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Using control groups to target on predicted lift: Building and assessing uplift model
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Using control groups to target on predicted lift: Building and assessing uplift model (2007)Using control groups to target on predict…A large scale benchmark for uplift modeling (2024)A large scale benchmark for u…Uplift modeling with value-driven evaluation metrics (2021)Uplift modeling with value-dr…Uplift modeling and its implications for B2B customer churn prediction: A segmentation-based modeling approach (2021)Uplift modeling and its impli…Targeting customers under response-dependent costs (2021)Targeting customers under res…Profit uplift modeling for direct marketing campaigns: approaches and applications for online shops (2021)Profit uplift modeling for di…Response transformation and profit decomposition for revenue uplift modeling (2019)Response transformation and p…Dynamic pricing of airline offers (2018)Dynamic pricing of airline of…Commodity Bundling and the Burden of Monopoly (1976)Prospect Theory: An Analysis of Decision under Risk (1979)Prospect theory: An analysis of decision under risk (1988)Personalization in airline revenue management: an overview and future outlook (2021)Highly debated but still unbundled: The evolution of U.S. airline ancillary products and pricing strategies (2022)Evaluation of passengers' expectations and satisfaction in the airline industry: an empirical performance analysis of online reviews (2023)Data mining for direct marketing: problems and solutions (1998)Online Display Advertising: Targeting and Obtrusiveness (2011)Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research (2015)On realising the utopian potential of big data analytics for maximising return on marketing investments (2020)Defection Detection: Measuring and Understanding the Predictive Accuracy of Customer Churn Models (2006)Marketing Analytics for Data-Rich Environments (2016)Multiple Treatment Modeling for Target Marketing Campaigns: A Large-Scale Benchmark Study (2022)Exploring uplift modeling with high class imbalance (2023)Green rewards vs. non-green rewards? The impact of hotel marketing incentives on guests’ green consumption intentions (2024)Real-World Uplift Modelling with Significance-Based Uplift Trees (2012)To Treat, or Not to Treat: Reducing Volatility in Uplift Modeling Through Weighted Ensembles (2021)Decision trees for uplift modeling with single and multiple treatments (2011)New insights into churn prediction in the telecommunication sector: A profit driven data mining approach (2011)Retention Futility: Targeting High-Risk Customers Might be Ineffective (2017)A gateway toward truly responsive customers: using the uplift modeling to increase the performance of a B2B marketing campaign (2023)Organizational Buying Behavior (1973)Counting Your Customers: Who-Are They and What Will They Do Next? (1987)Relationship quality as a predictor of B2B customer loyalty (2006)B2Boost: instance-dependent profit-driven modelling of B2B churn (2022)Bibliometric review on human resources management and big data analytics (2022)Proactive customer retention management in a non-contractual B2B setting based on churn prediction with random forests (2022)Database Marketing (2008)Database Marketing: Analyzing and Managing Customers (2008)
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  • 2019Response transformation and profit decomposition for revenue uplift modeling54 cited
  • 2021Uplift modeling and its implications for B2B customer churn prediction: A segmentation-based modeling approach50 cited
  • 2018Dynamic pricing of airline offers34 cited
  • 2024A large scale benchmark for uplift modeling33 cited
  • 2021Targeting customers under response-dependent costs26 cited
  • 2021Uplift modeling with value-driven evaluation metrics23 cited
  • 2021Profit uplift modeling for direct marketing campaigns: approaches and applications for online shops8 cited

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