What Is Customer Lifetime Value? The Customer Lifetime Value In A Nutshell

One of the first mentions of customer lifetime value was in the 1988 book Database Marketing: Strategy and Implementation written by Robert Shaw and Merlin Stone. Customer lifetime value (CLV) represents the value of a customer to a company over a period of time. It represents a critical business metric, especially for SaaS or recurring revenue-based businesses.

Understanding customer lifetime value

Early adopters began using the concept soon after and it has largely kept pace as the speed and complexity of the buyer journey increased at the turn of the millennium.

Customer lifetime value represents the total amount of money a customer is expected to spend on a business or product during their lifetime. The CLV of a Ferrari owner may equate to $2 million given the target demographic and quality or longevity of Ferrari’s sports cars. The CLV of a coffee addict to Starbucks may be just as lucrative when one considers how many cups of coffee are consumed over decades. 

For businesses, this is an important value to know because it determines how much money should be spent acquiring new customers versus retaining existing customers. Ultimately, CLV is a measure of customer relationship profitability, which should be higher than the cost of acquiring the customer in the first place.

Calculating the customer lifetime value

Customer lifetime value can be calculated by multiplying the average order value, purchase frequency, and average customer lifetime measured in years. 

For example, consider a long-distance runner who on average purchases a $220 pair of shoes twice a year for 5 years. The customer lifetime value is then 220 x 2 x 5 = $2,200. 

There are two general CLV calculation models.

Historical customer lifetime value 

As the name suggests, this model uses previous data to predict customer value and is useful for businesses whose customers only interact with them over a certain period of time. 

Importantly, the historical model does not consider whether the customer will continue to purchase from a business in the future. 

Predictive customer lifetime value 

Predictive customer lifetime value forecasts the buying behavior of existing and new customers. It can be used to identify the most valuable customers, products, or services, and improves retention.

Why is customer lifetime value important?

Customer lifetime values provide clarity on customer acquisition and retention costs, but it also plays an important role in:

  • Value-based customer segmentation – when an organization can identify its most valuable customers, it can send targeted VIP offers to reward loyalty. Data describing the demographic these buyers occupy can then be used in lookalike modeling. In this strategy, the business defines the attributes of a high-value customer and then looks for similar traits in other segments or demographics. Lastly, value-based customer segmentation can be used to upsell low-value customers to increase their CLV.
  • Competitive advantage business has never been more competitive, particularly online. Customer lifetime value is a useful tool for market differentiation because it maintains a focus on the customer.
  • Growth – some companies use customer lifetime value as justification for spending more money acquiring new customers. However, a better growth strategy is to reduce the churn rate by investing in customer retention, thus reducing churn and by incentivizing repeat customers spend which are both critical factors for businesses based on recurring revenues.

Key takeaways:

  • Customer lifetime value represents the value of a customer to a company over a predetermined time period.
  • Customer lifetime value can be calculated using historical or forecasted data by multiplying average order value, purchase frequency, and average customer lifetime measured in years.
  • Customer lifetime value allows an organization to focus its efforts on high-value customers where the return on investment is likely to be more significant. This strategy can be strengthened by increasing customer retention and reducing the churn rate.

Connected Business Frameworks

The Net Promoter Score (NPS) is a measure of the ability of a product or service to attract word of mouth advertising. NPS is a crucial part of any marketing strategy, since attracting and then retaining customers means they are more likely to recommend a business to others.
The customer journey – sometimes called the buyer or user journey – tells the customer experience with a businessbrand, product, or service. A customer journey is an alternative approach to other linear models like the sales funnel which hypothesizes that most customers follow the same path.
It’s possible to identify the key players that overlap with a company’s business model with a competitor analysis. This overlapping can be analyzed in terms of key customers, technologies, distribution, and financial models. When all those elements are analyzed, it is possible to map all the facets of competition for a tech business model to understand better where a business stands in the marketplace and its possible future developments.
Customer experience maps are visual representations of every encounter a customer has with a brand. On a customer experience map, interactions called touchpoints visually denote each interaction that a business has with its consumers. Typically, these include every interaction from the first contact to marketing, branding, sales, and customer support.
The term “user experience” was coined by researcher Dr. Donald Norman who said that “no product is an island. A product is more than the product. It is a cohesive, integrated set of experiences. Think through all of the stages of a product or service – from initial intentions through final reflections, from first usage to help, service, and maintenance. Make them all work together seamlessly.” User experience design is a process that design teams use to create products that are useful and relevant to consumers.
Gamification borrows key concepts from the gaming industry to encourages user engagement and experience. Some of those concepts include competitiveness, mastery, sociability, achievement, and status. The application of game principles to the business context, companies can design products that are more enjoyable to users and customers.
The bundling bias is a cognitive bias in e-commerce where a consumer tends not to use all of the products bought as a group, or bundle. Bundling occurs when individual products or services are sold together as a bundle. Common examples are tickets and experiences. The bundling bias dictates that consumers are less likely to use each item in the bundle. This means that the value of the bundle and indeed the value of each item in the bundle is decreased.

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