The 40-Minute Desk Research Window
This is not diligence. It is a plausibility filter. The investor is not trying to build conviction during this phase — they are trying to identify reasons to decline quickly. Understanding what they check, and in what order, is the most practical thing a founder can do before sending a deck.
The four claim categories below account for the majority of first-pass failures. Investors rarely articulate which specific claim failed when they pass — which is why founders often do not know what to fix between pitches.
The Four Claims Investors Check First
Market Size (TAM)
The first number cross-referenced. Investors check whether the TAM figure traces to a credible source and whether it was calculated bottom-up or cited from a press release. Top-down figures from analyst firms are treated as directional at best — bottom-up calculations are significantly more persuasive.
Traction Metrics
MRR, ARR, user counts, or growth rates are verified for internal consistency. A claimed £50k MRR from a 3-person team with no visible job postings and low web traffic fails the plausibility check. Investors triangulate traction claims against headcount, job history, and traffic data before accepting them.
Unit Economics
CAC, LTV, and payback period are checked against industry benchmarks for the described channel. A CAC that is implausibly low for the claimed acquisition strategy — for example, a CAC of £5 via paid social for an enterprise SaaS product — will fail immediately. Investors compare stated unit economics to comparable companies in their portfolio or deal history.
Competitive Landscape
Investors search for direct competitors not mentioned in the deck. A pitch that claims “there are no direct competitors” or omits a well-funded competitor that raised in the last 18 months signals that the founder has not done sufficient market research — or has done it and chosen not to disclose. Either is a reason to pass.
The Databases Investors Use
Desk research follows a predictable sequence. Investors are not conducting forensic analysis — they are using a small set of accessible databases to pressure-test the claims on the page in front of them. The table below covers the primary sources used for each claim type.
| Database | What investors use it for | Accessible to founders? |
|---|---|---|
| Crunchbase | Funding history, comparable deal sizes, competitor funding rounds, founding team history | Yes (free + Pro) |
| PitchBook | Deeper funding data, valuation history, LP-backed investor portfolios, M&A comparables | Expensive; some universities offer access |
| Founding team background verification, headcount plausibility, job posting history as growth proxy | Yes | |
| Companies House (UK) | Filed accounts, SIC code, incorporation date, registered directors, PSC register | Yes (free) |
| SimilarWeb | Web traffic, traffic source breakdown, engagement metrics — used to triangulate traction claims | Yes (free tier limited) |
| Carta / Pulley | Cap table benchmarking, option pool sizing, comparable equity grants at stage | Yes (if you're a Carta customer) |
| Google Scholar / PubMed | Technical and scientific claims — checking whether cited research actually says what the deck says it says | Yes (free) |
| Paid research (Gartner / IBISWorld / Euromonitor) | Cross-referencing TAM and market growth claims against professional analyst data | Expensive; often accessible via library |
Founders have access to most of these databases before pitching. The ones that require paid subscriptions — PitchBook, premium Gartner reports — can often be accessed through university libraries, accelerator programmes, or via relationships with lawyers and accountants who hold institutional subscriptions.
The Three Categories of Deck Failure
Desk research checks whether a claim is plausible. The deeper failures — the ones that surface once an analyst has time to actually open a cited report — cluster into three predictable patterns. In verification work, the most common finding is not a false number but a claim that needs source correction or category recalibration before it can be defended under questioning.
Category miscitation — using a benchmark from the wrong product sub-type. The most common failure. A B2B SaaS retention metric applied from a B2C benchmark report. The numbers look similar; the underlying populations are not comparable. DAU/MAU benchmarks sourced from the wrong product category are the single most frequent version of this.
Recency misalignment — citing data that is more than 18 months old in a fast-moving market. In AI infrastructure, developer tooling, or fintech compliance, a 2022 figure can be actively misleading by 2026.
Source laundering — citing a secondary source (a blog post, a slide deck, a news article) rather than the original research it references. The secondary source may have misquoted, rounded, or recontextualised the data. Analysts trace back to primaries.
Never cite a benchmark from a report published more than 18 months before your raise date. Markets move fast enough that a 2022 figure on SaaS churn is actively misleading in a 2026 investor meeting.
When a named human has already checked everything in a deck and signed the report, the dynamic in the partner meeting shifts. The founder is not defending claims under pressure — they are presenting verified evidence with a documented chain of custody. That shift matters psychologically as much as evidentially: founders who have run this process ahead of time have already confronted the hard questions and strengthened the weak answers, so the investor is not raising something they haven’t considered.
Red Flags That Trigger a Pass Without a Call
Investors rarely explain exactly why they passed. The following red flags are the most common causes of first-pass declines based on reported investor feedback and post-mortem analysis of failed fundraising rounds.
- TAM figure cannot be sourced. The stated market size cites a press release, a news article, or no source at all. When investors search for the underlying data, the number cannot be confirmed. This is one of the most common and avoidable red flags in early-stage decks.
- Traction inconsistent with observable signals. A claimed £80k MRR from a company with 4 LinkedIn employees, minimal web traffic, and no visible customers fails basic plausibility. Investors look for internal consistency — not just impressive numbers.
- Founding team has no verifiable connection to the problem domain. A team building a medical device with no clinical, regulatory, or healthcare operational experience — and no visible advisors with those credentials — fails the team-problem fit check.
- A well-funded direct competitor is not mentioned. Searching the category on Crunchbase returns a company that raised a Series B in the same space 14 months ago. The deck says “no direct competitors.” This signals either incomplete market research or deliberate omission — both are reasons to pass.
- Unit economics imply an implausible CAC. A stated CAC of £12 for a B2B SaaS product sold via enterprise sales cycles fails immediately. Industry benchmarks for comparable channels are well-known to investors. Numbers that are significantly outside those benchmarks require explicit explanation — without one, they signal that the economics have not been stress-tested.
Nine Questions That Surface Late in a Round
The checks above happen before the first call. A second set of questions tends to arrive later, during partner review or legal diligence, when a round is close to closing. Each is easier to answer in the deck than in a follow-up email.
“Where does this market size number come from, and what methodology did they use to arrive at it?” The most commonly asked and most commonly failed question. Top-down percentages (“we are taking 1% of a £4B market”) are the trigger. A bottoms-up model built from segment × conversion × ARPU is the only defensible answer.
“Which benchmark report did this retention figure come from, and does the product category actually match?” Founders pull the nearest-looking benchmark and apply it regardless of category fit. An analyst knows the difference between mobile social, B2B SaaS, and desktop productivity retention curves. The categories look similar on paper; the underlying user behaviour is fundamentally different.
“What churn assumption is this LTV built on, and where did that churn number come from?” LTV is the most reverse-engineered number in any deck. Founders often build it from an industry average rather than actual cohort data. An experienced investor can recognise the median B2B SaaS churn figure being used as a first-principles output.
Q4 — Competitive differentiation: “Have you looked at [named competitor] — they launched three months ago and appear to be in your space?” Any “only” or “first” claim is verified against Crunchbase, ProductHunt, and a targeted operator search within 60 seconds. An unnamed competitor is a question, not a comfort.
Q5 — CAC channel assumption: “What is this CAC based on, and is that channel actually open to you at this stage?” CAC figures built from aspirational channels (national TV, enterprise sales at Y CAC) before you have operated in them are among the most common financial-model failures.
Q6 — Customer evidence quality: “How many paying customers is this NPS score from, and how were they selected?” For example, an NPS score from a handful of customers the founder selected is not a statistically meaningful data point. Investors know this. The question probes whether the sample is representative or self-selected.
Q7 — Regulatory status: “What specific licences or approvals does this require in [jurisdiction], and what is the current status?” Particularly acute in fintech, health, and AI governance. A business that needs regulatory approval it has not yet begun pursuing has a CAC problem it hasn’t noticed yet — the cost of acquisition includes the cost of compliance.
Q8 — Team credential depth: “Has the team done this before, and if not, what replaces that experience?” Not a disqualifier; a prompt for evidence. Domain expertise, domain advisors with real involvement, or direct market experience all answer it. Vague team slides do not.
Q9 — IP ownership: “Is all the intellectual property clean, and do the assignment agreements reflect that?” Late discovery of IP gaps is a closing killer. Any code written by a founder before company incorporation, any contractor without a clear work-for-hire agreement, is a potential liability that surfaces in legal diligence.
What Founders Can Do Before Pitching
The gap between what investors check and what founders verify before pitching is where most first-pass failures occur. The following steps address the most common failure points systematically.
- 1 Source every quantitative claim in the deck to a primary or credible secondary source. If a TAM figure cannot be traced to a credible source, remove it or replace it with a bottom-up calculation that can be shown in two or three steps. Unsourced numbers fail the plausibility check even when they are accurate.
- 2 Run your unit economics through an industry benchmark comparison. Find two or three comparable companies — same stage, same channel, same geography — and check whether your CAC, LTV, and payback period figures are within a defensible range. If they are significantly better than benchmarks, prepare an explicit explanation of why.
- 3 Search Crunchbase for competitors before investors do. Find every company in your space that has raised in the last 24 months. Add the ones you are aware of to the competitive slide. Acknowledge the ones that are well-funded and explain your differentiation specifically. Silence about a well-known competitor is read as either ignorance or evasion.
- 4 Check LinkedIn headcount consistency with your traction claims. If your company’s LinkedIn page shows 5 employees but your deck claims £120k MRR, prepare an explanation for how that revenue is generated with that headcount. Investors will notice the discrepancy — explaining it pre-emptively is better than leaving it as a red flag.
- 5 Run a structured pitch deck verification before the first meeting. ThriveFinity’s Release Assurance applies the same four-stage verification sequence investors use — before you send a deck. Start free with First Signal (one claim, one rebuttal, no payment required) or commission a full Release Assurance Pack (£699₹29,999, named verifier). See also: how we verify pitch deck claims.
❓ Common Questions
How long do investors spend on initial due diligence before a first call?
What databases do investors use to verify startup claims?
What is the first claim investors check in a pitch deck?
What red flags cause investors to pass without a call?
What can founders do to verify their claims before pitching?
How do investors verify traction claims?
What are the most common ways a Series A deck fails under questioning?
What is source laundering in a pitch deck?
Sources
- Docsend — “How Investors Evaluate Startup Decks” (2022). Average deck viewing time, decision patterns, and page-level engagement data from 2.5m+ deck views.
- First Round Capital — “10 Years of Learnings” (2015). Investor decision-making patterns and team evaluation frameworks.
- CB Insights — “What Do Investors Do During Due Diligence?” (2021). Database usage and claim verification practices across 50 VC interviews.
- Companies House — UK corporate registration and filed accounts (free public access at companieshouse.gov.uk).
- Crunchbase — Funding and company data. Crunchbase Pro subscription required for full dataset access.
Put this into practice: Verify your deck’s claims before investors do — ThriveFinity Release Assurance →
