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Customer lifetime value

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Definition and Importance of Customer Lifetime Value
– Customer lifetime value (CLV) is a measure of the net profit contributed by a customer over their entire relationship with a company.
– CLV encourages firms to prioritize long-term customer relationships over short-term profits.
– CLV represents the upper limit on spending to acquire new customers.
– CLV is important in calculating the payback of advertising spent in marketing mix modeling.
– The term ‘customer lifetime value’ was first mentioned in the book ‘Database Marketing’ in 1988.
– The purpose of CLV is to assess the financial value of each customer.
– CLV differs from customer profitability (CP) as it looks forward and measures the future value of a customer relationship.
– Quantifying CLV involves forecasting future activity, making it more difficult to quantify than CP.
– CLV is calculated by determining the present value of future cash flows attributed to the customer relationship.
– CLV can be used for customer segmentation to identify the most profitable group of customers.

Construction and Methodology of Customer Lifetime Value
– The formula to calculate CLV when margins and retention rates are constant is: CLV = Margin * (Retention Rate / (1 + Discount Rate – Retention Rate)).
– The CLV model treats customer relationships as a leaky bucket, with a fraction of customers leaving each period.
– The CLV model has three parameters: constant margin, constant retention probability, and discount rate.
– The model assumes that if a customer is not retained, they are lost for good.
– CLV is a multiple of the margin and represents the present value of the expected length of the customer relationship.
– A simple formula for calculating CLV is: (Avg Monthly Revenue per Customer * Gross Margin per Customer) / Monthly Churn Rate.
– The numerator represents the average monthly profit per customer, and the denominator accounts for the chance of the customer remaining in future months.
– CLV calculation involves forecasting remaining customer lifetime, future revenues, costs, and calculating the net present value.
– Forecasting accuracy and tracking customers over time can impact CLV calculation.
– Retention models use inputs such as churn rate and retention rate to estimate CLV.

Applications of Customer Lifetime Value
– CLV metrics are commonly used in relationship-focused businesses with customer contracts.
– Industries such as banking, insurance, telecommunications, and business-to-business sectors utilize CLV.
– CLV principles can be extended to transactions-focused categories like consumer packaged goods.
– Retention has a significant impact on CLV, as low retention rates result in minimal increase in CLV over time.
– CLV-based segmentation combined with a share of wallet (SOW) model can help identify high CLV but low SOW customers for targeted marketing.

Uses and Advantages of Customer Lifetime Value
– CLV represents the monetary worth of each customer and helps determine how much a marketing department should spend to acquire each customer.
– It is used to judge the appropriateness of customer acquisition costs.
– CLV is used to calculate customer equity.
– It helps in managing customer relationships as an asset.
– CLV allows monitoring the impact of management strategies and marketing investments on customer asset value.
– Helps determine the optimal level of investments in marketing and sales activities.
– Encourages marketers to focus on the long-term value of customers.
– Enables implementation of sensitivity analysis to determine the impact of spending extra money on each customer.
– Facilitates optimal allocation of limited resources for marketing activities.
– Provides a basis for selecting customers and decision-making regarding customer-specific communication strategies.

Misuses and Dynamic Nature of Customer Lifetime Value
– CLV predictions using nominal figures can be biased slightly high.
– Total revenue should not be used to calculate CLV; net profit is the correct measure.
– CLV predictions may be inaccurate due to missing data on major drivers of customer value.
– Omitted predictors can cause inaccuracies in certain customer segments.
– CLV models may overvalue current customers at the expense of potential customers.
– CLV is a dynamic concept and not a static model.
– It takes into account the potential for marketing to change customer behavior.
– Effective marketing can turn low-value customers into high-value customers.
– CLV models should consider a larger number of middle-value customers.
– Survey data can be used to collect information on potential customers.

In marketing, customer lifetime value (CLV or often CLTV), lifetime customer value (LCV), or life-time value (LTV) is a prognostication of the net profit contributed to the whole future relationship with a customer. The prediction model can have varying levels of sophistication and accuracy, ranging from a crude heuristic to the use of complex predictive analytics techniques.

Customer lifetime value can also be defined as the monetary value of a customer relationship, based on the present value of the projected future cash flows from the customer relationship. Customer lifetime value is an important concept in that it encourages firms to shift their focus from quarterly profits to the long-term health of their customer relationships. Customer lifetime value is an important metric because it represents an upper limit on spending to acquire new customers. For this reason it is an important element in calculating payback of advertising spent in marketing mix modeling.

One of the first accounts of the term customer lifetime value is in the 1988 book Database Marketing, which includes detailed worked examples. Early adopters of customer lifetime value models in the 1990s include Edge Consulting and BrandScience.

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