For early stage startups, multi-year financial projections may feel too speculative to be a good use of your time, but there’s no avoiding them. In this article we explore 7 ways to make your projections as solid as possible, maximising your chances of fundraising and improving your decision making.

In the early days of a startup, financial projections seem like fantasy. Vague, imprecise… a total waste of time. So why do we, as founders, find ourselves extending that excel formula over and over again?

Even if we hate doing financial projections, they are useful; they give us insights into the short and long term of our business that we couldn’t figure out otherwise. They allow us to adjust and optimize our strategy in a way that is actually monetarily feasible.

Also, they need to be calculated in order to pitch to investors, arrive at a valuation, and close the deal.

So in the midst of all this uncertainty, how do we make projections, and how do we make sure that they are meaningful? It’s not only investors that need to have faith in your projections, also the founder and management team who will rely on them as a basis for building strategy.

We’ve talked about how to make projections in detail in this article, so here we’ll concentrate on how to make early stage projections reliable, solid and believable in seven main steps:

  1. Make sure you use all of your history
  2. Use industry benchmarks
  3. Use startup stage benchmarks
  4. Have a maximum of two critical variables as questions
  5. Make your model easy to change and stress test
  6. Ask for and listen to feedback
  7. Iterate and be reasonable

Step 1: Make sure you use all your (probably short) history

Everybody starts from here, but it is worth underlining: every bit of information, albeit small, skewed, or imprecise, is better than nothing.

Your initial advertising test, done with a budget of $100. That first sale price, even if the client is an old friend from high school. The number of prospects contacted and that incredibly premature conversion rate. These assumptions can seem small, but they need to be used, or at the very least considered, when creating your bottom up financial projections.

This emphasizes why there is so much focus on testing and iterating for new startup companies: to ensure they get the most solid data on which to build their models. You can’t test and tweak forever, but it’s worth spending the time that you can to test your assumptions.

Step 2: Use industry benchmarks

The viability, investability and valuation of your startup are heavily dependent on growth potential and final profitability margin.

Of course, neither is forecastable with a reliable degree of confidence from the early numbers of a new venture, and that’s where knowing the industry comes in. Even if your project is extremely innovative, it is likely to have some relation to another sector that currently has companies serving the same need. You should try to understand the numbers of these companies. How are they growing, what are their margins? How (and how fast) did they get started?

These are going to be great references for your own startup projections, especially for your net and gross profitability.

e.g. If the average profitability (in terms of gross profit divided by revenue) of the three most similar companies to you is 30%, your projections should take that into account. What does that mean? It means that they should either land in the vicinity of that number (at least in the third or fifth year future year) or have a reason to differ.

For example, a self driving truck delivery company will have higher margins than standard established truck delivery companies, coming from the strong assumption that AIs driving the trucks are cheaper than drivers.

Kevin Gibbon of Ship has a great segment on this in this podcast (all worth a listen).

You can find gross and net profit margins of publicly traded companies here and here.

Step 3: Use startup stage benchmarks

As a startup, your forecasted growth does depend on your business and the industry growth rate, but it is also heavily influenced by your stage of development. Startups have a tendency to grow slowly until they reach Product Market Fit (PMF), and then extremely quickly once there.

The inclination when creating a startup financial model is to blow these numbers through the roof, creating hyper-ambitious expectations and doubt among investors regarding your competence and rationality. To help avoid this, it’s a good idea to check the growth rate of startups that are similar to you, ideally in both stage and industry, but if not at least at the same stage (same funding amount, age, momentum…).

This information can be difficult to find, depending on your industry. If you do find it and would like to share it with other founders, please email us at info at, we’d love to help on this and collect these resources for the future.

e.g. The early growth of companies like Bolt, Monzo and Babylon Health is public information.

Step 4: Have a maximum of two critical variables as questions

Despite all the above, we often come across critical variables that – no matter how knowledgeable we are about the industry – can make or break the whole model. These are things like initial growth rate, main conversion rate, repeated customer rate, or churn.

For these variables, a tiny variation can prove critical. Of course we can rely on an industry average, but averages are (of course) not precise either.

The final trick to tackle this uncertainty is don’t. If you’ve done everything else well, you should have come down to one or two variables that are the most critical and also the most uncertain for now. That’s great, those are probably the next assumptions you should test as thoroughly as you can afford to.

My trick with these variables is: make your best guess, but pitch it and think about it as a question. For example: “We are really not sure about this conversion rate, but we know our company will be sustainable at 1%, great at 1,2% and a real potential unicorn at 1,5%. Our competitors, from what we can see, claim 1,1% but (because of x differentiator) we are confident we can do more. Of course, finding out this number is our number one priority right now and preliminary tests indicate…”

You can’t do this with all variables, but this approach turns the extremely tricky ones into a conversation that is positive, engaging and interesting for you, your team and potential investors. A known unknown being actively explored is better than a blind assumption.

Step 5: Make your model easy to change and stress test

Substance is not everything in financial projections; form and communication matters too. A poorly specified excel with difficult to change (or much much worse: hard coded) assumptions already instills doubt in the reader.

For the vast majority of early stage assumptions, small changes do not lead to meaningfully different projections. The startup still grows at an incredible pace and is very profitable. However, not being able to quickly understand the model and test the difference could lead to a meaningfully different outcome: no investment.

The best way to maximize the robustness of your projections in this case is to have a clear model with easily identifiable and adjustable assumptions that are clearly supported either by a note or by the formula used to calculate them. If you’d like to see a sample of the state of the art, check out our financial projections template, and for more detail, our partner ProjectionHub has templates for all types of businesses.

Step 6: Ask for and listen to feedback

Even if you follow all these steps, nobody expects you to know everything. Use your first investor meetings to understand their objections and incorporate them in future iterations.

The additive feedback that investors (or anyone that agrees to give you feedback) will have can be categorized in two categories:

  • Knowledge
  • Perspective

In the first category, Knowledge, is the feedback coming from the hands-on experience that the person you’re talking to has. This could be something they’ve seen or they learned, either about the industry, startup companies, local insight, fundraising, etc. Try to gather all information and update your projections and strategy accordingly.

Perspective feedback is also extremely valuable. Investors have a different perspective than you, and the same goes for your team. Each is going to read and understand your projections through the lens of their own perspective. An investor might give you the feedback that you are not ambitious enough. This might seem unreasonable, but it’s likely that they just need to see a greater rate of return if they are going to consider investment. Again, incorporate everything you can in your projections, ultimately you are trying to balance the motivating hopes and dreams of every stakeholder with what the company can “realistically” deliver.

Step 7: Iterate and be reasonable

It often happens that, through the process of doing this process diligently and thoroughly, you find your ambition has been rather brutally curtailed. You woke up thinking about $1bln in revenue in 6 months time, and now you suspect it will take much longer.

Don’t be discouraged by this. Unrealistic expectations are the problem, not the numbers. The most successful founders were probably realistic in their projections, and they still saw stronger growth than they thought reasonable or possible. The growth numbers of the fastest growing companies are mind bending… though perhaps not as much as the forecasts that exist only in excel.

Use this knowledge to improve your strategy, your pitch, and your valuation. Better planning will lead to better decisions and, ultimately, to what really matters: a successful company.