The Venture Capital Blueprint: Unlocking the Power of Financial Modelling. Part 2. Revenue build-up.
In the first part of Venture Capital Blueprint about financial modelling [link], we delved into the key steps and nuances of financial modelling. However, there’s much more to explore, especially when it comes to revenue modelling.
As is customary in our Venture Capital Blueprint series, you can access an illustrative revenue model template through this [link]. While primarily intended for demonstration purposes, this, coupled with the template from Part 1 [link], can serve as an excellent starting point for developing a robust financial model for your enterprise.
Top-Down Approach
You can approach your sales forecast in two ways. The first one is the “top-down” method, which involves estimating the market size and then assessing our target market share to project revenue.
When to use:
- Idea stage — when there are not enough data and parameters to rely on and build detailed bottom-up projections.
- Any other circumstances when quick, but less accurate estimation is sufficient (e.g., quick validation of another method results).
Top-down projections are usually performed because they’re simple and quick; however, their fundamental weaknesses are (i) low accuracy and (ii) the fact that they are often based on the industry ballpark rather than the company’s individual data, making them a less effective instrument for experimentation, target tracking, and business optimization.
How to employ:
To implement this approach, begin by evaluating the market size. I typically use the TAM — SAM — SOM framework, as shown in the example below, although other approaches can be perfectly viable as well.
- Estimate the total addressable market (TAM), which represents the entire global market for your product or service (e.g., ‘coffee drinkers around the world’).
- Then assess what percentage of the TAM aligns with your product or service, and determine the Serviceable Available Market (SAM) (e.g., ‘coffee drinkers in the UK’ for a UK-based direct-to-consumer coffee company).
- Define the percentage of the Serviceable Market that you intend to target to achieve the Serviceable Obtainable Market (SOM) (e.g., ‘specialty coffee drinkers in the UK between the ages of 20 and 35’).
- (Optional) Apply market growth rates and evaluate trends. When seeking product-market fit, it can be insightful to assess the dynamics of specific market segments and validate your chosen focus using market data (e.g., ‘the specialty coffee segment in the UK is growing x% p.a., which is 2 times faster than the overall coffee market’).
Based on the market size and the share you aim to capture; you will obtain the resulting sales forecast.
Additional notes:
- Although SOM is often considered the target market share, following the example above, I would further narrow the market to a percentage of 20 to 35-year-old specialty coffee drinkers.
- I always recommend calculating the target market through the number of customers. Instead of targeting, for example, 10% of a $100 million market, it’s better to target 10% of 100,000 paying customers (or more likely, 0.1%) and then apply the projected average purchase amount. This approach allows for a sanity check and better understanding of the results.
- Finally, additional adjustments can be made, such as accounting for seasonal upticks, major public events, or changes in legislation that might impact sales. However, since the top-down approach is generally quick and not very accurate, in most cases, these factors will have a minor effect on the result and can often be ignored to keep it simple.
Limitations
Apart from inherent imprecision, another pitfall of this approach is that it might tempt you to forecast sales too optimistically. Often, entrepreneurs calculate the target share by selecting a random percentage of the market without thoroughly assessing whether this target is realistically achievable. Even a small percentage could result in overly optimistic revenue targets.
Bottom-Up Approach
The bottom-up approach is second (though, likely the most widely used) method, offering much better precision and helping to avoid overly optimistic projections. It relies on the fundamental factors driving the business, such as hiring plans, marketing budgets, conversion rates, etc., which are then summarized into the budget.
When to use:
Always if you can 😀 and unless top-down approach is sufficient.
Bottom-up projections are based on multiple assumptions (which should be built on historical data where possible) and require much more time to calculate, all of which early-stage startup would rarely have. However, in most cases, it is worth investing time and effort in this approach because:
- It provides much more accurate and reliable results;
- It illustrates how multiple fundamental parameters work together, allowing you to test and adjust assumptions as you go (more about it in Part 1 of our VC Blueprint about financial modeling [link]);
- Alongside company growth, it helps evaluate performance and set up specific targets for each team (HR, sales, marketing, etc.).
Due to these advantages, I firmly believe that, regardless of the company’s stage (even if it’s pre-revenue), the development of proper bottom-up projections is a must and is crucial for the success of the venture.
How to employ:
General principles, logic, and the approach to projecting expenses are quite similar for the majority of businesses, as described in the previous VC Blueprint article [link], including a template you could use. However, to make this guide comprehensive, we need to delve deeper into ways to project the income side (GMV for marketplaces or Revenues) and supplement the original template with applicable revenue calculations available via this [link].
The choice of the right method often boils down to just two questions: ‘how do we attract and retain customers?’ and ‘what is our monetization model?’. It will work as follows:
1. Direct Sales
If the business is driven by direct sales, which is quite common for B2B businesses, revenue can be projected using assumptions on the ‘capacity’ and ‘effectiveness’ of each salesperson in combination with the hiring plan.
For example, one salesperson can make 10 cold calls a day with a 5% conversion to leads and a 1% conversion from leads to pilot projects. We can further assume (i) lengths of the sales cycle, (ii) not 100% conversion from pilots to paying customers, and (iii) take into account that the salesperson also spends time supporting clients throughout the onboarding.
By understanding these dynamics, we can project the growth of paying clients and determine the resources needed to execute the plan.
2. Digital Acquisition
The same logic applies to a digital marketing-driven business, but instead of a sales budget, we’ll use a marketing budget and parameters such as conversions, CAC (Customer Acquisition Cost), etc., for key acquisition channels.
3. Retention
Projecting retention is one of the trickiest elements. For early-stage companies, it is often sufficient to assume a certain small (and decreasing over time) percentage of the ‘total client base’ to reorder every month. However, for better precision (and if there is enough historical data), it’s better to project retention using cohort analysis.
Alongside the company’s development, cohorts can be further detailed, for example, to separately analyze different types or segments of clients with different consumption habits, which will further improve the accuracy of projections, and the sky is the limit! Also, for marketplaces (our main investment focus), it’s often necessary to develop two separate cohort analyses for the demand and supply sides, while the approach remains the same.
4. Monetization
Finally, by applying the relevant monetization model (subscription, transactional commission, one-off projects, etc.), we will complete revenue projections.
Additional notes:
- Depending on the business particularities, it’s often best to combine the above methods and monetization models to project each business line individually.
For example, B2B marketplaces would often have a classical take rate supplemented with a small portion of SaaS revenue, which is coming from clients with completely different parameters and hence should be modelled separately. - Such model will also be a great instrument to test assumptions (e.g., ‘what if the conversion to leads will be not 5%, but 7%?’), dynamically adjust them to account for the most recent historical data, as well as very granularly understand and monitor key business drivers, blockers, and the performance of key teams or specialists.
- No doubts, the financial model shall be tailored to correctly reflect all features and specifics of the particular business.
- All assumptions and results shall remain consistent across the model.
- Always compare results with the market size (as in the top-down approach), historical data, and available industry data to make sure projections make sense.
As an example: I am a fan of Y Combinator, who often put together guides (e.g., this guide to business models) and publish useful statistics for benchmarking, though there are certainly quite a few other reliable resources which can be of use.
Limitations
The main limitation of the “bottom-up” approach is directly linked to its strength — it is less dependent on external factors (the market) and instead relies mainly on the internal data of the company, hence might be complicated to build for pre-revenue startups.
Nevertheless, I am of the opinion that the development of bottom-up projections is a very helpful exercise even at the business planning (idea) stage. It serves as an invaluable instrument to gain a multitude of strategic insights and thoughtfully plan next steps.
The financial model described in Part 1 of this VC Blueprint (link) and these templates (accessible via link) are exemplary illustrations and function somewhat like a constructor that you can tailor for your purposes, but they are not a plug-and-play template. Please use them with care and remember: the real strength of financial modelling doesn’t solely reside in numerical data but rather in the strategic insights it provides.
