SaaS Application Uptime Stats
Most SaaS companies will promise 99% uptime, many will even promise 99.9% uptime. However, on average companies continue to experience 12 incidents of unplanned application downtime every year, each of which lasts 1-2 hours if it’s a critical failure and gets immediate attention, or more than 3 hours if it’s non-critical.
To be clear, 99.9% uptime still allows for more than 8 hours of downtime each year, but usually this is meant to cover scheduled maintenance, stress testing, disaster recovery testing, etc. If you’re following the arithmetic you’ve already figured out that on average companies are subject to as “little” as 12 and as much as 40+ hours of application outages each year. Recall scheduled maintenance would be downtime on top of this unplanned outage time. As such, many SaaS companies face uncomfortable contract conversations regarding violations of their Service Level Agreements (SLAs). Often the expectation is set at 99.9% in the SLA, and as such often performance fails to meet expectations.
In this situation, the right move is to set expectations with the customer appropriately from the start – otherwise at best you’ll lose upsell opportunities (see customer lifetime value below) and at worst you’ll lose customers altogether (see churn below).
Core SaaS Stats: Recurring Revenue, Lifetime Value and Churn
Recurring revenue is usually calculated monthly (MRR). Obviously you’d like it to grow as much as possible, but for frame of reference- the top-performing SaaS companies achieve $50 million dollars in annual revenue by their 8th year. This is a relatively new trend, as previously it had taken well over 10 years to hit this mark. It’s also worth noting that once they hit this point, some of these top-performing company’s revenues continued to roughly double year over year, which may or may not be a realistic place to set the bar for your organization.
Again I would direct you to a recent post on how using an application performance management system to help you handle SaaS application uptime can help protect your recurring revenue (the key word is “recurring”).
Customer lifetime value (CLV) takes MRR and extends it over the anticipated duration that a customer will continue doing business with your company (i.e. how long that recurring revenue will be recurring). Ideally, this will be many, many years, but realistically you won’t be able to capture all of that revenue for every customer. Additionally, the amount itself will fluctuate as customers downgrade their investment with you or as sales upsells customers.
Ideally, you’ll see 14% growth in your CLV annually, but that’s difficult to attain, especially with consistency. But let’s bring things back down to Earth for a minute: fluctuations aside, how long should you expect to retain a customer for purposes of calculating lifetime value?
Churn represents the fraction of customers or revenue (depending on how you calculate it) that you lose every year/quarter/month (the interval at which you measure churn usually corresponds with the interval of your contract renewals).
Churn can be the bane of your SaaS business. Lincoln Murphy wrote a great article about the importance of being clear about how you’re calculating churn. Here’s the short version: 5% annual good, 5% monthly horrible. Once you’ve calculated your churn rate, you can more accurately determine your average CLV.
But how can you prevent churn?
Alex Bloom outlined two key points that can help mitigate churn in a recent article on the New Relic blog. In short: focus on onboarding and engagement/use of your product. But read the article for the details of how.
For more information about financial metrics (as opposed to more technological metrics like SaaS application uptime), check out this article from New Breed and this “cheat sheet” from ChartMogul. Customer Acquisition Cost (CAC) for instance, is very important. I did not cover it in this article but you’ll find information about it in both of the linked resources.