Table 11 Sept 2026From “One customer model cannot predict every outcome”

The multi-outcome customer model card

Validate each customer outcome separately before one model score steers a relationship decision.

Table 1The multi-outcome customer model card

Synthetic outcome	Model family	Validation question	Influential variable class	Decision use	Transfer risk
Next purchase	Classification forest	Does the model separate future buyers from non-buyers?	Past purchase behavior	Prioritize a follow-up test	Purchase value is not profit
Partial defection	Classification forest	Does the model detect a declared reduction in activity?	Intermediary or channel behavior	Review relationship change	Defection boundary differs by channel
Profitability evolution	Regression forest	Does the model predict change in the declared profit measure?	Past behavior and cost boundary	Review economic exposure	Revenue-only validation misleads

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Source: Author's synthetic model-review framework grounded in Lariviere and Van den Poel (2005), Malthouse and Blattberg (2005), and Lemmens and Gupta (2020). The rows are illustrative and do not describe a live customer model.

PNG4:3, 1600 × 1200, with the title, the source line and the attribution set in the image isoglu-2026-one-customer-model-cannot-predict-every-outcome-fig02.png

Source and evidence

Each line names a claim related to this exhibit, its source, and how it was checked.

A LVP05-C1 Three outcomes, one sample: "three important measures of customer outcome next buy partial defection and customers profitability evolution", over "a real life sample of 100 000 customers taken from the data warehouse of a large european financial services company"Lariviere & Van den Poel. (2005)
A LVP05-C2 "both random forests techniques provide better fit for the estimation and validation sample compared to ordinary linear regression and logistic regression models"Lariviere & Van den Poel. (2005)
A LVP05-C3 The variables do not transfer between outcomes: "the same set of variables have a different impact on buying versus defection versus profitability behavior", with past customer behaviour "more important to generate repeat purchasing and favorable profitability evolutions"Lariviere & Van den Poel. (2005)
A MB05-C1 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 setsMalthouse & Blattberg. (2005)
A MB05-C3 "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)
A LG20-C1 The method, in the authors' words: "defining a profit-based loss function to predict, for each customer, the financial impact of a retention intervention"Lemmens & Gupta. (2020)
A LG20-C2 The ranking rule is incremental and net of cost: "customers are ranked based on the incremental impact of the intervention on churn and postcampaign cash flows, after accounting for the cost of the intervention", rather than by churn risk or response alone.Lemmens & Gupta. (2020)

Grades: A, verified against the printed page of the primary source · B, primary source, text layer only · C, authoritative secondary · D, reported.

From the essay

Growth that compounds

One customer model cannot predict every outcome

Next purchase, partial defection, and profitability are different outcomes: choose the model and validation question before trusting one customer score.

1 Sept 2026

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APA 7

Isoglu, S. (2026). The multi-outcome customer model card [Table]. isoglu.com. https://isoglu.com/insights/exhibits/isoglu-2026-one-customer-model-cannot-predict-every-outcome-fig02/

BibTeX

@misc{isoglu-2026-one-customer-model-cannot-predict-every-outcome-fig02,
  author = {Isoglu, Sinan},
  title = {{The multi-outcome customer model card}},
  year = {2026},
  howpublished = {Table 1, isoglu.com},
  url = {https://isoglu.com/insights/exhibits/isoglu-2026-one-customer-model-cannot-predict-every-outcome-fig02/},
  note = {From the essay {One customer model cannot predict every outcome}}
}

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<figure>
  <a href="https://isoglu.com/insights/exhibits/isoglu-2026-one-customer-model-cannot-predict-every-outcome-fig02/">
    <img src="https://isoglu.com/social/isoglu-2026-one-customer-model-cannot-predict-every-outcome-fig02.png" alt="Table 1: The multi-outcome customer model card" width="3200" height="2400">
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  <figcaption>Table 1: The multi-outcome customer model card. Source: Author&#39;s synthetic model-review framework grounded in Lariviere and Van den Poel (2005), Malthouse and Blattberg (2005), and Lemmens and Gupta (2020). The rows are illustrative and do not describe a live customer model. <a href="https://isoglu.com/insights/exhibits/isoglu-2026-one-customer-model-cannot-predict-every-outcome-fig02/">View exhibit</a>.</figcaption>
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