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Customer lifetime value is the profit an enterprise can generate from a single customer throughout the business relationship.

Do you know a 5% increase in customer retention results in a 25% to 95% increase in profit? The customer retention rate increases the customer lifetime value and reduces the amount that the enterprise spends on indirect expenses such as marketing, sales, and distribution. 76% of enterprises believe that the customer lifetime value is an important concept for them.

Considering the growing importance of customer lifetime value to businesses, this guide aims to answer the following questions:

  1. Why should you care about CLV?
  2. How can you measure customer lifetime value?
  3. How do you improve customer lifetime value?
  4. How do you use CLV in your OKRs?

Why should businesses care about CLV?

Here are four reasons that businesses should track and improve customer lifetime value:

1. CLV can increase investor & stakeholder confidence

Customer Lifetime Value is a key indicator of business health. A high CLV indicates that customers trust your business, and suggests you have a great product, and provide great service for your existing customers. If your CLV is high, you necessarily have a low customer churn. Either customers consider your service essential, or you’re taking great care of your customers.

When investors see that you have a history of loyal customers, they have more confidence in the future of your business, and the potential for it to be successful. Investors are more likely to contribute more to the business when they believe you have a steady cash flow and high-quality products and services.

2. Acts as a forecasting tool

The customer lifetime value is an important metric that helps to forecast profitability, set customer acquisition budgets, and create goals for future growth. It enables the enterprise to make forward-looking decisions.

A high CLV means businesses can likely anticipate their cash flow for a certain period of time. For example, an SaaS business can reliably estimate the cash flow they have from subscription costs. With this in mind, they can take calculated risks and make decisions to reinvest money into the business, dedicating it to growth and other initiatives.

3. Indicator of customer loyalty

The customer lifetime value helps to measure customers’ loyalty towards the brand. According to a survey conducted by XM Institute, loyal customers of an enterprise are five times as likely to repurchase and seven times as likely to try new offerings. If your customer loyalty is low, your team can develop a customer loyalty program to help improve your CLV, and track this metric using OKRs to determine whether your program is working.

4. Helps target ideal customers

An ideal customer is one who associates with the enterprise for the long term and makes repeated business transactions. By analyzing the characteristics of existing customers with high lifetime values, the marketing team of the enterprise can develop an ideal customer profile and customer acquisition strategy. This practice ensures the marketing department does not waste its resources targeting prospective customers that may not create value in the long run.

How to Calculate Customer Lifetime Value

There are 2 approaches to calculating customer lifetime value: Historical & Predictive.

The Historical Customer Lifetime Value Model

This model makes use of the historical transaction data, especially the average order value, to determine the customer lifetime value. The implementation of this model is possible only when the enterprise has several existing customers associated with it over a certain period.

There are four steps involved in measuring the customer lifetime value. They are:

  1. Determine the average purchase value
  2. Calculate the average number of purchases (per week, month, or year)
  3. Identify the retention period (number of months or number of years)
  4. Calculate the customer lifetime value

Customer Lifetime Value = Average Purchase Value x Average Number of Purchases x Retention Period

Take a look at the following examples to understand the calculation of the customer lifetime value in context.

Your Local Coffee Shop

Let’s say a commuter stops at their local coffee shop every morning on their way to work. They purchase coffee from the shop five times per week, and each coffee is valued at $4. Let’s say they do this for five years.

In this case, the Customer Lifetime Value = $4 x (54 weeks * 5 times a week) x 5 years = $5400

Software as a Service (SaaS) Company

Let’s assume a software company offers a project management tool with multiple monthly price plans. On average, every customer spends $50 per month. A customer typically subscribes to the tool for two years with the help of automatic monthly renewal payments.

In this case, the Customer Lifetime Value = $50 average purchase value x 24 purchases x 2 years = $2400.

While this model is simple, factors such as increasing competitive pressures and quickly changing consumer behaviors are making the result of this model less accurate. These factors create customer experiences and customer journeys that aren’t identical and comparable. When a better option is available, an active customer may quickly switch over and become an inactive customer. In contrast, an inactive customer may come back and start purchasing from the enterprise again. These uncertainties in consumer behavior might skew the data and provide inaccurate insights about the lifetime value of customers.

Ideally, this model is highly accurate if all customer journeys are identical and have been associated with the enterprise for roughly the same amount of time.

The Predictive Customer Lifetime Value Model

This model, unlike the historical model, focuses on analyzing the buying behavior of old clients, new clients, and potential clients, in addition to the historical data to determine the customer value. The predictive model helps the enterprise to fine-tune the customer profile, identify the most valuable customers, and determine the product or service that could bring the most sales.

You can calculate your predictive CLV in a number of ways, but you should use a formula that accounts for your churn rate to account for the rate at which you lose customers. This will give you the most accurate value.

ARPA X Gross Margin %Churn Rate

This particular formula, as explained on the For Entrepreneurs site, multiplies the average revenue per account/user by the gross margin percentage for the entire company. Then, divide this by the company’s churn rate. The quotient of this calculation is your CLV.

For example, a midsized subscription-based company has a current average revenue per account (ARPA) of $1,200 per year. Their gross margin is 80%, and their churn rate is 2% per month, which we’ll adjust to 24% per year to match the annual ARPA.

$1,200 multiplied by 80% (.80) results in a product of 960. 960 divided by the churn rate of 24% (.24) results in a quotient of 4,000, meaning the average CLV the company can expect is $4,000.

Software as a Service (SaaS) Company

Today, businesses are using tools such as machine learning (ML) and Artificial Intelligence (AI) to increase the results of the predictive customer lifetime value model. It enhances the efficiency of the marketing department by assisting it in:

  1. Creating the customer profile and determining the demographics and acquisition source of new customers
  2. Creating promotional campaigns
  3. Designing special promotional offers
  4. Sending out surprise gifts and delights to selected customers

How to Improve CLV

Businesses employ a wide range of techniques and methods to improve the lifetime value of customers. Here is the list of the top eight techniques you can adopt to improve the customer lifetime value for your business:

Customer Loyalty or Rewards Programs

79% of consumers, in a recent survey conducted by Bond Brand Loyalty, said that loyalty programs make them more likely to continue doing business with enterprises.

Businesses use customer loyalty and reward programs to retain customers and enhance their lifetime value. A good example of this is a loyalty punch card at a restaurant. With each visit, a customer gets a punch on the card. At 10 visits, they receive 20% off their meal. Most airline companies also offer discount coupons for frequent flyers to retain them. These incentives play a crucial role in increasing purchase frequency and reducing customer acquisition costs.

It is important for enterprises to not only implement loyalty programs but also establish a positive emotional connection. Another survey by the Bond Brand Loyalty revealed that the loyalty program members spend 27% more when the enterprise establishes a positive emotional connection.

Customer Experience

According to a survey conducted by PwC, 92% of customers leave a brand they love after a couple of bad interactions and experiences. Every touchpoint, interaction, and communication of the enterprise influences the customer’s experience. A brand that offers a smooth, hassle-free, and stress-free shopping experience would enjoy high customer lifetime value and repeat business. Amazon is a perfect example of offering an impeccable customer experience and passionate customer service. Factors such as the quick resolution of customer queries, hassle-free return pick-ups, and instant refunds helped Amazon to offer a superior customer experience.

Improve Customer Onboarding and Engagement Journey

Most customers don’t know what comes next in a business relationship. They eventually turn into one-time customers and increase the cost of acquisition for the enterprise. Successful enterprises implement appropriate frameworks that help streamline the customer onboarding journey. They effectively use social media platforms such as Facebook, Twitter, and Instagram to engage customers and improve their experience. According to research conducted by Gallup, customers who are fully engaged would represent a 23% higher share in profitability, relationship growth, and revenue. The research also found that customer engagement in the B2B industry helps enterprises to realize 63% lower customer attrition.

Improved Customer Service

Customer service is a cornerstone for the survival of the enterprise. Bad customer service can result in a fall in customer lifetime value as well as profitability. Did you know businesses lost $75 billion due to bad customer service in 2018? To increase the customer lifetime value, enterprises should focus on enhancing the quality of customer service and making every customer service interaction a positive one.

A dedicated customer relationship management (CRM) platform that tracks customer interactions and creates a seamless flow of information across the customer lifecycle would help the enterprise improve the customer lifetime value.

Customer Feedback

Good and bad experiences are part and parcel of a business. It is almost impossible for an enterprise to satisfy all customers. A few customers may undergo bad experiences irrespective of how good the service of an enterprise is. A bad experience can affect customer lifetime value if it goes unresolved.

This is where the customer feedback loop would rescue the enterprise from losing the customer. Besides letting the customer service team fix the issue, the marketing team should solicit feedback, give assurance to the customer, and ensure the issue is resolved quickly.

Marketing Automation

Marketing automation is a process of automating monotonous marketing tasks including email marketing, social media posting, and customer query handling with the help of software to enhance efficiency and provide a personalized experience for customers. 80% of companies using marketing automation for the last three years have revealed that they experienced an increase in revenue and customer engagement.

Automating customer interactions through chatbots and live chats would also increase customer engagement. In fact, chatbots have handled over 85% of customer service requests in 2021. Enterprises can increase the customer lifetime value if they use AI, ML, personalized email automation, and automated social media marketing.

Cross-selling and Up-selling

Cross-selling and up-selling, if executed perfectly, would not only bring additional revenue but also build customer relationships. Cross-selling encourages customers to buy complementary products. Up-selling, on the other hand, encourages customers to spend more money on the same product or service. Businesses can cross-sell and up-sell through packaged deals, volume discounts, warranties, and premium offerings. The customer lifetime value can be improved if enterprises can build relationships with customers through cross-selling and up-selling.

Underpromise and Overdeliver

In a business relationship, everything boils down to meeting customer expectations. Businesses should remember the phrase “Underpromise and Overdeliver”. The customer lifetime value can be significantly improved by overdelivering on your brand promise. Normally, brands make bold promises but fail to deliver on them. This results in a low customer satisfaction rate. Customers love to work with companies that over-deliver on their promises.

How to use CLV in your OKRs: Examples

You can use the Customer Lifetime Value KPI as a way to track the success of your high-priority objectives. To write a key result using this metric, you must first baseline the KPI, set a target that will help you achieve your objective, set a deadline, and assign an owner to ensure that this key result is successfully achieved.

OKR Examples using CLV

Now that you understand why CLV is important and how you can calculate and improve CLV, let’s look at some examples of CLV in the context of an OKR:
Objective: Become the industry standard for amazing customer experience

KR1: Increase our CLV from $8k to $12k

KR2: Increase Customer NPS from 40 to 70

KR3: Achieve a rating of 100 on G2 for customer support


David Griffin

Become the industry standard for amazing customer experience


Target Date: Q1-2022

Visibility: All Employees

key-icon5Key Results

Increase our CLV from $8k to $12k

Q1-2022 milestone-tracked-icon7 CLV
$8000 $12k $10.33k


Increase Customer NPS from 40 to 70

Q1-2022 roger-smith-assignee15 increase-icon Patient NPS
40 70 52.3


Achieve a rating of 100 on G2 for Customer Support

Q1-2022 alice-assignee5 milestone-tracked-icon8 Customer S..
50% 150% 86%


The first Key Result tracks an increase in CLV. This is a great metric to use to help quantify the progress of the objective “Become the industry standard for amazing customer experience” because the better the customer service is at a company, the more likely a customer is to stay for a long period of time. The longer a customer stays, the more they will spend, and therefore their CLV will increase, affecting the overall CLV for the organization.

Objective: Improve our customer loyalty

KR1: Launch a formal customer loyalty program

KR2: Decrease average response time from 12 hours to 4 hours

KR3: Reduce the churn from 20% to 10%


David Griffin

Improve our Customer loyality


Target Date: Q1-2022

Visibility: All Employees

key-icon5Key Results

Launch a formal customer loyality program

Q1-2022 milestone-tracked-icon7 Customer Loy..
0% 100% 50%

55 55


Decrease the average response time from 12 hours to 4 hours

Q1-2022 roger-smith-assignee15 increase-icon Average Resp..
12 hour(s) 4 hours(s) 9 hour(s)


Reduce the churn from 20% to 10%

Q1-2022 milestone-tracked-icon7 churn
20% 10% 17%


This OKR example doesn’t have CLV explicitly listed as a KPI used to measure the progress of the objective. However, you’ll see that the third key result is to reduce the churn from 20% to 10%. Churn is one of the main factors that affects CLV.

This key result choice highlights how you can affect the customer lifetime value by targeting other metrics in the organization.

The Final Word

The customer lifetime value is the profit or the value a customer can bring to an enterprise over the course of their entire relationship with the business. Enterprises that focus on enhancing the customer lifetime value outperform competitors and generate good revenues. Businesses can make use of models such as the Historical Customer Lifetime Value Model and the Predictive Customer Lifetime Value Model to calculate the lifetime value. Techniques such as loyalty programs, marketing automation, cross-selling, up-selling, customer feedback loop, and customer engagement would help enterprises enhance the customer lifetime value.

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