Optimizing Location-Based Mobile Advertising Using Predictive Analytics

References

• AdTheorent. (2016), “Barometric,” June 30, https://adtheorent.com.
   Google Scholar
• ——— (2017), “Machine Learning-Powered Predictive Advertising,” September 15, https://adtheorent.com.
   Google Scholar
• Ahmed, Rahnuma, Fred Beard, and Doyle Yoon (2016), “Examining and Extending Advertising's Dual Mediation Hypothesis to a Branded Mobile Phone App,” Journal of Interactive Advertising, 16 (2), 133–44.
   Google Scholar
• Alsaqer, Mohammed, Brian Hilton, Tom Horan, and Omar Aboulola (2015), “Performance Assessment of Geo-Triggering in Small Geo-Fences: Accuracy, Reliability, and Battery Drain in Different Tracking Profiles and Trigger Directions,” Procedia Engineering, 107, 337–48.
   Google Scholar
• Angel, Gary (2016), “Transforming the Digital Channel with Analytics,” presented at the Annual eMetrics Summit, San Francisco, CA, April.
   Google Scholar
• Atkinson, John S., John E. Mitchell, Miguel Rio, and George Matich (2018), “Your WiFi Is Leaking: What Do Your Mobile Apps Gossip About You?,” Future Generation Computer Systems, 80, 546–57.
   Web of Science ®Google Scholar
• Banerjee, Syagnik, and R.R. Dholakia (2008), “Mobile Advertising: Does Location-Based Advertising Work?,” International Journal of Mobile Marketing, 3 (2), 68–74.
   Google Scholar
• ———, and ——— (2013), “Situated or Ubiquitous? A Segmentation of Mobile e-Shoppers,” International Journal of Mobile Communications, 11 (5), 530–57.
   Web of Science ®Google Scholar
• ———, Vijay Viswanathan, Kalyan Raman, and Hao Ying (2013), “Assessing Prime-Time for Geotargeting with Mobile Big Data,” Journal of Marketing Analytics, 1 (3), 174–83.
   Google Scholar
• Barwise, Patrick, and Colin Strong (2002), “Permission-Based Mobile Advertising,” Journal of Interactive Marketing, 16 (1), 14–24.
   Google Scholar
• Bellman, Steven, Robert F. Potter, Shiree Treleaven-Hassard, Jennifer A. Robinson, and Duane Varan (2011), “The Effectiveness of Branded Mobile Phone Apps,” Journal of Interactive Marketing, 25, 191–200.
   Web of Science ®Google Scholar
• Bhat, Subodh, Michael Bevans, and Sanjit Sengupta (2002), “Measuring Users’ Web Activity to Evaluate and Enhance Advertising Effectiveness,” Journal of Advertising, 31 (3), 97–106.
   Web of Science ®Google Scholar
• Boyle, Cathy (2013), “The Effectiveness of Geotargeted Mobile Ads: Location Data Pumps Up Performance,” eMarketer, October 29.
   Google Scholar
• ——— (2015a), “Mobile Apps vs. Mobile Browsers,” eMarketer, February.
   Google Scholar
• ——— (2015b), “Mobile Audience Targeting,” eMarketer, May 15.
   Google Scholar
• ——— (2015c), “Mobile Website, App, or Both? How Channel Choices Are Made,” eMarketer, June.
   Google Scholar
• Briggs, Rex, and Nigel Hollis (1997), “Advertising on the web: is there response before click-through?” Journal of Advertising Research, 37 (2), 33–45.
   Web of Science ®Google Scholar
• ——— (2016a), “App Install Advertising,” eMarketer, September.
   Google Scholar
• ——— (2016b), “Location Intelligence,” eMarketer, April.
   Google Scholar
• Calder, Bobby J., Edward C. Malthouse, and Ute Schaedel (2009), “An Experimental Study of the Relationship between Online Engagement and Advertising Effectiveness,” Journal of Interactive Marketing, 23 (4), 321–31.
   Web of Science ®Google Scholar
• Cao, Longbing, Philip S. Yu, and Vipin Kumar (2016), “Nonoccurring Behavior Analytics: A New Era,” Computing Edge, 2 (4), 20–27.
   Google Scholar
• Carlson, Les, Stephen J. Grove, and Marla Royne Stafford (2005), “Perspectives on Advertising Research,” Journal of Advertising 34 (2), 117–149.
   Web of Science ®Google Scholar
• Carroll, Amy, Stuart J. Barnes, Eusebio Scornavacca, and Keith Fletcher (2007), “Consumer Perceptions and Attitudes Toward SMS Advertising: Recent Evidence from New Zealand,” International Journal of Advertising, 26 (1), 79–98.
   Web of Science ®Google Scholar
• Chamberlain, Lauryn. (2016), “GeoMarketing 101: What Is Geofencing?,” GeoMarketing, May 7, http://www.geomarketing.com/geomarketing-101-what-is-geofencing.
   Google Scholar
• Chatterjee, Patrali, Donna L. Hoffman, and Thomas P. Novak (2003), “Modeling the Clickstream: Implications for Web-Based Advertising Efforts,” Journal of Marketing Science, 22 (4), 520–541.
   Google Scholar
• Cho, Chang-Hoan. (2003), “The Effectiveness of Banner Advertisements: Involvement and Clickthrough,” Journalism and Mass Communication Quarterly, 80 (3), 623–645.
   Web of Science ®Google Scholar
• Creative Format Guidelines. (2011), “Best Practices for Conducting Online Ad Effectiveness Research: June 2011,” https://www.iab.com/wp-content/uploads/2015/05/BestPracticesForAdEffectivenessStudies.pdf.
   Google Scholar
• Dainow, Brandt (2005), “Things that throw your stats (Part 2),” iMedia Connection, http://www.imediaconnection.com.
   Google Scholar
• Dhar, Subhankar, and Upkar Varshney (2011), “Challenges and Business Models for Mobile Location-Based Services and Advertising,” Communications of the ACM, 54 (5), 121–28.
   Web of Science ®Google Scholar
• Dow, Cameron (2013), “Mobile Marketing and the Value of Customer Analytics,” International Journal of Mobile Marketing, 8 (1), 117–20.
   Google Scholar
• Elkins, Tobi (2016), “Marketing Automation,” eMarketer, February.
   Google Scholar
• eMarketer. (2016a), “A Closer Look at the State of Predictive Analytics,” July 20.
   Google Scholar
• ——— (2016b), “App Inventory: Programmatic's Diamond in the Rough,” July 8.
   Google Scholar
• ——— (2016c), “Clickthrough (CTR) and Conversion Rate for U.S. Digital Ads, by Format and Device, Q1 2016,” May 12.
   Google Scholar
• ——— (2016e), “Is Internet Time All about Apps?”, September 28.
   Google Scholar
• ——— (2016f), “Marketing Metrics Used by U.S. Professional Association Employees, 2014–2016,” August 14.
   Google Scholar
• ——— (2017), “Total Media, Digital and Mobile Ad Spending Worldwide, 2016-2020 (billions, % change and % of total),” December 14.
   Google Scholar
• Fong, Nathan M., Zheng Fang, and Xueming Luo (2015), “Geo-Conquesting: Competitive Locational Targeting of Mobile Promotions,” Journal of Marketing Research, 52 (5), 726–35.
   Web of Science ®Google Scholar
• Fulgoni, Gian M. (2016), “In the Digital World, Not Everything Matters: How to Distinguish ‘Valuable from Nice to Know’ among Measures of Consumer Engagement,” Journal of Advertising Research, 56 (1), 9–13.
   Web of Science ®Google Scholar
• Garber, Lee (2016), “Using Analytics to Makes Sense of Data,” Computing Edge, 2 (5), 9–14.
   Google Scholar
• Gneezy, Ayelet (2017), “Field Experimentation in Market Research,” Journal of Marketing Research, 54 (1), 140–43.
   Web of Science ®Google Scholar
• Grewal, Dhruv, Yakov Bart, Martin Spann, and Peter Pal Zubcsek (2016), “Mobile Advertising: A Framework and Research Agenda,” Journal of Interactive Marketing, 34, 3–14.
   Web of Science ®Google Scholar
• House Rabbit Society (2016), “About House Rabbit Society,” July 25, https://rabbit.org/about-us.
   Google Scholar
• Huizingh, Elko K.R.E., and Janny C. Hoekstra (2003), “Why Do Consumers Like Websites?,” Journal of Targeting, Measurement, and Analysis for Marketing, 11 (4), 350–61.
   Google Scholar
• Interactive Advertising Bureau (2015), “Interactive Advertising Bureau: Display and Mobile Advertising Creative Format Guidelines: 2015 Advertising Creative Guidelines for Display and Mobile—Updated for HTML5,” June 28, http://www.iab.com/wp-content/uploads/2015/11/IAB_Display_Mobile_Creative_Guidelines_HTML5_2015.pdf.
   Google Scholar
• ——— (2016), “MRC Mobile Viewable Ad Impression Measurement Guidelines: Final Version,” June 28, http://measurementnow.net/wp-content/uploads/2015/01/FINAL-062816-Mobile-Viewable-Guidelines-Final-1.pdf.
   Google Scholar
• ——— (2017), “IAB New Standard Ad Unit Portfolio,” July 27, https://www.iab.com/wp-content/uploads/2017/08/IABNewAdPortfolio_FINAL_2017.pdf.
   Google Scholar
• Kaushik, Avinash (2010), “Web Analytics 2.0,” Wiley Publishing: Indianapolis, Ind.
   Google Scholar
• Kim, Eunice, Jhih-Syuan Lin, and Yongjun Sung (2013), “To App or Not to App: Engaging Consumers via Branded Mobile Apps,” Journal of Interactive Advertising, 13 (1), 53–65.
   Google Scholar
• Kressman, Jeremy (2015), “App Marketing,” eMarketer.
   Google Scholar
• Laszlo, Joe (2009), “The New Unwired World: A Lab Status Report on Mobile Advertising,” Journal of Advertising Research, 49 (1), 27–43.
   Web of Science ®Google Scholar
• Lawrence, Stacy (2000, June 12), “Beyond Banner Clicks,” The Standard, atwysiwys://2/http://thestandard.com/research/metrics/display/0,2799,15855,00.htm
   Google Scholar
• Lee, Sangmee, Ki Joon Kim, and S. Shyam Sundar (2015), “Customization in Location-Based Advertising: Effects of Tailoring Source, Locational Congruity, and Product Involvement on Ad Attitudes,” Computers in Human Behavior, 51 (Part A), 336–43.
   Google Scholar
• Limpf, Nina, and Hilde A.M. Voorveld (2015), “Mobile Location-Based Advertising: How Information Privacy Concerns Influence Consumers' Attitude and Acceptance,” Journal of Interactive Advertising, 15 (2), 111–23.
   Google Scholar
• Ma, Chuang, Hao Helen Zhang, and Xiangfeng Wang (2014), “Machine Learning for Big Data Analytics in Plants,” Trends in Plant Sciences, 19 (12), 798–808.
   PubMed Web of Science ®Google Scholar
• Maity, Moutusi, and Cara Lee Okleshen Peters (2005), “A Primer for the Use of Internet Marketing Research Tools: The Value of Usability Studies,” Interactive Marketing, 16 (3), 232–47.
   Google Scholar
• Malthouse, Edward C., and Hairong Li (2017), “Opportunities for and Pitfalls of Using Big Data for Advertising Research,” Journal of Advertising, 46 (2), 227–35.
   Web of Science ®Google Scholar
• mBlox (2013), “Mobile Engagement: What Consumers Really Think,” https://www.thelbma.com/files/495-MBL_Global_Mobile_Engagement_09-23-13FINAL.pdf.
   Google Scholar
• Merisavo, Marko, Sami Kajalo, Heikki Karjaluoto, Ville Virtanen, Sami Salmenkivi, Mika Raulas, and Matti Leppäniemi (2007), “An Empirical Study of the Drivers of Consumer Acceptance of Mobile Advertising,” Journal of Interactive Advertising, 7 (2), 41–50.
   Google Scholar
• Mobile Marketing Association. (2016), “Mobile Web Advertisement Guidelines,” April, http://www.mmaglobal.com/documents/mobile-web-advertising-measurement-guidelines-version-30.
   Google Scholar
• Mokbel, Mohamed F., and Justin J. Levandoski (2009), “Toward Context and Preference‐Aware Location‐Based Services,” in Proceedings of the Eighth ACM International Workshop on Data Engineering for Wireless and Mobile Access, New York: ACM, 25–32.
   Google Scholar
• Nasco, Suzanne Altobello, and Gordon C. Bruner II (2008), “Comparing Consumer Responses to Advertising and Non-Advertising Mobile Communications,” Psychology and Marketing, 25 (8), 821–37.
   Web of Science ®Google Scholar
• Nichols, Wes (2013), “Advertising Analytics 2.0,” Harvard Business Review, 91 (3), 60–68.
   PubMed Web of Science ®Google Scholar
• Nittala, Rajyalakshmi (2010), “Registering for Incentivized Mobile Advertising: Discriminate Analysis of Mobile Users,” International Journal Mobile Marketing, 6 (2), 42–53.
   Google Scholar
• Okazaki, Shintaro, and Patrick Barwise (2011), “Has the Time Finally Come for the Medium of the Future? Research on Mobile Advertising,” Journal of Advertising Research, 51 (1), 59–71.
   Web of Science ®Google Scholar
• Pagani, Margherita (2004), “Determinants of Adoption of Third Generation Mobile Multimedia Services,” Journal of Interactive Marketing, 18 (3), 46–59.
   Google Scholar
• Park, Taezoon, Rashmi Shenoy, and Gavriel Salvendy (2008), “Effective Advertising on Mobile Phones: A Literature Review and Presentation of Results from 53 Case Studies,” Behaviour and Information Technology, 27 (5), 355–373.
   Web of Science ®Google Scholar
• Petrock, Victoria (2016a), “Artificial Intelligence for Marketers,” eMarketer, October.
   Google Scholar
• ——— (2016b), “Artificial Intelligence 2016,” eMarketer, October.
   Google Scholar
• Perrin, Nicole (2017), “Marketing Technology 2017,” eMarketer, June.
   Google Scholar
• Pickrell, Shiyi (2016), “Customer Centric Analytics,” in Presented at the Annual eMetrics Summit, San Francisco, CA, April.
   Google Scholar
• Punyatoya, Plavini (2011), “How effective are Internet Banner Advertisements in India,” Journal of Marketing and Communication, 7 (1), 4–10.
   Google Scholar
• Putnam-Farr, Eleanor, and Jason Riis (2016), “‘Yes/No/Not Right Now’: Yes/No Response Formats Can Increase Response Rates Even in Non-Forced-Choice Settings,” Journal of Marketing Research, 53, 424–32.
   Web of Science ®Google Scholar
• Ravada, Siva, Mohamed Ali, Jie Bao, and Mohamed Sarwat (2013), “ACM SIGSPATIAL GIS Cup 2013: Geo-Fencing,” in Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, New York: ACM, 584–87.
   Google Scholar
• Robinson, Helen, Anna Wysocka, and Chris Hand (2007), “Internet Advertising Effectiveness: The Effect of Design on Click-through Rates for Banner Ads,” International Journal of Advertising, 26 (4), 527–541.
   Web of Science ®Google Scholar
• Roche, Jamie (2005), “Conversion is the New Acquisition,” iMedia Connection, http://imediaconnection.com.
   Google Scholar
• Rosenkrans, Ginger, and Keli Myers (2012), “Mobile Advertising Effectiveness,” International Journal of Mobile Marketing, 7 (3), 5–24.
   Google Scholar
• Ryan, Jillian (2015), “Predictive Technology May Be Powerful, But It's No Crystal Ball,” eMarketer, June 8.
   Google Scholar
• ——— (2016), “Predictive Analytics in B2B Marketing,” eMarketer, April 21.
   Google Scholar
• Sanders, Nada R. (2016), “How to Use Big Data to Drive Your Supply Chain,” California Management Review, 58 (3), 26–48.
   Web of Science ®Google Scholar
• Schonberg, Edith, Cofino Thomas, Robert Hoch, Mark Podlaseck, and Susan Spraragen (2000), “Measuring Success,” Communications of the ACM, 43 (8), 53–57.
   Web of Science ®Google Scholar
• Shakeel, Usman, and Mike Limcaco (2016), “Leveraging Cloud-Based Predictive Analytics to Strengthen Audience Engagement,” SMPTE Motion Imaging Journal, 125 (8), 60–68.
   Google Scholar
• Shankar, Venkatesh, Mirella Kleijnen, Suresh Ramanathan, Ross Rizley, Steve Holland, and Shawn Morrissey (2016), “Mobile Shopper Marketing: Key Issues, Current Insights, and Future Research Avenues,” Journal of Interactive Marketing, 34, 37–48.
   Web of Science ®Google Scholar
• Shin, Wonsun, and Trisha Tsui-Chuan Lin (2016), “Who Avoids Location-Based Advertising and Why?,” Computers and Human Behavior, 63, 444–52.
   Web of Science ®Google Scholar
• Singh, Surendra N., Nikunj Dalal, and Nancy Spears (2005), “Understanding web home page Perception”, European Journal of Information Systems, 14 (3), 288–307.
   Web of Science ®Google Scholar
• Snow, Allison, and Laura Ramos (2017), “The Forrester Wave™: Predictive Marketing Analytics for B2B Marketers, Q2 2017,” Forrester, June 14, http://content.6sense.com/rs/958-TTM-744/images/ForresterWaveReport.pdf.
   Google Scholar
• Soroa-Koury, Sandra, and Kenneth C.C. Yang (2010), “Factors Affecting Consumers’ Responses to Mobile Advertising from a Social Norm Theoretical Perspective,” Telematics and Informatics, 27 (1), 103–13.
   Google Scholar
• Sterling, Greg (2015), “Moasis: Location Is the Key to Mobile Ad Relevance and Personalization Company Believes That Location Is Only Being Superficially Utilized Today,” Marketing Land, August 25, http://marketingland.com/moasis-location-is-the-key-to-mobile-ad-relevance-and-personalization-140107.
   Google Scholar
• Tadena, Nathalie (2015), “Marketers Say They Would Spend Even More on Digital Ads if Measurement Improved,” Wall Street Journal, July 6, http://blogs.wsj.com/cmo/2015/07/06/marketers-say-they-would-spend-even-more-on-digital-ads-if-measurement-improved/.
   Google Scholar
• Tsang, Melody M., Shu-Chun Ho, and Ting-Peng Liang (2004), “Consumer Attitudes Toward Mobile Advertising: An Empirical Study,” International Journal of Electronic Commerce, 8 (3), 65–78.
   Web of Science ®Google Scholar
• van 't Riet, Jonathan, Arief Hühn, Paul Ketelaar, Vassilis-Javed Khan, Ruben Konig, Esther Rozendaal, and Panos Markopoulos (2016), “Investigating the Effects of Location-Based Advertising in the Supermarket: Does Goal Congruence Trump Location Congruence?,” Journal of Interactive Advertising, 16 (1), 31–43.
   Google Scholar
• Vatanparast, Ramin, and Ali Hasan Butt (2010), “An Empirical Study of Factors Affecting Use of Mobile Advertising,” International Journal of Mobile Marketing, 5 (1), 28–40.
   Google Scholar
• Walsh, Mark (2012), “Moasis Takes Mobile Ads Hyperlocal,” MediaPost, July 23, http://www.mediapost.com/publications/article/179238/moasis-takes-mobile-ads-hyperlocal.html#ixzz21eRttHPA.
   Google Scholar
• Xu, Heng, Oh, Lih Bin, and Hock-Hai Teo (2009), “Perceived Effectiveness of Text vs. Multimedia Location-Based Advertising Messaging,” International Journal of Mobile Communications, 7 (2), 154–77.
   Web of Science ®Google Scholar
• Yeager, Bryan (2016), “Attention and Engagement Metrics: Going Beyond the Impression,” eMarketer, October 10, https://www.emarketer.com/Report/Attention-Engagement-Metrics-Going-Beyond-Impression/2001869.
   Google Scholar