Customer Lifetime Value
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Table Of Contents
What Is Customer Lifetime Value (LTV)?
Customer lifetime value or LTV is the company's total revenue from one customer during its lifetime. It helps predict customers' responses and spending on their products and services.
The importance of customer lifetime value lies in forecasting the company's future sales. It enables individual businesses and organizations about future insights on product development, marketing, and customer support. In addition, it helps to maintain steady cash flow by bringing loyal customers. However, ignoring the LTV can impact the firm's profitability figures.
Table of contents
- Customer lifetime value is the average company sales derived from a single client. It helps the company identify potential loyal customers that will generate future sales.
- The two types of LTV models include historical and predictive approaches. These approaches use cohort, aggregate, probabilistic, and machine learning techniques.
- The formula to calculate it is Customer Lifetime Value (LTV) = Average Value of Sale × Number of Transactions × Retention time × Profit Margin
- Companies can improve the LTV by improving communication, customer experience, and welcoming return back policies
Customer Lifetime Value (LTV) Explained
Customer Lifetime Value (LTV) refers to the projected revenue that a business earns from one customer. It estimates the money a company will gain throughout a customer's lifetime. In addition, it determines how much they should invest in retaining a single customer.
Since LTV is a long-term concept, it is necessary to understand that not all customers are equally important. Therefore, the company focuses on certain targeted customers more than others. The customer lifetime value prediction helps in getting the most profitable customers. In addition, it helps identify the potential audience that will increase its future cash flows.
Customer lifetime value depends on the pre-existing data and future behavior of customers. Following are the types of lifetime value customers:
#1 - Historical LTV
As the name suggests, historical LTV refers to using past data to find customer value. It uses aggregate and cohort models to find the LTV. This model is useful when a certain customer group is loyal to a business. However, it neglects existing and inactive customers. Also, the historical LTV might be inappropriate since some inactive members might buy products in the future.
#2 - Predictive LTV
The predictive LTV forecasts customer behavior using machine learning and a probabilistic model. The companies use different coding systems to identify the potential audience. Also, it points out factors that can improve customer retention and sales.
Factors
Certain factors weigh down the LTV, disrupting the brand image in the customer's mind. For example, if an active customer feels unvalued, there might be negative rumors or information about the brand. It is likely to impact the customer lifetime value prediction. Thus, it is necessary to understand the impact of these factors on the company. Let us look at them:
#1 - Churn Rate
Active customers stop buying and turn into inactive customers at a churn rate. Startups and small businesses have a high churn rate. It helps in understanding the effect of lifetime value prediction. This rate differs from business to business based on competitive advantage.
To calculate the churn rate, subtract the customers at the end of the period from those at the beginning. Then, divide the difference by the initial customers. For example, a startup had 800 customers initially, and now the number dropped to 600. Therefore, the churn rate is 25% indicating that 25% of customers have switched to another brand.
#2 - Brand Loyalty
The number of customers loyal to a brand determines the customer retention percentage. These loyal customers act as marketing agents that spread awareness about the business. Therefore, highly loyal customers will decrease the churn rate and improve LTV. For example, a 2021 report by Consumer Intelligence Research Partner (CIRP) states that 90% of customers choose Apple products compared to other brands. In contrast, the customer retention period of Samsung is 38%.
Customer Lifetime Value Formula
Here is the customer lifetime value formula for calculating future customer estimates.
Customer Lifetime Value (LTV) = Average Value of Sale × Number of Transactions × Retention time × Profit Margin
Here,
- Average value of sale = average sales of the company.
- Number of transactions = average number of times a customer shops with them.
- Retention time = the number of days, months, or years a customer stays loyal to them.
- Profit margin = Average margin a company makes a profit.
However, there are two more formulas based on their types:
- Historical approach
Customer lifetime value (LTV) = Total revenue for chosen period/ Total number of customers
- Predictive approach
Customer lifetime value (LTV) = T x AOV x AGM x ALT/ Number of customers for the period
Here,
- T = The average Number of transactions per month
- AOV = Average order value (total revenue/ number of orders)
- AGM = Average gross margin (Total revenue (TR) - cost of sales/ TR x 100)
Calculation (With Example)
Let us look at an example of calculating a company's average customer lifetime value.
Suppose Jordan has been running a restaurant for the past three years. Every month, 100 customers visit his food joint. Out of these 100, three customers revisited the outlet four times in the past two years. The average sales of the outlet were $850, and the profit margin was 15%. Jordan wants to know the average sales one customer will generate in the future. Thus, he calculates the average customer lifetime value of his business.
Customer Lifetime value = Average Value of Sale × Number of Transactions × Retention time × Profit Margin
= $850 x 4 x 2 x 15%
= $1020
This figure indicates that Jordan will have an estimated future cash flow of $1020 from its customers.
How To Increase The LTV?
Improving the LTV increases the long-term sales of the company. However, if a company sells good products but lacks customer retention, it will attract losses soon. As a result, the profitability ratios and the company's brand image will also turn negative. Thus, it is necessary to improve the LTV to boost the company's morale. Let us look at the following steps to improve the LTV of the business:
- Improve customer experience
It is one of the significant steps as it contributes to the consumer retention period. If a company provides a good experience, customers will be ready to pay more to have their products. However, a bad experience can spread a mouth of negativity among others. Customer experience-enhancing tactics include good after-sales service, easy interface, and discounts.
- Good communication
Companies should ask for feedback, reviews, and improvements from customers. They should find ways to stay in touch with the customers. Also, keep them posted about the offers, sales, and upcoming events. Connect with customers on social media platforms like Instagram and Facebook. It helps in increasing the customer's lifetime value.
- Welcoming return back policy
Sometimes, customers step back because they see no return policy on the sites. The same goes for the guarantee and warranty periods. Companies should improve their existing delivery and payment systems to keep customers.
Frequently Asked Questions (FAQs)
LTV is one of the important financial metrics of the company. It helps in understanding the financial viability and long-term perspective of the firm. Also, it estimates the future revenues from the existing customers.
Following are the steps to calculate LTV in excel:
- Extract the data regarding sales and customers
- Enter the cells' average value of sales, the number of transactions, retention period, and profit margin.
- In the below cell, press "=," multiply all four elements and press enter.
Companies can use LTV to predict future growth, discover profitable acquisition models, handle customers, and identify the potential audience.
The steps for building a customer lifetime value model are as follows:
● Define the timeframe for the LTV model
● Select the approach: historical or predictive
● Select the associated tools for the model
● Analyze if the model is useful and effective.
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