An experienced sales and marketing leader, Stephanie O'Dear currently serves as head of marketing for the Retirement Solutions Group at Empower Retirement. In this role, Stephanie O'Dear works closely with a team of data scientists to create models to help the company evaluate and pursue leads. One of those models is the Customer Lifetime Value (CLV).
As its name indicates, Customer Lifetime Value aims to predict the total amount of revenue that a customer will generate throughout his or her relationship with a company. Businesses typically calculate and express it within the parameters of a certain period of time, such as six months or a year, as there is no accurate way of predicting how long a customer will remain with a business.
There are a number of ways in which a company can determine CLV, from the basic to the in-depth. The most basic estimate is available by subtracting the customer's percent chance of making a repeat purchase from the number one, then dividing the customer's average order value by the resultant number. From this total, the company subtracts the cost of acquiring the customer to get a CLV.
Many companies use CLV to determine which customers are driving the most value for the company and thus to make decisions about the allocation of targeted marketing dollars. CLV may also be a predictive tool in understanding the potential impact of customer retention or other efforts, as it can determine how CLV would grow with increased average order value or rate of repeat purchase. CLV is just one of the many tools available in today's savvy marketer's toolkit which combines available data and predictive modeling for optimal results.
