Assuming you’re operating a B2C SaaS startup, numerous forecasting methods may come into play. However, some models, particularly those utilising the following approaches, may fall short when used for fundraising.
- The top-down approach entails estimating the total market size and projecting the percentage of the market captured each year.
- The “Month-over-Month% increase” approach involves setting a baseline and estimating the MoM% rise in revenue.
The issue with these approaches lies in their lack of detail. For instance, a founder might claim to capture 3%, 5%, and then 10% of the market share, but the question remains – how? What resources does it take to get there? What are the key targets he needs to achieve that market share?
A more refined approach involves the “bottom-up” method. It suggests examining the business’s key performance indicators (KPIs) and making certain assumptions to drive the revenue forecast.
Let’s consider a company selling a £50 per month subscription to consumers, acquiring users through social marketing with a Cost Per Acquisition (CPA) of £20 per user and a monthly advertising budget of £4000.
To model this scenario, we start with a “corkscrew calculation”, delineating the opening balance, new users, and closing balance. The closing balance is then rolled over to the next month, and the process repeats. The number of users acquired is calculated by dividing the advertising budget by the CPA, which equals 200 users.
Users acquired= advertising budget ÷ CPA
Monthly recurring revenue (MRR)
Next, we calculate the Monthly Recurring Revenue (MRR) by multiplying the monthly subscription fee by the number of users signed up at the end of each month.
In the above case example, the revenue for the whole year comes to £780,000 on a £48,000 advertising budget – great, isn’t it? However, in reality, some users will unsubscribe over time. This “churn” of users needs to factor into our model. Suppose we start with 200 users in January and only 180 remain by December – we have a churn of 20 users.
With all other assumptions staying unchanged, we have 2180 users left in Dec, and our annual Revenue falls by £66,000.
Churn rate %
To calculate our monthly churn rate, we use the following formula
Churn rate % = No. of lost users ÷ Beginning of month users
- In month 2, we lost 20 out of the original 200 users in Jan. That’s a 10% churn rate.
- In month 3, we started with 380 users, and we still only lost 20 users, so the churn rate has improved to 5.3%.
- In month 12, the churn rate is only 1% because we lose 20 users out of the 2000 users!
Putting all together
Now that we’ve seen how each part plays out, let’s connect them, but this time, we make an assumption on a 5% monthly churn rate
The revenue for the entire year is now £653,200, a drop from £780,000 without churn.
Wrapping up: Why/How is this useful?
Let’s look at the objective of this exercise – taking the key performance indicators in the business and making certain assumptions to drive the revenue forecast.
Through this model, the founder explains that
- Marketing budget of £4000 p.m is a key use of funds and the reason for fundraising.
- Users churn rate of 5% is a healthy level for the industry; and the founder went on to explain his plans to reduce the churn rate further
- CPA target of £20 indicates a great return considering each user pays £50 for an average lifespan of 20 months, resulting in a £1000 Lifetime Value.
- Monthly subscription fee is £50. The founder explains that this is the basic plan and that his company also offers more premium products and also annual subscription plan which is fantastic for the company’s cash flow
This detailed and tangible model will serve as a more appealing basis for investor discussions than a simplistic focus on 10% month-to-month growth or capturing 10% of the UK market share.
Ivan is a highly accomplished finance expert, raising millions in seed finance as an interim CFO. He has developed 100+ financial models, guiding high-growth startups to secure investments from top-tier VCs, angels, and crowd investors. Before co-founding Inverse, he ran a venture-backed biotech startup and spent 4.5 years as a senior analyst at a leading crowdfunding platform.
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