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5 minute read · Published July 13, 2024

Your customer retention model should start earlier than you think

Latest Update September 12, 2024

I probably don’t need to tell you how important it is to manage churn. But humor me as I walk you through this scenario. 

Let’s say there are 2 companies who both grow their customer base by 20% every month. But there’s one critical difference: company 1 has a 7% churn rate, while company 2 has a 10% churn rate. Despite having the same exact growth rate, company 1 will outperform company 2 by 177% in just 2 years. 

So even a 3% difference in churn has a massive impact on revenue, even in the relatively short term.

Okay, now that you’re really sold on the importance of minimizing churn, let’s talk about how to predict it early so that you can act quicker to keep your customers. 

The dangerous misconception

Too often, teams start looking for indicators of churn too late to take meaningful action to prevent it. This is why churn is often handled in a reactive manner, with de-escalation tactics hailed as one of the best solutions to customers who are on their way out the door. 

Offering discounts or incentives as a last-ditch effort has its value, but it shouldn’t be at the core of your customer retention strategy. 

To manage churn in a truly savvy fashion, you’ve got to start playing offense earlier. That means working earlier indicators of churn into your customer retention model, starting to look for red (or even yellow) flags as early as the first touchpoint. 

This gives you real leverage to strategically foster stronger, more long term relationships with more customers. 

Identifying early predictors of churn

So your users just hopped into your platform. How do you tell the difference between someone just starting to ramp up and someone who is likely to churn (whether it’s immediately or a few months down the road)? 

If you track the following trends, you should be able to identify correlations between certain thresholds of metrics and customers who are willing to churn. 

For example, you can identify early “red zones,” “orange zones,” or “green zones” for the following buckets to help you prioritize proactive retention strategies. 

Engagement levels during onboarding

Customer engagement is one of the clearest indicators of churn—low engagement shoots their probability of churning way up when compared to highly engaged users. 

And engagement starts with onboarding. This is your first chance at seeing how invested users are. If you have a formal onboarding flow (which you should), keep tabs on how swiftly and how completely they move through it. This includes setup tasks, quick-win actions, and engagement with tutorials. 

Customers who are hardly engaging with onboarding materials or clicking around on the platform in this crucial first week or so are not getting the education they need about how to best leverage your platform. This can set them up for a frustrating or disengaged experience with your product. 

Frequency of usage

After your users have successfully been onboarded, they’ll hopefully quickly fall into some sort of regular engagement pattern. Track this over the first couple of weeks or months after onboarding to see how well they’re leveraging the platform once they’re all ramped up.

Declining usage patterns are critical early warning signs of churn. Regular interaction with your platform is one of the most essential pieces for building strong user habits and encouraging long-term engagement. 

A handful of specific metrics you may want to monitor include: 

  • Daily/Weekly Active Users (DAU/WAU): Track the ratio of daily to weekly active users to gauge consistent engagement.
  • Feature usage: Identify which features are being used and how often. A drop in the usage of core features points tool declining interest.
  • Session length and depth: Measure how long users stay on the platform and the extent of their interactions within each session.

Customer support interactions

One source of rich information to predict churn in a reliable customer retention model is interactions with customer support teams or self-service materials. 

High numbers of support requests might indicate dissatisfaction, especially if the issues raised are significant or recurring. However, the complete lack of engagement with support teams or resources may also indicate a lack of investment in the product.

You want to monitor these interactions closely to see if they’re indicating the start of a rocky relationship, the start of a highly invested relationship, or one that could go either way and so you want to monitor it closely. 

You can also use sentiment analysis to extract more concrete insight from messages with customer support to get a temperature check on how your new users are feeling. 

Feedback and surveys

What better way to gauge how likely your customers are to stay with you than to just ask them yourself, whether directly or indirectly?

By requesting feedback early in the process, whether that’s during onboarding or in the first few days of real engagement, you can uncover users with initial frustrations or unmet expectations. 

You could go straight to the heart of the issue and ask how they’d rate their experience with the product or how likely they are to continue their subscription based on the initial experience. You could also ask more indirect questions to reveal their opinions. Scheduling intentionally-timed in-app surveys about topics like how easy a certain feature is to use, or how valuable a feature is can help you track a broader range of indicators about their likelihood to continue to use your platform. 

What your users feel at the beginning of their journey with your company is likely to continue in the same direction unless strategic intervention is taken. Getting this insight early can help you act quicker and more proactive to turn it around if needed. 

Proactive retention strategies

Having a solid customer retention model is important to be able to identify power users and those who may be at risk of churning. But you need to take it a few steps further and actually leverage that information to effect change in your churn rate. 

Personalization

There’s been no better time than now to invest in scaling personalization in SaaS products. With so many new tools out there, you’re more able than ever to tailor a user’s experience to exactly what’s going to motivate them to stay. 

Let’s say your customer retention model puts a spotlight on a few users who are at risk of churning due to a range of factors, from not completing onboarding to frustration expressed to customer support to low sign-in frequency. Using user assistance tools like Command AI, you can send them custom nudges based on their engagement, or even target them with a highly relevant and adaptive conversation with an AI agent. 

For example, for the user who never finished onboarding, they could receive a nudge to get a quick, interactive walkthrough of one of the core functionalities. 

Giving every single user these customized recommendations and content can help you to be more targeted in your retention strategies. 

Feedback loops

Creating a continuous feedback loop is essential for maintaining customer satisfaction and addressing issues in time to really make a difference. Regularly reaching out to customers to gather feedback and provide support shows that you value their input and are committed to improving their experience.

You can schedule regular surveys and check-ins to get feedback from your customers. This can include post-purchase surveys, periodic satisfaction surveys, in-app feedback prompts, or virtual check-ins with your customer success team.

You can use AI to scale these efforts, too, using tools like Copilot’s AI agents. Automated systems can start personalized conversations with customers at key points in their journey, such as after onboarding or following a purchase. This ensures that feedback is gathered consistently and that customers feel supported throughout their experience.

Of course the big thing here is to not just collect the feedback, but to actively use it, whether that means making changes to your product or providing additional attention or support to a user. 

Don’t start pulling data for your customer retention model too late

If you want to be like company 2 and outgrow all of your competitors with higher churn than you, you need to start keeping your eyes peeled for customers in the red earlier. If you do, you’ll be able to catch problems earlier and not have to rely so much on (unreliable) de-escalation techniques.

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