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Customer Lifetime Value

Natalie Samuels
  • Updated
Customer lifetime value (LTV) is the predicted total of all future revenues (or profits) that a particular customer will generate for a business. Using accurate estimates of LTV as the basis for marketing decisions will maximize the company’s revenues (or profits). The catch is that calculating accurate predictions of customer LTV is a significant challenge.
 

The Advantages of Utilizing Customer Lifetime Value

It is easy to always focus on the present, but this is often not the best way to tap into the full potential value of each customer. For example, looking at conversion rates and first purchases while ignoring the long-term value of customers may lead marketers to invest resources in acquiring “cheap” customers with low total revenue value, instead of paying more to acquire customers which will continue to deliver a steady stream of income for years to come. Likewise, marketers and retention experts should focus resources on nurturing customer relationships with those customers who will continue to be a source of substantial revenue over the long term, while conserving resources that would be wasted on low-value customers.

When a company has a reliable means of predicting LTV, it will be possible to better manage customer relationships, maximize the effectiveness of marketing and retention actions, optimize the resources invested in retaining each customer, and better attain accurate customer metrics.
 
In brief, the goal of using LTV is to focus on finding, nurturing, and retaining those customers which create the most value for the company over the long term.
 

The Difficulty in Calculating Customer Lifetime Value

Calculating customer lifetime value (LTV) requires accurate estimates of future events and is therefore very challenging. It is difficult to predict parameters such as how long a customer will remain engaged with a company and how much the customer will spend in each period, especially when the customer is new. Further compounding the challenge is the fact that the data required to perform the calculations may be hidden deep within multiple databases.

Some simplistic approaches try to lump customers into logical groupings such as all customers who came from a particular source, who live in a particular location, or who bought a particular product/service. More sophisticated approaches attempt to use well-known statistical techniques to try to predict the future, such as linear regression or Bayesian probabilistic models. However, all of these have large (or huge!) margins of error and therefore present a very risky basis when used for important marketing decisions.
 

The Optimove Approach to Calculating Customer Lifetime Value

At the core of Optimove’s ability to accurately predict the most effective marketing actions for each customer is a unique method of calculating Customer Lifetime Value for each new (and existing) customer. The customer LTV forecasting technology built into Optimove is based on advanced academic research and was further developed and improved over several years by a team of first-rate PhDs and software developers. This method is battle-tested and proven as an accurate and effective approach in a wide range of industries and customer scenarios.

Without revealing too much about the “secret sauce” of Optimove’s customer LTV forecasting technology, the approach combines continual dynamic micro-segmentation and a unique, mathematically-intensive predictive behavior modeling system. The former intelligently and automatically segments the entire customer base into a hierarchical structure of ever-smaller behavioral-demographic segments. This segmentation is dynamic and updated continually based on changes in the data. The latter is based on the fact that the behavior patterns of individual customers frequently change.
 
By merging the most exacting micro-segmentation available anywhere with a deep understanding of how customers move from one micro-segment to another over time – including the ability to predict those moves before they occur – an unprecedented degree of accuracy in customer LTV forecasting is attainable.

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