Data-driven way To Improve Customer Retention and Churn

Data-driven way To Improve Customer Retention and Churn

Acquiring new customers is very critical for your business but what about the existing ones. Here’s the data-driven path to improve your customer retention.

Source: SuperOffice

What’s better for your business than acquiring a new customer? If you’re wondering that acquiring more than one new customer is the answer then it’s probably wrong. It’s about retaining the customers you already have because not only will it cost less but it’ll also yield better ROI than customer acquisition. A Harvard Business Review suggests that retaining an existing customer is about 5 to 25 times cheaper than acquiring a new one.

So, let’s take an in-depth look at data-driven ways that will allow you to reduce customer churn and improve retention.

What is Customer Retention?

Source: Forbes

Before getting into the details and strategies to improve customer retention and churn, it’s important to fully understand the concept. Customer retention refers to the set of actions that you, as a business owner, take to keep your existing customers from leaving. It starts with the very first interaction of a customer with your company and continues throughout the customer’s lifecycle or journey.

In order to take the right actions at the right time, you’ll need to use insightful customer retention analytics. Such data allows you to predict which customers are likely to churn and how you can stop them.

Why Customer Retention Matters?

Source: Mention-Me

According to the Gartner Group study, only a 5 percent increase in your customer retention can lead to a 25 to 125 percent increase in profits. It’ll only result in a net negative for your business if you spend a huge amount of money to acquire new customers but fail to retain them. That’s why customer retention is critical for the profitability and growth of your organization.

How to Calculate Customer Retention Rate?

Retention rate is basically the percentage of the customers that your businesses manage to retain in a specific period of time. It’s the complete opposite of your business’s customer churn rate. d

For example, if your business had 1,000 customers at the month’s start and you gain 160 customers and lose 80 during the month, then you’ll have 1,080 customers in total at the month’s end. So, the retention rate will be:

((1,080 – 160)/1,000) x 100 = 92 percent

4 Important Customer Retention Analytics to Use

Source: GetTheMatic

As mentioned, retention analytics provides you with valuable insights that you can use to offer a personalized customer experience. According to the HubSpot stats, 93 percent of customers with excellent customer experience are likely to purchase again from your business. You can offer a personalized customer dashboard, emails, rewards, deals, discounts, and offers to ensure a better customer experience. The following are the most important types of retention analytics that you should use.

1. Perspective Analytics

The perspective analytics provides you with the data to understand what your customers think and want from your business. It allows you to offer the best and most relevant solution to your customers.

2. Predictive Analysis

It’s one of the most commonly used retention analytics and as the name implies it predicts the most probable future scenarios. For example, you can find out the batch of customers that might churn along with the reasons why. This way you can craft strategies to keep them from leaving your business.

3. Diagnostic Analytics

It provides you with the data that allows you to understand why a specific event happened. For example, you can have churn indicators to figure out why certain customers left. It’s a great way to learn about your weaknesses and how to overcome them.

4. Consumption Analytics

It’s also known as outcome analytics and it provides you with valuable data to learn about your customer behaviors against a specific outcome. You can use this data to learn how your customers are using your services and products and how you can improve their experiences.

Best Data-Driven Practices to Improve Customer Retention

Source: AgileCRM

You can use the following data-driven practices to improve your customer retention and reduce churn rate.

1. Use Your Customer’s Data to Change your Strategies

Source: Clickz

It’s critical for your business to use customer data and implement organizational changes as soon as possible to meet your customer’s expectations. Your data mustn’t be in silos because it only works as a barrier and keeps you from understanding your customers.

The first step is to organize your data around customers. It’ll provide you with a single view of your customers and you can achieve it in two steps.

Step One: Data Integration

Your business will have customer data on different touch points such as call center management system, marketing automation system, email marketing platform, point-of-sale system, and data warehouse. You’ll need to integrate that data using a customer journey analytics platform that offers ETLT (Extract, Transform, Load, Transform) capabilities.

Step Two: Customer Identity Matching

Now you’ll need to unify the integrated data by bringing together different pieces related to each individual customer. It’ll allow you to build robust identities to learn about each customer more deeply.

2. Use Behavioral Segmentation

Source: WebEngage

Many organizations still classify their customers based on their region, product type, and gender. Resultantly, the retention offers are largely undifferentiated and almost identical. On the other hand, behavioral segmentation allows you to create meaningful clusters of customers with desired characteristics. This way, you can treat each cluster differently according to their specific needs in order to ensure a personalized experience.

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      3.Utilize the Power of Artificial Intelligence and Machine learning

Source: FSDSolutions

Your retention rate will improve significantly, if you remember your customers and ensure respect, attention, and consideration during their entire lifecycle. However, using traditional analytics tools to mine insights against millions of different customer journeys is undoubtedly a slow and laborious process. That’s where AI-enabled tools equipped with machine learning algorithms come into play. They can sift through a more complex and much larger data set and provide you with insights to improve your customer retention.

Final Words

The large customer data volume that your organization possesses isn’t only a challenge but it also brings so many opportunities to the table. It’s important to bring your unstructured and structured data together. 

Consider using the data-driven techniques discussed above to turn your customer data into a meaningful source to make the most informed decisions. It’ll allow you to differentiate each customer interaction with your business and offer a personalized experience to improve your retention rate.