A Hierarchical Bayes Model of Primary and Secondary Demand
Marketing Science
The Decomposition of Promotional Response: An Empirical Generalization
Marketing Science
Modeling the Clickstream: Implications for Web-Based Advertising Efforts
Marketing Science
A Comparison of Online and Offline Consumer Brand Loyalty
Marketing Science
Modeling Browsing Behavior at Multiple Websites
Marketing Science
Observed and Unobserved Preference Heterogeneity in Brand-Choice Models
Marketing Science
On Customized Goods, Standard Goods, and Competition
Marketing Science
Modeling Online Browsing and Path Analysis Using Clickstream Data
Marketing Science
Customized Products: A Competitive Analysis
Marketing Science
The Effect of Product Assortment Changes on Customer Retention
Marketing Science
How to Compute Optimal Catalog Mailing Decisions
Marketing Science
Observed and Unobserved Preference Heterogeneity in Brand-Choice Models
Marketing Science
On Customized Goods, Standard Goods, and Competition
Marketing Science
Knowledge-based approach to improving micromarketing decisions in a data-challenged environment
Expert Systems with Applications: An International Journal
Personalization and choice behavior: the role of personality traits
ACM SIGMIS Database
Up close and personalized: a marketing view of recommendation systems
Proceedings of the third ACM conference on Recommender systems
Dynamic Customer Management and the Value of One-to-One Marketing
Marketing Science
Optimizing time limits for maximum sales response in Internet shopping promotions
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Improved response modeling based on clustering, under-sampling, and ensemble
Expert Systems with Applications: An International Journal
The Advertising Mix for a Search Good
Management Science
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The main objective of this paper is to provide a decision-support system of micro-level customized promotions, primarily for use in online stores. Our proposed approach utilizes the one-on-one and interactive nature of the Internet shopping environment and provides recommendations on when to promote how much to whom. We address the issue by first constructing a joint purchase incidence-brand choice-purchase quantity model that incorporates how variety-seeking/inertia tendency differs among households and change over time for the same household. Based on the model, we develop an optimization procedure to derive the optimal amount of price discount for each household on each shopping trip. We demonstrate that the proposed customization method could greatly improve the effectiveness of current promotion practices, and discuss the implications for retailers and consumer packaged goods companies in the age of Internet technology.