There are endless opinions about how to reduce churn in your business.
Some argue the key is to form a robust customer success culture. Others argue you should focus on your product experience.
But when I read these well-intentioned strategies, I think of motherhood and apple pie. Everyone would agree with these tactics. The issue is these recommendations are quite general in nature. They are too high-level to implement and make a notable impact.
A better approach involves two specific activities that are easy to get your arms around. When done in tandem, they will significantly reduce churn.
Understand your customer intentions, behaviors, and hopes
First, it all starts with your customer journey. You need to see the full timeline of how customers discover, buy, adopt, and thrive with your product.
A helpful exercise to understanding your customer journey is journaling how your go-to-market (GTM) teams interact with your customers. For instance, how do they coordinate handoffs within the team?
Similarly, it’s crucial that your GTM team has well defined roles. As in, do you know what your customer success manager’s true role is?
Just as importantly, you need to understand your customer's specific activation moments using your data. You need the full picture of your customer, not just bits and pieces.
What is an activation moment?
Activation moments are specific sets of behaviors your customers exhibit in your customer journey that make them statistically likely to continue using your product.
For example, Facebook has proven that once a new user signs up and adds 10 friends in the first 7 days, they will be a lifelong platform user. This is such a great, concrete example of an activation moment. It also illustrates that an activation moment can also occur later in the customer journey.
It’s also common to see a number of disparate activities work together to cement the activation moment. It could result from full product adoption, X number of QBRs, and Y number of support tickets.
The actual behavioral signals and amounts, of course, can vary for every SaaS company, and might even change over time. So, in some ways, this is an ongoing exercise.
Next, understand your customer data
With a solid grasp of your customer journey, you’re now ready to build a data model. I might be biased here, but what could be more fun than an effective churn prediction model?
A churn prediction model is critical because we typically “experience” churn when it’s too late. Unfortunately, churn is a lagging indicator.
But a churn prediction model fixes this. Instead—if done well—it creates a set of leading indicators.
For most SaaS products, how your customers use your product is the first leading indicator of their likelihood to continue using it.
But usually, there are many more leading indicators. In fact, we’ve found the best inputs for a churn model include:
Customer Journey + Business Data = Churn Proof!
Finally, a good churn prediction model should also explain the factors that historically led to churn. This will better inform your GTM teams of the actions they can take to prevent it.
Just knowing that a customer might churn is not enough.
Your GTM teams need to understand why a prediction was made. For example, a prediction could show that an increase in average support ticket resolution time will lead to churn. If this is known, your GTM team can take specific, targeted action to proactively address this before it ever becomes an issue.
When you bring together your customer's journey with a predictive data model, you change the game.
This approach allows you to stop relying on anecdotes and “maybes”. It enables you to pinpoint specific causes of churn. And it gives you the power to do something about it.
That’s how you become churn proof.
If this approach intrigues you, let's talk!