SaaS Financial Modelling
9 March 2020 | Written by Chironjit Das and Lance Rubin
Introduction to the co-author
Chironjit is a Chartered Management Accountant with over a decade of experience in financial and management accounting. He also holds a Masters of Banking and Finance from Macquarie University.
He has worked in enterprises small and large, including FTSE 100 companies to small start-ups and not-for-profits. He is currently the co-founder of a retail tech start-up looking to combat counterfeits of consumer goods.
Why did Chironjit select the topic and why is he passionate about it?
Every business, from a small start-up to a large enterprise, needs some form of a financial model to guide them through their finances, as well as track key performance metrics.
Service subscription (i.e., X-as-a-service in general and SaaS in specific for software-as-a-service model) companies rely on a subscription model to generate revenue, as opposed to traditional product sales.
Like other industries, there is no one-size-fits-all model for SaaS companies. For example, there are two common types of subscription specifically licence subscription (fixed) and pay-as-you-use subscription.
Licence subscription is generally what we commonly see in most popular SaaS software (e.g Microsoft Office 365), where in actuality you are purchasing the right to use the software for a given time. Pay-as-you-use models meanwhile are based on actual usage. An example of this is Amazon Web Services, where you pay only the amount of computing power you use.
Assumptions and underlying revenue / profit / industry drivers do differ from one company to the next. In my case, I first started looking into it when I joined a start-up and had to come up with the first set of models to present to potential investors.
Service subscription models are increasingly prevalent as they are viewed by investors as being a more sustainable business model as they allow the company to have a recurring revenue stream that is less volatile.
Margins are also perceived to be particularly lucrative (70-80 percent gross margin) for SaaS businesses. The bulk of the cost tends to be fixed, hence driving down the cost-per-customer with every increase in the number of users.
This subscription model has been primarily popularised by start-ups but is also seen by customers as being more attractive as costs for the service are paid on a monthly basis as opposed to a lump sum up-front.
The popularity of this model has meant more and more businesses that may have operated as traditional companies (such as software companies selling software bundles / licenses, law firms selling services, etc) are also switching over to subscription style offerings to capture the benefit of customers and also the attractive valuation multiples they could get as a scalable sustainable business.
Topic and context in a few sentences
SaaS modelling involves financial models that account for software-as-a-service business models. The primary differentiator to a conventional / traditional business model is that the revenue per customer is generally recurring under some form of subscription-based revenue.
This presents some challenges as the cost sometimes cannot be front-loaded or priced in directly for all products, especially when this cost relates to the development of the technology which underpins the value proposition.
Customer Acquisition Cost (CAC) and Long Term Value (LTV)
Rather, pricing has to be determined based on metrics like acquisition costs (more commonly known as Customer Acquisition Cost or CAC) and the expected value over the lifetime of the customer (also known as Lifetime Value or LTV) to the business.
Factors such as customer churn, tiered pricing, and secondary value (such as from the monetisation of data) have to be taken into account as well when trying to build a SaaS financial model.
The CAC and LTV are often cited as the two most important metrics to track for start-ups. The key focus is the multiple by which LTV exceeds CAC ie how much value is generated per customer over the cost of acquiring that customer.
A LTV/CAC ratio of at least two times would be a minimum depending on the stage of the business. CAC doesn’t include all the costs of the business, so LTV needs to exceed CAC by multiples.
In general, they provide a good indication of whether the product / service being sold is or can be truly profitable. You can also use these two metrics to determine the price of your service.
The CAC is a measure of the amount spent to acquire your customers, and this primarily relates to advertising and marketing costs that the company incurs to acquire customers.
This value can and will be different depending on the sales type and channel. For example, utilising online advertising as a sales channel will yield you a different acquisition cost from utilising sales development (ie hiring and using a sales team).
The LTV is generally calculated from the expected value (the subscription fee or sales price, say per month) multiplied by the expected amount of time (number of months) you expect the average customer to stay with you.
While the lifetime of a customer using your service will differ from industry to industry, there are averages you can deduce (or straight up find online) for different industries.
Internally and most accurate, you can use your own customer data to determine how long the average customer stays with you and when they leave.
Similar to when staff leave an organisation this is referred to as turnover or in the case of customers the rate of churn over a lifetime of that customer. For example, if 1% of your customers leave every month, what would the expected turnover be for the whole set?
Importantly as mentioned above, your CAC should be lower than the LTV for the product / service for your business to achieve cash flow break-even and eventually profitability at scale. This may also help you determine the price.
If your acquisition cost is high, and you have a known average customer retention rate, then your pricing should be high enough to be able to cover the CAC and contribute to covering the remaining business expenses that are not included in CAC (e.g. non-sales related salaries, rent, admin expenses etc).
It’s often the case that SaaS businesses remain unprofitable for a number of years before they achieve break-even and scale to cover in excess of the total business expenses.
What about those other expenses? As these are apportioned indirectly, the general way of accounting for this tends to follow more traditional aspects of modelling fixed operating or administration expenses and therefore often excluded from CAC.
If you find that the market cannot support both your price for your product/service and low churn rate i.e. your expected LTV, then there may be an issue with the product strategy or the business viability.
If you are in a start-up, or using the financial model to raise funds, other aspects do have to be included when building the models.
It goes without saying that the financial model should be a 3-way including an Income Statement, Balance Sheet and Cash Flow Statement, but depending on the business maturity, expense appetite and in-house skills to build it this may not be possible. The founders may opt for a more cash-flow only or revenue based financial model, but this comes with certain risks.
Capitalisation Table (Cap Table)
The other key aspect of any modelling is the inclusion of the Capitalisation Table (aka Cap Table) and the valuation metric (price per share) for current and incoming investors including staff who may have access to the employee share option plan (ESOP).
Cap Tables are a basic table indicating number of shares, price per share at various times and the % ownership which changes over time effectively also known as dilution.
The complexity of this table would depend on factors such as share structure, convertible notes, dilution (e.g. diluting interests such as options ), discounts and such. In general, there are also columns for pre-and post-raise/money, as most investors would like to see the level of shareholding once all factors have been taken into account once they have invested.
Depending on the price for the shares at each point in time (commonly known as a round), if the price goes up it is called an up-round and if it goes down it’s a down-round. Down rounds may indicate some issues with either the company’s ability to raise capital based on the market demand or some fundamental issues with their business model. Below is an example of a Cap Table for pre and post raise.
The factors that determine the share price (which at this stage is generally unlisted) is a combination of traditional valuation methodologies and other industry specific methods.
The valuation for companies under the traditional sense generally use 2 methods i.e. discounted cash flows (DCF) and enterprise value (EV) multiples, also known as EBITDA multiples.
If you want to understand more about valuations read the previous article in the series which explores all the different types of methods and is certainly a topic in and of itself, but in general, this is how investors know how much the company is worth, and so the expectation would be for this to be included (even if some may choose to do their own analysis).
The other industry specific valuation metrics (which would be combined with, but ideally not replace the above) have been born out of the SaaS business models and M&A transactions developed over recent times. For example a fintech lending company may be valued based on its price to loan book, price to cumulative loans written or revenue multiples.
Whilst the other industry based methods are useful for comparison to recent transactions, as the financial modeller you need to be careful at simply relying on any one method and ideally have a range of methods which you then do a weighted average for the most accurate blend of valuations.
If you had to teach this topic in a class to school kids what key tips would you give them to focus on
I think the easiest way to describe an X-as-a-service model is to imagine that you are in the business of loyalty. You make something that a customer uses regularly, and your expectation is that you may not make money from the customer upfront (like selling a product off the shelf) but over the course of the customers’ lifetime you will.
Think about the games you are playing for “free” on your iPad, tablets, Xbox or PlayStation. They are free because over time they draw you into purchasing some additional skins, powers, credits, tokens etc. They lure you in and get you addicted then you want to succeed and continue playing by spending money. This is much the same for SaaS business models which rely on a great user experience to keep customers “addicted” to their products.
Your incentive is to make products in ways that a customer would want and feel the need to use regularly. Of course, this may be misused (for example, companies tweaking the service to drive abusive or addictive behaviour, and thus higher usage).
It must be noted that this is not an entirely alien concept in traditional retail. In retail, there are often ways to replicate certain aspects of it through loyalty campaigns, coupons or loss leaders (sell something at a loss to get the customer to come in and possibly buy more or repeatedly to make up for that initial loss).
A common one is 2 for the price of 1. It might seem crazy to sell a product at half its price, but it could potentially triple your sales volume and make back the lost profit.
What practical steps can people take now to learn more
Google is an awesome place to start.
You will find some free examples, both by finance professionals and by start-ups. There are also good paid templates and examples for learning, and if this is something you are focused on, it may be helpful to get some of these. There are plenty of examples of Cap Tables available.
If you are from a non-finance background, the best place would be to read up a little on the basics, find a template that looks suitable and then start working from there.
As mentioned in prior articles reviewing other people’s financial models is a great way to understand their thinking and logic.
This will likely suffice in the initial rounds of capital raising as it’s not as important to have robust financials but more importantly is a compelling story, a minimal viable product (MVP) with actual examples of paying customers.
It is likely more important to the investor that you have the basic understanding of your inflows, outflows and the key metrics of growth (which is usually mainly revenue, CAC & LTV).
You cannot get away from having a Cap Table so make sure you have this at the very least as this will be critical at the point when investors part with their money.
In later raises, it may help (or even be necessary) to get professional help in building more fine-tuned or complex 3-way financial models.
Where are good places (links) to find out more on the topic
Two that Chironjit recommends are here:
https://baremetrics.com/blog/SaaS-financial-model
http://christophjanz.blogspot.com/2016/03/SaaS-financial-plan-20.html
Another option for finance professionals may include Corporate Finance Institute(CFI) or the Financial Modelling Institute (FMI).
If you’re keen to try out a CAC or LTV calculator, this may be a place to get some quick numbers:
https://www.cenario.co/free-ads-spend-calculator
If you visit Eloquens they have an entire category dedicated to SaaS models.
https://www.eloquens.com/category/startups/software-as-a-service-SaaS/78
How important is this skill in the context of learning Financial Modelling?
In general, if you intend to be in the start-up industry, you will have to know it. But general skills play a more important role.
To be a great financial modeller you need to be a great model auditor, and a great model auditor needs to have had the experience of specifying, designing, building and delivering a financial model.
If you are already good at building a particular type of model, you should not have trouble getting comfortable with SaaS modelling. After all, the basic tenets of finance still apply.
How does all this disruption, AI and automation talk impact this topic
There has been increasing attempts to automate the process of forecasting and managing financial metrics. However, the primary issue is that every start-up is slightly different and drivers to revenue and costs may be very different. Hence building cookie-cutter models are not something that works in most cases.
It is not likely that AI will significantly change this in the short or medium term, for 2 main reasons: firstly, most real models are actually kept private, and getting access to the volume of data needed is relatively hard; second, the models vary widely, especially in assumptions, drivers to revenue / costs, share structure, depreciation and taxation.
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