IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v30y2011i5p837-850.html
   My bibliography  Save this article

Measuring the Lifetime Value of Customers Acquired from Google Search Advertising

Author

Listed:
  • Tat Y. Chan

    (Olin Business School, Washington University in St. Louis, St. Louis, Missouri 63130)

  • Chunhua Wu

    (Olin Business School, Washington University in St. Louis, St. Louis, Missouri 63130)

  • Ying Xie

    (Olin Business School, Washington University in St. Louis, St. Louis, Missouri 63130)

Abstract

Our main objective in this paper is to measure the value of customers acquired from Google search advertising accounting for two factors that have been overlooked in the conventional method widely adopted in the industry: (1) the spillover effect of search advertising on customer acquisition and sales in off-line channels and (2) the lifetime value of acquired customers. By merging Web traffic and sales data from a small-sized U.S. firm, we create an individual customer-level panel that tracks all repeated purchases, both online and off-line, and tracks whether or not these purchases were referred from Google search advertising. To estimate the customer lifetime value, we apply the methodology in the customer relationship management literature by developing an integrated model of customer lifetime, transaction rate, and gross profit margin, allowing for individual heterogeneity and a full correlation of the three processes. Results show that customers acquired through Google search advertising in our data have a higher transaction rate than customers acquired from other channels. After accounting for future purchases and spillover to off-line channels, the calculated value of new customers using our approach is much higher than the value obtained using conventional method. The approach used in our study provides a practical framework for firms to evaluate the long-term profit impact of their search advertising investment in a multichannel setting.

Suggested Citation

  • Tat Y. Chan & Chunhua Wu & Ying Xie, 2011. "Measuring the Lifetime Value of Customers Acquired from Google Search Advertising," Marketing Science, INFORMS, vol. 30(5), pages 837-850, September.
  • Handle: RePEc:inm:ormksc:v:30:y:2011:i:5:p:837-850
    DOI: 10.1287/mksc.1110.0658
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.1110.0658
    Download Restriction: no

    File URL: https://libkey.io/10.1287/mksc.1110.0658?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Deleersnyder, B. & Geyskens, I. & Gielens, K.J.P. & Dekimpe, M.G., 2002. "How cannibalistic is the internet channel? A study of the newspaper industry in the United Kingdom and the Netherlands," Other publications TiSEM 16dcb25c-7ea9-4c75-bdf6-5, Tilburg University, School of Economics and Management.
    2. Benjamin Edelman & Michael Ostrovsky & Michael Schwarz, 2007. "Internet Advertising and the Generalized Second-Price Auction: Selling Billions of Dollars Worth of Keywords," American Economic Review, American Economic Association, vol. 97(1), pages 242-259, March.
    3. Makoto Abe, 2009. "“Counting Your Customers” One by One: A Hierarchical Bayes Extension to the Pareto/NBD Model," Marketing Science, INFORMS, vol. 28(3), pages 541-553, 05-06.
    4. Bas Donkers & Peter Verhoef & Martijn Jong, 2007. "Modeling CLV: A test of competing models in the insurance industry," Quantitative Marketing and Economics (QME), Springer, vol. 5(2), pages 163-190, June.
    5. Siddharth Singh & Sharad Borle & Dipak Jain, 2009. "A generalized framework for estimating customer lifetime value when customer lifetimes are not observed," Quantitative Marketing and Economics (QME), Springer, vol. 7(2), pages 181-205, June.
    6. David C. Schmittlein & Donald G. Morrison & Richard Colombo, 1987. "Counting Your Customers: Who-Are They and What Will They Do Next?," Management Science, INFORMS, vol. 33(1), pages 1-24, January.
    7. Zsolt Katona & Miklos Sarvary, 2010. "The Race for Sponsored Links: Bidding Patterns for Search Advertising," Marketing Science, INFORMS, vol. 29(2), pages 199-215, 03-04.
    8. Anindya Ghose & Sha Yang, 2009. "An Empirical Analysis of Search Engine Advertising: Sponsored Search in Electronic Markets," Management Science, INFORMS, vol. 55(10), pages 1605-1622, October.
    9. Anindya Ghose & Sha Yang, 2007. "An Empirical Analysis of Search Engine Advertising: Sponsored Search and Cross-Selling in Electronic Markets," Working Papers 07-35, NET Institute, revised Sep 2007.
    10. Deleersnyder, B. & Geyskens, I. & Gielens, K. & Dekimpe, M.G., 2002. "How Cannibalistic is the Internet Channel?," ERIM Report Series Research in Management ERS-2002-22-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    11. David C. Schmittlein & Robert A. Peterson, 1994. "Customer Base Analysis: An Industrial Purchase Process Application," Marketing Science, INFORMS, vol. 13(1), pages 41-67.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hitesh Sood & Rajendra Prasad Sharma, 2021. "Customer Digital Engagement and Lifetime Value: An Empirical Study of Telecom Services in India," FIIB Business Review, , vol. 12(4), pages 415-424, December.
    2. Thomas Niemand & Sascha Kraus & Sophia Mather & Antonio C. Cuenca-Ballester, 0. "Multilevel marketing: optimizing marketing effectiveness for high-involvement goods in the automotive industry," International Entrepreneurship and Management Journal, Springer, vol. 0, pages 1-26.
    3. Kannan, P.K. & Li, Hongshuang “Alice”, 2017. "Digital marketing: A framework, review and research agenda," International Journal of Research in Marketing, Elsevier, vol. 34(1), pages 22-45.
    4. Bernd Skiera & Nadia Abou Nabout, 2013. "Practice Prize Paper ---PROSAD: A Bidding Decision Support System for Profit Optimizing Search Engine Advertising," Marketing Science, INFORMS, vol. 32(2), pages 213-220, March.
    5. Ivan Guitart & Stefan Stremersch, 2021. "The impact of informational and emotional television ad content on online search and sales," Post-Print hal-03193729, HAL.
    6. Bayer, Emanuel & Srinivasan, Shuba & Riedl, Edward J. & Skiera, Bernd, 2020. "The impact of online display advertising and paid search advertising relative to offline advertising on firm performance and firm value," International Journal of Research in Marketing, Elsevier, vol. 37(4), pages 789-804.
    7. Antonia Köster & Christian Matt & Thomas Hess, 2021. "Do All Roads Lead to Rome? Exploring the Relationship Between Social Referrals, Referral Propensity and Stickiness to Video-on-Demand Websites," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 63(4), pages 349-366, August.
    8. Haoyan Sun & Ming Fan & Yong Tan, 2020. "An Empirical Analysis of Seller Advertising Strategies in an Online Marketplace," Information Systems Research, INFORMS, vol. 31(1), pages 37-56, March.
    9. Ashwin Aravindakshan & Olivier Rubel & Oliver Rutz, 2015. "Managing Blood Donations with Marketing," Marketing Science, INFORMS, vol. 34(2), pages 269-280, March.
    10. Klapdor, Sebastian & Anderl, Eva M. & von Wangenheim, Florian & Schumann, Jan H., 2014. "Finding the Right Words: The Influence of Keyword Characteristics on Performance of Paid Search Campaigns," Journal of Interactive Marketing, Elsevier, vol. 28(4), pages 285-301.
    11. Thomas Blake & Chris Nosko & Steven Tadelis, 2015. "Consumer Heterogeneity and Paid Search Effectiveness: A Large‐Scale Field Experiment," Econometrica, Econometric Society, vol. 83, pages 155-174, January.
    12. Elliot Shin Oblander & Sunil Gupta & Carl F. Mela & Russell S. Winer & Donald R. Lehmann, 2020. "The past, present, and future of customer management," Marketing Letters, Springer, vol. 31(2), pages 125-136, September.
    13. Kohsuke Matsuoka, 2020. "Exploring the interface between management accounting and marketing: a literature review of customer accounting," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 31(3), pages 157-208, September.
    14. Weijia Dai & Hyunjin Kim & Michael Luca, 2016. "Which Firms Gain from Digital Advertising? Evidence from a Field Experiment," Harvard Business School Working Papers 17-025, Harvard Business School, revised Jan 2023.
    15. Hongshuang (Alice) Li, 2022. "Converting free users to paid subscribers in the SaaS context: The impact of marketing touchpoints, message content, and usage," Production and Operations Management, Production and Operations Management Society, vol. 31(5), pages 2185-2203, May.
    16. Chunhua Wu, 2015. "Matching Value and Market Design in Online Advertising Networks: An Empirical Analysis," Marketing Science, INFORMS, vol. 34(6), pages 906-921, November.
    17. Huan Yu & Ye Shi & Yugang Yu & Jie Liu & Feng Yang & Jie Wu, 2020. "Business analytics: online promotion with gift rewards," Annals of Operations Research, Springer, vol. 291(1), pages 1061-1076, August.
    18. Clarence Lee & Elie Ofek & Thomas J. Steenburgh, 2018. "Personal and Social Usage: The Origins of Active Customers and Ways to Keep Them Engaged," Management Science, INFORMS, vol. 64(6), pages 2473-2495, June.
    19. Thomas Niemand & Sascha Kraus & Sophia Mather & Antonio C. Cuenca-Ballester, 2020. "Multilevel marketing: optimizing marketing effectiveness for high-involvement goods in the automotive industry," International Entrepreneurship and Management Journal, Springer, vol. 16(4), pages 1367-1392, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jerath, Kinshuk & Fader, Peter S. & Hardie, Bruce G.S., 2016. "Customer-base analysis using repeated cross-sectional summary (RCSS) data," European Journal of Operational Research, Elsevier, vol. 249(1), pages 340-350.
    2. Avi Goldfarb, 2014. "What is Different About Online Advertising?," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 44(2), pages 115-129, March.
    3. Park, Chang Hee & Park, Young-Hoon & Schweidel, David A., 2014. "A multi-category customer base analysis," International Journal of Research in Marketing, Elsevier, vol. 31(3), pages 266-279.
    4. Thorsten Wiesel & Koen Pauwels & Joep Arts, 2011. "Practice Prize Paper --Marketing's Profit Impact: Quantifying Online and Off-line Funnel Progression," Marketing Science, INFORMS, vol. 30(4), pages 604-611, July.
    5. Kinshuk Jerath & Liye Ma & Young-Hoon Park & Kannan Srinivasan, 2011. "A "Position Paradox" in Sponsored Search Auctions," Marketing Science, INFORMS, vol. 30(4), pages 612-627, July.
    6. Alex Kim & Subramanian Balachander & Karthik Kannan, 2012. "On the optimal number of advertising slots in a generalized second-price auction," Marketing Letters, Springer, vol. 23(3), pages 851-868, September.
    7. Patrick Hummel, 2018. "Hybrid mechanisms for Vickrey–Clarke–Groves and generalized second-price bids," International Journal of Game Theory, Springer;Game Theory Society, vol. 47(1), pages 331-350, March.
    8. Michael Platzer & Thomas Reutterer, 2016. "Ticking Away the Moments: Timing Regularity Helps to Better Predict Customer Activity," Marketing Science, INFORMS, vol. 35(5), pages 779-799, September.
    9. David A. Schweidel & George Knox, 2013. "Incorporating Direct Marketing Activity into Latent Attrition Models," Marketing Science, INFORMS, vol. 32(3), pages 471-487, May.
    10. Makoto Abe, 2015. "Deriving Customer Lifetime Value from RFM Measures:Insights into Customer Retention and Acquisition," CIRJE F-Series CIRJE-F-962, CIRJE, Faculty of Economics, University of Tokyo.
    11. Tudoran, Ana Alina & Hjerrild Thomsen, Charlotte & Thomasen, Sophie, 2024. "Understanding consumer behavior during and after a Pandemic: Implications for customer lifetime value prediction models," Journal of Business Research, Elsevier, vol. 174(C).
    12. Lydia Simon & Jost Adler, 2022. "Worth the effort? Comparison of different MCMC algorithms for estimating the Pareto/NBD model," Journal of Business Economics, Springer, vol. 92(4), pages 707-733, May.
    13. Yi Zhu & Kenneth C. Wilbur, 2011. "Hybrid Advertising Auctions," Marketing Science, INFORMS, vol. 30(2), pages 249-273, 03-04.
    14. Patrick Bachmann & Markus Meierer & Jeffrey Näf, 2021. "The Role of Time-Varying Contextual Factors in Latent Attrition Models for Customer Base Analysis," Marketing Science, INFORMS, vol. 40(4), pages 783-809, July.
    15. Avi Goldfarb & Catherine Tucker, 2011. "Search Engine Advertising: Channel Substitution When Pricing Ads to Context," Management Science, INFORMS, vol. 57(3), pages 458-470, March.
    16. Kinshuk Jerath & Peter S. Fader & Bruce G. S. Hardie, 2011. "New Perspectives on Customer "Death" Using a Generalization of the Pareto/NBD Model," Marketing Science, INFORMS, vol. 30(5), pages 866-880, September.
    17. Berman, Ron & Katona, Zsolt, 2010. "The Role of Search Engine Optimization in Search Rankings," MPRA Paper 20129, University Library of Munich, Germany.
    18. Song Yao & Carl F. Mela, 2011. "A Dynamic Model of Sponsored Search Advertising," Marketing Science, INFORMS, vol. 30(3), pages 447-468, 05-06.
    19. Xiaoquan (Michael) Zhang & Juan Feng, 2011. "Cyclical Bid Adjustments in Search-Engine Advertising," Management Science, INFORMS, vol. 57(9), pages 1703-1719, February.
    20. Sha Yang & Anindya Ghose, 2010. "Analyzing the Relationship Between Organic and Sponsored Search Advertising: Positive, Negative, or Zero Interdependence?," Marketing Science, INFORMS, vol. 29(4), pages 602-623, 07-08.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormksc:v:30:y:2011:i:5:p:837-850. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.