Customer lifetime value

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Definition and Importance of Customer Lifetime Value
– Customer lifetime value (CLV) is a prediction of the net profit contributed to the future relationship with a customer.
– CLV encourages firms to focus on the long-term health of customer relationships rather than quarterly profits.
– CLV represents an upper limit on spending to acquire new customers.
– CLV is an important metric in calculating the payback of advertising spent in marketing mix modeling.
– The concept of CLV 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 future activity.
– Quantifying CLV involves forecasting future activity, while quantifying CP is based on past activity.
– CLV is the present value of future cash flows attributed to the customer relationship.
– CLV allows for customer segmentation to focus on 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: CLV = Margin x (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 the 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 commerce example to calculate CLV: (Avg Monthly Revenue per Customer x Gross Margin per Customer) / Monthly Churn Rate.
– CLV calculation process consists of forecasting remaining customer lifetime, future revenues, costs, and net present value.
– Forecasting accuracy and difficulty in tracking customers over time may affect CLV calculation.
– Retention models make simplifying assumptions in estimating CLV.

Applications of Customer Lifetime Value
– CLV metrics are mainly used in relationship-focused businesses with customer contracts.
– Examples include banking, insurance services, telecommunications, and the business-to-business sector.
– CLV principles can be extended to transactions-focused categories by incorporating purchase behavior models.
– Retention has a decisive impact on CLV, as low retention rates result in minimal CLV increase over time.
– CLV can be used to inform marketing resource allocation and customer segmentation strategies.

Misuses and Downsides of CLV
– CLV predictions should use net present value (NPV) for accurate results.
– CLV should be calculated based on net profit, not total revenue or gross margin.
– CLV predictions may be inaccurate due to missing data on key customer drivers.
– CLV models may omit important predictors, leading to inaccuracies in certain customer segments.
– CLV models may overvalue current customers and neglect the potential value of new customers.

NPV vs. Nominal Prediction, Net Profit vs. Revenue, Segment Inaccuracy and Comparison with Intuition
– The most accurate CLV predictions use NPV, recognizing future revenue at the value of money.
– NPV calculations require a discount rate, while nominal CLV calculations use non-discounted figures.
– Nominal CLV predictions tend to be slightly higher, especially for future revenues.
– CLV should be calculated based on the full net profit expected from the customer.
– Mistakenly calculating CLV based on total revenue can inflate its value.
– Ecommerce reporting systems often report Lifetime Revenue instead of net profit-based CLV.
– CLV predictions may be inaccurate due to missing data on the nature of the customer relationship.
– Specific demographic factors that intuitively affect customer value are often omitted from CLV predictions.
– Inaccuracies in CLV predictions can occur in certain customer segments.
– CLV models should consider additional predictors beyond the basic formula.
– Effective marketing can transform low-value customers into high-value customers, challenging CLV models that neglect this potential. References:https://en.wikipedia.org/wiki/Customer_lifetime_value

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Customer lifetime value