Long Lags and Large Returns: Experimental Evidence from Advertising to Businesses

References

• Almon S (1965) The distributed lag between capital appropriations and expenditures. Econometrica 33(1):178–196.Crossref, Google Scholar
• Anderson ET, Simester DI (2004) Long-run effects of promotion depth on new versus established customers: Three field studies. Marketing Sci. 23(1):4–20.Link, Google Scholar
• Assmus G, Farley JU, Lehmann DR (1984) How advertising affects sales: Meta-analysis of econometric results. J. Marketing Res. 21(1):65–74.Crossref, Google Scholar
• Barth ME, Clement MB, Foster G, Kasznik R (1998) Brand values and capital market valuation. Rev. Accounting Stud. 3(1):41–68.Crossref, Google Scholar
• Blake T, Nosko C, Tadelis S (2015) Consumer heterogeneity and paid search effectiveness: A large-scale field experiment. Econometrica 83(1):155–174.Crossref, Google Scholar
• Bojinov I, Simchi-Levi D, Zhao J (2023) Design and analysis of switchback experiments. Management Sci. 69(7):3759–3777.Link, Google Scholar
• Bublitz B, Ettredge M (1989) The information in discretionary outlays: Advertising, research, and development. Accounting Rev. 64(1):108–124.Google Scholar
• Corey RE (1996) Industrial Marketing Strategy: An Overview (Harvard Business School Publishing, Boston).Google Scholar
• Cramer-Flood E (2021) Worldwide digital ad spending 2021. Accessed May 21, 2024, https://www.emarketer.com/content/worldwide-digital-ad-spending-2021.Google Scholar
• Cramer-Flood E (2023) US CPG industry digital ad spending 2023. Accessed May 21, 2024, https://www.emarketer.com/content/us-cpg-industry-digital-ad-spending-2023.Google Scholar
• Dai W, Kim H, Luca M (2023) Frontiers: Which firms gain from digital advertising? Evidence from a field experiment. Marketing Sci. 42(3):429–439.Link, Google Scholar
• Donchak L, McClatchy J, Stanley J (2022) The Future of B2B Sales is Hybrid (McKinsey and Company, New York).Google Scholar
• Du RY, Xu L, Wilbur KC (2019) Immediate responses of online brand search and price search to TV ads. J. Marketing 83(4):81–100.Crossref, Google Scholar
• Dubé J-P, Hitsch GJ, Manchanda P (2005) An empirical model of advertising dynamics. Quant. Marketing Econom. 3(2):107–144.Crossref, Google Scholar
• Eastlack JO, Rao AG (1989) Advertising experiments at the Campbell Soup Company. Marketing Sci. 8(1):57–71.Link, Google Scholar
• Eskin GJ, Baron PH (1977) Effects of price and advertising in test-market experiments. J. Marketing Res. 14(4):499–508.Crossref, Google Scholar
• Goldfarb A, Tucker C (2011) Online display advertising: Targeting and obtrusiveness. Marketing Sci. 30(3):389–404.Link, Google Scholar
• Gonzalez A (2022) Basic of Sales Management (IE Business Publishing, Madrid).Google Scholar
• Gopalakrishna S, Chatterjee R (1992) A communications response model for a mature industrial product: Application and implications. J. Marketing Res. 29(2):189–200.Crossref, Google Scholar
• Gordon BR, Zettelmeyer F, Bhargava N, Chapsky D (2019) A comparison of approaches to advertising measurement: Evidence from big field experiments at Facebook. Marketing Sci. 38(2):193–225.Link, Google Scholar
• Grewal R, Lilien GL, Bharadwaj S, Jindal P, Kayande U, Lusch RF, Mantrala M, et al. (2015) Business-to-business buying: Challenges and opportunities. Cust. Need. Solut. 2(3):193–208.Crossref, Google Scholar
• Han BH, Manry D (2004) The value-relevance of R&D and advertising expenditures: Evidence from Korea. Internat. J. Accounting Audit. Perform. Eval. 39(2):155–173.Google Scholar
• Hartmann WR, Klapper D (2018) Super bowl ads. Marketing Sci. 37(1):78–96.Link, Google Scholar
• Heath C, Staudenmayer N (2000) Coordination neglect: How lay theories of organizing complicate coordination in organizations. Res. Organ. Behav. 22:153–191.Crossref, Google Scholar
• Hu Y, Lodish LM, Krieger AM (2007) An analysis of real world TV advertising tests: A 15-year update. J. Advert. Res. 47(3):341–353.Crossref, Google Scholar
• Hu Y, Lodish LM, Krieger AM, Hayati B (2009) An update of real-world TV advertising tests. J. Advert. Res. 49(2):201–206.Crossref, Google Scholar
• Huang S, Aral S, Hu YJ, Brynjolfsson E (2020) Social advertising effectiveness across products: A large-scale field experiment. Marketing Sci. 39(6):1142–1165.Link, Google Scholar
• Imbens GW, Rubin DB (2015) Causal Inference in Statistics, Social, and Biomedical Sciences (Cambridge University Press, Cambridge, UK).Crossref, Google Scholar
• Johnson GA, Lewis RA, Nubbemeyer EI (2017) Ghost ads: Improving the economics of measuring online ad effectiveness. J. Marketing Res. 54(6):867–884.Crossref, Google Scholar
• Johnson GA, Lewis RA, Reiley DH (2017) When less is more: Data and power in advertising experiments. Marketing Sci. 36(1):43–53.Link, Google Scholar
• Joo M, Wilbur KC, Cowgill B, Zhu Y (2014) Television advertising and online search. Management Sci. 60(1):56–73.Link, Google Scholar
• Kalyanam K, McAteer J, Marek J, Hodges J, Lin L (2018) Cross channel effects of search engine advertising on brick & mortar retail sales: Meta analysis of large scale field experiments on Google.com. Quant. Marketing Econom. 16(1):1–42.Crossref, Google Scholar
• Köhler C, Mantrala MK, Albers S, Kanuri VK (2017) A meta-analysis of marketing communication carryover effects. J. Marketing Res. 54(6):990–1008.Crossref, Google Scholar
• Koyck LM (1954) Distributed Lags and Investment Analysis, vol. 4 (North-Holland Publishing Company, Amsterdam).Google Scholar
• Krishnamurthi L, Narayan J, Raj SP (1986) Intervention analysis of a field experiment to assess the buildup effect of advertising. J. Marketing Res. 23(4):337–345.Crossref, Google Scholar
• Kumar V, Venkatesan R, Reinartz W (2008) Performance implications of adopting a customer-focused sales campaign. J. Marketing 72(5):50–68.Crossref, Google Scholar
• Lambrecht A, Tucker C (2012) Paying with money or effort: Pricing when customers anticipate hassle. J. Marketing Res. 49(1):66–82.Crossref, Google Scholar
• Lewis RA, Rao JM (2015) The unfavorable economics of measuring the returns to advertising. Quart. J. Econom. 130(4):1941–1973.Crossref, Google Scholar
• Lewis RA, Reiley DH (2014) Online ads and offline sales: Measuring the effect of retail advertising via a controlled experiment on Yahoo!. Quant. Marketing Econom. 12(3):235–266.Crossref, Google Scholar
• Lewis RA, Rao JM, Reiley DH (2011) Here, there, and everywhere: Correlated online behaviors can lead to overestimates of the effects of advertising. Proc. 20th Internat. Conf. World Wide Web WWW ‘11 (ACM, New York), 157–166.Crossref, Google Scholar
• Liaukonyte J, Teixeira T, Wilbur KC (2015) Television advertising and online shopping. Marketing Sci. 34(3):311–330.Link, Google Scholar
• Lilien GL (2016) The B2B knowledge gap. Internat. J. Res. Marketing. 33(3):543–556.Crossref, Google Scholar
• Lodish LM, Abraham M, Kalmenson S, Livelsberger J, Lubetkin B, Richardson B, Stevens ME (1995) How TV advertising works: A meta-analysis of 389 real world split cable TV advertising experiments. J. Marketing Res. 32(2):125–139.Crossref, Google Scholar
• Malhotra NK, Uslay C, Bayraktar A (2016) Relationship Marketing Re-Imagined: Marketing’s Inevitable Shift from Exchanges to Value Cocreating Relationships (Business Expert Press, New York).Google Scholar
• Mizik N, Jacobson R (2004) Are physicians “easy marks”? Quantifying the effects of detailing and sampling on new prescriptions. Management Sci. 50(12):1704–1715.Link, Google Scholar
• Molloy W, Strang D, Guyatt G, Lexchin J, Bédard M, Dubois S, Russo R (2002) Assessing the quality of drug detailing. J. Clin. Epidemiol. 55(8):825–832.Crossref, Google Scholar
• Moriarty RT, Spekman RE (1984) An empirical investigation of the information sources used during the industrial buying process. J. Marketing Res. 21(2):137–147.Crossref, Google Scholar
• Parasuraman A (1981) The relative importance of industrial promotion tools. Indust. Marketing Management. 10(4):277–281.Crossref, Google Scholar
• Sahni NS (2015) Effect of temporal spacing between advertising exposures: Evidence from online field experiments. Quant. Marketing Econom. 13(3):203–247.Crossref, Google Scholar
• Sahni NS (2016) Advertising spillovers: Evidence from online field experiments and implications for returns on advertising. J. Marketing Res. 53(4):459–478.Crossref, Google Scholar
• Sahni NS, Nair HS (2020) Does advertising serve as a signal? Evidence from a field experiment in mobile search. Rev. Econom. Stud. 87(3):1529–1564.Crossref, Google Scholar
• Sahni NS, Narayanan S, Kalyanam K (2019) An experimental investigation of the effects of retargeted advertising: The role of frequency and timing. J. Marketing Res. 56(3):401–418.Crossref, Google Scholar
• Shapiro BT, Hitsch GJ, Tuchman AE (2021) Generalizable and robust TV advertising effects. ECTA 89(4):1855–1879.Crossref, Google Scholar
• Sharma A (2002) Trends in internet-based business-to-business marketing. Indust. Marketing Management 31(2):77–84.Crossref, Google Scholar
• Shree D, Singh RK, Paul J, Hao A, Xu S (2021) Digital platforms for business-to-business markets: A systematic review and future research agenda. J. Bus. Res. 137:354–365.Crossref, Google Scholar
• Simester D (2017) Chapter 11—Field experiments in marketing. Banerjee AV, Duflo E, eds. Handbook of Economic Field Experiments, vol. 1 (North-Holland, Amsterdam), 465–497.Crossref, Google Scholar
• Smith TM, Gopalakrishna S, Chatterjee R (2006) A three-stage model of integrated marketing communications at the marketing-sales interface. J. Marketing Res. 43(4):564–579.Crossref, Google Scholar
• Tellis GJ, Chandy RK, Thaivanich P (2000) Which ad works, when, where, and how often? Modeling the effects of direct television advertising. J. Marketing Res. 37(1):32–46.Crossref, Google Scholar
• Tucker C, Zhang J (2010) Growing two-sided networks by advertising the user base: A field experiment. Marketing Sci. 29(5):805–814.Link, Google Scholar
• Xiong R, Athey S, Bayati M, Imbens G (2024) Optimal experimental design for staggered rollouts. Management Sci. 70(8):5317–5336.Google Scholar
• Young A (2019) Channeling Fisher: Randomization tests and the statistical insignificance of seemingly significant experimental results. Quart. J. Econom. 134(2):557–598.Crossref, Google Scholar