Most founders understand the concept of finding product-market fit.
As a feeling, it’s the moment the “pull” outweighs the “push”.
As data, it shows up as clear ICPs (Ideal Customer Profile), consistent sales-cycle lengths, pricing that’s accepted and standardised, customers successfully using the product as it exists today, and month-on-month growth with a flattened retention curve.
But we all know this, and there’s an event every week on finding PMF. The next question gets far less airtime, yet it’s what often makes the difference between being VC-backable for global growth. It’s also where we see teams diverge in how they talk about it and how they approach it.
How do you build a repeatable go-to-market function after you’ve achieved product-market fit?
The task shifts to building a system that can source and acquire those customers repeatably. We call this a repeatable GTM motion. The more that system takes shape, the more confidence you can have in the business’s growth profile, which is exactly what investors are trying to understand.
repeatable systems + more capital = scale.
We’re GTM and data nerds, so we love this part. We enjoy digging into how founders build a systematic engine, because it’s powerful (and satisfying) to reach the point where you can predict how a business will grow, and intervene early when something starts to drift. The best founders and teams bring a systems-thinking approach here. There’s a reason it’s called an engine: you can tune it.
Below, we introduce what we mean by a repeatable GTM: the two engines inside a GTM system that create and close demand, and the signs you’ve built a systematic GTM engine that’s humming along.
Repeatability
This can be distilled into two main questions.
Does it work without you?
If every deal still requires the founder in the room, whether for credibility, relationships, a specific way of telling the story, or deep industry knowledge, you don’t yet have a repeatable sales motion.
Does another dollar produce a predictable dollar out?
Repeatable implies that if you increased sales and marketing spend, something forecastable would happen down the line. It doesn’t have to be perfectly linear, but it does need to be predictable.
These two questions are the crux of knowing if you’ve got a repeatable GTM motion.
To pass them, you need to understand that a GTM is one system made up of two interconnected machines.
The machines of a repeatable GTM system
The demand machine. Can you reliably create qualified pipeline, and do you know which channels produce it?
The conversion machine. Given qualified pipeline, can people who aren't you, the founder, convert it at a predictable rate?
They look like one system from the outside, but they are completely different problems with completely different fixes. When a founder tells me "sales isn't working", the first job is always to work out which side of the machine is actually broken, because it’s likely they’ve spent most of their time pulling levers on the wrong one.
💡 Plot the two machines against each other and you get four places a company can sit:
Both machines working: you have a repeatable GTM motion. Your focus should be on growing and tuning it.
Conversion machine without a demand machine: capable reps around an empty conveyor belt of prospects. Often misdiagnosed, because it looks like a sales problem and it's actually a strategy problem.
Demand machine without a conversion machine: pipeline arrives, conversion is founder-dependent or erratic. This is the good problem to have, because execution is much easier to fix than demand. You can hire better, coach more and tighten the playbook.
Neither: You’re likely in founder-led sales mode and it’s where most people start but make sure you don’t stay here.
Everything else is detail inside one of the two machines. From here, there are six specific components we look for in a repeatable GTM engine. The first two live in the demand machine, the next two in the conversion machine, and the final two are signs you’ve got a healthy system overall.
Demand Side
Demand engine: can you reliably create qualified pipeline?
The first component is the existence of a demand engine at all: machinery that creates qualified pipeline deliberately, and separately from the people who close it.
What this looks like in practice: named channels with owners and budgets, a clear answer to "where did last quarter's pipeline come from?", and new pipeline that doesn't depend on reps self-generating leads or the founder's personal network.
So we ask one simple question.
If you handed a rep ten qualified opportunities tomorrow, would they close at your historic rate?
If yes, your problem is demand, so stop hiring sellers and go build pipeline machinery.
If no, your problem is sales execution. It could be falling down at onboarding, coaching, process or talent.
Dialability: how would you 2x it?
The second component is whether you can answer the question every investor eventually asks: how would you double your revenue? A good answer should talk about demand levers, which can be divided into three categories.
Linear levers: outbound sales development or performance marketing, classically are linear in the truest sense. A dollar in and a relatively knowable amount out. Double the team or budget and you’ll roughly double the pipeline. Reliable, dialable, but they never compound because you're buying pipeline at a relatively fixed exchange rate. This assumes your product never changes, and you continue to target the same type of customer.
Diminishing returns levers, like search engine marketing (and SEO) including keyword bidding, ad auctions, pay-per-click, tail over as you spend more. There are only so many people searching for your category at any one time. Once you've bought them all, the next dollar buys less than the last.
Compounding levers include organic search, brand awareness, community, ecosystem and they get cheaper over time, which is why everyone wants them. The catch: you can't really buy acceleration in the early stage. Tell your marketing team to double organic demand this quarter and it won't matter whether you hand over fifty grand or a million. The channel moves somewhat on its own clock.
When we diligence a startup we audit the demand machine and ask where do prospects come from? List your demand sources, tag each one as linear, diminishing-returns, or compounding, and look at the mix.
All linear means your growth is bought, not built. All compounding means you might not be able to reliably hit a number. A healthy demand machine has diversity.
🔍 What a legible demand machine looks like: Traild
Traild, from our portfolio, builds accounts payable automation with fraud protection, selling to mid-market manufacturers, distributors and construction businesses.
You can read our investment notes on Traild here where we detail this.
Their demand engine runs through ERP ecosystems, via a hybrid of direct sales and partnerships with ERPs and VARs (Value Added Resellers). The in-house direct motion is systematic and predictable. The team know their funnel maths, have a repeatable way of acquiring leads, and close within a predictable range.
Traild starts direct in a new ecosystem, earning the credibility and trust to build long-term relationships with the VARs and ERPs. These partners already hold relationships with thousands of end customers, so their referrals become a major channel alongside the outbound. As Traild becomes the ecosystem's default solution, inbound builds – and it's the inbound that creates a compounding demand and conversion.
They know exactly who their customer is, how many of them there are, and have a systematic playbook to acquire them that compounds as they penetrate an ecosystem. When we say a company's growth is "easy to underwrite", this is a great example.
Conversion Side
Predictability: how consistently do opportunities move and close?
The third component is whether things move through your funnel in ways you can predict. What we look for is conversion rates becoming more consistent over time. As prospects move from stage to stage, month to month.
Once they are, you can run the maths backwards: start from the growth target, divide through by win rate and average deal size, and you know exactly how much qualified pipeline the demand engine owes you each month. Founders who operate this way set top-of-funnel targets from revenue goals, not vibes.
The sophistication upgrade on funnel maths is weighted pipeline.
The old adage says you need three times pipeline coverage on your number.
But coverage isn't interchangeable, because deals from different sources close at wildly different rates. A prospect generated from a ad word click will convert at a different rate a lead the founder brought in after reconnecting from working together years ago.
At Firmable, an inbound deal is roughly two and a half times more likely to close than an outbound-sourced ones. So three-times coverage built from outbound and three-times built from inbound are completely different when they’re weighted. This means you can weight your pipeline by source-specific win rates to add predictability to your forecast.
Founder independence and sales execution
Can a rep you hired, onboarded and handed an opportunity close it while you’re away? This is sales execution. It encompasses onboarding, coaching, playbooks, process.
These signals sit in the team data: ramp times that are predictable, quota attainment that’s consistent across reps rather than one hero carrying three passengers, and win rates that don’t collapse when the founder leaves the room.
Signs you have a high quality GTM engine
Aim: can you point it at high value customers?
Not every dollar of revenue is the same. We get a lot more comfort when the customers closing look and feel similar, and ideally are the ICP. The evidence we love to see is segmentation as a closed loop: you defined your best-fit customer six months ago, pointed the demand engine at that profile, and the data now shows you winning a fatter share of those deals. Growing concentration in the profile of your customers, not just the count, is what we’re looking for.
Aim also covers revenue quality. The thing to look out for here is experimentation revenue.
This is a relatively recent phenomenon. Everyone feels the pressure to adopt AI. Paul previously wrote about how startups can seize this opportunity here. But because everyone is excited to try AI solutions, a lot of this growth can be defined as experimental revenue.
What this looks like is deals close, pipeline looks solid, dashboards are green. Then pilots fail to convert or customers churn.
The last part of aim is how much space is left in your market. Repeatability varies by segment and by geography. For example, you can be repeatable with mid-market companies in Australia and have nothing that transfers to enterprise, or to the same segment in a different geography. Know where your proven segment ends, and how much TAM sits inside it.
Systems thinking: is a systems thinker driving GTM?
Repeatability in GTM is a spectrum. What we need to get comfortable with is whether the team will get there. The leading indicator that ties everything above together is pattern recognition and systems thinking.
Founders and CRO’s who have it are thoughtful about segments, motions and insights. They talk about their funnel as an engine with levers, and they can tell you which customer profile closes well and what they're doing to find more of them. They know when a section is broken, and have ideas on fixing it.
These leaders can point to repeatability across various models and spreadsheets.
The customer cube. Every customer's MRR, month by month, segmented by customer type. A simple but often insight-rich table that informs much of the evidence across PMF and GTM repeatability. We can see new account acquisition, expansion and churn, and the patterns within them. Here we look for velocity and consistency across target segments.
Funnel data. Top of funnel through to converted opportunities, across channels. First, whether a company can produce this at all is a strong signal they're systems thinkers. Then we read for consistency in volume (or steady growth) and stabilising conversion rates – do the percentages hold month to month, or does every month tell a different story?
Pipeline analytics. Whether a company can take the learnings from its historical funnel conversion patterns and apply them to live pipeline: a data-backed view of what's likely to close, often well ahead of quarter end. This is where we build high conviction in near-term growth pathways.
Sales team performance. Broken down to the individual rep – ramp time, quota attainment, and consistency across the team. If reps ramp in similar patterns and close at similar rates, that's a strong sign the motion is repeatable. One rep smashing target while three miss isn't repeatability.
At Firmable, for example, we know roughly what each SDR delivers in qualified pipeline every month so we can model the demand machine from the bottom up. We also know our closing rates. So when we add SDRs we know the pipe, know the coverage, know the revenue.
Run it on yourself
Do you have a demand engine that's separate from your sales team? Could you say how you'd double it, and which levers you'd pull? Do you know your conversion rates by stage and source, and can you work backwards from a growth target to a top-of-funnel number? Does it close without you? Is the revenue landing with customers your targeting and will they renew? Are you running the whole thing like an interconnected system?
Answer those and your machines will be revving.
