← Every exhibit
The customer-prioritization misclassification card
Keep the predicted group, future group, error cost, and profitability object visible before prioritizing a customer.
| Review field | Predicted at decision date | Future or observed check | Decision question |
|---|---|---|---|
| Group | Which cutoff and model create the selected group? | Which group is defined after the horizon? | Is the comparison time-consistent? |
| False exclusion | Who was not selected? | Who later enters the target group? | What is the cost of missing them? |
| False inclusion | Who was selected? | Who later remains outside the target group? | What attention or service cost was spent? |
| Profitability | Which inputs form predicted value? | Which revenue, cost, price, and margin fields are realized? | Are the forecast and outcome objects the same? |
| Refresh | When is the rank recalculated? | When can the outcome be evaluated? | Does the horizon match the decision? |
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Reference & Evidence
Source: Author's portfolio review framework grounded in Malthouse and Blattberg (2005) and Mulhern (1999). The percentages are shown only as bounded source results; the matrix prompts are synthetic and contain no customer data.
Each line is a claim from the register this journal publishes against, resolved from the register at build time.
- A The question is feasibility, not desirability: relationship-marketing strategies "presume that a firm can accurately predict the future profitability of customers", and the paper is "a detailed empirical evaluation of how accurately the future profitability of customers" can be predicted across four industry data sets Malthouse & Blattberg. (2005) ·
MB05-C1 - A The 20-55 rule, as posited: of the actual best customers, "approximately 55% will be misclassified and not receive special treatment". The authors call these "two new empirical rules of thumb based on these results", so they are rules of thumb from four data sets, not constants. About 15% of the future bottom 80% may be misclassified and receive special treatment. Malthouse & Blattberg. (2005) ·
MB05-C2 - A "the feasibility of such strategies depends on the probabilities and costs of misclassifying customers", so it turns on prediction accuracy, forecast horizon, and the costs of misclassification. Malthouse & Blattberg. (2005) ·
MB05-C3 - A The paper is METHOD, not an empirical finding, in its own words: "This paper provides a conceptual and methodological foundation for measuring customer profitability" by extending customer-lifetime-value approaches to broader target-marketing applications. Mulhern. (1999) ·
MUL99-C1 - A Concentration is analysed as a distribution, not asserted as a ratio: "a sharply descending curve for the ordering of customer profit" corresponds to a skewed frequency distribution, and the Lorenz curve's shortcoming is that "it cannot portray percentiles of customers who represent a financial loss to a firm" Mulhern. (1999) ·
MUL99-C2
Grades: A, verified against the printed page of the primary source · B, primary source, text layer only · C, authoritative secondary · D, reported.