model, and the trajectory.

Category 5: The Team (Questions 23-26)

Q23: Why are you the team to build this?

Best answer: Specific prior experience that is directly relevant to this problem, not general credentials.

Q24: What are the gaps in the current team?

Best answer: An honest answer with the specific hires planned and the timing.

Q25: How do you divide responsibilities?

Best answer: Clear domains for each founder with minimal overlap, and a specific example of how a recent decision was made.

Q26: Have you worked together before?

Best answer: If yes, what you built together. If no, how you tested the working relationship before committing.

Category 6: The Raise (Questions 27-30)

Q27: What is your raise timeline?

Best answer: A specific target close date, the current state of the process, and who else is in conversations.

Q28: Who else is in the round?

Best answer: An honest answer. If no one yet, say you are building the syndicate. Do not exaggerate existing commitments.

Q29: What are you looking for in an investor beyond capital? Best answer: Specific value-adds you need (sector connections, operating expertise, international expansion) that map to why you are talking to this specific firm.

Q30: What would make you not take our money?

Best answer: A thoughtful answer about stage fit, sector expertise, or partner involvement that demonstrates you have thought about the relationship beyond the check.

Summary

These 30 questions appear in some form in virtually every institutional fundraising process. The founders who close faster are not the ones with the best answers in the room. They are the ones who prepared the answers before arriving. Map every question to your model and your traction data, practice the answers until they are fluent, and flag the two or three where you are genuinely uncertain. Uncertainty with honesty is a strength. Uncertainty with performance is a liability. Use our test your fundraising readiness to put this into practice.

Common Mistakes Founders Make During Fundraising

The most expensive fundraising mistake is starting too late. Most founders begin outreach when they have 3-4 months of runway, which means they are negotiating from a position of desperation rather than strength. The rule of thumb: start fundraising when you have 9-12 months of runway, which gives you time to be selective, build relationships before asking, and walk away from bad terms.

The second most common mistake is treating all investors as interchangeable. A $1M cheque from a generalist angel who does not understand your space is materially less valuable than the same cheque from a domain-expert who can open doors, advise on hiring, and provide credibility with the next round's investors. Spend time mapping which investors have backed comparable companies and who can genuinely add value beyond capital.

Sharing your financial model too early before you understand what narrative it supports is another frequent error. Investors will poke at your assumptions; if you have not stress-tested your own model, you will be caught flat-footed. Run your own sensitivity analysis before sharing. Know which assumptions drive the outcome, which are defensible, and which are genuinely uncertain and why you have chosen your specific estimate.

Finally, many founders fail to maintain competitive tension. Investors move faster when they know others are interested. Running a tight, parallel process meeting multiple investors in the same 4-6 week window is not rude; it is expected professional behaviour. Telling an investor you have other conversations at a similar stage is appropriate; it signals that the opportunity is competitive.

What Investors Are Actually Evaluating

Early-stage investors particularly pre-seed and seed are making a bet on the team before there is sufficient evidence to bet on the business. The three questions they are answering are: can this team build what they say they are building, can they sell it, and can they raise again? Everything in your pitch, your data room, and your financial model feeds these three questions.

At Series A, the emphasis shifts toward evidence of product-market fit and the beginnings of repeatable unit economics. Investors at this stage want to see cohort data showing retention, CAC by channel broken out from blended numbers, NRR above 100% for SaaS, and a clear model for how spending $X in sales and marketing generates $Y in predictable ARR.

Soft signals matter too. Responsiveness, clear communication, and handling difficult questions well all feed into an investor's assessment of whether they want to work with this team for the next 7-10 years. Founders who over-explain, become defensive about their model, or cannot answer basic questions about their own business quickly undermine confidence.

Frequently Asked Questions

How much detail should my financial model include?

Enough to demonstrate that you understand your unit economics and cost structure, but not so much that navigating the model requires a manual. The test: can an investor who has never seen your business understand the key assumptions and how they drive the output within 10 minutes? If yes, the model has the right level of detail. Build the complexity behind the scenes if you need it; present the clarity on the surface.

When should I share my financial model with investors?

Share the model after a first meeting has gone well and there is clear interest. Sending your full model as part of an initial cold outreach buries the key insights in complexity. Lead with the summary metrics (ARR, growth rate, burn, runway, NRR) in the deck; share the full model when an investor asks, which signals real engagement.

How do investors check whether my projections are credible?

They benchmark against comparable companies at your stage, check the internal consistency of your model (does headcount scale sensibly with revenue, do COGS move in the right direction with volume), and stress test the key assumptions. The question they are asking is not "will these exact numbers come true" they know they will not but "does this team think rigorously about their business and understand what drives it?"

What is the biggest red flag in a startup's financials?

Inconsistency between what founders say and what the numbers show. If the pitch says strong retention but the cohort data shows declining NRR; if the growth narrative is compelling but the CAC data shows customer acquisition is getting harder and more expensive; if the gross margin story is software-like but the actual margin is 45% because of significant services delivery these gaps between narrative and data destroy credibility quickly.