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Optimal Price Targeting

Smith, Adam N; Seiler, Stephan; Aggarwal, Ishant; (2022) Optimal Price Targeting. Marketing Science 10.1287/mksc.2022.1387. (In press). Green open access

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Abstract

The paper compares the profitability of personalized pricing policies that are generated from different models of demand and using different data inputs.

Type: Article
Title: Optimal Price Targeting
Open access status: An open access version is available from UCL Discovery
DOI: 10.1287/mksc.2022.1387
Publisher version: https://doi.org/10.1287/mksc.2022.1387
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Social Sciences, Business, Business & Economics, targeting, personalization, heterogeneity, choice models, machine learning, PROMOTIONS, BRAND, STRATEGIES, VARIABLES, SELECTION, ONLINE, SMOTE, MODEL
UCL classification: UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > UCL School of Management
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL
URI: https://discovery.ucl.ac.uk/id/eprint/10156641
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