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      Predicting and Reducing Customer Churn

      Sep 09, 2019

      4 minute read

      “In the world of Internet Customer Service, it’s important to remember that your competitor is only one mouse click away.” – Doug Warner


      Source –

      Spark and Park is a parking management company at the airport that lets you reserve a parking spot. Upon entering the parking lot, you are instantly greeted by an attendant who accompanies you to the allotted parking spot. Then, the shuttle arrives and the driver helps you load your luggage, offers refreshments, and even an umbrella if necessary!

      This is what good customer experience is all about.

      Several bad experiences, or even one glitch, and a customer may bid adieu. It’s that simple!

      Retaining customers is the need of the hour! In fact, according to Bain & Company, a mere 5% increase in customer retention can increase a company’s profitability by 75%.


      In our blog post, we talk about what customer churn means for SaaS companies and the important factors of predicting churn. So read on!

      What is customer churn?

      “Customer churn is when an existing customer, user, player, subscriber or any kind of return client stops doing business or ends the relationship with a company.”

      This could mean the cancellation of a membership/subscription, closure of an account, not renewing a contract, and so on.

      Also known as customer attrition, churn is the percentage of customers/users who stopped using your brand within a specific time frame.

      Here is how you can calculate churn –


      For instance, let’s say you had 400 customers and lost nearly 20 last month. Then, your monthly churn rate is 5%.

      But why is churn rate paramount to companies in the first place? Well, that is because retaining a customer is more cost-efficient than acquiring a new customer!

      According to a report by Forbes, it is 5 times more expensive to acquire new customers than it is to retain them.

      How to predict and reduce churn rate?

      1. Determine customers who are at-risk

      Some customer behaviors are more predictive of churn. However, it is difficult to proactively spot these behaviors in real-time to retain the customers at-risk.

      Organizations are leveraging customer journey analytics to improve their ability to identify customers who might leave.

      This is done by simply understanding customer preferences and figuring out ways to reduce customer friction.

      2. Ascertain most profitable customers

      All customers are important. But not all customers are equal.

      While you may want to retain all, your limited resources don’t give you the green signal. Which is why it is a good idea to focus on high-value customers first.

      Customer journey analytics gives you a comprehensive and quantitative image of the entire customer journey.

      It weaves together every touchpoint to improve the end-to-end customer journey, substantially.

      Leverage customer journey analytics and group your customer into segments by –

      • Profitability
      • Response to offers to stay
      • Readiness to leave

      3. Target the right prospects

      Let’s face it, however good your retention strategy might be, it will be a major waste of resources if you are attracting the wrong audience.

      When you focus on the right customers, you will be able to reduce churn in the future. Hence, it is a good idea to target those people who are fit for your product in the long-term.

      Customer data can help you segment customers on the basis of behavioral, product, and demographic attributes. You can also keep a close check on how your customers are impacting your business, the risk of churn, and customer lifetime value.

      Important factors to predict customer churn

      Now comes the main question that every SaaS company might want to know—if I want to stop customers from churning, which important metrics do I need to assess?

      Here are some important metrics that are vital to your customer retention/success strategy –

      1. Customer demographic features that contain basic information about a customer (e.g., age, education level, location, income)

      2. User behavior features describing how a person uses a service or product (e.g., lifecycle stage, number of times they log into their accounts, active session length, time of the day when a product is used actively, features or modules used, actions, monetary value)

      3. Support features that characterize interactions with customer support (e.g., queries sent, number of interactions, history of customer satisfaction scores)

      4. Contextual features representing other contextual information about a customer

      Key Takeaway

      For a SaaS company, nothing is more heartbreaking than your customers switching to another brand, or you having to send a “We’ll miss you!” email.

      It is important that your company allocates enough time and resources to carry out a good customer retention policy. Don’t just look to reduce your customer churn rate, look to reducing your churn rate while increasing your profits.

      Know More About Our Advanced Analytics Solutions Including Customer Churn

      At Grazitti Interactive, we have a team of experienced data scientists that have helped enterprises—including many Fortune 500s—with all their data needs. Visit our web page for more information about our advanced analytics solutions. Or send us an email at [email protected] and we’ll take it from there.

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