Customer Lifetime Value (CLV): Definition
Customer Lifetime Value (CLV) is defined as the present value of a customer has for a brand or an organization because of the purchases they have made in the past or the predictable net profit associated with a customer, throughout their predictable life cycle of being associated with an organization or a brand. In other words, it is the value a business will derive from its customers during their association with a company.
Market research heavily relies on data. In this age of technology, most of the market researchers prefer to track everything, be it emails, social media, website visits, hits and clicks and even checkouts. There are some tools that might help measure the entire customer journey to start to finish and estimate the value of each touchpoint in that journey.
Customer Lifetime Value is an important metric as businesses would want to think about the overall market spending. CLV helps businesses make important decisions about different departments like- sales, marketing, product development and customer service and support. For example:
- Marketing: What amount of money will be spent on acquiring a new customer?
- Product: What changes in the product will best suit the need of the customers?
- Customer support: How much money needs to be spent to acquire talented customer support staff, so they provide impeccable customer service?
- Sales: What types of a customer should sales personnel spend the most time on trying to acquire?
CLV is a fundamental metric business use to measure and evaluate their performance campaigns. CLV is a long-time indicator of business health. CLV is calculated based on purchases made by customers in the past and the prediction of purchases they will make in the future. Let us understand the concept of historic CLV and predictive CLV.
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Customer Lifetime Value (CLV) Formulas
Customer Lifetime Value is calculated based on historical customer lifetime value and predictive customer lifetime value. The historic method analyzes the data collected in the past and makes judgment on the value of a customer purely based on the past transactions. On the contrary, predictive method as the name suggests, predicts the value of customers on the predictions of the purchases that are going to make in future. In the following section, we will learn more about CLV formulas.
Historic Customer Lifetime Value
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. If you have access to all the past transaction made by your customers, historic customer lifetime value can be calculated using the following formula:
Customer Lifetime Value (Historic)= (Transaction 1+ Transaction 2 + Transaction 3….+ Transaction N) X AGM
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.
There is one downside to calculating historic CLV, it gets extremely complex to calculate it on an individual basis.
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Predictive Customer Lifetime Value
Predictive CLV is 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
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)
R = monthly retention rate
D = monthly discount rate
This model is a predictive model and may not the exact forecast.
It is essential for businesses to do these calculations to get a real-time understanding of how valuable the customer is to a business or a brand.
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Importance of Customer Lifetime Value (CLV)
One cannot keep emphasizing enough the importance of customer lifetime value as it is one of the most important metrics for any business or brand. Customer churn is bad for any business. It is a known fact that acquiring new customers is costly than to retain existing ones. Thus to enhance customer retention strategy a business needs to keep calculating its CLV. Here are the five reasons why CLV is important in increasing profitability, retention and overall business success:
- It predicts real-time ROI
CLV helps an organization or business focus on the channels that will bring in maximum returns through most profitable customers. Optimize your marketing channels to understand the net worth of the customer rather than knowing only about the first few purchases. You are, therefore, maximizing your customer lifetime value in relation to the cost of customer acquisition.
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- Helps enhance marketing retention strategy
The amount of money you spend on your marketing campaign should not be just valued on the instant revenue it generates. For example, a marketing campaign should not just focus on just converting your one-time purchasers into repeat customers but should also add value to the average CLV of the segment of customers you are targeting as a business.
- Create an effective message for the target audience
A business or an organization should know to segment their customers base by CLV so they can improve the relevance of the marketing strategy to retain customers and reduce customer churn. An insightful way of doing this would be to segment your target audience and manufacture products to best suit their needs, this will send an effective message to your consumers and they will return repeatedly to make purchases.
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- Helps in understanding customer behavior
By organizing the data obtained from studying CLV, organizations can maintain a trait book to understand what triggered the first purchase. Once this analysis is done and results are obtained, similar triggers can be used with prospective clients or consumers in order to turn them into first time purchasers.
- A better output from customer support
When consumers feel valued, that is when they keep coming back to the brand to make purchases. To achieve this a brand must provide exceptional customer service to its clients. Clients who think positively about a brand, speak positively of the brand, thus increasing the Net Promoter Score. These are the consumers who will not only purchase regularly from you but will recommend you to their friends and family.
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