Gut feelings are one thing, but it’s cold hard numbers that quantify your progress and show whether you’re on the right path.
To find out how your software as a service (SaaS) business is performing, you will need to start collecting and measuring some key metrics very early on – ideally at the very beginning. The main benefit here is it gives you the whole picture instead of just a snapshot of your business performance. Equally important, you’ll discover whether you’re building the right things or just wasting your time on something nobody is going to use.
While there are many sets of data you can collect and measure – you’ll want to have the ones that truly matter to your SaaS business that also fit into your definition of success.
We’ve tried to keep things simple and listed some necessary metrics worth keeping a close eye on below.
1. Monthly Recurring Revenue
Monthly recurring revenue (MRR) is essentially predictable income you can expect each month from paying users.
Seeing as most SaaS businesses operate under a subscriptions model, you will want to know how much revenue you’re expected to generate each month to show you’re able generate revenue each month. Therefore you would include both monthly and yearly subscriptions into your calculations.
But as Christoph Janz (Managing Partner at Nine Point Capital) points out in his slide deck – be careful not to mix the two of them up! For instance, if you have three monthly users who are paying €100 and one yearly user paying €1200 – you will want to divide the yearly amount by twelve to get the monthly number.
One of the most important insights you get is how people are using your product – and how many are using it on a daily basis. You’ll definitely want to keep track of daily users and see whether your numbers are increasing each month.
Some keep data you may want to track would be:
- How often they login
- How long they use the app
- The intervals between logins
Keep a look out for usage patterns and analyse what people are actually doing with your product versus what you expected them to do.
In the book Lean Analytics, they suggest segmenting users into those who do what you want and those who don’t so you can identify common characteristics between. For instance you might spot that loyal users come from one social network, live in the same area or are the same age.
You can even A/B test a change to see if an addition of a feature leads to more stickiness among users in group A. Ideally you’ll want to find out what feature(s) lead to people using your products more.
Just like Twitter did when they found that people who followed more than 10 people, were more likely to return and use the social network. What followed was Twitter introducing a “Who to follow” box to persuade folks to add more followers to their profile.
3. Churn Rate
Your churn rate is the percentage of people who abandon your service over a period time. This measured on a weekly, monthly and quarterly basis.
In the online world, a user can be considered churned when they’ve been inactive for 90 days.
The important things to know are the number users and cancelations you have. Which brings us to this simple equation for measuring churn.
You may want to track churn for both paid and free users of your product. Both groups of users can churn by cancelling their accounts, while paid users can cancel their subscription and go back to the free model.
But as Shopify data scientist Steven H. Noble points out, using the formula above doesn’t give you the full picture and suggests measuring churn daily to get the most accurate numbers. For more information, check out Noble’s post: Defining Churn Rate
4. Cohort Analysis
One way to break down your churn analysis is through cohorts which are a group of people who share a common characteristic. For instance all users who registered for your product on April 7th are a cohort.
In a cohort analysis you’ll look to analyse your user’s behaviour over time to see if their any relationships between them. One example could be when you’ve introduced a new feature and see whether users churned or became more engaged with your product.
Another application of a cohort analysis is when it’s used to analyse churned users.
Your churn rate will show you when users abandoned your product, but adding a cohort analysis can show you which group of users left based on the time they signed up.
5. User Acquisition Cost
No business is without its costs, and the cost of acquiring users comes in handy when you’re looking to grow a sustainable business.
Just like the name implies, it measures how much it costs to attract a user to use your product. And it’s a metric you’ll want to know when planning your sales and marketing activities.
You can get your costs using the following formula:
Nevertheless, if you want to see if you’re making a profit from your users you’ll need to know your average revenue per user and the lifetime value of your users – both of which are covered below.
6. Average Revenue per User
This is how much revenue you’re actually getting from users and is calculated with the formula below.
Once you know how much revenue each user is generating for you, you’ll want to find ways you can increase. This can be done either by attracting more users (not a good idea if your UAC are high), up-selling and cross selling.
With a SaaS product, you’ll offer more features for an increased fee per month. Another thing you can do is up-sell the annual plan by giving a 20% discount, just like LinkedIn does.
7. Lifetime Value of User
The lifetime value of a user is different from the ARPU as it is a prediction of the revenue that you’ll receive from the entire relationship between you and the user. In other words this isn’t money you have in the bank but is more of a projection of what you can receive from a customer.
Now there are many variables you can include in the formula, but best to keep things simple in the beginning by using your churn rate and the average revenue per user with the formula below.
Where it can get interesting is when you start segmenting your users to find out which group has the best lifetime value for your business.
Without knowing the lifetime value of a user you will not know how much you can spend on user acquisition.
Every business is different and has different tracking needs, so it’s up to you to decide how specific you want to measure the metrics above. But in the end, you get a true representation of how you’re performing and able to make informed decisions. The key here is to make tracking and reporting a habit.
Did you notice a key metric missing? Let us know in the comments.
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