Big Data

SaaS Churn Analytics: How to Spot and Win Back High-Risk Users

Pinterest LinkedIn Tumblr

One of the biggest problems SaaS companies face today is customers and users suddenly abandoning their service.

In truth, customer churn is unavoidable. So let’s get that out of the way right at the start.

The good news, however, is that it’s also reversible. It’s also predictable, meaning customers in danger of leaving your service can be spotted and won back.

So, if you’ve noticed a high level of customer turnover at your company, don’t despair. Take action.

This article will help you develop an early warning system for customers at risk of churning and provide you with practical advice on stopping churn in its tracks.

Can Churn Be Predicted?

The short answer is yes.

That’s crucial to know because customer churn represents a great hazard for your SaaS business, and predicting churn is the first step towards preventing it.

Submit Guest Post Big Data

Think about it. You’ve devoted the time and effort to find a lead for your company. You nurtured it through the customer journey to turn it into a customer. Only for that customer to leave you.

Visit here: Top Big Data Companies

That’s time and money down the drain.

On the other hand, the odds of selling your product to an existing customer are 60-70%, while the probability of selling to new customers hangs low, around 5-20%.

That’s why it’s worth your while to invest energy into preventing existing customers from churning.

Predicting which customers are at high risk of churning boils down to knowing your customers. That’s where SaaS churn analytics come in.

Analytics provides you with valuable data on customers who have recently abandoned your service. This data can be demographic, geographic, and psychometric.

With enough data, you can define which customers might leave you and then do something about it.

Collecting the Right Data

This is the hard part of churn prevention. It requires you to analyze ex-customer data and look for patterns.

As you look at those metrics, you may notice patterns of behavior starting to arise.

You can use those patterns to segment ex-customers into models of high-risk customers.

If a customer is an approximate match to one of your models, bingo! You can consider them a high-risk user.

Of course, using machine learning and AI can improve this process immensely.

Another way you can collect data is to segment customers during the onboarding process for your software.

For example, you can ask users to tell you how they will be using your software and sort them into cohorts according to the software functions.

If your churn rates are higher within some of those cohorts, those are the functions that need improvement.

This strategy actually comes from real life and is used by many B2B companies. We know it’s effective because 35% of them have reported reduced churn rates because of it.

Predicting churn takes a lot of work. However, it’s essential because it’s the first step towards doing something about it.

Can High-Risk Users Be Won Back?

Fortunately, the answer to this question is once again yes!

The average company mistakenly thinks that once a customer goes out the door, they are lost forever.

That kind of reasoning is especially detrimental to contemporary businesses.

Today, competition is at an all-time high, and brand loyalty is lower than ever. People have more service providers to choose from.

Especially with SaaS companies, they rarely have a reason to make a personal connection with the company.

All of this means that, at the global level, churn rates are always rising. Consequently, winning back customers is more important than ever.

In fact, your chances of winning back a customer who has abandoned your service is as high as 20-40%!

With enough data at your disposal and ex-customers neatly sorted into segments, the job is already halfway done.

All that’s left to do is take action and stop a customer from churning. In concrete terms, this means concentrating your efforts on specific customers and finding ways to improve their user experience.

A Proactive Approach to SaaS Churn Analytics

Once you’ve detected a high-risk user, there are many things you can do to prevent them from churning.

It all depends on the customer’s personality and circumstances, as well as what kind of service you’re providing.

For example, relationship-oriented and self-service-based SaaS companies will address churn very differently.

For some users, the best approach might be to reach out directly, over the phone, or by email. For instance, your customer support rep can offer to help the user with using the software features.

On the other hand, some users might react better to a gift, access to premium features, or a symbolic price reduction for using the service. Gifts and savings are potent motivators.

Sometimes, you won’t even need to predict churn. For example, a dissatisfied customer might contact you to voice their displeasure. Handling unhappy customers is a valid churn prevention method.

Keep in mind that the causes of churn are personal and varied. That means your approach to each instance of customer churn should be individual as well.

Can Analytics Reduce Future Churn?

Analyzing churn rates has two more benefits.

The first has to do with the earliest stage of the customer journey—the lead generation process.

Knowing your high-risk user profiles can help you raise red flags when prospecting leads.

If your marketing team determines that the lead is highly likely to abandon your service, you may want to skip over them to save you much trouble down the line.

Secondly, and this has already been hinted at, churn rates can help you determine which product functions need to be improved.

If a cohort of customers who use a particular function of your software is more likely to churn, then that aspect of your software needs work.

Having improved a single aspect of your service, you can expect churn rates to drop.

This is how useful it is to keep a close eye on churn rates. Not only can it help you predict churn and stop it, but it can also help you determine the best leads for your company and figure out which aspect of your product needs improvement.

Conclusion

Churn analytics is a powerful weapon available to any SaaS company that tracks customer metrics. By keeping tabs on customer churn, you’re developing your own model of predicting and preventing customer churn, one of the biggest dangers to the SaaS business model.

Keeping churn rates low will help you boost revenue, increase user experience and keep morale among employees high.

Remember that a customer at risk of churning is by no means unsalvageable. With that in mind, you will stop dreading customer churn as a catastrophe and start looking at it as an opportunity.

Joe Peters is a Baltimore-based freelance writer and an ultimate techie. When he is not working his magic as a marketing consultant, this incurable tech junkie devours the news on the latest gadgets and binge-watches his favorite TV shows. Follow him on @bmorepeters