What is customer churn? A strategic guide.

The goal of any business is to attract customers and keep them. Businesses need to continue to figure out why customers are leaving and what they can do to be better. Identifying the reason for customer turnover starts with determining the customer churn rate. This guide outlines the business impact of churn, diagnoses its root causes and provides suggestions to improve customer retention to drive sustainable growth.

This post will cover:

What is customer churn?
How do you calculate customer churn?
What are the root causes of customer churn?
How to reduce customer churn
Analyse and improve customer retention with Adobe Customer Journey Analytics

Customer churn is the rate at which a brand loses its customers. Customer churn happens when a customer decides to stop using a company’s product or service. The higher the churn rate, the more customers are leaving your business for a competitor.

Businesses always want to minimise customer churn and improve customer satisfaction. By improving customer retention, companies can build long-term profitability by keeping many of their customers happy.

The churn rate is the percentage of customers lost over time, which is typically attributed to a lack of compelling brand experiences that meet their needs, wants or desires. Businesses need to know what their churn rate is to identify lost sales opportunities and refine their operations. Far from a static number, it is a leading indicator of a brand’s inability to meet evolving consumer desires.

Why is predicting churn important?

Businesses can break down churn into components that they can use to make predictions. Running a predictive base churn rate on customers who exhibit certain behaviours, such as irritation or indifference during the sales process, helps businesses reduce churn.

Reducing churn offers major benefits for companies. It costs money to acquire a paying customer. It's better to keep existing customers paying on an ongoing basis than to continually spend money trying to acquire new customers for a single transaction.

To calculate churn, decide on a timeframe within which to examine performance. Divide the number of lost customers from one period to the next by the total number of customers in the former period, then multiply by 100.

The goal is to see how many customers remain at that lookback window. It’s essentially a division problem. For example, if a company has 100 subscribers on 1 January and 90 subscribers on 1 February, the churn rate for that period is 10%.

Additionally, some companies consider seasonality or other specifics within a timeframe that could change the calculation.

Predicting customer churn.

Predicting churn can uncover new considerations and businesses often create models that can predict specific customer behaviours, to see how those behaviours might affect churn.

For example, a business may look at the number of website log ins as one of the factors for predicting churn. If the number of log ins drops by a certain percentage, that could indicate a risk. A business could then take that information to identify customers who are at risk of churning and target them specifically.

Businesses usually have calculations to predict the number of customers or the number of subscriptions based on their churn rate or churn rate indicators. However, one of the most important insights that comes from a churn rate is calculating profit or revenue.

To solve churn, you must first diagnose its strategic root causes. While individual reasons can vary, they typically fall into three high-level categories that a leader can influence.

• A disconnected customer experience.

When a customer's journey is fragmented and inconsistent across your website, mobile app and support channels, it creates frustration. A lack of seamless, omnichannel engagement can be a primary driver of customer dissatisfaction and ultimately, churn. For a business-to-business (B2B) company, the customer expectation could be post-sales service and support. If the customer doesn’t get that support, the next contract cycle is likely to fall through.

If the customers are unsatisfied with their current experience with a brand, they will leave. Considering the different factors that influence churn can help to keep customers happy.

• Failing to evolve with customer needs.

The customer relationship doesn't end after the first purchase. Brands that fail to demonstrate ongoing value through relevant content, proactive communication and personalised offers often see their customers lose interest and drift away to competitors. To identify why customers leave, businesses should start by identifying what they’re not delivering to their customers. There are so many competitors serving the same consumer need, which means businesses need to satisfy every customer need to reduce churn.

• Ineffective or reactive customer support.

Poor customer service is one of the fastest ways to lose a customer. Reacting to problems is not enough. A lack of proactive support, anticipating issues and keeping in touch to customers before the customer needs support are all missed opportunities to build loyalty and prevent churn.

The impact of customer churn.

Churn rate can significantly affect financial performance and forecasting. Let’s say a company that sells enterprise software gets 100 new customers in a month, but by the following month, they’ve lost 10 customers and now have 90. That’s a 90% retention rate, which might not seem bad. But if those 10 customers are responsible for 80% of revenue, the company has lost their most important customers.

The revenue impact from that churn rate is astronomical — while the customer churn rate is only 10% , the revenue churn rate is 80%. On the other hand, if a customer loses 10 customers that account for 20% of the revenue, the impact is not as harsh. Looking at multiple results of churn provides a more complete snapshot of the health of a business.

To secure the investment needed to combat churn, a CMO must frame the problem in terms of its impact on the C-suite metrics that matter most.

• Reducing profitability and customer lifetime value (LTV).

A high churn rate is a direct drain on profitability. Retaining customers allows you to build on the initial acquisition cost and maximise lifetime value.

• Increasing customer acquisition costs (CAC).

When you lose customers, you are forced to spend more on marketing and sales to constantly replace those customers. This creates a treadmill of expensive acquisition that can mask underlying problems with your product or customer experience (CX), driving up your overall CAC.

• Damaging brand reputation and market perception.

Customer sentiment is now more public than ever before. A high churn rate is often a symptom of a poor CX, which can lead to negative reviews and word-of-mouth that damages your brand's reputation and makes it harder to attract new customers.

There are several ways that businesses can reduce customer churn. Leveraging AI agents to provide product customer support, A/B testing and offering page-level heatmapping on exit pages are all solutions that can provide value to customers and improve retention.

• Leverage predictive analytics, AI and machine learning to identify at-risk customers.

The most powerful way to reduce churn is to predict it. By analysing customer behaviour data, you can build models that identify the signals and patterns that occur before a customer stops using your product or service. The business impact of this approach is significant. A recent report from McKinsey on using AI to power the next-best experience found that one company was able to cut churn by 10% by using predictive models to deliver proactive, personalised interactions.

The solution: Adobe Customer Journey Analytics allows you to use algorithmic attribution to compare which marketing channels are responsible for specific page-level conversions and automatically assigns appropriate attribution weight at each channel touchpoint. Additionally, the Data Insights Agent enables marketing leaders to learn which web landing pages have the most exits month on month.

• Automate personalised engagement to demonstrate value.

Once you've identified at-risk customers, you can use automation to deliver proactive, personalised retention campaigns. This could be a targeted email with helpful content, a special offer or a notification about a new feature. These automated journeys keep your brand top-of-mind and reinforce the value of your product or service.

The solution: The Product Support Agent in Customer Journey Analytics allows teams to diagnose and escalate product issues through self-service support. You can use natural language prompts to get quick answers on high-level questions. Another feature that is in development is integrating AI Assistant to use chat logs and issue descriptions, providing contextual insights to resolve product issues.

• A/B test to identify optimal customer experiences.

By analysing the actions of the customers who leave, businesses can identify some potential causal factors and run tests on website landing pages. For example, a business that has lost thousands of dollars identified an increase in bounce rate. This company then assessed all exit pages from their website to determine where users are getting confused or frustrated. A/B testing can be run on those pages to improve overall usability and to better align webpage content with user expectations.

The solution: Quantum Metric, a third-party integration with Customer Journey Analytics allows you to visually heatmap how users engage with landing page content. You can view heatmaps by clicking the page you want to apply heatmapping to in Customer Journey Analytics.

Analysing customer churn rate provides an opportunity for a business to re-evaluate their offerings and consider improvements. By looking at the churn rate with both long- and short-term lenses, a business can determine whether the cause of increased churn is a short-term problem, like an issue with the website or a long-term problem, like a disruption in the industry. By paying attention to churn rates, businesses can continually evaluate the experiences they provide to customers and keep evolving to meet their audience’s expectations.

To find out how Adobe Customer Journey Analytics can help your business begin to diagnose why customers are leaving, watch this overview video now.