How to Build a Killer Startup Sales Forecast?
By Lior Ronen (@Lior_Ronen) | Founder, Finro Financial Consulting
Every founder has been there.
They want to get a bank loan, and they've asked for their startup's sales forecast.
Founders want to raise funds, need to show potential investors their sales forecast for the next three years.
Or use it internally for cash flow management or support the internal decision-making process.
Either way, you cannot avoid building a (hopefully) accurate sales projections.
But there are so many elements to crunch into the revenue projections, where should you start from?
First, we'll see what sales forecasting methods exist and which one YOU should use.
Then, we'll look into the different elements that impact the sales forecast.
And last, we'll discuss how to align the sales forecast to your business plan and growth expectations.
Before We Start
Before we dive into the world of sales forecasting, we need to lay down the foundations for the topic.
Every business, no matter whether that's a SaaS startup in San Franciso, financial services firm in New York, or a lawnmower business in Long Island, Every business, has only two components that impact its revenues: sales volume (or quantity) and pricing.
That might not sound very sexy, but these are the only two components that impact a business' revenues.
Every other element is either a derivative, driver or part of these components.
Every business’ sales include only two components
What Is A Sales Forecast?
A sales forecast is the business's estimated plan for future sales that considers its sales volume, client growth, conversation rate if there is a free price tier, churn rate, gross prices, discounts, and more.
There are a few methods and approaches for estimating every aspect of a startup financial model.
Sales forecasting is no different. There are two main approaches: top-down forecast and bottom-up forecast.
Top-Down Sales Forecast
This approach is also known as the TAM / SAM / SOM model and allows you to estimate your future sales from the macro level.
In this approach, you start from the Total Addressable Market (TAM) level at the top and slowly drill down to the company level.
This method could be useful for small businesses with an e-commerce retail sales component or have a direct-to-consumer sales model. Alternatively, it could be used to verify from the macro-level the sales forecast a startup built in the bottom-up method.
First, you need to assess the TAM's overall size, whether in dollar terms or volume of products sold. In theory, you need to aggregate the sales figures or sales volume of all companies in the space in the last year, but in real life, you can just use the market leaders' figures and extrapolate it to the overall TAM.
Building a top-down sales forecast
Then, we drill down one level down to the Serviceable Addressable Market ('SAM'). At this level, we estimate what percentage of that TAM is directly competing with your product or service specifically. One educated guess could use the market leader's relevant revenue to the segment as the SAM assumption.
The last level is the Serviceable Obtainable Market ('SOM'), your business market share out of the SAM. This should be in percentage terms.
Multiply the sales volume by the average unit sales price in the market to get a dollar amount.
The annual revenues can increase year over year in this model and There are two ways to do it.
The first one is by increasing the estimated market share that the business will obtain each year.
The second one is or by the natural increase of the niche/market or a mix of the two.
Bottom-Up Sales Forecast
This approach looks at the revenue forecast from the micro-level.
First, you need to think of how you generate revenues. You have a startup that sells software in a subscription model and one-off training sessions relevant to the software.
So you have two revenue sources: subscriptions and services.
You need to estimate the sales volume and pricing for every revenue stream every month in the next few years. I suggest building different assumptions and calculation sections for every revenue stream.
Subscriptions-Based Revenue Model
6 steps of building a sales forecast for a subscription-based business
Step 1: Building the Free Accounts User Base
In a subscription-based or SaaS business, the company sells licenses to users at a few price points. So, we need to mimic the customer acquisition and sales process in our forecasting model.
Let's say a SaaS startup advertise heavily on social media and offer a free license to new users.
Let’s assume it’s a classic freemium revenue model.
It attracts new users to use the service for free and convince them later to sign up for a premium plan.
There are two common ways to execute a freemium model.
The first one, is offering a full access for free for the first year or first month followed by a discounted price for the next months or the next year.
The second one is offering a free tier with limited features that allows you to upgrade to a premium account to open additional features.
No matter which freemium strategy your choose, you need to capture in your forecast these three essential elements to understand how many users you will have in your free tier:
1. Number of potential clients that will see your ads on social media.
2. Click-through-rate (CTR): how many people will click on your ad.
3. Sign-ups: how many people that saw your ad, clicked it, will sign up for the free plan or trial.
You need to repeat this calculation for every month or year in your forecast, using reasonable assumptions.
Step 2: Building the Premium Accounts User Base
Since the freemium model uses the free price plan to attract premium users, you need to add a conversation rate assumption to estimate how many free users will upgrade to a premium account and become paying customers.
I would suggest breaking the subscriptions forecast to free, single-user accounts and multi-user accounts.
The conversion from free to premium is a different single-user account plan to an enterprise or corporate account with multiple users and more complex internal procurement processes.
Single-user accounts: you can either look at the historical data if you have any or if you have no past sales, you can use an assumption relevant to your industry or niche.
Multi-user accounts: you can consider all the accounts in a trial as your sales pipeline, which falls under your sales team's responsibility. Then, by looking at the historical sales, every sales rep succeeded in closing in a specific time period.
At the end of this exercise, you need to have a clear conversion rate of single-user accounts from free to premium and estimate the number of multi-user accounts that will convert every month.
Step 3: Combining the Free Users and Conversion Rates
We set two of our forecast's primary foundations: the free accounts are the foundations of the user base forecast, and the premium accounts are the foundations of the revenue model.
The next step in our forecasting process is to combine the two by applying the conversion rates we came up with in step 2 on the user base we built in step 1.
We need to apply the growth rates that we expect to see on the user base forecast we have so far.
Growth rates can either be used as manual inputs in future years to grow the user base or an output calculation after we put together the user base forecast as described above.
Anyway, the most important thing is to see the growth rates following a reasonable trend to the niche, in this case, for SaaS companies.
Step 4: Adjusting User Base Forecast To Company's Roadmap
Let's say that you plan to launch a new product, feature, or even a new business line next year. That will have a direct impact on the sales forecast, right?
To improve the revenue projection's accuracy, you need to adjust the user base forecast to future development in the business.
For example, if you release a new feature available only for premium accounts - will it improve conversion rates after the release? You might want to include this impact in your forecast assumptions.
Another example is if you also enable a new feature to the free accounts after a future feature release to premium accounts. Will, that impact conversion rates? Will that increase the number of new sign-ups?
Step 5: Leaving Users
Forecasting the number of new customers alone is not enough. You also need to look at the number of leaving clients who choose to stop the plan and therefore need to be subtracted from the user base.
The base way to estimate the churn rate is to look at the historical data and see how many clients left every month and the churn fluctuations during the year and between years.
However, if your startup in its early stages and you don't have enough (or any) data, you can make a reasonable assumption and tweak it going forecast.
At this point, your premium user base should look like this: Existing accounts + new accounts - leaving accounts = total user base.
Building the user base in a subscription-based business
Step 6: Add Pricing
As I wrote above, sales volume (in this case, the user base) is just one revenue forecast element. The second element is the unit price.
In your forecast, you need to build a pricing metric that breakdown the license price per month or year, for every pice plan if you have more than one premium plan, and for every account type (single user vs. multi-user).
Of course, the price could fluctuate over time. For example, they might grow to drop after releasing a new product or feature.
In the pricing forecast, you need to consider the gross price you offer and the discount you might offer to new premium clients.
Step 7: Put It All Together
Now that we have a clear user base forecast and pricing forecast, we need to multiply the two to have our new sales forecast.
Product Sales Forecast
In the example above, I assumed that the business has two revenue streams: subscriptions and services or product sales.
After we thoroughly went through the subscriptions forecast, the product sales forecast is a walk in the park, and there are two scenarios here:
1. That your service is a PAID onboarding training that you provide to existing clients
In this case, to set up the sales volume, we'll use the number of new users every month or year.
To that number, we will apply the percentage of new users that will require onboarding training every year.
Then, we need to multiply that number by the training price.
If you have a few training types, just include a different conversion rate for each training and a separate price.
2. Additional services that you provide
In this case, to set up the sales volume, we'll need to assume the number of sales we'll be able to make in the first month.
We will then set up a growth rate (monthly or yearly) to show the revenue stream's growth trend.
In the last phase, we will, of course, multiply the number of services sold by their prices.
Insights
Once you've built the sales forecast, you can generate initial insights about your business:
1. ARPU: This is the Average Revenue Per User, and it's basically a weighted average of the revenues you generate from every user.
This is usually calculated on an annual basis by dividing the total annual revenue by the total number of users at the end of the year.
This figure could also indicate whether the customer acquisition cost ('CAC') is worth it.
2. MRR: This is the Monthly Recurring Revenues that illustrate how much revenue a subscription business generates every month from consistent, predictable sales to subscribers (hence, recurring).
By calculating the MRR, you can see how much revenue your startup generates from the recurring activity and how much from attracting new clients.
Different niches have different preferences, but in general, you want to see a growing MRR that is accountable for the majority of the business' revenues.
MRR is frequently used by venture capital funds to measure the growth of the core business, the subscription model's strength, and the efforts needed to grow the business.
There are many advantages to having a large portion of recurring revenues since the company needs to retain the customer rather than attract them - the cost differences are significant between the two.
Wrapping Up
This post covered the most relevant elements you need to know to build a killer startup revenue model.
A sales forecast is only one aspect of the financial model that should include the operating and gross margins, cost of goods sold, operating expenses, KPI metrics, and cash flow projections.
