Optimizing price levels in e-commerce applications with respect to customer lifetime values
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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Proceedings of the 11th International Conference on Electronic Commerce, ICEC 2009. ed. / Patrick Y. K. Chau; Kalle Lyytinen; Chih-Ping Wei. Association for Computing Machinery, Inc, 2009. p. 169-175 (ACM International Conference Proceeding Series).
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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TY - CHAP
T1 - Optimizing price levels in e-commerce applications with respect to customer lifetime values
AU - Funk, Burkhardt
N1 - Conference code: 10
PY - 2009/8/12
Y1 - 2009/8/12
N2 - In a recent paper we have shown how Internet retailers could optimize their price levels according to their strategy. The discussed method optimizes short-term profitability by determining the exact demand curve. The method involves the application of empirical price tests. For this purpose visitors of an Internet retailer are divided in statistically identical subgroups. Using the A-B testing method different prices are shown to each subgroup and the conversion rate as a function of price is calculated. We describe the organizational requirements, the technical approach, and the statistical analysis applied to determine the price optimizing the per-order profit and the average customer lifetime value. In this paper we review the results of a field study carried out with a large Internet retailer and shows that the company was able to optimize a specific price component and thus increase the contribution margin per order by about 7%. In addition we argue that at the same time the customer lifetime value could be enhanced by 13%. We conclude that the discussed method could be applied to answer further research questions such as the temporal variation of demand curves. Copyright © 2009 ACM.
AB - In a recent paper we have shown how Internet retailers could optimize their price levels according to their strategy. The discussed method optimizes short-term profitability by determining the exact demand curve. The method involves the application of empirical price tests. For this purpose visitors of an Internet retailer are divided in statistically identical subgroups. Using the A-B testing method different prices are shown to each subgroup and the conversion rate as a function of price is calculated. We describe the organizational requirements, the technical approach, and the statistical analysis applied to determine the price optimizing the per-order profit and the average customer lifetime value. In this paper we review the results of a field study carried out with a large Internet retailer and shows that the company was able to optimize a specific price component and thus increase the contribution margin per order by about 7%. In addition we argue that at the same time the customer lifetime value could be enhanced by 13%. We conclude that the discussed method could be applied to answer further research questions such as the temporal variation of demand curves. Copyright © 2009 ACM.
KW - Business informatics
KW - Demand curve
KW - Electronic commerce
KW - Posted prices
KW - Price dispersion
KW - Price optimization
KW - Price partitioning
KW - Price tests
KW - Pricing strategy
KW - Sustainability sciences, Communication
UR - http://www.scopus.com/inward/record.url?scp=70450263489&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/983bbc27-7028-3ed3-b693-d8882bd2a2a0/
U2 - 10.1145/1593254.1593280
DO - 10.1145/1593254.1593280
M3 - Article in conference proceedings
SN - 978-160558586-4
T3 - ACM International Conference Proceeding Series
SP - 169
EP - 175
BT - Proceedings of the 11th International Conference on Electronic Commerce, ICEC 2009
A2 - Chau, Patrick Y. K.
A2 - Lyytinen, Kalle
A2 - Wei, Chih-Ping
PB - Association for Computing Machinery, Inc
T2 - ACM Conference on Electronic Commerce - EC 2009
Y2 - 6 July 2009 through 10 July 2009
ER -