Customer Lifetime Value CLV Calculation Methods

Customer lifetime value (CLV) is one of the most important components of marketing spend for an organization. It defines a metric prediction of a profit associated with a customer’s future relationship with a brand or an organization. The model is based on multiple factors that offer varying levels of sophistication and accuracy depending on various predictive analytics techniques.  

Since the duration of a future relationship cannot be defined by an absolute number – a prediction of this number is considered. The customer lifetime value is also called the lifetime customer value (LCV) or the life-time value (LTV). The customer satisfaction level (CSAT) and the customer effort score (CES) are important aspects of the customer lifetime value.

Customer lifetime value influences most marketing analytics metrics including marketing mix modeling and marketing ROI. It finds its origins in the practice of CRM but there is a renewed focus on the importance of long-term customer relationships along the customer journey.

Learn more: Customer Satisfaction Survey Questionnaires + Templates

Customer Lifetime Value (CLV) calculation: Methods with Steps

As discussed above, the customer lifetime value calculation defines marketing spends and provides a gap analysis with understanding the behavior of existing and prospective customers. CLV is a cornerstone of market research and is an important metric in decoding the profitability of an organization.

There are multiple methods for calculating customer lifetime value. The method chosen depends on the level of data collection and the success metrics for an organization. Some of the most widely used methods of calculating the customer lifetime value are:

Historic Customer Lifetime Value Calculation Method with Steps

Historic CLV is the sum of gross profit from all the past purchases made by an individual customer. The sum of all gross profits is the value of the transactions. To calculate historic customer lifetime value, assuming you have access to all past purchases, you can use the following formula:  

Customer Lifetime Value (Historic)= (Transaction 1+ Transaction 2 + Transaction 3….+ Transaction N) X AGM

Where:

N= Last Transaction made by the customer at your store

AGM = Average Gross Margin

Calculating CLV based on net profit gives a business the actual profit a customer is contributing to the business. Historic customer lifetime value takes into account customer service cost, cost of returns, acquisition cost, marketing cost etc. However, the downside to calculating historic CLV is that it gets extremely complex to calculate it on an individual basis.

Predictive Customer Lifetime Value Calculation Method with Steps

Predictive CLV is a more accurate value, that is predicted through an algorithm based on predictions of purchases that will be made by a consumer i.e the total value a customer will eventually give to a business over their entire lifetime.

In practice this can be a little difficult to achieve considering the fact there may be fluctuation in price, discounts offered etc. There are a number of ways of calculating predictive CLV that vary widely in complexity and accuracy.

Simple Predictive CLV can be calculated using the formula:

CLV= ((Tx AOV) AGM) ALT

Where:

T = Average monthly transactions

AOV= Average order value

ALT= Average Customer Lifespan

AGM= Average gross margin

This equation becomes gross margin contribution per customer lifespan (GML). Therefore,

                                                                         CLV= GML (R/1+D-R)                                                                   

Where:

R = monthly retention rate

D = monthly discount rate

This model is a predictive model and may not be the exact forecast.

Learn more: Net Promoter Score (NPS) calculation

Lifespan Customer Value Calculation Method with Steps

Another widely used method to calculate the CLV is the lifespan customer value calculation. This method requires you to have the customer value and multiply that by the customer lifespan. This CLV calculation method consists of 5 steps. They are:

  1. Calculate the average purchase value: This number can be derived by dividing the revenue of the organization by the total number of purchases in the year. This timespan should be of a fixed time, like a year or 2 years.
  2. Calculate the average frequency purchase rate: This number can be derived by dividing the number of purchases by the unique customers that made a purchase over that time period.
  3. Calculate the customer value: The average customer value can be derived by multiplying the average purchase value and the average frequency purchase rate.
  4. Calculate the average customer lifespan: The customer lifespan can be derived by averaging the number of years does a customer buy from a business.
  5. The last step would be multiply the customer value and the average customer lifespan. This can help calculate how much revenue a customer can contribute in their life cycle with you.

This research method, although extensive isn’t conclusive to deriving the lifetime customer value. This method, however, is widely used and is very similar to the predictive customer lifetime value calculation method.

Cohort Analysis

The cohort analysis method is another method that is used to calculate the customer lifetime value. This calculation method bunches today customers with similar characteristics. This helps organizations draw conclusions between groups of people. However, if there are any changes in market dynamics, this reporting isn’t as conclusive.

Individualized CLV

Another CLV calculation method is where organizations look at a broader perspective of calculating value. This is primarily by evaluating distribution methods, marketing methods, landing pages, campaigns, etc. This means that the spend of social media marketing vs the spend of digital marketing can be calculated. This helps to manage ROI.

All the above customer lifetime value (CLV) calculation methods are used by organizations depending on their data collection methods and their reporting objectives.