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Response transformation and profit decomposition for revenue uplift modeling
16 references·12 citing·36 second hop
Response transformation and profit decomposition for revenue uplift modeling (2019)Response transformation and profit decomp…Targeting customers for profit: An ensemble learning framework to support marketing decision-making (2019)Targeting customers for profi…A Literature Survey and Experimental Evaluation of the State-of-the-Art in Uplift Modeling: A Stepping Stone Toward the Development of Prescriptive Analytics (2018)A Literature Survey and Exper…Retention Futility: Targeting High-Risk Customers Might be Ineffective (2017)Retention Futility: Targeting…Enhancing two-stage modelling methodology for loss given default with support vector machines (2017)Enhancing two-stage modelling…Do Coupons Expand or Cannibalize Revenue? 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A machine learning price elasticity model for predicting upselling acceptance of premium airline seating (2023)Will they take this offer? 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References

  • 2015Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research1,277 cited
  • 2011Online Display Advertising: Targeting and Obtrusiveness817 cited
  • 1998Data mining for direct marketing: problems and solutions658 cited
  • 2006Defection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models574 cited
  • 2011New insights into churn prediction in the telecommunication sector: A profit driven data mining approach460 cited
  • 2017Retention Futility: Targeting High-Risk Customers Might be Ineffective292 cited
  • 2002Bayesian neural network learning for repeat purchase modelling in direct marketing218 cited
  • 2011Decision trees for uplift modeling with single and multiple treatments177 cited
  • 2002The true lift model147 cited
  • 2018A Literature Survey and Experimental Evaluation of the State-of-the-Art in Uplift Modeling: A Stepping Stone Toward the Development of Prescriptive Analytics115 cited
  • 2012Real-World Uplift Modelling with Significance-Based Uplift Trees90 cited
  • 2016Do Coupons Expand or Cannibalize Revenue? Evidence from an e-Market82 cited
  • 2014Ensemble methods for uplift modeling81 cited
  • 2019Targeting customers for profit: An ensemble learning framework to support marketing decision-making80 cited

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  • 2017Enhancing two-stage modelling methodology for loss given default with support vector machines79 cited
  • 2014Mining for the truly responsive customers and prospects using true-lift modeling: Comparison of new and existing methods72 cited
  • Cited by

    • 2021Uplift modeling and its implications for B2B customer churn prediction: A segmentation-based modeling approach50 cited
    • 2020On realising the utopian potential of big data analytics for maximising return on marketing investments30 cited
    • 2021Targeting customers under response-dependent costs26 cited
    • 2023Will they take this offer? A machine learning price elasticity model for predicting upselling acceptance of premium airline seating26 cited
    • 2021Uplift modeling with value-driven evaluation metrics23 cited
    • 2022Machine Learning Methods for Data-Driven Demand Estimation and Assortment Planning Considering Cross-Selling and Substitutions22 cited
    • 2025Dynamic Marketing Uplift Modeling: A Symmetry-Preserving Framework Integrating Causal Forests with Deep Reinforcement Learning for Personalized Intervention Strategies18 cited
    • 2024Rankability-enhanced Revenue Uplift Modeling Framework for Online Marketing15 cited
    • 2023Exploring uplift modeling with high class imbalance15 cited
    • 2022Multiple Treatment Modeling for Target Marketing Campaigns: A Large-Scale Benchmark Study14 cited
    • 2023Improving Shopping Mall Revenue by Real-Time Customized Digital Coupon Issuance13 cited
    • 2024Predicting and optimizing marketing performance in dynamic markets9 cited