How public SaaS companies report churn, and what you can learn from them

While doing some research for another post I just stumbled on this excellent overview from Pacific Crest on the churn rates of publicly listed SaaS companies. I’ve seen posts with churn benchmarks of public SaaS companies before, but this one is by far the most comprehensive collection I’ve seen and I think it’s very useful.

What’s maybe even more interesting than taking a look at the numbers themselves is to see how different companies define churn (or the inverse, retention). Since there is no official US-GAAP definition of churn or retention, different companies use different ways to measure and report these metrics. And because public companies are under the scrutiny by the SEC, any non-GAAP metric they report must be accompanied by a razor-sharp definition.

Most public SaaS companies report churn in the form of their dollar-based net retention rate, i.e. the inverse of net MRR/ARR churn (as opposed to account/logo churn), which compares the recurring revenue from a set of customers across comparable periods. Here’s a particularly nice description of this metric, coming from AppDynamics:

“To calculate our dollar-based net retention rate for a particular trailing 12-month period, we first establish the recurring contract value for the previous trailing 12-month period. This effectively represents recurring dollars that we should expect in the current trailing 12-month period from the cohort of customers from the previous trailing 12-month period without any expansion or contraction. We subsequently measure the recurring contract value in the current trailing 12-month period from the cohort of customers from the previous trailing 12-month period. Dollar-based net retention rate is then calculated by dividing the aggregate recurring contract value in the current trailing 12-month period by the previous trailing 12-month period.”

If you take a look at the data assembled by Pacific Crest you’ll see that many companies use the same logic with minor variations. For example, some companies look at the trailing 12 month period, while others look at calendar years, quarters, or months.

Some companies exclude customers that do not meet certain criteria, for example:

• Box includes only customers with $5k+ ACV and annual contracts
• Alteryx considers only customers which have been paying customers for at least one quarter.
• AppDynamics includes only customers who have been paying customers for at least one year.
• Zendesk excludes customers on the starter plan.

This makes perfect sense: It tells you what type of customer the company is focused on, and you can see the retention metrics in regards to this type of customer.

Other companies use variations that I think are questionable. Some companies report customer count-based retention, which I think is much less interesting than dollar-based retention. Some report renewal based on the number of seats; one company, Fleetmatics, reports churn based on the number of vehicles under subscription. But the majority of companies does report dollar-based net retention rate in a way that allows for an apples-to-apples comparison across companies.

What can you learn from this?

(1) There is not one perfect definition of churn that is right for every SaaS company. Depending on the specifics of your business you might want to:

• focus on monthly, quarterly or annual retention
• exclude customers that churned within the first, say, two months
• include only customers that represent the core of your business, e.g. customers above a certain ACV

(2) Having said that, dollar-based net retention is the way to go. You should stay close to the definition above and tweak it with care.

(3) There may not be one perfect way to define and measure churn, but there sure are lots of ways to get it wrong. :) One classic example is to calculate a monthly churn rate and to mix in annual plans with monthly plans. By including customers on annual plans who aren’t up for renewal in the period you’re measuring you’re underestimating your true churn rate.

(4) Whatever metric you choose, make sure that you use it consistently and that you have a razor-sharp definition.

Bonus tip: Whenever you report numbers, be it in monthly updates or in a Board deck, include footnotes or an appendix with definitions of every metric that you’re reporting. I can almost guarantee you that this will save you ten minutes of discussion with your VC Board member(s) who (understandably) want to make sure that they understand the numbers you’re showing them. :)

Update / September 17, 2019: Another bonus tip, we recently invested in a company called Brightback that helps you reduce churn by making it easy to implement sophisticated, personalized "churn deflection" pages and workflows. Have a look! :)

Benchmarking your SaaS startup

People often ask me questions like:

• "How many people can I expect to sign up on my SaaS website?"
• "My conversion rate is x% – is that good or bad?"
• "My churn rate is x% – is that OK?"
• "What kind of growth rates are VCs looking for?"

While we have quite a lot of data from our SaaS portfolio companies and from SaaS startups pitching to us (which I'll be happy to share, in aggregated form, in another post), I thought it would be good to increase our sample size by asking a larger number of SaaS startups to provide us with some key metrics:

SaaS metrics benchmarking survey

If you're a SaaS startup I'd love you to participate in the survey. I kept it as short and simple as possible, focusing on three of the most important metrics for early-stage SaaS startups:

1. Visitor-to-trial signup rate
2. Signup-to-paying conversion rate
3. Account churn rate

As soon as I have a meaningful number of submissions I'll share the results (in aggregated form) with the participants and will also publish them here.

Thanks in advance to all participants!

The 8th DO for SaaS startups - Stay on top of your KPIs

“What gets measured gets done” – it seems like the source of this quote, often attributed to management expert Peter Drucker, isn’t certain, but its meaning is clear and very relevant for every SaaS founder. If you want to make sure that you make best use of your scarce resources, you need to have a clear understanding of your objectives and the KPIs that measure your progress towards those objectives.

Depending on the stage that you’re in you’ll want to focus on different metrics. I’ve tried to illustrate this in the following diagram:

(click image for larger version)

As you can see, I segmented the company lifecycle into three major phases: pre product/market fit, post product/market fit but pre-scale, and post-scale (being fully aware that there is no distinct definition of “product/market fit” and “scale” and that the transition from one phase to the next one is a gradual one). At the bottom I noted what these phases usually mean in terms of the stage of your product and company and which funding level it typically corresponds with. Note that the x-axis is not a true-to-scale representation of time elapsed. For a true-to-scale representation I would have to add much more space between the Series A and the Series B and between the Series B and the Series C.

The key message of the chart is that in the beginning you can focus on a small set of metrics, but as time goes by and you’re making progress you need to add additional KPIs to your cockpit.

Let’s have a closer look at each of the three phases.

Pre product/market fit

I’ve written about it before in my posts about sales and unscalable hacks: In the very beginning, when you’re in the process of finishing the first version of your product and trying to get the first customers, you shouldn’t worry too much about metrics. Firstly there just aren’t many metrics to keep an eye on yet. Secondly you should be obsessively focused on getting to product/market fit (Marc Andreessen’s words), and that means you should spend your time talking to customers and developing the product.

That said, the following metrics are relevant in the pre product/market fit phase:

• User feedback: Most of the user feedback that you collect in this phase is qualitative rather than quantitative, but if you talk to a larger number of potential users you might also be able to add some quantitative elements. For example, you could ask users to rate your prototype and see if that rating goes up over time.
• Development velocity: I don’t know if (or how strictly) you should use a software development methodology like Scrum, which allows you to nicely visualize your development velocity, in the very early days, when you’re maybe just two developers – I would be very interested in your thoughts on that question. At any rate, however, I think it’s a good idea to break down your project into a larger number of smaller pieces, features or “story points” early on. This will help you in getting an understanding of your development speed, which later on will become more and more important.
• Waiting list signups: When you put up a landing page to collect email addresses for your waiting list, track how many signups you’re getting. Driving signups probably isn’t a key priority for you at this stage but it’s an indication of interest in your product and hey, you’ll still have some space on your Geckoboard which you can fill with a nice chart! :)

Once you let potential customers try your product, the real fun begins. At that point, you should track signups and some indicators for activation and usage, which, for obvious reasons, are precursors to your ultimate goal, paying customers. What the right indicators for activation are depends on the type of your product. It could be a profile completion and the setup of a customized pipeline in case of a CRM application, the installation of a tracking snippet for a Web analytics product or… you get the idea. Similarly, usage metrics are highly specific to your application, so think about what the right events and parameters are in your particular case and make sure that you instrument your application accordingly. If your solution is a little more enterprisey and you’re working with a higher-touch sales model you may also want to track qualified leads along with trial signups.

In order to succeed you need happy customers who do free marketing for you, otherwise customer acquisition will always be an uphill battle. Therefore you should also consider regular Net Promoter Score (NPS) surveys. If you’re looking for the best survey tool, I have a tip for you.

Post product/market fit, pre scale

As you’re slowly but surely getting to product/market fit and starting to get the first paying customers (yay!), your trial-to-paid conversion rate becomes one of the most vital metrics. It’s hard to give you a benchmark, since your conversion rate not only depends on the quality of your product and the onboarding experience but also on many other things such as leads quality, pricing and many other factors. With that caveat in mind, the typical range that we’re seeing is between 5% and 25%.

Equally important is your retention, usually tracked by measuring churn (the inverse of retention), since your CLTV (customer lifetime value) is a direct function of how much you charge your customers and how long they stay on board. As a very rough rule of thumb you should try to get your churn rate to 1.5-3% per month.

Make sure to track churn not only on an account basis but also on an MRR basis. Your MRR-based churn rate will hopefully be significantly lower than your account-based churn rate, since smaller customers tend to have a higher churn rate and because your loyal customers will hopefully pay you more and more over time. Also, make sure that you avoid SaaS Metrics Worst Practice #8, mixing up monthly and yearly plans. Finally, if you want to get a good estimate of your customer lifetime, take a look at retention on a cohort basis.

If you don’t have a KPI dashboard yet that gives you an at-a-glance look at your key metrics, now is the time to build one. Here’s a template that I’ve created, along with some additional notes.

As you’re moving on, arguably the most important metric becomes MRR, and specifically net new MRR that you’re adding each month. Net new MRR is calculated using this simple formula:

Also keep an eye on your ARPA (average revenue per account). It’s an important metric at all times for obvious reasons, but as you’re nearing the next phase it’s becoming even more important.

Post scale

When you’ve reached a certain level of success, say you’re at around $500k MRR, the biggest challenge (besides growing a bigger organization and mastering all kinds of growing pains of course) is to find ways to profitably acquire customers at a much higher scale. By this time you’ve picked all the low-hanging fruits, and you may have maxed out what you can reasonably spend on AdWords to buy traffic and leads.

Therefore you’ll have to focus on the relationship between your CLTV and your CACs (customer acquisition costs), your CLTV/CAC ratio, which measures the ROI on your sales and marketing investments. Another way to look at it is your CACs payback time, which tells you how many months of subscription revenue it takes to recoup customer acquisition costs. If I had to choose I’d pick this one, since CLTV is always an estimate which can be more or less accurate.

A few last points:

• Many startups struggle to get all these numbers together because different numbers are collected in different systems (e.g. Web analytics software, billing systems, self-made databases,...), which often leads to inconsistencies. I don’t have a simple and general advice for this issue, I might address it in another post.
• If you’re not sure which metrics to track, e.g. which events in your application, err on the side of tracking too much data even if you have no immediate use for it. You never know if it becomes useful in the future, and the costs for tracking large amounts of data are no longer very high nowadays.
• If you want to read more about SaaS metrics, I highly recommend David Skok’s blog and Joel York’s blog, as well as Jason M. Lemkin and Tomasz Tunguz.

That was it for the 8th DO for SaaS startups – questions, comments and suggestions are as always very welcome!

[Update 01/17/2015: There's a new company called ChartMogul (which we invested in) which makes it easy to get a real-time dashboard of your SaaS metrics. Check it out!]