Uplift modeling and its implications for B2B customer churn prediction: A segmentation-based modeling approach
Abstract Business-to-business (B2B) customer retention relies heavily on analytics and
predictive modeling to support decision making. Given this, we introduce uplift modeling as …
predictive modeling to support decision making. Given this, we introduce uplift modeling as …
To do or not to do? Cost-sensitive causal classification with individual treatment effect estimates
Individual treatment effect models allow optimizing decision-making by predicting the effect
of a treatment on an outcome of interest for individual instances. These predictions allow …
of a treatment on an outcome of interest for individual instances. These predictions allow …
Improving uplift model evaluation on randomized controlled trial data
B Bokelmann, S Lessmann - European Journal of Operational Research, 2024 - Elsevier
Estimating treatment effects is one of the most challenging and important tasks of data
analysts. Personalized medicine, digital marketing, and many other applications demand an …
analysts. Personalized medicine, digital marketing, and many other applications demand an …
Rankability-enhanced revenue uplift modeling framework for online marketing
Uplift modeling has been widely employed in online marketing by predicting the response
difference between the treatment and control groups, so as to identify the sensitive …
difference between the treatment and control groups, so as to identify the sensitive …
Uplift modeling with generalization guarantees
In this paper, we consider the task of ranking individuals based on the potential benefit of
being" treated"(eg by a drug or exposure to recommendations or ads), referred to as Uplift …
being" treated"(eg by a drug or exposure to recommendations or ads), referred to as Uplift …
Explicit feature interaction-aware uplift network for online marketing
As a key component in online marketing, uplift modeling aims to accurately capture the
degree to which different treatments motivate different users, such as coupons or discounts …
degree to which different treatments motivate different users, such as coupons or discounts …
Uplift modeling and its implications for appointment date prediction in attended home delivery
D Wang, Q Xu, Y Feng, J Ignatius, Y Yin… - Decision Support Systems, 2024 - Elsevier
Successful attended home delivery (AHD) is the most important aspect of e-commerce order
fulfillment. Prior literature focuses on incentive scheme development for customers' choices …
fulfillment. Prior literature focuses on incentive scheme development for customers' choices …
Multimodal machine learning for prognosis and survival prediction in renal cell carcinoma patients: a two-stage framework with model fusion and interpretability …
Current medical limitations in predicting cancer survival status and time necessitate
advancements beyond traditional methods and physical indicators. This research introduces …
advancements beyond traditional methods and physical indicators. This research introduces …
Uplift modeling with value-driven evaluation metrics
RM Gubela, S Lessmann - Decision support systems, 2021 - Elsevier
Measuring the success of targeted marketing actions is challenging. Research on
prescriptive analytics recommends uplift models to guide targeting decisions. Uplift models …
prescriptive analytics recommends uplift models to guide targeting decisions. Uplift models …
Weighted doubly robust learning: An uplift modeling technique for estimating mixed treatments' effect
B Zhan, C Liu, Y Li, C Wu - Decision Support Systems, 2024 - Elsevier
Estimating the effect of mixed treatments is a crucial problem in causal inference. While
previous studies have focused on econometric analysis, few have positioned the mixed …
previous studies have focused on econometric analysis, few have positioned the mixed …