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What Is Customer Lifetime Value?

Customer lifetime value (CLTV) is the expected profit that a single customer brings to a company over the course of their lifetime. CLTV represents a shift in emphasis from quarterly or annual profits to the long-term relationships with customers.

Details

Why Is It Important to Have a Good Life Time Value Model?

CLTV is an important metric for determining a reasonable customer acquisition cost (CAC). In short, many companies spend too many resources on growth through acquiring new customers and not enough on retaining existing ones.

Subsequently, to ensure continued profitability, companies must keep CLTV larger than CAC. A good CLTV model allows companies to easily monitor these parameters, enlarge the CLTV, and stay profitable.

What Internal Data Should I Have for a Good Life Time Value Model?

Calculating CLTV is based on average purchase value, average purchase frequency rate, and average customer lifespan. Further, to improve the CLTV, a good model should also use data from sales history, customer maintenance history, and customer feedback.

What External Data is Essential for a Good Life Time Value Model?

Above all else, competitor data is necessary for a good CLTV model. Include, for example, information about new competitors in your market segment, significant changes in your competitors’ statuses, and your competitors’ average customer lifespan and CAC.

Finally, include any data about the customer, online or offline. For example, ethnographic and demographic data can prove very useful when building CLTV models and analyses.

What External Data May Prove Useful for a Good Life Time Value Model?

Additional useful data include psychological analyses relating to customer retention and improvements in customer satisfaction.

What Are the Main Challenges of the Life Time Value Use Case?

The main challenges of CLTV are predicting and calculating customer lifespan (especially for young companies) and the analyzing the efficacy of different complex marketing channels. Similarly, accurately calculating gross profit margins is very challenging.

Interesting Case Studies and Blogs to Look Into

Hubspot: How to Calculate Customer Lifetime Value
Kaviyo: AI-Powered Customer Lifetime Value

Tangible Examples of Impact

Data-driven CLTV prediction models have been shown to achieve accuracy of about 80-90% while other models have achieved near-perfect accuracy. For more details, click through to this article: Towards Data Science: Measuring users with Customer Lifetime Value (CLTV): an example with complete Python code

Relevant datasets

Home by Vendigi

by Vendigi

Home by Vendigi provides audience data for all things home buyers, remodelers, and sellers. Their data comes from first-party sources like top multiple listing systems (MLSs) major brokers like RE/MAX, Coldwell Banker, Century 21, and Sotheby’s.

Users of Vendigi’s Home data range from home and garden retailers to insurance institutions to telecom companies.

4.3 (3)   Reviews (1)

Fiind Account-Based Marketing

by

Account-Based Marketing by Fiind provide businesses with AI powered target accounts based on their fit and buying intent along with services for measuring and optimizing targeted campaigns.

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Fiind Data Stewardship

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Fiind’s Data Stewardship services provide data management for businesses to enhance the success of their marketing and sales results.

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Fluent Mobile User Acquisition

by fluent

Mobile User Acquisition by Fluent allows businesses to have more successful campaigns and more engagement through mobile app users.

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Fluent Audience Now

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Audience Now by Fluent is a platform that provides targeted audience data for businesses to gain insights that improve their reach, visibility and increase customer and user acquisition.

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