Understanding the value of each customer to your business is crucial for growth and profitability. Customer lifetime value (CLV) is a key metric that helps you measure the total revenue generated by a customer over their entire relationship with your business.
In this article, we’ll guide you through the process of calculating CLV, and how to use this information to drive business growth.
To calculate customer lifetime value (CLV), there are different formulas you can use. One common formula is to multiply the customer value (the average value of a sale multiplied by the average number of transactions) by the average customer lifespan (12). Another formula is to multiply the average total order amount by the average number of purchases per year and retention rate (3). At an individual level, you can simply multiply how much that customer spends by the average number of purchases per year and the average retention time (4). There are also online calculators and tools available to help you calculate CLV (5).
Importance of Customer Lifetime Value
Customer Lifetime Value plays a significant role in shaping your business’s future. Two main areas where CLV proves its worth are:
Business growth
A high CLV indicates that your customers are generating substantial revenue for your business. This revenue enables you to invest in expansion, marketing, and product development, ultimately driving business growth.
Customer retention
Focusing on improving CLV encourages businesses to develop strategies for retaining existing customers. Customer retention boosts loyalty and increases the likelihood of referrals, both of which contribute to a better Net Promoter Score (NPS).
Key Components of CLV
Before calculating CLV, it’s important to understand its key components.
The main factors that influence CLV are:
Average purchase value
The average purchase value represents the typical amount a customer spends on a single transaction. To calculate this, divide the total revenue generated by the number of transactions.
Average customer lifespan
This refers to the length of time a customer continues to do business with your company. It’s important to understand customer longevity and how it relates to customer loyalty.
Average purchase frequency rate
The average purchase frequency rate indicates how often a customer makes a purchase within a given time period. To calculate this, divide the number of transactions by the number of unique customers during the same period.
Calculating CLV
There are two main methods to calculate CLV:
Historical CLV
Historical CLV is calculated based on a customer’s past behaviour. This method involves multiplying the average purchase value by the average purchase frequency rate and then multiplying the result by the average customer lifespan.
Predictive CLV
Predictive CLV uses historical data and predictive models to forecast a customer’s future behaviour. This method is more complex but provides a more accurate estimation of a customer’s future worth. Two approaches for calculating predictive CLV are:
Predictive model
Predictive models use algorithms to analyse historical data and project future customer behaviour. These models can help businesses make informed decisions about customer acquisition and retention strategies.
Machine learning
Machine learning algorithms can be used to create even more accurate predictive models by continuously learning from new data. This approach can provide businesses with valuable insights into future lifetime value and inform their marketing and customer support efforts.
Increasing CLV
Once you’ve calculated CLV, you can focus on strategies to improve it.
Some effective ways to increase your customers’ lifetime value include:
Upselling
Upselling involves offering your customers higher-priced plans or upgraded packages. By persuading customers to opt for more expensive options, you can increase their value to your business.
Cross-selling
Cross-selling is the practice of offering related products or product bundles to customers.
This strategy not only enhances the customer experience but also boosts the average purchase value and total customer value.
Improving customer support
Providing excellent customer service can play a crucial role in retaining customers and enhancing their lifetime value.
By offering timely assistance and resolving issues effectively, you can ensure customer satisfaction and loyalty, which contribute to increased CLV.
In Summary
Calculating customer lifetime value is an essential step in understanding the overall worth of your customers and making informed decisions to grow your business.
By focusing on strategies such as upselling, cross-selling, and improving customer support, you can increase CLV and drive revenue, profitability, and expansion.
Investing time and resources in understanding and maximising CLV will help you build a sustainable and successful business.
FAQs
What is the main difference between historical and predictive CLV?
Historical CLV is calculated based on a customer’s past behaviour, while predictive CLV uses historical data and predictive models to forecast a customer’s future behaviour.
How can machine learning help in calculating CLV?
Machine learning algorithms can be used to create more accurate predictive models by continuously learning from new data, providing valuable insights into future lifetime value and informing marketing and customer support efforts.
Why is customer retention important for CLV?
Customer retention boosts loyalty and increases the likelihood of referrals, both of which contribute to a better Net Promoter Score (NPS) and increased CLV.
What role does customer support play in increasing CLV?
Providing excellent customer service can play a crucial role in retaining customers and enhancing their lifetime value, ensuring customer satisfaction and loyalty, which contribute to increased CLV.
How can upselling and cross-selling contribute to CLV?
Upselling persuades customers to opt for more expensive options, increasing their value to your business. Cross-selling offers related products or product bundles to customers, enhancing the customer experience and boosting the average purchase value and total customer value.