Smith, Adam N;
Seiler, Stephan;
Aggarwal, Ishant;
(2022)
Optimal Price Targeting.
Marketing Science
10.1287/mksc.2022.1387.
(In press).
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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-pp.ucl.ac.uk/id/eprint/10156641 |
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