Ultimate Guide “How to Estimate Demand for Early Stage Startups?”

Ultimate Guide “How to Estimate Demand for Early Stage Startups?”

If you are a founder in the process of creating financial projections for your pre-revenue company for the first time, most likely you have two thoughts.

Thought # 1: “This is hard”, and

Thought # 2: “This is futile because, without any data, I can only guess what my sales would be!”

Well, you are HALF right. It IS hard to estimate demand for a pre-revenue company, precisely because there is no financial history. However, it is NOT futile, because creating your financial plan helps you to evaluate the financial feasibility of your business and to create a blueprint against which you can measure the effectiveness of your strategy.

“Hard” does not mean “impossible”. In this article and the corresponding video , we discuss a simple-to-follow four-step framework you can use to properly formulate revenue assumptions and build proforma revenue projections for your company.

  • Step #1: Create Market Share Goals

To start off, let’s set your objectives properly. You are not guessing what your sales are going to be. You are setting goals for which level of sales you plan to achieve.

In order to formulate those goals, you first need to figure out the percentage of market share of the overall addressable market that you would like to capture in years one through five.

To determine the size of your addressable market, we suggest that you do market research. Remember to consider all customer segments and all revenue streams. Once you calculate the total market size, you can set goals for what percentage of that market you plan to capture as your company evolves.

It is very important to set your market share goals conservatively. A lot of startup founders set their sales goals too high, and as a result lose credibility with investors. However, going to the other extreme and setting your goals too low is just as bad, because this makes your company an unattractive investment. It is crucial to set realistic goals and think through how you will achieve them.

When you figure out your market share goals for each year, you can multiply them by the market size in each year, respectively, to calculate your revenue goals for years one through five.

As you project the market size growth, don’t forget to incorporate the industry growth rate from your market research.

  • Step #2: Set Your Marketing Budget

The size of your marketing budget is a discretionary decision. However, as you ponder how large or small it should be, you must consider your capital constraints because as an early-stage startup, you do not have access to a lot of capital.

  • Step #3: Choose Your Marketing Channels

The next step is to figure out how you are going to allocate your marketing budget amongst different go-to-market strategies, which are your marketing channels, in years one through five. Some channels are paid, such as paid advertising, and some are free, such as TV or podcast interviews.

You should model both free and paid strategies, but only allocate your budget amongst those that require investment.

  • Step #4: Project sales from each channel based on that channel’s conversion rate

Every marketing channel has a conversion rate. To estimate it, you can use your own data or an industry standard. When you apply a conversion rate to your marketing channel, you can calculate the expected demand for that channel over the next five years.

Revenues are calculated by multiplying that demand (quantity) by the price of your product or service.

Lastly, don’t forget to reconcile your results from Step # 4 with your revenue goals in Step #1 to see if your goals are realistic. You might have to adjust your projections or change your marketing mix as necessary to ensure the resulting revenues are in line with your vision.

Financial Modeling Tips

  • What Makes a Great Financial Model?

BTB Go to Market Strategy

  • How to Model BTB Sales Force

BTC Go to Market Strategy – Conversion

  • Conversions from Digital Marketing Strategy

  • Conversions from Influencers

  • Conversions from Social Media Strategy

  • Conversions from Podcasts

  • How to Model Word of Mouth

  • How to Model user Multiplier Effect

BTC Go to Market Strategy – Marketing Budget

  • How to Set a Marketing Budget in Line with Sales Goals

  • How to Select Marketing Channels

Price

  • How to Calculate an Average Price

Customer Acquisition Cost

  • How to Calculate Customer Acquisition Cost

Break- Even Analysis

  • Break-even analysis: What marketing budget produces sales to cover your fixed costs?


Check more financial modeling and strategic finance tips on our YouTube page here

Excel Tricks. How to Model Various Business Scenarios

A financial model is a quantitative representation of the company’s business plan. In a way, it is the company’s brain, demonstrating how its strategic decisions affect different functions and translate into financial results.

For that brain to work properly, we need to correctly create the step by step instructions of what happens with the company as a result of its strategic decisions, or financial model assumptions. The process of creating such assumptions and logic is the expertise of The Startup Station and the crux of our unique methodology.

The final step is the implementation of this logic, and this requires knowledge of Excel.

Read more about four most useful Excel tricks you can use for modeling a variety of business scenarios in our blog here.

  • About Author

Victoria Yampolsky , CFA, is the President and Founder of The Startup Station, a comprehensive resource for modeling and valuing early-stage startups. She evaluates the financial feasibility of business models and specializes in the financial modeling and valuation of pre-revenue companies. She also created a finance curriculum for early-stage founders and launched The Startup Station’s educational program in 2015. Since then, more than 1,000 founders have attended her online and in-person finance classes and learned the basics of financial modeling, valuation, and startup financing.

Previously, Victoria worked for the Deutsche Bank Research Department and performed IT consulting for CapGemini’s Financial Services Division. Victoria holds a Bachelor’s Degree, Cum Laude, in Computer Science, with a minor in Mathematics, from Cornell University and an MBA, with honors, from Columbia Business School. Victoria is also on the Advisory Board of the Computing and Information Science (CIS) Department of Cornell University.

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