Cookie Settings

By clicking "Agree," you consent to the storage of cookies on your device to enhance site navigation, analyze site usage, and support our marketing efforts. For more information, please refer to our Privacy Policy.

Blog

Customer lifetime value simply explained.

CLV is more than just a number. It shows you how to develop successful marketing and a solid business strategy.
von
Michael Hauschild
13.11.2024 12:47
5
minutes to read
Share this post
Customer lifetime value

The Customer Lifetime Value (CLV) describes the total revenue that a customer generates over the entire duration of their relationship with a company. It shows not only the current value of a customer, but also the potential growth that can be achieved through strong customer loyalty. This makes CLV an important benchmark for recognizing the value of customer relationships and making strategic marketing decisions.

Why is CLV so important?

CLV is more than just a number. It shows you how to develop successful marketing and a solid business strategy. If you know how much money your customers bring you over time, you can:

Make better decisions: You know which customers you should particularly care for and where to use your marketing budget most effectively.

Strengthen customer loyalty: With targeted promotions and offers for your most valuable customers, you can strengthen their loyalty.

Optimize marketing campaigns: You can better measure and adjust how successful your campaigns are.

Promote sustainable growth: By focusing on the needs of your most valuable customers, you build a solid foundation for your business.

Abstrakte Form eines Pfades

Stay up to date

Just follow us on LinkedIn.

Data news for pros

Want to know more? Then subscribe to our newsletter! Regular news from the data world about new developments, tools, best practices and events!

Abstrakte Form eines Pfades des Data Institute

Stay up to date

Just follow us on LinkedIn.

Abstrakter Pfad des Data Institutes

Challenges when calculating CLV

Calculating CLV is often not easy in practice. A key challenge is that Accurately predict customer lifespan. Many factors, such as market changes, customer preferences and external influences, make it difficult to reliably determine the duration of the customer relationship. It can also be complex to include indirect effects such as word of mouth and customer recommendations on CLV.

How do I calculate CLV?

The formula for CLV may look complicated at first glance, but it is actually very simple:

CLV = Average revenue per customer * Number of purchases * Customer lifeduration - Customer Aquisition Costs

Let's take our regular customer from the bookstore. He spends an average of €20 per visit and comes 52 times a year. If he remains loyal to you for five years, his CLV (excluding acquisition costs) is 5,200€.

Limits of CLV and potential pitfalls

Although the CLV is a valuable tool, it also has its limits. It is based on assumptions about future customer loyalty and buying behavior, which may prove to be inaccurate. Another pitfall is focusing on the highest-rated customers — this could lead to neglecting potentially valuable new customers and emerging customers. Seasonal fluctuations or special promotions can also influence CLV and should be taken into account when interpreting.

The versatility of CLV: examples from other industries

CLV is not only relevant in retail or e-commerce. For example:

Banks and insurance companies: Customers who use multiple products such as current accounts, credit cards and insurance usually have a higher CLV. A bank could develop targeted up-selling strategies to increase this value by offering additional savings products or loans.

Gyms: Members who regularly make personal training bookings or take part in special courses in addition to their basic contract also have a higher CLV. Through targeted incentives and personalized training offers, these customers can be tied even more closely to the studio.

Modern technologies and data analysis for CLV optimization

Thanks to modern data analysis tools and artificial intelligence, the calculation and use of CLV is becoming increasingly precise and effective. Machine learning algorithms can analyze customer data in real time to make precise predictions about future customer behavior. In this way, targeted measures can be developed to maximize CLV and further increase customer loyalty.

Conclusion

Customer lifetime value is a valuable indicator that helps you understand your customers better and develop your business sustainably. Use CLV to develop tailored strategies for your most valuable customers.

Apply the CLV concept in your company and discover the potential of your customer relationships for long-term success!

Which services fit this topic
?

<svg width=" 100%" height=" 100%" viewBox="0 0 62 62" fill="none" xmlns="http://www.w3.org/2000/svg"> <g clip-path="url(#clip0_5879_3513)"> <path d="M19.376 60.0625H11.626C10.5992 60.0594 9.61537 59.6502 8.88933 58.9242C8.16329 58.1981 7.75404 57.2143 7.75098 56.1875V42.625C6.72421 42.6219 5.74037 42.2127 5.01433 41.4867C4.28829 40.7606 3.87904 39.7768 3.87598 38.75V27.125C3.86178 26.3578 4.00243 25.5956 4.2895 24.884C4.57658 24.1723 5.0042 23.5259 5.5468 22.9833C6.08939 22.4407 6.73582 22.0131 7.44744 21.726C8.15906 21.439 8.92126 21.2983 9.68848 21.3125H21.3135C22.0807 21.2983 22.8429 21.439 23.5545 21.726C24.2661 22.0131 24.9126 22.4407 25.4552 22.9833C25.9977 23.5259 26.4254 24.1723 26.7124 24.884C26.9995 25.5956 27.1402 26.3578 27.126 27.125V38.75C27.1229 39.7768 26.7137 40.7606 25.9876 41.4867C25.2616 42.2127 24.2777 42.6219 23.251 42.625V56.1875C23.2479 57.2143 22.8387 58.1981 22.1126 58.9242C21.3866 59.6502 20.4027 60.0594 19.376 60.0625ZM9.68848 25.1875C9.42999 25.172 9.17114 25.2114 8.92903 25.3033C8.68692 25.3952 8.46706 25.5374 8.28395 25.7205C8.10084 25.9036 7.95865 26.1235 7.86678 26.3656C7.77491 26.6077 7.73544 26.8665 7.75098 27.125V38.75H11.626V56.1875H19.376V38.75H23.251V27.125C23.2665 26.8665 23.227 26.6077 23.1352 26.3656C23.0433 26.1235 22.9011 25.9036 22.718 25.7205C22.5349 25.5374 22.315 25.3952 22.0729 25.3033C21.8308 25.2114 21.572 25.172 21.3135 25.1875H9.68848ZM15.501 19.375C13.9682 19.375 12.4698 18.9205 11.1953 18.0689C9.92083 17.2173 8.92749 16.0069 8.34091 14.5908C7.75433 13.1747 7.60086 11.6164 7.89989 10.1131C8.19893 8.6097 8.93704 7.22878 10.0209 6.14493C11.1048 5.06107 12.4857 4.32295 13.989 4.02392C15.4924 3.72488 17.0506 3.87836 18.4668 4.46494C19.8829 5.05152 21.0933 6.04485 21.9449 7.31933C22.7964 8.59381 23.251 10.0922 23.251 11.625C23.2484 13.6796 22.4311 15.6494 20.9782 17.1022C19.5254 18.5551 17.5556 19.3724 15.501 19.375ZM15.501 7.75C14.7346 7.75 13.9854 7.97727 13.3481 8.40306C12.7109 8.82885 12.2142 9.43404 11.9209 10.1421C11.6277 10.8502 11.5509 11.6293 11.7004 12.381C11.85 13.1327 12.219 13.8231 12.7609 14.365C13.3029 14.907 13.9933 15.276 14.745 15.4255C15.4967 15.5751 16.2758 15.4983 16.9839 15.205C17.6919 14.9117 18.2971 14.4151 18.7229 13.7778C19.1487 13.1406 19.376 12.3914 19.376 11.625C19.375 10.5976 18.9664 9.61258 18.2399 8.8861C17.5134 8.15962 16.5284 7.75103 15.501 7.75ZM55.7351 8.246C54.278 6.76535 52.3111 5.89611 50.2353 5.81546C48.1595 5.73482 46.131 6.44885 44.5635 7.812C42.9959 6.44885 40.9675 5.73482 38.8917 5.81546C36.8159 5.89611 34.8489 6.76535 33.3918 8.246C31.8601 9.81001 31.0022 11.912 31.0022 14.1011C31.0022 16.2903 31.8601 18.3922 33.3918 19.9563L44.5596 31.2713L44.5635 31.2674L44.5673 31.2693L55.7351 19.9563C57.2668 18.3922 58.1247 16.2903 58.1247 14.1011C58.1247 11.912 57.2668 9.81001 55.7351 8.246ZM52.9761 17.2341L44.5673 25.7533L44.5635 25.7494L44.5596 25.7533L36.1509 17.2341C35.3299 16.3979 34.8699 15.2729 34.8699 14.1011C34.8699 12.9293 35.3299 11.8043 36.1509 10.9682C36.9696 10.1724 38.0664 9.72714 39.2082 9.72714C40.35 9.72714 41.4468 10.1724 42.2656 10.9682L44.5538 13.3068L44.5635 13.2971L44.5732 13.3068L46.8594 10.9682C47.6783 10.1718 48.7755 9.7262 49.9178 9.7262C51.06 9.7262 52.1572 10.1718 52.9761 10.9682C53.7971 11.8043 54.257 12.9293 54.257 14.1011C54.257 15.2729 53.7971 16.3979 52.9761 17.2341Z" fill="currentColor"/> </g> <defs> <clipPath id="clip0_5879_3513"> <rect width="62" height="62" fill="currentColor"/> </clipPath> </defs> </svg>

Customer Centricity

The focus is always on customers and their wishes how to measure it and translate insights into action.

<svg width=" 100%" height=" 100%" viewBox="0 0 62 62" fill="none" xmlns="http://www.w3.org/2000/svg"> <g clip-path="url(#clip0_5879_2165)"> <path d="M21.3122 46.5H40.6872V50.375H21.3122V46.5ZM25.1872 54.25H36.8122V58.125H25.1872V54.25ZM30.9997 3.875C25.8611 3.875 20.933 5.91629 17.2995 9.54981C13.666 13.1833 11.6247 18.1114 11.6247 23.25C11.4937 26.0658 12.0331 28.8726 13.1985 31.4392C14.364 34.0059 16.1222 36.2592 18.3285 38.0138C20.266 39.8156 21.3122 40.8425 21.3122 42.625H25.1872C25.1872 39.06 23.0366 37.0644 20.9441 35.1462C19.1332 33.7595 17.69 31.9499 16.7408 29.8759C15.7917 27.802 15.3655 25.5269 15.4997 23.25C15.4997 19.1391 17.1327 15.1967 20.0396 12.2898C22.9464 9.38303 26.8889 7.75 30.9997 7.75C35.1106 7.75 39.0531 9.38303 41.9599 12.2898C44.8667 15.1967 46.4997 19.1391 46.4997 23.25C46.6317 25.5286 46.2025 27.8047 45.2499 29.8788C44.2973 31.9529 42.8504 33.7616 41.036 35.1462C38.9628 37.0837 36.8122 39.0213 36.8122 42.625H40.6872C40.6872 40.8425 41.7141 39.8156 43.671 37.9944C45.8757 36.2428 47.6331 33.9929 48.7986 31.4295C49.964 28.8662 50.5042 26.0628 50.3747 23.25C50.3747 20.7056 49.8736 18.1862 48.8999 15.8355C47.9262 13.4848 46.499 11.3489 44.6999 9.54981C42.9008 7.75067 40.7649 6.32352 38.4142 5.34983C36.0635 4.37615 33.5441 3.875 30.9997 3.875Z" fill="currentColor"/> </g> <defs> <clipPath id="clip0_5879_2165"> <rect width="62" height="62" fill="currentColor"/> </clipPath> </defs> </svg>

Data Strategy

When what happens how and why — that explains the data strategy.

Abstrakte Form eines Pfades

Interest in receiving regular news in your inbox

Just subscribe to our newsletter.

Data news for pros

Want to know more? Then subscribe to our newsletter! Regular news from the data world about new developments, tools, best practices and events!

Abstrakte Form eines Pfades des Data Institute

Interest in receiving regular news in your inbox

Just subscribe to our newsletter.

Abstrakter Pfad des Data Institutes