Response transformation and profit decomposition for revenue uplift modeling
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DOI: 10.1016/j.ejor.2019.11.030
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Cited by:
- Daniel Baier & Björn Stöcker, 2022. "Profit uplift modeling for direct marketing campaigns: approaches and applications for online shops," Journal of Business Economics, Springer, vol. 92(4), pages 645-673, May.
- Goic, Marcel & Rojas, Andrea & Saavedra, Ignacio, 2021. "The Effectiveness of Triggered Email Marketing in Addressing Browse Abandonments," Journal of Interactive Marketing, Elsevier, vol. 55(C), pages 118-145.
- Bokelmann, Björn & Lessmann, Stefan, 2024. "Improving uplift model evaluation on randomized controlled trial data," European Journal of Operational Research, Elsevier, vol. 313(2), pages 691-707.
- Vairetti, Carla & Gennaro, Franco & Maldonado, Sebastián, 2024. "Propensity score oversampling and matching for uplift modeling," European Journal of Operational Research, Elsevier, vol. 316(3), pages 1058-1069.
- Tobias Cagala & Ulrich Glogowsky & Johannes Rincke & Anthony Strittmatter, 2021.
"Optimal Targeting in Fundraising: A Machine-Learning Approach,"
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- Tobias Cagala & Ulrich Glogowsky & Johannes Rincke & Anthony Strittmatter, 2021. "Optimal Targeting in Fundraising: A Machine-Learning Approach," CESifo Working Paper Series 9037, CESifo.
- Haupt, Johannes & Lessmann, Stefan, 2022. "Targeting customers under response-dependent costs," European Journal of Operational Research, Elsevier, vol. 297(1), pages 369-379.
- Zhen-Yu Chen & Zhi-Ping Fan & Minghe Sun, 2023. "Machine Learning Methods for Data-Driven Demand Estimation and Assortment Planning Considering Cross-Selling and Substitutions," INFORMS Journal on Computing, INFORMS, vol. 35(1), pages 158-177, January.
- Tobias Cagala & Ulrich Glogowsky & Johannes Rincke & Anthony Strittmatter, 2021. "Optimal Targeting in Fundraising: A Causal Machine-Learning Approach," Papers 2103.10251, arXiv.org, revised Sep 2021.
- Johannes Haupt & Stefan Lessmann, 2020. "Targeting customers under response-dependent costs," Papers 2003.06271, arXiv.org, revised Aug 2021.
- Gabriel Okasa, 2022. "Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance," Papers 2201.12692, arXiv.org.
- Verbeke, Wouter & Olaya, Diego & Guerry, Marie-Anne & Van Belle, Jente, 2023. "To do or not to do? Cost-sensitive causal classification with individual treatment effect estimates," European Journal of Operational Research, Elsevier, vol. 305(2), pages 838-852.
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Keywords
OR in Marketing; Profit Analytics; Uplift Model; Causal Machine Learning;All these keywords.
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