How Search Engine Advertising Affects Sales over Time: An Empirical Investigation

As a mainstream marketing channel on the Internet, Search Engine Advertising (SEA) has a huge business impact and attracts a plethora of attention from both academia and industry. One important goal of advertising is to increase sales. Nevertheless, while previous research has studied multiple factors that are potentially related to the outcome of SEA campaigns, effects of these factors on actual sales generated by SEA remain understudied. It is also unclear whether and how such effects change over time in highly dynamic SEA campaigns. As the first empirical investigation of the dynamic advertisement-sales relationship in SEA, this study builds an advertising response model within a time-varying coefficient (TVC) modeling framework, and estimates the model using a unique dataset from a large E-Commerce retailer in the United States. Results reveal the effects of the advertising expenditure, consumer behaviors and advertisement characteristics on realized sales, and demonstrate that such effects on sales do change over time in non-linear ways. More importantly, we find that carryover has a stronger effect in generating sales than direct response does, conversion rate is much more important than click-through rate, and ad position does not have significant effects on sales. These findings have direct implications for advertisers to launch more effective SEA campaigns.

[1]  Shanshan Hu,et al.  Sponsored Search Marketing: Dynamic Pricing and Advertising for an Online Retailer , 2015, Manag. Sci..

[2]  K. Train,et al.  A Control Function Approach to Endogeneity in Consumer Choice Models , 2010 .

[3]  Song Yao,et al.  A Dynamic Model of Sponsored Search Advertising , 2010, Mark. Sci..

[4]  Ming Fan,et al.  An Empirical Analysis of Seller Advertising Strategies in an Online Marketplace , 2020, Inf. Syst. Res..

[5]  Jan Stallaert,et al.  An Economic Analysis of Online Advertising Using Behavioral Targeting , 2010, MIS Q..

[6]  Randall L. Schultz,et al.  Marketing Models and Econometric Research , 1976 .

[7]  Rex Du,et al.  Leveraging Trends in Online Searches for Product Features in Market Response Modeling , 2015 .

[8]  Stanley R. Johnson,et al.  Varying Coefficient Models , 1984 .

[9]  S. Albers,et al.  Submission to the 2009-2010 ISMS-MSI Practice Prize Competition Dynamic Marketing Budget Allocation across Countries , Products , and Marketing Activities , 2010 .

[10]  Stefan Stremersch,et al.  Sales Growth of New Pharmaceuticals Across the Globe: The Role of Regulatory Regimes , 2008, Mark. Sci..

[11]  K. Sudhir,et al.  Forecasting Marketing-Mix Responsiveness for New Products , 2010 .

[12]  Xiaoquan Zhang,et al.  Cyclical Bid Adjustments in Search-Engine Advertising , 2011, Manag. Sci..

[13]  Aditya G. Parameswaran,et al.  Information seeking , 2011, Commun. ACM.

[14]  Dengpan Liu,et al.  Dynamic Budget Allocation in Competitive Search Advertising , 2016 .

[15]  Gerard J. Tellis,et al.  How Well Does Advertising Work? Generalizations from Meta-Analysis of Brand Advertising Elasticities , 2011 .

[16]  Runze Li,et al.  A time-varying effect model for intensive longitudinal data. , 2012, Psychological methods.

[17]  D. Clarke Econometric Measurement of the Duration of Advertising Effect on Sales , 1976 .

[18]  Peter E. Rossi,et al.  Even the Rich Can Make Themselves Poor: A Critical Examination of IV Methods in Marketing Applications , 2014 .

[19]  Robert Fildes,et al.  Marketing Models and Econometric Research , 1977 .

[20]  Scott A. Neslin,et al.  Driving Online and Offline Sales: The Cross-Channel Effects of Traditional, Online Display, and Paid Search Advertising , 2013 .

[21]  P. Naik Marketing Dynamics: A Primer on Estimation and Control , 2015 .

[22]  Ricardo J. Caballero,et al.  Beyond the Partial-Adjustment Model , 1992 .

[23]  Prasad A. Naik,et al.  Understanding the Impact of Synergy in Multimedia Communications , 2003 .

[24]  Randall A. Lewis,et al.  The Online Display Ad Effectiveness Funnel & Carryover: A Meta-study of Predicted Ghost Ad Experiments , 2016 .

[25]  Z. Katona,et al.  Quality Score that Makes You Invest , 2020 .

[26]  D. Clarke,et al.  Sales-Advertising Cross-Elasticities and Advertising Competition , 1973 .

[27]  Matt P. Wand,et al.  Smoothing and mixed models , 2003, Comput. Stat..

[28]  Vibhanshu Abhishek,et al.  Optimal Bidding in Multi-Item Multislot Sponsored Search Auctions , 2013, Oper. Res..

[29]  Michael D. Smith,et al.  Location, Location, Location: An Analysis of Profitability of Position in Online Advertising Markets , 2008 .

[30]  Peter J. Danaher,et al.  The Effect of Competitive Advertising Interference on Sales for Packaged Goods , 2008 .

[31]  Insu Park,et al.  Using Big Data to Model Time-Varying Effects for Marketing Resource (Re)Allocation , 2016, MIS Q..

[32]  Ashish Agarwal,et al.  The Impact of Competing Ads on Click Performance in Sponsored Search , 2016, Inf. Syst. Res..

[33]  Anindya Ghose,et al.  An Empirical Analysis of Search Engine Advertising: Sponsored Search in Electronic Markets , 2009, Manag. Sci..

[34]  Oliver J. Rutz,et al.  From Generic to Branded: A Model of Spillover in Paid Search Advertising , 2011 .

[35]  Bernard J. Jansen,et al.  Aggregate Effects of Advertising Decisions: A Complex Systems Look at Search Engine Advertising Via an Experimental Study , 2018, Internet Res..

[36]  Makoto Ohta,et al.  Production Technologies of the U.S. Boiler and Turbogenerator Industries and Hedonic Price Indexes for Their Products: A Cost-Function Approach , 1975, Journal of Political Economy.

[37]  Tammo H. A. Bijmolt,et al.  The Effect of Electronic Word of Mouth on Sales: A Meta-Analytic Review of Platform, Product, and Metric Factors , 2016 .

[38]  John D. C. Little,et al.  BRANDAID: A Marketing-Mix Model, Part 1: Structure , 1975, Oper. Res..

[39]  J. Farley,et al.  How Advertising Affects Sales: Meta-Analysis of Econometric Results , 1984 .

[40]  Jie Zhang,et al.  Optimal Budget Allocation Across Search Advertising Markets , 2015, INFORMS J. Comput..

[41]  Steven Tadelis,et al.  Consumer Heterogeneity and Paid Search Effectiveness: A Large Scale Field Experiment , 2014 .

[42]  Donald S. Tull,et al.  The Carry-over Effect of Advertising , 1965 .

[43]  Jie Zhang,et al.  A Budget Optimization Framework for Search Advertisements Across Markets , 2012, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[44]  Bernard J. Jansen,et al.  The effect of ad rank on the performance of keyword advertising campaigns , 2013, J. Assoc. Inf. Sci. Technol..

[45]  Sridhar Moorthy,et al.  Advertiser Prominence Effects in Search Advertising , 2017, Manag. Sci..

[46]  Paul H. C. Eilers,et al.  Flexible smoothing with B-splines and penalties , 1996 .

[47]  Anindya Ghose,et al.  Analyzing the Relationship Between Organic and Sponsored Search Advertising: Positive, Negative, or Zero Interdependence? , 2010, Mark. Sci..

[48]  Vahab S. Mirrokni,et al.  Budget Optimization for Online Campaigns with Positive Carryover Effects , 2012, WINE.

[49]  Hermann Ebbinghaus (1885) Memory: A Contribution to Experimental Psychology , 2013, Annals of Neurosciences.

[50]  T. Oum,et al.  Advertising Quality in Sales Response Models , 1987 .

[51]  Jaap E. Wieringa,et al.  Early Marketing Matters: A Time-Varying Parameter Approach to Persistence Modeling , 2010 .

[52]  Hemant K. Bhargava,et al.  Implementing Sponsored Search in Web Search Engines: Computational Evaluation of Alternative Mechanisms , 2007, INFORMS J. Comput..

[53]  Dominique M. Hanssens,et al.  Market Response Models: Econometric and Time Series Analysis , 1989 .

[54]  Jie Zhang,et al.  Dynamic dual adjustment of daily budgets and bids in sponsored search auctions , 2014, Decis. Support Syst..

[55]  Charles B. Weinberg,et al.  The Effects of Serial Correlation and Data Aggregation on Advertising Measurement , 1983 .

[56]  Wilfried R. Vanhonacker,et al.  Carryover Effects and Temporal Aggregation in a Partial Adjustment Model Framework , 1983 .

[57]  Vamsi K. Kanuri,et al.  A Meta-Analysis of Marketing Communication Carryover Effects , 2017 .

[58]  D. Ruppert Selecting the Number of Knots for Penalized Splines , 2002 .

[59]  Bernard J. Jansen,et al.  The seventeen theoretical constructs of information searching and information retrieval , 2010, J. Assoc. Inf. Sci. Technol..