If you’ve ever wondered why your startup didn’t get funded — or how to craft a pitch investors actually say yes to — this page is for you.
How Investors Really Decide Which Startups Get Funded
This is your founder-first guide to understanding how venture capital really works behind the scenes. No jargon, no vague advice — just clear insights into how investors make decisions and what it takes to get a “yes.”
Whether you're a first-time founder or seasoned operator prepping for your next round, this resource is built to sharpen your fundraising approach and help you see your startup the way a VC would.
Before you pitch, What VCs Want helps you get clear on what investors actually need to believe.
What You’ll Get From This Page:
- A clear understanding of how venture capital really works — and whether it’s the right path for your startup
- A practical, inside look at how investors assess startups, make decisions, and what signals they’re actually looking for during fundraising
Quick Navigation:
- Is VC Even Right for You?
- What VCs are Looking For
- What VCs Don’t Typically Fund
- The One Question Every VC Asks
- Why VC Feedback Often Conflicts
- 7 Ways VCs Evaluate Startups
- What Traction Really Means
- B2B SaaS
- Consumer
- Frontier Hardware / Deep Tech
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James Palmer
Principal, Blackbird Ventures
I’m James, a Principal at Blackbird Ventures. I invest in the most ambitious Aussie and Kiwi founders - sometimes before the idea has a name - because I believe the boldest companies begin as sparks of obsession. I’ve led our investments into Cotiss, Ivo, Kwetta, Nextwork, Vertus Energy and Watchful and supported our investments into OpenStar and Ternary Kinetics.
I back people who can’t stop thinking about the problems they’re driven to solve, then roll up my sleeves and play a small role in converting those sparks into generational businesses. My job is simple: serve founders, stretch their ambition, and lift the ceiling on what New Zealand can build.
Blackbird shares that ambition. We are an Australia and New Zealand’s largest firm investing in wild hearts with the wildest ideas, right from the beginning, with more than $7 billion under management - including breakout stories like Canva, Halter and Tracksuit. From AI enabled services to space, we bring the weight of at scale capital, a 60-strong team, and a the strongest network of founders excited to share lessons and help one another take on the world.
If you’re building pre-idea, pre-product or pre-anyone-else-believes, this page is your launchpad. Let’s talk about what founders really want, and how we can get you there.
Connect: LinkedIn | Blackbird Ventures
1. Is VC Even Right for You?
VCs are hunting for companies that can grow unreasonably fast, in large accelerating markets, and have a chance at becoming category leaders.
You already know startups are risky; the numbers sharpen that picture. Roughly 70% of VC-backed companies return less than the capital invested. Only 1-2% become billion-dollar category leaders.
Why does VC still make sense? Power-law returns. A single Canva-sized win can repay an entire fund, many times over. Covering scores of write-offs.
Portfolio theory in practice (Example)
- Typical seed fund: $100M, 30 investments.
- Target ownership per deal: 15% initially diluted down to 6%.
- Goal: Each investment could return $300M+ (3× fund) if everything clicks.
Portfolio rank | Exit valuation | Fund’s stake at exit | Cash back to fund |
1 | $3.0 B | 6 % | $180 M |
2 | $1.5 B | 6 % | $90 M |
3 | $750 M | 6 % | $45 M |
4 | $375 M | 6 % | $22.5 M |
5 | $188 M | 6 % | $11.3 M |
Remaining 25 startups | $23 M → $0.006 M | 6 % each | $12 M combined |
Even with two unicorns and a few other strong wins, the blended outcome just clears 3x overall.
That’s why partners insist on “return-the-fund” potential in every pitch.
The scorecard so far
- Starting any tech company is tough.
- Building a unicorn is tougher (≈ 1-2 % odds).
- VCs therefore need every deal to have a chance at fund-returning scale.
Three non-negotiables for VC fit
To give yourself a chance at this outcome - your business needs:
- Transformative product insight—not incremental change.
- Addressable market large enough to clear $1 B revenue.
- Velocity—a credible path to $100 M+ ARR inside ~8 years.
Founder requirements
- Edge: unique insight into the problem.
- Pace: execute faster than incumbents can react.
- Learning curve: scale yourself from pre-seed to public-company CEO.
The foundations of the term venture capital stem from ad-venture capital — this is funding to back bold missions with a low probability but non-zero chance at huge outcomes.
Venture capital isn’t designed to build “just” good businesses — it’s designed to fund rare outliers that can reach billion-dollar outcomes.
That means most startups, even strong and profitable ones, are not a fit for the VC model.
Most startups don’t meet those conditions. And that’s okay.
Venture capital for a very specific kind of company.
It’s not a marker of value, legitimacy, or ambition — many beautiful businesses will be built and achieve success if it’s absence.
What VCs Don’t Typically Fund
Local-only ambition | Few ANZ segments can produce $1 B+ outcomes. Global TAM is mandatory. |
Narrow or declining market | Venture math assumes a credible path to $1 B in revenue—accelerating markets only. See “The One Question Every VC Asks.” |
Fast-follower / clone | Category ownership accrues to the original disrupter; copycats rarely win power-law prizes. |
Unscalable unit economics | To grow from $0 → $100 M+ ARR in < 8 yrs you need margins that improve, not erode, at scale. |
Weak “why-now” | Funds recycle every decade. If the window to dominate isn’t opening soon, partners can’t justify the risk. |
⚠️ Venture capital isn’t validation; it’s a tool for a specific job.
If your company can thrive on profits or smaller capital, that may be the smarter route.
2. The One Question Every VC Asks
Every venture investor is filtering for one thing: “Could this startup return our fund?”
If the answer is no, they’ll likely pass — even if they like you, even if the business is “doing well,” even if the market is interesting.
- The question is about math, not emotion.
- This is why VCs don’t invest in solid businesses. “Good” often isn’t enough.
- They need to believe your company could one day be worth $1B+, and that they’ll own enough of it to drive returns at a fund level.
What Does it Take to Achieve These High Heights?
There are two main markers:
- Size
- Target ≥ $100 M ARR while still compounding at 50 %+.
- For SaaS that can translate to a $1 B+ exit; hardware or deep-tech often need more revenue to hit the same mark.
- Velocity
- Roughly 7–8 years to reach that scale.
- Funds have a 10–12-year life; they need to find an exit at the end of the life of the fund.
Practical takeaway: show a credible model that connects today’s traction to $100M ARR in < 8 years.
What Do VCs Need to Believe to Invest?
👀 VCs don’t need to believe on day one. They are typically looking for a sparkle at the interface between team, market and product, something that is so fresh and different that it could explode in popularity and capture the zeitgeist of the market.
Over time traction, growth and continual reinvention will be the markers of success and keep a company either on OR off the venture path.
But right at the beginning it is about squinting and seeing a path to dominance in an important market.
3. Why VC Feedback Often Conflicts
Feedback from venture capital funds can be disorienting and is often conflicting. This is for two major reasons:
Fund Strategy and Investor Composition
- VC firms differ in approach: some write early cheques, others invest post-product market fit. Some diversify, others concentrate.
- Inside a firm, each partner has their own lens. You need one person to champion you internally.
- Conflicting advice from VCs often reflects these internal differences—not that your startup is wrong.
How to Decode a Fund’s Strategy
- Portfolio scan—sector, stage, geography.
- Public memos/posts—recurring themes and language.
- Ticket & role—do they lead or co-invest?
- Back-channel calls—ask founders where diligence pressure landed.
Fund Size = Fund Strategy
- VCs promise their backers ~3.5× net returns; gross that’s about 5×.
- Because power laws dominate (80 %+ of value in 1-2 holdings), each cheque must aspire to return the fund.
This dictates the scale of company an investor will back:
- For a large fund (e.g. Blackbird), a “fund returner” could mean 10% ownership in a $4B company.
- For a small fund (e.g. Outset), that could be 5% of an $800M outcome.
Bonus: Quickfire Realities
- Do NZ-only outcomes excite VCs?
- Do VCs care about <$500M exits?
Rarely. Exceptions include fintech like Sharesies, Emerge, Debut. Most other sectors need global scale early to hit $1B+ potential.
Yes—those are great outcomes. But for top-tier fund performance, a $50M+ fund needs at least two >$500M exit to hit return targets. For a larger fund the reality is a $500M exit is great but not sufficient to generate world class returns.
4. How VCs Evaluate Startups
VCs aim for fund-returning outcomes—companies capable of $1B+ valuations. That journey begins with you, the founding team.
Founders
Market Size and Slope
Product
Distribution
Team
Durability
Product Roadmap
5: What Traction Really Means
Traction = Proof.
When VCs did into the customer conversations, the revenue, the engagement - they are looking for verifiable external validation of your underlying hypothesis.
Traction looks very different by stage, market and product category. So let’s unpack three core buckets:
- B2B Software / AI Enabled Services
- Consumer tech
- Deep tech
B2B SaaS
Framing: B2B companies should solve an urgent and important need for a well defined persona. The product needs to deliver on a core promise - delivering transformative value to that user.
B2B SaaS Traction to Raise Each Round
Pre-product 👉 | 100+ customer conversations | Your user / persona is excited to spend time with you and discuss their problems - signalling an urgent problem to be solved. For Kiwi companies US cold outbound is the highest value customer discovery. |
Pre-seed 👉 | 3 - 5 design partners | Can you convince 3 -5 representative customers to allocate time and resource in providing feedback and using the product. If you can get them to pay something - that is better.
👀 Waitlist Fugazi: Push hard for customers to pay ASAP. Product feedback in the absence of paying for the product can lead you down the wrong path. |
Seed 👉 | Power users and first paying customers | Ideally for a seed round the product has a wildly happy early cohort of paying customers. Sales are most likely all founder led to keep feedback loops tight. Early renewals (>100% NRR), high engagement and low churn are all good signs here. International revenue > local revenue. |
Series A 👉 | Millions (target US$3M+) in revenue and an early GTM channel ready for scale | To raise a Series A you need strong signals of early product market fit and an early and repeatable sales motion that enables your company to add resource and scale revenues. The path to Series B is all about maintaining explosive growth rates. |
Series B 👉 | Tripled revenue and positioned to scale | Every round from here is about maintaining escape velocity and staying on the venture path - is there clear line of sight to $100M+ in revenue? Are you building a GTM engine with channel diversification fit for scale? Are you building an organisation that can source, win and onboard talent rapidly and at scale?
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⚠️ Disclaimer These markers move with market sentiment and the relative pace of growth in different categories. For many years it was par for the course to stand up a good series A on the back of US$1M of ARR. Those days are over.
AI native companies are redefining how quickly B2B companies can grow. $1M → $10M inside 12 months is increasingly common - often powered by either (1) Bottoms up PLG adoption by individual users; or (2) New category creation and fresh budget lines - opening huge new TAMs with unbound top of funnel.
If you are not building with an AI tailwind at your back beware… the traction bar may feel much higher. See below both the median and upper quartiles ARR for Series A’s have grown quickly over the last 24 months post GPT4.
Resources: First Round - Levels of PMF
- In particular I love the 4 P’s framework. Suggesting the four vectors you can pivot around include (Persona, Problem, Promise and Product).
Consumer
Framing: Generational consumer businesses rely on simple, fresh insights, executed seamlessly. If the idea doesn’t work quickly and express an early and insatiable level of customer demand - it is unlikely to with more resources.
Consumer Traction to Raise Each Round
Pre-product 👉 | 1k+ customer waitlist | • Can you demonstrate pent up demand for your idea? Is there evidence of a clear problem and sharp product insight. This could also be ranking on Product Hunt, an engaged community in discord / slack or a successful Kickstarter campaign.
👀 Disclaimer: For consumer software - it is increasingly rare to see pre-product rounds get done. With the cost of building lower than ever - there is seldom an excuse to have no product in the hands of customers. |
Pre-seed 👉 | 100s of raving fans | Can you build and ship a product that has extreme early user love and adoption? Demonstrates real engagement & low enough churn that we can model viral or paid loops. Early distribution insights and evidence of that users will power distribution without reliance on purely paid acquisition. |
Seed 👉 | Scaling users and early revenue mechanics (maybe) | From a small cohort of raving fans to early signals of organic growth rapid growth - for products with social hooks we would expect to see at least 20% mom user growth. Day 30 retention should stabilise and a core persona will be honed in on.
Organic user growth and retention > revenue at this stage. Especially if there is a social component with real network effects in place. |
Series A 👉 | Accelerating revenue and virality. | If monetised target US$3M+ of ARR if free 10k’s of users with improving DAU/WAU (40%+ is strong here). Early user love is now propelling organic growth and engagement shows a habit is forming around the consumer behaviour. |
🚨 Challenge: Consumer has been a hard place to find venture scale success over the last decade.
BeReal and Clubhouse were each the closest to breakout success within consumer social - experiencing rapid growth and equally rapid deceleration. Funding in consumer has been scarse.
AI is changing this and we have seen a shift in consumer behaviour - particularly in the wildly explosive Open AI customer numbers (>800M MAU). We have equally seen flash in the pan consumer use cases - Character AI being an example.
Actionable Insight: Focus organic growth strategies propelled by your users. Unit economics are notoriously tricky in consumer as you’re working within much lower bands of willingness to pay. Resources: Frameworks - Chris Paik
Frontier Hardware / Deep Tech
Framing: Frontier-hardware startups must kill the technical risk and prove real, demand - simultaneously. Every round maps to a technical de-risking gate and commercial proof-point that together reveal a credible path to category-defining scale.
There is no room for marginal value propositions. Deep tech companies must forge a path to no-brainer customer adoption.
Nuance: Deep tech milestones can be wildly different depending on the ambition of the technical pursuit, the capital profile and the category of customer. It is normal for there to be no revenue or tangible commercial traction ahead of a Series B. So take 👇 with a grain of salt.
#1 Focus: The central focus of a deep tech thesis should be a clear eyed and front loaded focus on technical de-risking - underpinned with a increasingly convincing customer validation and traction — highlighting that IF you succeed in your technical pursuit, rapid revenue growth will follow.
Deep Tech Traction to Raise Each Round
Pre-product 👉 | Core technology thesis | Bench top prototype meets the core spec. 20+ customer conversations gives confidence on the core spec. Early technical proof points provide resolution to the question of what technical milestones prove the path to commercial value. |
Pre-seed 👉 | System prototype in a relevant environment + early intent | Demonstrate a full subsystem at subscale and land 1-3 LOIs or paid development agreements with customers that .
👀 LOI vanity: unpaid “interest” letters with no engineering integration ≠ traction. |
Seed 👉 | First pilots & a manufacturing path | Pilot scale plant proves out commercial yields and first step up in scale. Progress to signed pilot/NRE contracts. Line of sight to dominant unit economics relative to substitutive product.
👀 Burn discipline: Hardware VCs watch the cash-to-learning ratio. |
Series A 👉 | Commercial scale and contracted back book of revenue | Target the first commercial scale unit of production that validates unit economics (ROIC >40%, <24 month payback on plant), achives first revenue and unlocks the path to a strong booked revenue. Supply chain and manufacturing should be maturing through this process with a well defined path to BOM down engineering and strong gross margins > 50%.
👀 Customers first: cap-ex gets funded only when customer demand pulls it. |
Series B 👉 | Commercial scale and contracted back book of revenue | The best hardware businesses radpidly transform from R&D mastery to supply chain and manufacturing excellence.
👀 Unit-cost honesty: glossy volume curves crumble if real COGS isn’t on track. |
Fundraising Masters More
Deep-tech ventures are capital intensive and often monetise later than software peers, so founders must become world-class storytellers and fund-raisers.
Master these muscles and you’ll match the higher funding bar that frontier tech demands—turning bold engineering into a category-defining company.
Your credibility depends on:
- Narrative Arc → Moonshot Impact. Paint a future where solving today’s hard science unlocks a multi-billion-dollar market—and why you will become the monopoly winner.
- Convert the wildly technical → simple clarity. The best deep tech founders can articulate deeply technical topics into non-technical language. Reduce jargon while bringly to life the technical challenges.
- Risk-Reduction per Dollar. Make investors feel every check removes a specific technical or market risk on a defined schedule. Thoughtfully design the capital strategy in line with these gates.
- Cadenced Capital Strategy. Build strong syndicates with investors who have capacity to follow on; hardware timelines are long, so give yourself more contingency, raise 12 months before cash-out.
- Visual Evidence. Hardware is visceral—bring parts, videos, telemetry. Let investors feel the progress.
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Blackbird Ventures
We invest in companies, not rounds. From the very beginning, and at every stage of the journey to come.
Blackbird is a venture capital fund based in Australia and New Zealand. We invest in every type of technology from software to space, unified by the biggest of ambitions.
We have more than 7 billion dollars under management and a portfolio of over 100 companies including some of the most successful Australian and New Zealand startups such as Canva, SafetyCulture and Culture Amp.
Reach out for investment here ⚡
