TY - CHAP

T1 - Employing A-B tests for optimizing prices levels in e-commerce applications

AU - Funk, Burkhardt

N1 - Conference code: 15

PY - 2009

Y1 - 2009

N2 - Price dispersion in the Internet is a well studied phenomenon. It enables companies to adjust prices to a level appropriate to their strategy. This paper deals with question how Internet retailers should do so. The discussed method optimizes short- and long-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. A field study carried out with a large Internet retailer is presented and shows that the company was able to optimize a specific price component and thus increase the contribution margin per order by about 7% while 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.

AB - Price dispersion in the Internet is a well studied phenomenon. It enables companies to adjust prices to a level appropriate to their strategy. This paper deals with question how Internet retailers should do so. The discussed method optimizes short- and long-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. A field study carried out with a large Internet retailer is presented and shows that the company was able to optimize a specific price component and thus increase the contribution margin per order by about 7% while 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.

KW - Business informatics

UR - http://www.scopus.com/inward/record.url?scp=84870265538&partnerID=8YFLogxK

M3 - Published abstract in conference proceedings

AN - SCOPUS:84870265538

SN - 9781615675814

T3 - Proceedings of the Americas Conference on Information Systems (AMCIS)

SP - 347

BT - 15th Americas Conference on Information Systems 2009, AMCIS 2009

PB - AIS eLibrary

T2 - Americas Conference on Information Systems - AMCIS 2009

Y2 - 6 August 2009 through 9 August 2009

ER -