For any business that depends upon recurring revenue from in-contract customers, customer retention rate is a strong predictor of long-term profitability. There is a reason for this. Today’s customers are increasingly more aware and have a very low barrier to switching their providers. With just one click of a button, they can cancel ongoing relationships and switch to a new provider with equal ease.

For recurring revenue businesses, this situation gets further complicated because of the very high costs of new customer acquisition. For example, in the home security and automation industry, while the recurring monthly revenue (RMR) lingers around $46, the cost of acquiring this same customer can rise to as high as $400. This essentially means that in the first year, there is hardly any profit from this customer. On top of that, if the customer cancels, that’s a double whammy because the company not only loses all the money spent on acquiring the customer, but it will have to spend an equal amount again to replace the lost customer revenue.

No wonder in industries like home security, pest control, deregulated energy providers, home warranty and so on, CXOs are obsessed with moving the needle on their customer retention metrics.

Economics Of Customer Cancellations

First, let’s determine how customer cancellations affect the financial aspects of the business — with some hypothetical figures. For this calculation, let’s focus on an example of a fictitious pest control company with 500,000 customers.

Like many other recurring revenue industries, pest control companies see high customer churn. After talking to several leaders in the industry, we found that an average pest control company can have an annual churn of around 40%. This is huge! It means that our fictitious company will lose 200,000 customers by the end of the year.

Now, if the average revenue per customer is $250, it means the company would lose $50 million in revenue from 200,000 canceled customers. Here, we are not even accounting for acquisition costs.

In competitive markets, this is a significant headwind for a company aspiring growth and profitability.

How Can You Reduce Customer Cancellations?

Here are some insights we have developed after analyzing customer churn at several recurring revenue businesses:

• If we divide the customer base into high, medium and low predicted cancellation risks, based on my experience and observations, the top one-third will cancel at a 10-times higher rate than the bottom one-third.

• Similarly, ranking locations by risk showcases that higher-risk locations identify cancellations three times more than the lower-risk branches.

With these insights, if we focus on moving customers from high-risk segments into low-risk segments, we can deliver up to a 10% boost in retention rates.

Lowering The Churn Risk Of High-Risk Customers

Identifying high-risk customer segments and moving them to low-risk segments requires a comprehensive understanding of the needs, pains and churn risk for every customer — long before a customer decides to cancel. This can be achieved with a five-point action plan:

1. Leverage Artificial Intelligence (AI): AI helps companies like Amazon, Netflix and Google better understand customers in an attempt to accurately predict their behavior. Companies can leverage the same technology to predict complex risk patterns, thereby proactively engaging with every customer before they choose to cancel.
2. Use Multiple Prediction Models: Using multiple machine learning models allows you to analyze risks from multiple angles, reveal retention opportunities and enable micro-segmentation based on multiple customer health attributes.
3. Leverage Insights From Customer Interactions: Interaction insights assist with identifying addressable, lower-cost retention opportunities based on what customers are saying (e.g., service issues, multiple callbacks, competitor offers, etc.), as opposed to more expensive and difficult opportunities uncovered by traditional and less-reliable models (e.g., low FICO, high price, etc.).
4. Implement Location-Specific Strategies: Rank your branches by predicted customer risk and arm branch heads with visual analytics for high-risk routes, top-risk drivers and top-performing field reps to make every home visit, interaction, etc., risk-aware
5. Prescriptive Care Agent Guidance: A combination of a 360-degree view of customer health, predicted risk and next-best offers can be used to enable care agents to proactively engage with at-risk callers.

This five-point plan achieves significant revenue impact by focusing on understanding customers’ real needs, wants and sentiments, predicting their future behavior and, most importantly, by enabling your teams — branch heads, field reps, care agents, etc. — to take proactive action before time runs out.