Published: 4 September 2024
Contributors: Teaganne Finn, Amanda Downie
Customer lifetime value (CLV) is the total worth of or profit from a customer to a business over the entirety of their relationship. It is one of the most important metrics for tracking customer experience and value.
As the name suggests, CLV looks at how valuable a customer is to the organization as a whole, not just during a single interaction.
The metric is key to understanding overall customer retention rates and customer loyalty. Rather than looking at individual transactions with a business, the CLV considers all potential transactions a customer has or will make during the full customer lifespan. It uses that information as a basis for calculating customer revenue.
There are two ways to measure customer lifetime value. The first is historic customer lifetime value and the second is predictive customer lifetime value. The historic CLV looks at how much an existing customer has already spent with the business. The predictive CLV is an estimate of how much a customer might spend.
The historic CLV is more straightforward than the predictive CLV. The latter requires an algorithmic process that tracks historical data and uses it to predict the duration of a customer relationship and its overall value. While it’s a bit more of a complex calculation, the predictive CLV might help the organization see which area of the customer journey needs further investment. Separately, the predictive model considers factors such as customer acquisition costs (CAC) and average purchase frequency rates.
The CLV—also known as the CLTV or LTV—can help an organization gauge customer loyalty and understand how much churn is occurring on an average basis. By understanding the CLV, an organization can better understand the needs of their existing customers and invest in those loyal customers.
Tracking CLV allows for organizations to make more informed decisions based on real values. The data collected is based on factors such as how long a customer typically buys from the business and how much they are spending over the lifetime of that relationship. By understanding these figures, an organization is more informed to build a strategy that focuses on growing customer relationships over time.
Understanding the CLV can also boost the quality of the products and services the organization offers, help with an organization’s overall decision making, and boost the average customer lifespan. An organization’s CLV should be a base to shape the overall business strategy, whether that be continuing to invest in retaining customers or a focus on bringing in new customers.
By keeping on top of customer data and CLV calculations, an organization can stabilize cashflow and help achieve more growth, lower churn rates and their overall bottom line. Knowing the metric isn’t enough; achieving value from the data requires an organization to act.
The net promoter score (NPS) is an important metric focused on how likely a customer is to recommend the produce or service. Unlike a CLV model, the NPS measures customer loyalty through a single-question survey. The CLV considers the total value that a customer brings over the entire relationship with the organization.
A customer satisfaction (CSAT) survey score, on the other hand, is a customer satisfaction metric based on specific moment in the individual customer journey. CSAT is directly linked to revenue and tangible touchpoints for understanding the lifetime value of a customer.
The CLV is a crucial measurement for an organization and knowing current customers’ lifetime values can help them develop targeted strategies to help ensure brand loyalty and maintain good profit margins.
The basic customer lifetime value formula is:
CLV = (customer value) x (organization’s average customer lifespan)
The formula tells the organization what the average customer is worth to the business throughout the entire customer lifecycle. There are more complex equations that might consider gross margin, operational expenses, among others.
Step one of the basic CLV model equations is to find the customer value. This requires the organization to find the average purchase cost and average frequency rate of a customer’s purchases, then taking those two numbers and multiplying them. An organization can find that information by looking at e-commerce analytics tools or retrieving an estimate. Another way is to implement a CRM to help ensure and confirm that the data is accurate.
The next step is finding the average number of years that a customer stays active divided by the total number of customers, which will end up being the organization’s customer lifespan. Once the organization has both of those figures, it can then make the customer lifetime value calculation.
Finding the customer lifetime value gets more complicated or less complicated depending on the size of the organization, its products and its business models. There are other formulas to consider when approaching the CLV, and it might be useful to look at the CLV by customer segments.
Identify what drives high CLV and use that information to target high-value customers through bolstered marketing efforts, paid ads and social media.
Identify actions to make less valuable customers more valuable. This might be through a loyalty program or improved customer support.
Coffee shop
There are various examples of calculating customer lifetime value, but one easy example is a coffee shop. The coffee shop has four locations with an average sale of USD 5. The typical customer is a local person who visits two times per week, 50 weeks per year, over an average of five years.
The formula: CLV = USD 5 (average sale) x 100 (annual visits) x 5 (years) = USD 2500
Software as a Service (SaaS) subscription
For this example1, a UX designer uses a subscription service that has multiple price plans, but on average the customer is spending USD 20 per month. A customer typically subscribes for four years and uses a monthly payment model.
The formula: CLV= USD 20 (average sale) x 12 (annual purchase) x 4 (years) = USD 960
Car dealership
A car dealership is a good example of a business with a higher average sale amount, but a lower purchase volume. Customer A buys a new car for USD 40,000 every five years. Based on customer expenditures and purchase frequency, Customer A is loyal to the brand and keeps buying cars over the span of 15 years.
The formula: CLV= USD 40,000 (average sale) x 0.2 (annual purchases) x 15 (years) = USD 120,000
Build a loyalty program
Reward programs have become popular and effective. By offering discounts and perks, the business is motivating a customer to keep coming back. This type of approach can drive higher CLVs and give customers an opportunity to spread positive messaging.
Example: A company offers a discount code to a customer if they reach a certain spending amount. This makes the customer feel special and appreciated, while also getting them to continue shopping.
Increase average order value
One way to boost an organization’s average CLV is by making customers spend more on goods and services. A strategy might be offering free shipping or bonuses to customers who reach a certain expenditure amount. This type of incentive can entice the most valuable customers to spend more in a single purchase, return for future purchases and encourage them to share such bonuses to new customers.
Example: When a customer is purchasing goods online, the business can offer free shipping after a specific expenditure amount. This might incentivize the customer to add more of what they love and complete the purchase in order to get the free shipping reward.
Create personalized experiences
Customer feedback has shown that shoppers want real-time personalized experiences. Organizations should aim to segment customers based on search history, purchasing behavior and other datapoints in order to retain the best customers.
Example: When a customer is browsing online, search results can align with the customer’s purchase history and highlight discounts on favorite products or new items they are more likely to buy.
Streamline customer experiences
Separate from creating a personalized shopping experience, customers also want a streamlined experience no matter where they are purchasing the product or service. Customers are coming from multiple touchpoints and expect a seamless omnichannel experience.
Example: A customer sees an ad offer on a social media platform. When they click the link, the branding and messaging that appears should reflect what existed in the ad. And if the customer needs support in a purchase, the customer support agent should be aware of the offer from the ad.
Optimize onboarding process
Some organizations offer a product or service that, once purchased, the customer is left to figure out how to use on their own. An organization should make sure it is not leaving its customers behind and instead following through postpurchase. This develops a better customer relationship over time.
Example: Once the customer makes a purchase, it’s important for a company to continue the messaging. There should be clear communication on everything from delivery estimates and set up to support services and return policies.
Improve customer service
Organizations can see CLV values fall drastically with bad customer service. They should focus on making each interaction positive to help ensure customer loyalty, for both short and long-term sentiment.
Example: An organization should train its customer support team on all aspects of customer engagement, including communication and problem-solving. And they should be expected to have in-depth knowledge of the goods or services for which they are providing support.
Use omnichannel support
Customers seek assistance at any point in time, from anywhere that is convenient for them. Organizations need to offer omnichannel support options including phone, email and social media platforms. This smoother path to support anytime, anywhere often results in higher customer sentiment and customer retention.
Example: A company should implement chatbots into their customer support strategy to speed up response times and provide 24/7 support.
Upsell and cross-sell
An organization might consider upselling to existing customers rather than bringing in a new one. This type of strategy might require a marketing strategy that entices the customer to buy a more expensive item or multiple products or services at once.
Example: A customer might be looking at a product that is the base model. An organization might suggest the upgraded version by highlighting the additional benefits and long-run cost savings.
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Footnotes
1 What is customer lifetime value (CLV) (link resides outside IBM.com), Forbes, 14 June 2024