Journal article 91 views 21 downloads
A novel response model and target selection method with applications to marketing
Australian & New Zealand Journal of Statistics, Volume: 66, Issue: 1, Pages: 48 - 76
Swansea University Author:
Yuzhi Cai
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DOI (Published version): 10.1111/anzs.12406
Abstract
Response models used in marketing are not always constructed for later marketing optimisation, which often results in unsatisfactory results in target selection for future marketing activities. To solve this problem, we develop a new binary response model and a new marketing target selection method....
| Published in: | Australian & New Zealand Journal of Statistics |
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| ISSN: | 1369-1473 1467-842X |
| Published: |
Wiley
2024
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| Online Access: |
Check full text
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa65339 |
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| Abstract: |
Response models used in marketing are not always constructed for later marketing optimisation, which often results in unsatisfactory results in target selection for future marketing activities. To solve this problem, we develop a new binary response model and a new marketing target selection method. The proposed model can predict multiple propensity scores per customer through customer-specific propensity score distributions, which is not possible with existing response models, filling a gap in the literature. The target selection method can determine the best propensity scores from those predicted by the proposed model and use them to select customers for further marketing activities. Our simulation results and application to real marketing data confirm that the performance of the proposed model in target selection is significantly better than that of the existing models, including some popular machine learning methods, which indicate that our method can be very useful in practice. |
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| Keywords: |
marketing; propensity score; quantile function; response model; target selection. |
| College: |
Faculty of Humanities and Social Sciences |
| Funders: |
Swansea University |
| Issue: |
1 |
| Start Page: |
48 |
| End Page: |
76 |