Practice Prize Winner - ECO: Entega's Profitable New Customer Acquisition on Online Price Comparison Sites

Market liberalization of the German household electricity market has led to an excessive number of competitors (1,150 electricity providers) and volatile price dynamics on price comparison sites. To date, providers that are struggling to achieve a top ranking on price comparison sites do not appear to implement a consistent or elaborate strategy for attracting customers. We developed a pricing tool, E lectricity C ontract O ptimization (ECO), that addresses this highly competitive market situation by integrating various available data sources, such as data from price comparison sites, demographic data, and regional sales or cost data. ECO sets regionally varying one-time bonuses to attract new customers on price comparison sites with the goal of optimizing sales and profit targets or optimally allocating sales budgets. Based on two field experiments, we demonstrate that ECO’s optimization procedure reduces ENTEGA yearly sales costs for new customer business, on average, by 35% relative to previously used pricing heuristics. ENTEGA uses ECO monthly to analyze different scenarios or to set prices and one-time bonuses on price comparison sites.Data, as supplemental material, are available at http://dx.doi.org/10.1287/mksc.2015.0943 .

[1]  Venkatesh Shankar,et al.  Why Aren't the Prices of the Same Item the Same at Me.Com and You.Com?: Drivers of Price Dispersion Among E-Tailers , 2001 .

[2]  Michael R. Baye,et al.  Information Gatekeepers on the Internet and the Competitiveness of Homogeneous Product Markets , 2001 .

[3]  P. K. Kannan,et al.  Dynamic Pricing on the Internet: Importance and Implications for Consumer Behavior , 2001, Int. J. Electron. Commer..

[4]  John Morgan,et al.  Brand and Price Advertising in Online Markets , 2004, Manag. Sci..

[5]  Erik Brynjolfsson,et al.  Consumer Decision-Making at an Internet Shopbot , 2001 .

[6]  R. Lal,et al.  When and How is the Internet Likely to Decrease Price Competition , 1999 .

[7]  Eric K. Clemons,et al.  Price Dispersion and Differentiation in Online Travel: An Empirical Investigation , 2002, Manag. Sci..

[8]  Venkatesh Shankar,et al.  Effective Marketing Science Applications: Insights from the ISMS-MSI Practice Prize Finalist Papers and Projects , 2013, Mark. Sci..

[9]  J. LeSage Introduction to spatial econometrics , 2009 .

[10]  John Morgan,et al.  Estimating Firm-Level Demand at a Price Comparison Site: Accounting for Shoppers and the Number of Competitors , 2004 .

[11]  Michael R. Baye,et al.  Chapter 6 Information, Search, and Price Dispersion , 2006 .

[12]  Glenn Ellison,et al.  Search, Obfuscation, and Price Elasticities on the Internet , 2004 .

[13]  Cenk Kocas,et al.  Evolution of Prices in Electronic Markets Under Diffusion of Price-Comparison Shopping , 2002, J. Manag. Inf. Syst..

[14]  J. Chevalier,et al.  Measuring Prices and Price Competition Online: Amazon.com and BarnesandNoble.com , 2003 .

[15]  Brian T. Ratchford,et al.  Price dispersion on the internet: A review and directions for future research , 2004 .

[16]  Austan Goolsbee,et al.  Does the Internet Make Markets More Competitive? Evidence from the Life Insurance Industry , 2000, Journal of Political Economy.

[17]  Michael R. Baye,et al.  Information, Search, and Price Dispersion , 2006 .

[18]  A. Pazgal,et al.  Internet Shopping Agents: Virtual Co-Location and Competition , 2001 .

[19]  Brian T. Ratchford,et al.  On the Efficiency of Internet Markets for Consumer Goods , 2003 .

[20]  Cenk Kocas A Model of Internet Pricing Under Price-Comparison Shopping , 2005, Int. J. Electron. Commer..