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Customer Lifetime Value (LTV) is a metric that tracks and estimates the total value of a customer to a business over their lifetime of purchases with a company. Also known as CLV, customer lifetime value has become a critical metric for driving growth in companies and maximizing profit in today s extremely tight-margin ecommerce market.

Tracking Customer Lifetime Value over time and comparing it against both previous periods as well as with other companies in the same industry when possible enables a company to better understand how well its products and services are connecting with customers and meeting their needs.

It also helps predict how likely a customer is to continue purchasing from the company and where improvements can be made to improve the company s products or services and the overall customer experience.

Small changes in the various steps of the customer experience can have major impacts on a customer LTV, and it’s critical to accurately and continually measure the increase or decrease in LTV against product changes and/or new customer support directives in order to know which efforts are resonating best with customers.

How to Calculate Historical Customer Lifetime Value

Customer Lifetime Value can be tracked on a historical (past) or predictive (future) model or a combination of the two depending on a company s need.

In a historical model, a very simple example of tracking LTV would be calculating the total number of purchases each customer has made in a fixed period (say 2 years), deducting the costs spent (advertising and marketing, for example) to acquire and retain the customer, and then averaging that net revenue over the total customer base to get the net customer lifetime value.

So in a historical model, if your business has 100 customers, each of whom has spent an average of $50 in the past two years, the total revenue for the company would be $5,000. If customer acquisition and retention costs totaled $3,000, the total net profit would be $2,000. Averaging this amount over 100 customers would generate a net Customer Lifetime Value of $20.

How to Calculate Predictive Customer Lifetime Value

A predictive customer lifetime value model would be similar to the historical model and would use many of the same data points, but it s a more complex model that also needs to include the predicted amount of revenue generated by a customer over a future period of time while taking into account the average length of time the customer can be expected to remain loyal i.e. continue purchasing products with the company.

In this case, to generate a reliable predictive LTV, the company would need to have models in place based on historical data to accurately predict how long the average customer remains with a company and how likely and frequently they are to continue making new purchases or remain active on a subscription plan.

How to Boost Customer Lifetime Value

There are countless ways to make improvements across the business to generate higher customer lifetime values. The key is to first have an accurate and efficient method for tracking CLV in order to know which initiatives are making the most impact on the customer lifetime value so that net profit can be maximized and the company continues to grow.

Examples of potential needle movers for boosting customer lifetime value include:

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