Here’s a scene that plays out every week in investor meetings around the world.
A founder walks in with a polished deck and a meticulously formatted financial model. The slides are sharp. The narrative is compelling. The product demo landed well. Then the investor flips to the assumptions tab. Within 90 seconds, they’ve identified three numbers that don’t hold up. The questions that follow aren’t about the product anymore. They’re about whether the founder understands their own business.
The meeting isn’t formally over, but the outcome was decided the moment those assumptions fell apart.
This happens because most founders build financial models to tell a story they want to believe, rather than a story they can defend. The ambition is fine. The problem is that the model doesn’t show the mechanics behind the ambition, and experienced investors can spot the gaps immediately.
After 30 years of building, reviewing, and stress-testing financial models across IPOs, PE exits, and trade sales in over 20 jurisdictions, I’ve seen the same seven assumptions get attacked first. Every time. Here they are, and here’s how to fix them before you walk into the room.
1. Revenue Growth Rate
This is the assumption that kills more meetings than any other. The typical founder approach goes something like: “We’re in a $10 billion market. If we capture just 1% of that, we’ll be doing $100 million in revenue.”
Investors have heard this exact sentence thousands of times. It tells them nothing about how you’ll actually acquire customers, at what cost, through which channels, and at what velocity. It’s top-down reasoning that works backwards from a number you want to hit, not forwards from the reality of how your business actually generates revenue.
What investors want to see instead is a bottoms-up revenue model. This starts with your current pipeline or customer base and builds forward: we have 50 qualified leads this month, converting at 8%, with an average deal size of $15,000. That gives us 4 new customers adding $60,000 in monthly revenue. We’re growing lead volume by 15% month-on-month through paid acquisition and content. Here’s what that looks like over 24 months.
Every number in that chain can be tested, challenged, and defended. That’s what makes it credible.
If your model shows 3–10x annual growth, you need to explain the specific mechanism: which channels, at what conversion rate, supported by what team. If you can’t articulate that chain, your growth rate is a wish, not a projection.
2. Customer Acquisition Cost
Founders consistently underestimate CAC because they calculate it wrong. The typical mistake is dividing marketing spend by new customers. That leaves out founder-led sales time, content creation costs, event sponsorships, trial infrastructure, onboarding support, and the uncomfortable reality that most early customers came through personal networks, not repeatable channels.
True fully-loaded CAC includes every cost associated with acquiring a customer: marketing spend, sales salaries and commissions, tools and infrastructure, content production, and the founder’s own time valued at a reasonable rate. If you spent 40 hours last month in sales meetings, that’s a real cost, and it needs to be in the CAC calculation.
The other common mistake is projecting that CAC will decrease as you scale. Sometimes it does. More often, it increases as you exhaust your warm network and low-hanging fruit, moving into colder audiences through more expensive channels. Investors know this. If your model shows declining CAC without a clear explanation of why, it’s a red flag.
As a rule of thumb, if your CAC payback period is greater than 15 months, investors will question whether your unit economics work at all. If it’s greater than 18 months, you need a very compelling argument about long-term retention to keep them engaged.
3. Churn Assumptions
Churn is the most dangerous assumption in any recurring revenue model because small changes compound into massive differences over time.
A 2% monthly churn rate sounds manageable. Most founders hear “2%” and think “that’s tiny.” But 2% monthly churn means you’re losing roughly 22% of your customer base every year. If you’re acquiring 20 new customers per month but churning 2% of an expanding base, there’s a ceiling on how large your business can grow. At some point, churn eats the same number of customers you’re adding, and growth flatlines.
The difference between 2% monthly churn and 1% monthly churn is enormous over a 3-year projection. At 2%, you lose about half your starting base. At 1%, you retain roughly 70%. On a base of 500 customers with $500 average monthly revenue, that’s a difference of over $500,000 in annual recurring revenue by Year 3.
Investors stress-test churn before anything else because it’s the number that most directly determines whether your business model works at scale. If your model assumes churn will decrease without explaining the specific product changes or customer success investments that will drive that improvement, it won’t survive scrutiny.
Be honest about your churn. If you’ve only been operating for 12 months, say so. Present a range rather than a point estimate. Investors respect intellectual honesty far more than false precision.
4. Hiring Velocity
A common pattern in early-stage models: revenue is projected to grow 5x in Year 2, supported by a hiring plan that adds 20 engineers, 5 salespeople, and 3 customer success managers. The problem is that the model doesn’t connect those hires to specific revenue outcomes.
What does each incremental engineer produce in terms of product capacity? How many customers can each salesperson manage? What’s the ramp time before a new hire is fully productive? If a salesperson takes 6 months to ramp and your model shows them generating full revenue from Month 1, that’s a material error that cascades through your entire projection.
Investors look at the ratio of headcount to revenue. Revenue per employee should increase over time as you achieve economies of scale. If your model shows revenue per employee declining as you hire, that signals an efficiency problem. If it shows revenue per employee increasing dramatically, investors will question whether you’ve accounted for the management overhead, infrastructure costs, and coordination complexity that come with growth.
The fix is straightforward: tie every hire to a specific milestone or capacity constraint. Engineer 11 is needed because the current team is shipping at X velocity and the roadmap requires Y. Salesperson 4 is needed because the existing team is at Z% of capacity. This creates a hiring plan that investors can evaluate against your revenue projections.
5. Gross Margin Trajectory
Early-stage gross margins are almost always misleading, and experienced investors know it.
In the early days, margins can be artificially high because the founder is doing customer success (so there’s no COGS for support), infrastructure is minimal (you’re on the free tier of every cloud service), and you haven’t yet invested in the operational foundations that a real business requires. Alternatively, margins can be artificially low if you’re doing heavy professional services or custom implementations to land early customers.
Either way, your current margins don’t represent where they’ll settle at scale. The investor question is: what will margins look like when you have 500 customers? When you need a real customer success team? When you’re processing real data volumes? When you’ve moved to production infrastructure?
A good financial model shows the margin trajectory explicitly. It accounts for the costs that will increase as you grow (infrastructure, support, compliance) and the economies of scale that will improve margins (amortised development costs, better vendor pricing, operational efficiency). If your model shows flat 80% margins from Year 1 to Year 5, that’s either naive or dishonest. Neither is a good look.
6. Time to Revenue
The gap between product launch and meaningful revenue is almost always longer than founders project. There’s an optimism bias built into every startup: we’ll launch the product, customers will sign up, and revenue will follow immediately.
In practice, several things slow this down. Sales cycles are longer than expected, particularly in B2B where procurement processes, security reviews, and stakeholder alignment add weeks or months. Pilots and proof-of-concept periods mean customers are using the product but not paying. Integration timelines with existing systems create delays. Compliance requirements in regulated industries add entire phases to the sales process.
If your model shows revenue starting 30 days after product launch, investors will ask: based on what? What evidence do you have that customers can evaluate, approve, procure, and implement your product in 30 days?
The fix is to model a conservative ramp-up period based on the actual sales process you’ve observed or researched. If your average sales cycle is 60 days, your model shouldn’t show revenue from a new channel until at least 90 days after that channel is activated. Build in the friction, and your projections will be both more credible and more useful for planning.
7. Cash Runway Assumptions
This is the assumption that reveals whether a founder thinks like an operator or an optimist. Too many models are built around the assumption that everything will go exactly according to plan, which means the projected cash runway takes the company precisely to the next milestone with nothing left over.
Investors see this as reckless. Things never go according to plan. Sales cycles slip. A key hire takes longer to find. A customer churns unexpectedly. An integration breaks. A competitor launches. Any one of these events can burn additional cash, and if you’ve left zero buffer, any deviation from plan becomes an existential threat.
The industry standard is to raise enough capital for 18–24 months of runway, with at least 3 months of operating expenses as a cash buffer beyond your key milestones. If your model shows 14 months of runway after a raise and you’re planning to start your next round at Month 12, investors will question whether you’ve been realistic about timing.
Model your cash with contingency built in. Show that you’ve thought about what happens when things go wrong, not just when they go right. This is the difference between a financial model and a wish list.
The Stress-Test Framework
Before you present to any investor, run your model through these seven questions yourself:
Can I explain the specific mechanism behind my revenue growth rate?
Is my CAC fully loaded, including my own time?
Have I modelled the compounding effect of my churn rate over 36 months?
Is every hire in my plan tied to a specific milestone or capacity constraint?
Does my margin trajectory account for the costs of scaling?
Is my time-to-revenue assumption based on an observed or researched sales cycle?
Do I have at least 3 months of cash buffer beyond my key milestones?
If you can’t defend each assumption with data or a credible logic chain, the investor will find the weakness. Better to find it yourself first.
Radley Finance stress-tests these exact 7 assumptions automatically. The CFO Review module runs 22 analysis rules — including LTV:CAC ratio checks, runway calculations, and revenue-per-employee benchmarks — flagging issues as Critical, Review, or Opportunity before you walk into the room. Combined with the built-in scenario toggle (Conservative/Base/Aggressive), you’ll know where you’re exposed before anyone else does.
Get investor-ready in under an hour with Radley Finance
This post is the first in a series on fundraising and investment for founders. The next installment will look at how to build revenue projections that withstand investor scrutiny.
