Understanding Customer Churn: Using Data To Keep Your Customers Coming Back for More

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Introduction

"Retention is the new acquisition. It's far more cost-effective to nurture the customers you have than to constantly chase new ones."

This quote by Brian Balfour, founder and CEO of Reforge and ex-VP of Growth at HubSpot, encapsulates a fundamental shift in how successful businesses have started approaching growth. (Brian Balfour on Why Retention Matters More Than Benchmarks (clevertap.com))  

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While acquiring new customers has always been a priority, retaining existing ones is now being recognized as a crucial indicator and driver of sustainable growth. The graph below perfectly encapsulates how trends in customer retention vs acquisition have evolved over time.  

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The changing trends owe themselves to increased competition and cheaper modes of product distribution to name a few. (Acquisition is Easy. Retention is Hard. | Product Habits)

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What of a business that has an attractive sales pitch and successfully acquires customers every day but is unable to sustain customer interests and provide the desired customer experience. It’s not an ideal scenario for a business that is there to stay and leave a lasting mark and legacy.  

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The following article expands on how retaining customers is the way to go in this era of unparalleled market competition. It further delves into how we can salvage a vastly available resource: data, to grant our businesses a competitive advantage of scalable and sustainable growth that is customer focused.  

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What is Customer Churn and Why is it Important?

Understanding and mitigating customer churn—the rate at which customers stop doing business with an entity—is paramount for any company looking to thrive in today’s competitive market.  Customer churn is an important Key Performance Indicator (KPI) that has a direct impact on a company’s profitability. Research by Bain & Company indicates that increasing customer retention rates by 5% can boost profits by 25% to 95%. This is because retaining customers often costs significantly less than acquiring new ones. Moreover, loyal customers tend to spend more overtime, providing a stable recurring revenue.  

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For example, SaaS companies, which operate on subscription models, are particularly sensitive to churn rates. A slight increase in churn can have devastating effects on recurring revenue. Zuora's Subscription Economy Index (SEI) highlights that companies with high retention rates grow revenues 3-4 times faster than those with low retention rates. This highlights the need for businesses to focus on retention strategies to ensure long-term growth and stability. (Acquisition is Easy. Retention is Hard. | Product Habits)

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Real World Success Stories:

Let us now look at some businesses that are succeeding in their respective domains by focusing efforts on customer retention and adding value for their clients.  

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Netflix, with a low monthly churn rate of 2.5% stands apart in comparison to other newer platforms. This impressive feat is a direct result of extensive library content that is shown customized to the user’s interests.  Netflix Boasts Best Monthly Churn Rate, Disney+ Comes In Second 04/15/2021 (mediapost.com).  

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Another example is that of the popular fitness company ‘Peloton’ that boasts a monthly churn rate of just 1.1% owing to its focus on community engagement and exclusive content that creates a sticky user experience that keeps customers coming for more. How to Calculate Churn Rate in 5 Easy Steps [Definition + Formula] (hubspot.com)

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Measuring and Analyzing Churn:

To accurately measure and analyze customer churn, you need data that is measurable and capable of being analyzed. Having data ensures you can create data-driven experiences for customers that are personalized and are catering to their unique needs. Here's how to measure and analyze churn.

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Measuring Churn:

Before making complex calculations take these 2 steps to ensure you’re accurate measuring churn.

1. Defining Churn: Regarding what constitutes as ‘churn’ might vary depending on the context of the business. For instance, for a subscription-based service, churn might mean a customer canceling their subscription for a particular product whereas for a retail business, it could mean a customer who has not made a purchase within a certain amount of time.  

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2. Calculating Churn Rate: The churn rate is typically calculated by dividing the number of customers lost during a particular time by the number of customers at the start of that period. For example, if a company had 1,000 customers at the beginning of the month and lost 50 by the end, the churn rate would be 5%.

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Churn Analysis:

Data Scientists and data analysts utilize various tools and techniques to identify the factors that result in churn. These can include but are not limited to:

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1. Cohort Analysis: By grouping customers based on shared characteristics or user behaviors, patterns can emerge regarding certain groups being more prone to churn than others. This can then be investigated further to help produce a solid plan to counteract the phenomenon. For example: sign up dates can be used to look at user behavior over time. If more customers that churn do so within a brief period of signing up, this could mean a bad user experience or more support and help that is required to mitigate and help make onboarding for subscriptions or products more seamless.  

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2. Customer Feedback Analysis: Analyzing customer feedback, including surveys, reviews, and social media comments, can help identify common reasons why customers leave. Sentiment analysis tools can automate the process of understanding customer emotions and opinions. To know more about how to use sentiment analysis to help your business, click here.  

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3. Behavioral Segmentations: Segmenting customers based on their behavior throughout their journey for e.g.: purchase frequency, frequency of log ins, product usage, interaction with customer support etc. may help identify patterns and point towards areas that require improvement.  

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4. Customer Journey Mapping: This involves mapping the entire customer journey to understand key touchpoints that may contribute to churn. By identifying these critical moments, businesses can pinpoint where customers are likely to disengage. For example, analyzing traffic at various stages of your website can provide valuable insights into where customers lose interest in the funnel. It might reveal that site loading times are driving users away or highlight other issues that need attention. Once these factors are identified, they can be promptly addressed, preventing small problems from escalating into significant challenges for the business.

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5. Predictive Modeling: This is a powerful tool for identifying at risk customers before they churn, so highly customized solutions can then be provided. Different machine learning algorithms can be utilized for this purpose to predict churn based on historical data.

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Metrics To Use While Conducting Customer Churn Analysis

Understanding how to conduct customer churn analysis is only the first step. Officially carrying it out requires the use of the right metrics to understand why customers left your business. Here are some common but crucial metrics to use in your customer churn analysis so that you can intervene immediately and convince your customers to keep buying from you:

1. Customer churn rate

The customer churn rate is the percentage of customers who have stopped using your product or service within a given period, typically one month or one year. To calculate the customer churn rate, divide the number of customers who have left during that period by the total number of customers at the start of the period.  

2. Monthly recurring revenue (MRR) churn

This metric helps you assess the percentage of monthly recurring revenue that you may have lost after a particular number of customers unsubscribed to your services. This is best calculated by dividing the total MRR lost due to customer churn in a particular period by the total MRR at the start of that time.

3. Customer lifetime value (CLV)

The customer lifetime value is an estimate of the total revenue you can expect from a single customer over their lifetime. This metric helps measure the effectiveness of your marketing and sales strategies that are being leveraged to retain customers.

4. Customer acquisition cost (CAC)

The CAC is the money spent to acquire a new customer. It helps determine whether it is more cost-effective for a business to focus on acquiring new customers or is it better to focus on retaining existing customers.

5. Net promoter score (NPS)

The net promoter score measures a customer’s satisfaction and loyalty to your product or service. By using survey responses, this metric measures the likelihood of customers recommending your product or service to other people. The higher the score, the higher the level of satisfaction the customer had while using your product.

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Best Practices for Reducing Customer Churn

While all the guidelines and metrics discussed earlier can help reduce customer churn, there is a set of best practices that will ensure this outcome is achieved efficiently:

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1. Keep track of what users are doing

Analytics reveals the behaviors (or lack thereof) that best predict churn. Use real usage data to define account health—identify which features are used and how often. By pinpointing actions linked to long-term retention, you can spot users veering off track and proactively engage with them.

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2. Segment your users into cohorts and fully utilize cohort analysis

A cohort is a user group that shares similar demographics or behaviors. By putting users into cohorts, you can keep track of what your users are doing, or might do, while interacting with your product. Pair it up with an analytics tool like Heap to identify which cohorts need attention and which ones will drive more revenue.

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3. Keep everyone on the same data through effective data consolidation

Consolidate all your data on your customers so that your product, marketing, sales, and customer success teams can identify which customer cohorts to target and what steps can be taken to ensure they get a good user experience while interacting with the business’s product or service.

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4. Make it easier for customers to interact with your product

Sometimes, your customers may not know how to use your product or make the most out of your service. Create instructional materials, like webinars, articles, white papers, and training courses, so that customers are not left to figure things out on their own. Supplement this with discounts and upsells to demonstrate your value and competence.

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5. If you lose customers, learn where did they churn

Many dissatisfied customers won’t complain. While interviews and exit surveys provide insights, they often lack clarity on the real problems that were faced. To outpace competitors, focus on offering a better product, superior service, or innovative solutions. Align user feedback with behavioral data to identify pain points, such as where users struggle or experience delays. This is where analytics tools excel.

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Conclusion:

From a business perspective, understanding and addressing customer churn is crucial for any business aiming to enhance profitability and growth. By leveraging data to identify churn drivers, predict at-risk customers, and implement targeted retention strategies, businesses can significantly reduce churn rates. In a competitive market, retaining customers through data-driven insights not only saves costs but also fosters long-term customer loyalty, ensuring sustained business success. Today's data driven world brings with it a plethora of opportunities to work with various sorts of data to get to know our customer base better and tailor our businesses to best fit the customer's needs.

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At Data Pilot, we understand the critical role of customer data in decision-making. With our data-driven expertise and a comprehensive toolkit of robust data analytics and BI tools, we help companies in the retail space extract business value from their data.

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Before we begin, we take the time to understand your business vision and goals, enabling us to deliver cost-effective recommendations and solutions that address your biggest challenges. If you’re a retailer, contact Data Pilot today so that you can start leveraging your customer data today and use it to drive customer loyalty.

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Written by:  Nawal Asim