Traction is proof — but it looks different in SaaS, consumer, and deep tech. Learn what signals matter at each stage and how to show credible momentum.
1. Traction = Proof
When VCs dig 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
2. 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
- Pre-seed 👉 3–5 design partners
- Seed 👉 Power users and first paying customers
- Series A 👉 Millions (target US$3M+) in revenue and an early GTM channel ready for scale
- Series B 👉 Tripled revenue and positioned to scale
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.
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.
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.
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.
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?
⚠️ 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:
- Bottoms-up PLG adoption by individual users
- 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. 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.
3. 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
- Pre-seed 👉 100s of raving fans
- Seed 👉 Scaling users and early revenue mechanics (maybe)
- Series A 👉 Accelerating revenue and virality
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.
Can you build and ship a product that has extreme early user love and adoption? Demonstrates real engagement and low enough churn that we can model viral or paid loops. Early distribution insights and evidence that users will power distribution without reliance on purely paid acquisition.
From a small cohort of raving fans to early signals of organic 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.
If monetised, target US$3M+ of ARR. If free, tens of thousands 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 OpenAI 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 are working within much lower bands of willingness to pay.
Resources: Frameworks — Chris Paik
4. 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 a 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 increasingly convincing customer validation and traction. Highlight 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
- Pre-seed 👉 System prototype in a relevant environment + early intent
- Seed 👉 First pilots & a manufacturing path
- Series A 👉 Commercial scale and contracted back book of revenue
- Series B 👉 Commercial scale and contracted back book of revenue
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.
Demonstrate a full subsystem at subscale and land 1–3 LOIs or paid development agreements with customers.
👀 LOI vanity: Unpaid “interest” letters with no engineering integration ≠ traction.
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.
Target the first commercial-scale unit of production that validates unit economics (ROIC >40%, <24-month payback on plant), achieves 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.
The best hardware businesses rapidly 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 matters more in deep tech.
Deep-tech ventures are capital intensive and often monetise later than software peers, so founders must become world-class storytellers and fund-raisers.
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 bringing 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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