Part 3: How VCs Evaluate Startups

The most common reason a VC investor will pass is the one they seldom share… they don’t believe in the founder(s).

Why the Question Matters- Investment decisions at the earliest of stages begin and end with the founding team. It is the first gate and many investors will be willing to invest singularly on the strength of a team even in the absence of an idea.

The assessment of founders and their capacity to go from a standing start to building a category defining company is the single most important decision. Here are common traits we look for:

Life’s Work:

• Are these founders doing their life’s work?
• What secret have these founders discovered?
• What drives an insatiable need to solve it?

Talent Magnets:

The team you build is the company you build.

• Can you find and recruit undiscovered talent?
• Is there a cult-like fervour at the heart of this company?
• Is everyone on the team relentlessly resourceful and operate at pace?

Learn It All:

Founders need to rapidly master fresh domains over the course of a scaling journey - they might begin with an earned secret, as a world class technologist - but steadily need to grok sales, marketing, people, culture, the list goes on.

• Do these founders have an insatiable hunger to learn?
• Are they continuously probing for feedback and calibrating what to take a leave?

Product Obsessed:

In an AI-transformed world the best products earn founders the right to explosive growth and the most exciting roadmaps offer a path to category leadership.

Extreme Speed:

The path to a escape velocity relies on speed.

• Do you operate with extreme urgency?
• Do they have a fast learning cycle time?

Venture capital is there to prove, disprove and discover a secret about the world - the faster a founding team can chart a path to these learnings, the more they will compound.

Evidence: Building a shipping product, evidence of short learning loops (how have you changed your strategy?), depth and breadth of customer feedback.

Is now the right moment—and is your market slow-moving or fast-moving?

Can this market support a fund returning outcome?

Why the Question Matters

Right-time entries enjoy tail-winds: lower customer acquisition costs, faster adoption, friendlier regulators.

Mistimed launches burn cash educating a market that isn’t listening yet or one that doesn’t grow into a venture scale outcome.

Bottom-up TAM beats “Gartner says it’s $300B.” Break down customer segments, current pain, and willingness-to-pay.

Avoid: “If we capture 5 % we’re huge.” Instead, explain why you win first customers, then land-and-expand.

Fast Moving Market

Every startup should solve urgent and important problems - motivating rapid adoption with the right product.

Different product markets experience wildly different adoption curves.

Before LLMs lawyers were notoriously bad customers.

Slow moving, decision by committee, technology averse and inept.

However, AI has shifted this - by delivering a clear 10x in value we’ve seen a massive acceleration in adoption.

Evidence of this urgency will shine through first in the ease of customer discovery and second speed of purchase.

Explosive growth relies on a powerful and accelerating customer need 💥

Inflections 👉 Tailwinds

Market inflections drive tailwinds 🏄

• Technology – a concrete capability jump (phone-based GPS → ride-sharing; LLMs → Agentic everything).
• Regulatory – rule changes that unlock latent demand (Medicare’s 2020 tele-health ruling).
• Societal / Adoption – shifts in norms or critical-mass uptake (trust tipping-point enabled Airbnb).

How Investors Analyse Markets

What not to do?

❌ Reference random industry reports

❌ Size your market with reference to spend rather than pricing power

❌ State you only need to win 5% of a massive market

Investors will make both bets. Obviously large enough markets (think about the myriad successful start ups focussed on payroll) — and markets that are too small today powered by tailwinds driving rapid growth.

At a minimum I want to believe in a path to US$200M+ of revenues growing >50% pa. with a non-zero path to $1B of revenue.

Look no further than Surge - growing from $0 - $1B+ in revenue in less than 3 years. They built the right product (RL data provisioning) at the right time (LLM take off) 🛫

This is what makes now such an amazing time to build. AI makes so many fresh customer experiences possible 🚀

Is your product 10 times better than anything else available in market?

Why the Question Matters: Investors back step-changes, not tweaks. A 10× jump in one or several core dimensions (speed, cost, accuracy, delight) cuts through noise, lets you price with margin, and makes copy-cats look second-rate.

While 10 times is a high bar across most categories, Chris Paik’s framework expands on how this can be framed across multiple vectors.

”10X is hard to come by through a single optimisation (i.e. a 10x more delicious apple).

It is typically achieved by a combination of vectors that multiply together (i.e. 5x cheaper, 2x better = 10x). This is the basis for the common saying “cheaper and better.”

10x is Relative

10x is always a market relative to existing products available in market.

• Markets with slow moving and decades old incumbents can be more vulnerable to an inflection.
• Markets with a large number of fresh well funded competitors require a greater degree of re-imagination to cut-through.

The Idea Maze

Walking investors through the idea maze is a powerful skill.

• Document the dead ends. List every past startup, corporate effort, and academic project in your area and the reason each stalled.
• Mark the trapdoors. For every step of your roadmap, identify the biggest risks (regulatory, capital intensity, network effects, etc.) and how you’ll neutralize them.
• Surface the secret. Tie your product to a change in technology, distribution, or culture that only recently unlocked the opportunity (“why now”).
• Tell the story crisply. The maze narrative should be so clear that the listener feels they could guide someone else through it after one conversation.

This demonstrates depth of knowledge and a level of first principles thinking that is rare.

How Investors Pick it Apart

• Benchmark the product against today’s best alternative on a single, legible metric.
• “Pattern-matching” - VCs will meet with many companies in the same category, creating a clearer vision of what is fresh and different.
• Stress-test whether the advantage endures as the market reacts - are their compounding advantages?
• Search for products that provoke a visceral emotional response in the customer

Potential Founder Blind Spots

• Bundle vs. spike: 3–4× better on several axes can beat a single 10× spike.
• Cost curves: hardware or deep tech may only need a smaller edge up front if you can then believe technology can achieve a 10x through economies of scale.

Evidence that Convinces

• Independent benchmark results or side-by-side demos.
• Early customers volunteering NPS scores or case-studies
• Accelerating customer referrals and word of mouth inbound.

Does your product sell itself, or have you engineered a repeatable motion?

Why the Question Matters- Superior distribution routinely beats superior tech. Without a scalable path to market, better products die in obscurity.

Some Distribution Patterns

Category defining businesses require both a product and distribution insights.

• Templates → SEO

Canva for example leveraged pre-designed templates to build a self propelling distribution advantage across SEO. While the product was meaningfully behind Adobe - it was discoverable and immediately valuable to less technically inclined users.

• Turn sharing into onboarding

Links (Figma, Discord) or templates (Canva) double as acquisition.

• Give away the ‘viewer’ experience

So every user becomes a silent evangelist (Figma).

• Friction-free “anyone-can-join” links + generous freemium

Viral adoption inside teams, then across organizations, amplified by app-store and hardware partnerships (Zoom).

How Investors Pick it Apart

• Unit economics: payback period (<12 months), sales-cycle length, gross margin (75%+).
• Growth loops: referrals, network effects, platform integrations.
• Channel depth: if more resource is added will efficiency scale or rapidly diminish?

Potential Founder Blind Spots

• ACV vs education
• High contract values ($100k+) → longer sales cycles and requires buyer education & ROI proof.
• Low contract values / self-serve (<$10k p.a.) → can scale with zero-touch PLG, require no education. ****
• B2B motion should always start as founder-led sales
• Partnerships take twice as long and seldom work as expected.

Evidence that Convinces

• Organic sign-ups outpacing paid.
• Viral coefficient > 1 or referral share of new ARR.

Do you have the right team to drive real product innovation?

Why the question matters: Ideas die in the wrong hands. Early hires hard-wire culture, pace, and technical DNA.

Investors will obsess over the quality of early talent. The founding team’s taste in people. Ability to win them over. And the level of cultural alignment and pace that they have injected in the company from day one.

A common belief is that all of the great early stage start ups are cults in some way - just as you should be excited to work for the founders you invest in, they should be excited to work for the early talent they select.

How Investors Pick it Apart

• Founder-market-fit: personal obsession, earned secret, or unfair access.
• Complementary skill mix—no all-CEO teams.
• Evidence of shipping speed: prototypes and demos, customer feedback

Potential Founder Blind Spots

• Missionaries vs. mercenaries: stock options alone can’t buy passion.
• Diversity of thought beats monoculture brilliance.

Evidence that Convinces

• Demo delivered in weeks, not months.
• References on grit and humility.
• Key talent already working below market cash because they “can’t not do this.”
• Ask yourself this - would you work for their early employees?

Is there a path to a durable advantage in 10–20 years?

Why the question matters- VC pricing bakes in compounding over a decade. An early edge need to translate into durable moats over the medium term.

🏰 Moats- Defensibility at the beginning of an early stage start up is a myth.

My favourite framework for moats is Hamilton Helmer’s Seven Powers:

• Scale Economies

When average unit cost keeps falling as volume rises, a large leader can price or spend in ways a smaller rival simply can’t match without destroying its own economics. Most hardware companies enjoy scale economies at scale. Anything were large cost lines can be amortised across a larger group of users / customers.

• Network Economies

Every new user makes the product or service more valuable for every existing user, creating a self-reinforcing, often winner-take-most flywheel that newcomers struggle to ignite. Social networks. Marketplaces.

• Counter-Positioning

A challenger adopts a superior business model that incumbents could copy only by cannibalising their current profits, so the rulers stay put while the rebel gains ground.

• Switching Costs

Customers face meaningful financial, procedural or emotional costs to move elsewhere, so even an attractive alternative must overcome a built-in “lock-in” penalty. ERPs like SAP or Netsuite. Most systems of record aim to establish switching costs.

• Branding

Allows a company to achieve a higher margin selling a product of the equivalent quality - owing to a perception of identity or status because buyers “just prefer the brand.”

• Cornered Resource

Exclusive or preferential access to something uniquely valuable (a patent, scarce talent, long-term rights, etc.) deprives competitors of the raw material they’d need to imitate the leader’s success.

• Process Power

Proprietary, continuously improving routines or cultures deliver lower costs or superior products, and are so embedded that rivals can’t replicate them quickly even if they see exactly what’s being done.

As you can see very few of these manifest right at the beginning of a startup. Scale economies, network effects and process power occur at scale. Branding emerges as a function of time. Switching costs rely on a breadth of product that cannot be delivered on day one. Cornered resources are brittle until commercialised.

Most every startup attempts their own version of counter-positioning. If you haven’t then do you really have a secret about the world worth pursuing?

Simple advice… the best path to building enduring moats is to become large and enjoy all of the benefits of being large. Simplify the job to delivering the most valuable product features in the shortest period of time. Too much focus on “building” moats too early will distract from delivering customer value - early love and the path to explosive growth.

There are of course ways to thoughtfully build network effects and switching costs into your product - just remember that there is always a flip side. Network effects businesses suffer a cold start problem - can you deliver customer value in the absence of the network. Just as markets or product categories with natural switching costs - will of course have incumbents that enjoy those benefits too.

Winning teams open with a wedge: a pinpoint solution that reshapes one critical task and earns passionate adoption on minimal burn. Speed and focus are non-negotiable at this stage.

A wedge is just act one. Category leaders map a clear journey from that initial toe-hold toward a platform vision. Investors fund progress and momentum; give them a roadmap that stretches far beyond today’s release and convinces them the first step is the gateway to market dominance.

Why This Question Matters: At Blackbird we always ask ourselves the question- “Is the product roadmap spellbinding?”

How Investors Pick it Apart

• Dig into the technology - how much toil and talent is really needed to build the product?
• Plans for moat deepening: is there a path to 👉 data fly-wheels, ecosystem lock-in, standard-setting
• Pricing durability: Should we expect a price appreciation or decline as capability becomes more commoditised
• Sensitivity to margin compression or new entrants.

Potential Founder Blind Spots

• Pure technology advantages decay but transform into economies of scale and process power
• Network effects strengthen over time but fresh technology waves can usurp the value
• Long-term talent pipelines (academia, visas) matter more than people realise.

Evidence that Convinces

• Multi-year contracts or usage-based revenue with retention > 90 %.
• Road-map showing step-function moat upgrades (e.g., proprietary chips in year 3).
• Competitive analyses updated quarterly plus sensitivity tests.