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However, these metrics fail to reflect financial outcomes and may mislead strategic decisions. We introduce\n                    <jats:italic>e-Profits<\/jats:italic>\n                    , a novel business-aligned evaluation metric that quantifies model performance based on customer lifetime value, retention probability, and intervention costs. Unlike existing profit-based metrics such as Expected Maximum Profit, which assume fixed population-level parameters,\n                    <jats:italic>e-Profits<\/jats:italic>\n                    uses Kaplan\u2013Meier survival analysis to estimate tenure-conditioned (customer-level) one-period retention probabilities and supports granular, per-customer profit evaluation. We benchmark six classifiers across two telecom datasets (IBM Telco and Maven Telecom) and demonstrate that\n                    <jats:italic>e-Profits<\/jats:italic>\n                    reshapes model rankings compared to traditional metrics, revealing financial advantages in models previously overlooked by AUC or F1-score. The metric also enables segment-level insight into which models maximise return on investment for high-value customers.\n                    <jats:italic>e-Profits<\/jats:italic>\n                    provides a transparent, customer-level evaluation framework that bridges predictive modelling and profit-driven decision-making in operational churn management. All source code is available at:\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/github.com\/Awaismanzoor\/eprofits\" ext-link-type=\"uri\">https:\/\/github.com\/Awaismanzoor\/eprofits<\/jats:ext-link>\n                    .\n                  <\/jats:p>","DOI":"10.1007\/s41060-026-01044-6","type":"journal-article","created":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T11:18:31Z","timestamp":1772018311000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["e-profits: a business-aligned evaluation metric for profit-sensitive customer churn prediction"],"prefix":"10.1007","volume":"22","author":[{"given":"Awais","family":"Manzoor","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"M. 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