The best SaaS business model thinking
There is a lot out there about the economics of SaaS business models. Tom Tunguz publishes regular insights about the performance of listed SaaS companies. David Skok offers some excellent analysis. His blog describes the formulas and ratios that drive growth and profitability. SaaStr provides practical tips and advice that are valuable to any entrepreneur. You could build up a list of metrics from these sources that runs to 10 pages or more.
I am not about to try to summarise all this great material in one blog post. This is not a guide to the economics of a SaaS business model. Reading great analysis and working with SaaS startups is a great way to learn. Some key ideas strike me as worth sharing.
CLV is key to unit economics
SaaS is about unit economics. You can calculate a realistic customer lifetime value (CLV) from the available data. I wrote a detailed post on the subject a couple of months ago - find it here. CLV is the building block of long term value. It shows the route to sustainable profit. The formula for CLV includes direct cost and cost per acquisition. Your direct cost should take account of cost to serve. Few SaaS companies can just sign up a customer and watch the money roll in. Those awesome margins need to support a proper service framework. You must keep your users engaged.
Every startup need to get to product/ market fit. At this stage SaaS companies are gaining paying customers with a repeatable process. The results of this process are also predictable. They can estimate the CLV of each customer. But they are not profitable. Now SaaS suffers from an old fashioned challenge. New Business Strain (NBS).
New Business Strain
NBS is an idea from the life insurance industry. In simple terms the cost of acquiring a customer is all incurred upfront. Value is realised over a period of years. Accounting and cash flow follow a more basic model. Growing a business means high short term CPA. This outweighs annual profits from recurring customers. You need more money than you are earning to keep growing. Financing this strain is the purpose of Series A investment and beyond. The alternative is slower growth.
B2B is not viral
Consumer business models can generate hyper growth and profits. This occurs when viral spread reduces CPA to near zero. This kind of viral growth is not open to B2B SaaS. Viral cycle times are much longer. Months not hours. When recommendations do happen they generate warm leads not direct sales. It may be slow and partial but viral still matters. Jason Lemkin wrote a great post about this. Over time, references from your customers will make a difference. Growth will multiply and CPA will come down. When this kicks in, NBS will shrink fast. It just takes time.
Lifetime is a key word in CLV. The number that determines L is churn. The value of your business is sensitive to tiny variations in churn. 2% per month gives a half life of 3 years. That is you will lose 50% of your current customers by the end of three years. Increase this to 3% and the half life reduces to just 2 years. Churn should be a small number. But your margin for error is tight.
Engagement is the great unknown
The biggest gap I see in current SaaS thinking is engagement. Measuring the economics of engagement is hard. We have a crude measure for pre sales engagement. Conversion of leads into paying customers. We have another simple number for post sales engagement. Churn. The process between is more of an art than a science. Finding which steps in the process reduce conversion rates would generate immediate value. Fine tuning service and support to reduce churn will pay long term dividends. Concentrate on measuring behaviour first. If you can attach a numerical value great. Build the model specific to your business from the ground up.
I am leading a workshop for a bunch of Scottish SaaS companies in early March. We will focus on one aspect of engagement. Looking forward to learning some best practice then.
Benchmarks - handle with care
Smart analysis of SaaS performance has led to some well constructed benchmarks. For example Annual Contract Value (ACV) to marketing cost ratio should be around 2:1. This shows a healthy level of NBS. Or Brad Feld's recent suggestion the rule of 40%. The sum of your net margin and your growth rate should be at least 40%. There are many other examples. All are rules of thumb suggested by experienced investors and entrepreneurs. Such benchmarks are due respect. But handle with care. General rules like this are a good indicator of progress but a bad way of setting goals. Think of benchmarks like a thermometer. They give a rough guide to general health. They are not a management tool. You would stay sick for a long time if doctors just focused on reducing your temperature.
I encourage you to read and follow some of the blogs suggested in this post. If you would like help building a SaaS model for your business, get in touch.
Arsham Memarzadeh of @OpenView Partners published a blog post on 13 November "Why Enterprise Mobility Calls For New Metrics and How You Can Help Fill The Void." He is identifying with a common problem. Many investors and advisors struggle to understand how tech start ups make money. Founders explanations are often unclear and business plans rarely include a simple description of the business model. Mobile start ups are even more poorly understood.
Helping investors, leaders and teams
Metrics might help solve this problem. Good business metrics do 3 things - paint a picture of the business for outsiders especially investors; help leaders make better decisions; and influence the behaviour of teams. In a start up context they can help investors, focus management, build culture and drive performance.
Finding the right answers
How can you select measures which help achieve these objectives? Tomasz Tunguz (@tomtunguz) has attempted to fill part of this gap with his regular analysis of public filings by SaaS companies. This is useful but limited by regulatory requirements. To fully answer the question think about these dimensions.
Clarity and transparency
It will take some time to find common metrics which work for each business model and give investors and analysts an accepted basis for comparing companies. Until then the best approach is to try get a clear, easily explained picture of your business. I have to admire the openness of Buffer (@buffer) who have shared their investor term sheet, entire performance dashboard and even the salary levels of everyone in the management team. The dashboard is produced by another start up that believes in full transparency, @baremetrics.
How can we find measures that are clearly linked to business outcomes, communicate the right messages and will be understood by non finance people? What metrics do you use to drive success for your start up?
In the startup cauldron cash flow and burn rate can feel like the only financial measures that matter. You must keep focus on the kitty to survive but money in the bank is not how your business generates value. Many founders find it hard to pin down the measures that show progress in value creation. There are a number of ways to look at this but one common approach is to understand and measure customer lifetime value or CLV.
The fundamentals of CLV
Simply CLV is the total revenue you will receive from a customer over the whole time that individual or company is your customer (R) less the direct cost of sales to that customer (C) less the cost of acquiring that customer (A). R-C-A=CLV.
It should be obvious that this matters to any business but it is especially important to many startups.
For pretty much any business model, R-C needs to be greater than A. If not then the cost of acquiring a customer exceeds the benefit and you cannot hope to generate value. Note in this case that a customer and a user are not the same. Google for example has millions of users who contribute no revenue. This is fine so long as there is also a market of paying customers.
CLV can be a measure of value creation
Once you understand how much value each customer generates then you can start developing a long term model of business value and capital requirements. If 10,000 customers generate £10 million of CLV for example you can estimate the running costs and for a given amount of sales and marketing investment you can figure out how long it would take for your business to reach this number of customers. While this rule of thumb works for many businesses, it is especially useful for SaaS or other subscription based models.
CLV provides a window on operational metrics
CLV can also be a guide to understand which operational measures really matter. Every startup today has a bewildering variety of analytics at their fingertips. Which need to be monitored constantly and which are just interesting? In a fairly typical freemium SaaS business for example, A will be calculated by looking at the cost of sales and marketing divided by the number of customers that sign up and then multiplied by the rate of conversion into paying customers. Once the business has enough information to estimate the rate of churn, this can be used to estimate customer life. So if you lose 20% of your customers every year, typical life is 5 years. Multiply this by your average monthly revenue and hey presto you have a value for R.
Now your SaaS business can focus on number of sign ups, cost per sign up, conversion rate, average subscription and churn rate. Track direct costs every month and you have the complete model in 6 figures.
Of course each of the numbers in this kind of model is tough to estimate. When you start out you don't know how much your customers will pay or for how long. Figuring out how much it costs to sign up 100 customers might be quick but how many of those turn into loyal customers paying regular money? The risk increases if you need to employ a sales force to acquire customers.
Use seed funding to test CLV potential
These are all great questions. In my mind the purpose of raising seed funding is to answer them as robustly as possible. Test out how much it costs to acquire customers. Get feedback on what people will pay and how you can improve the design to make them more loyal - from a CLV point of view a year of extra usage may be worth more than a 10% increase in price for example. Demonstrate you can scale your product and your team to meet demand and that you know how much this costs.
Build a CLV model to demonstrate value
Once you have a robust proven model you have a basis on which you and other investors can make projections about future growth. You can show how you would spend that £5 million Series A round and calculate the value your business would create as a result. Your company will still be a high risk investment but you will have a model to work with at least.
Different companies require different approaches but CLV is a widely understood and applied concept. Build a model that demonstrates how your early progress creates CLV and you will have a great conversation with potential investors.
How Metrics Damage Teamwork and Morale....
“There’s no I in team” is one of the most hackneyed, happy clappy management cliches. It has a less well known but equally tired companion “All of team is in measurement but it is completely screwed up.”
Let me try to explain. A few years ago the firm I worked for elected a new leader. Less than a year later he brought in an outsider to run the business unit I worked in. Both leaders were more charismatic and inspiring than their predecessors. Both men have gone on to achieve great things, in many ways transforming their businesses and achieving profitability and growth in very difficult economic circumstances. Many of their priorities were similar and one common area was an emphasis on greater collaboration, hunting in packs as it is sometimes called, to leverage the power of the whole organisation. Both failed to make real progress in this area.
There are many reasons for this but one is the use of performance metrics. In my business, the previous boss had always believed that performance should be rewarded on the basis of team performance. He had never tried to measure it. At the end of each year, we would simply have a conversation. How did you do? was never the first question. Why did this account over perform? How can this group do better? were more typical. At the end, we would look at my contribution to those team achievements or struggles and reach a conclusion.
The new man and his leadership group took a different approach. He announced that collective rather than individual performance would be the new philosophy, perhaps without realising that it was actually the old approach as well. His management group backed this up with a series of measures in every arena. Revenue, profitability, utilisation, investment, compliance, relationship strength and many more were measured and reported weekly. In the face of consistently strong performance, some landmark new client engagements and the acquisition of brilliant new talent, one of the most important measures of morale went into reverse. Staff satisfaction and engagement scores dropped every six months and after a few years, employee turnover started to rise inexorably.
Why did this happen and how can Startups learn from this experience? The answers are complex and as yet little understood. Essentially this is a human problem. If you measure something and translate that into a message for a machine, the outcome will be entirely predictable. People are different. The messages that individuals and groups take from any given metric are impossible to predict. I love the Amazon “two pizza” rule which says a team can be no larger than can be fed with two pizzas. But even this with say a dozen people has many different moving parts. It is not just 12 individuals and one team. Every group of two, three or more people has its own dynamic with within the team. All have a different view of the team leader (if there is one). The law of unintended consequences basically runs riot in this environment. One of the wrongest and therefore most dangerous sayings in the dictionary of tired cliches is “What gets measured gets done.”
Anyone who follows this blog may be confused, didn’t we say a few weeks ago that measurement was really important to Startups? True and it is but it can also cause problems. Teamwork is also vital in the intense, close knit environment of a Startup. There is a simple answer. No internal measures. None. Nil. Nada. Zip. All measures should be directly linked to the customer. Winning them, keeping them happy, delivering what they need. No matter how precise, resist the temptation to measure internal performance. Forget attendance, productivity, quality and everything else. Truthfully, if I was running a large business again, I would be sorely tempted to do the same thing. Especially if it was a service business.
Perhaps I am too negative. We have the opportunity to develop metrics that could not have been imagined a few years ago. Which measures have been used successfully to build teams and drive business change? Where have you seen measurement work effectively? I would love to read your comments.
Measurement helps with investment, management and exit
I realised when I first started to write this blog that I have a bit of an obsession with measurement. About 500 words in, I still had not reach my first point and it was clear that I had at least six articles rattling around in my head. I have decided to spare readers for now and focus on just one thing, the importance of measuring when looking at the investment potential of a startup.
Generally speaking, startup valuations lack any discernible frame of reference. Potential investors naturally fall back on financial projections because this is where they are comfortable or rely more on a gut feel about the product, the market and the people. There is no panacea which can make the future predictable for a new business but I believe non financial measurement should have a place in any startup evaluation.
The basis for this view is simple. The digital revolution has not changed the principles of business but it has transformed a couple of things. Measuring is one of those things. For businesses selling online or in the software and mobile apps world, it is already possible to measure and track just about everything. Without spending any money! Much of what you need and what a business owner could only dream about a few years ago is available in a couple of clicks through a bunch of fee tools, most prominent of which is Google Analytics. If you have a website of any kind go check this out. Number of customers, source of clicks, usage rate, page dwell time, sales rate and much more is just sitting waiting to be analysed.
Over time, as the tools become even better, as the mobile Internet adds location and other context data and as the Internet of Things starts to take a grip, the range of businesses for everything can be measured will grow and grow.
Great but what does this mean for the potential investor? Three main things:
Startups will never be a perfect environment. Even online measures will be based on a small user base and a limited timeframe. Like any measure they will also reflect the past and in the digital world, the future will most certainly be different. However, measurement is a tool that every investor and every leader in a Startup should be using and it can make a big difference to the chances of success.
Kenny Fraser is the Director of Sunstone Communication and a personal investor in startups.