Churn is the metric that measures how much business you’ve lost both in terms of percent of customers or in revenue.
It has become the nightmare of all SaaS business owners.
And for good reasons…
In a sector where acquisition costs are hitting the roof and competition is fiercer than ever, keeping one’s customers and investing in them for future revenues isn’t a strategy – it’s a prerequisite to success.
“Honestly, for those companies, it isn’t a lack of customers in the front door that is stopping their growth; it’s the constant flow of customers out the back door that is killing their business!” – Lincoln Murphy
That’s why customer success has become the heart of successful companies.
And while the day-to-day dedication to retention is crucial to the process, the post-mortem analysis of churn is of great interest too.
Churn analysis enables companies to understand the diverse reasons behind the loss of a customer and empowers them with the knowledge to both anticipate future churns and action the right win-back strategies.
⇒ Discover the 3 pillars of a good churn analysis.
When diving into churn analysis providing context to your data is extremely relevant.
3 contextual frameworks are essential to this process:
The macro-context of your company is defined by the mega-trends that affect it.
It looks quite abstract and hard to grasp but really this a question of common sense.
The covid-19 situation is a good example.
While it affects all of us on a personal level and most economic agents on another – the type of impact may vary according to the product or service your company offers.
For instance, we know that video-call solutions and collaborative workspaces of the likes of Slack and Zoom boomed over the last year.
So if your company does the same thing but lost many customers in the last year, you’d better take the macro-context into consideration … in reverse… and wonder why on earth your churn rate is so high. You’ll probably discover that the cause of your churn is to be found in your product or customer services.
It’s better always to be in the know.
The consideration of the macro-context in which you operate will help discard or shed light on the broad elements you should keep in mind while tackling your churn analysis.
On top of the trends that shake the world, the sector or industry in which you operate is always, to a certain extent, a place of competition – more or less direct or intense.
Your churn is also directly related to your competitive environment.
If your company competes in red oceans – where industry boundaries are well defined and companies try to outperform their rivals to grab a greater share of the existing market – you ought to acknowledge that your competitors are trying to take your customers away from you.
Monitoring your competitors’ activity to be able to identify a clear competitive reason to a churn, such as a competitor’s newly launched feature, is paramount.
Here you start opening your company’s data vault.
Before getting down to the peculiar reasons for a churn, it is important to start by grouping your customers according to a set of shared experiences that have an objective impact on their relationship with you.
These are cohorts. A cohort is simply a group of people with shared characteristics.
For instance, we all know that onboarding is a critical stage in a SaaS customer’s life.
Evidently, different types of onboardings will trigger different product usage. It is thus important to group customers by their sign-up time periods, types of onboardings received, CS onboarding leads etc.
You’ll probably discover patterns you were not aware of.
The same rule should apply to difficulties experienced by certain customers.
You had an important outage 6 months ago that affected all, or part of your customer base?
Check out this pattern and analyze its impact on your churn.
SaaS companies aren’t a monolithic group of companies sharing the exact business characteristics.
Naturally, they all enjoy a recurring revenue model, and generally offer a service that goes beyond the technological product on which they are built.
The depth of this service will trigger important differences among SaaS, especially when it comes to the type of relationship they entertain with their customers.
From native product-led companies offering a simple and viral product to more complex SaaS solutionswith higher value propositions – Customer success won’t mean the same.
Therefore, customer churn won’t be analyzed according to the same principles, from the same angle.
Per nature, low-touch companies handle or can handle, an important number of customers.
Onboarding, adoption enhancement, renewals, and support generally are fully automated.
In that case, churn is analyzed using objectives voluminous data collected in your product and through questionnaires.
The stickiness of your product will be at the center of your analysis.
These generally are BtoB solutions with high added value and a much smaller number of customers (accounts).
This naturally means that the data to analyze is less numerous and the results of the churn analysis more correlated to the feedbacks of the customer success team.
Your churn analysis will encompass more human and corporate factors than low-touch companies.
In addition, the depth of the customer’s connectivity and data flow between a solution provider and its customer is important. And despite increased easiness in doing so, switching solutions is still a hard choice for a company.
Consequently, win-back strategies won’t be automatic nor standardized – and will generate less return on investment.
The advent of SaaS has reshuffled the cards of customer knowledge by creating data points at every step of the customer journey…and raised more questions than ever before in the tech industry.
Starting from “how many people really are using my solution?” and “are they satisfied?” to “how many users and/or paying customers do I have?” and “how much money do they generate each month?”.
Now, if the SaaS model makes this data available… it does not mean that is it easily accessible. Nor commonly used in churn analysis.
And that’s unfortunate. Because the reasons behind your customer’s churn are left behind by your customers everywhere in your product along their journey.
When it comes to customers who churned, you must be able to answer 3 critical questions about them:
Who were they? what did they do? Were they a good fit for me after all?
No need for a lot of explanations for that one. These are your customer metrics.
From launch to scale, measuring your success starts from very simple maths operations: adding and grouping.
Knowing the number of people using your solution (number of contacts), or companies (number of accounts), and how many are paying customers (number of paying customers).
Plain and simple.
These are your product metrics.
SaaS recurring revenue model means that growth revolves entirely around your customer’s lasting satisfaction with your product – hopefully long after sign-up.
As such, teams involved in revenue generation should be concerned by the way the customers interact with the product at all times.
The heart and soul of SaaS companies.
Ultimately, what you are offering is a product. And what people are doing with it should be of great concern to you.
Monitor and gather activity by day, week, or month – at contact and account levels.
Then get down to session lengths, feature usage, and license utilization.
This literally means looking closely at your churned customers to reconsider your customer fit score.
Put simply, a better customer fit will result in less churn.
And looking at your past and current churn is a great way to refine your ideal customer profile.
After all, your churned customers were once willing to pay for your product – you can thus assume an initial fit – try to see why and where you were wrong.
Your target customer profile is a compilation of firmographic, geographic, and demographic segmentation.
Uncovering a pattern among your churned customers will be of considerable help in this process.
In order to do so, you must focus on criteria such as country, company size, roles, etc…