Many businesses today have adopted tweeting as a new form of product marketing. However, whether and how tweeting affects product demand remains inconclusive. The authors explore this question using a randomized field experiment on Sina Weibo, the top tweeting website in China. The authors collaborate with a major global media company and examine how the viewing of its TV shows is affected by (1) the media company's tweets about its shows, and (2) recruited Weibo influentials’ retweets of the company tweets. The authors find that both company tweets and influential retweets increase show viewing, but in different ways. Company tweets directly boost viewing, whereas influential retweets increase viewing if the show tweet is informative. Meanwhile, influential retweets are more effective than company tweets in bringing new Weibo followers to the company, which indirectly increases viewing. The authors discuss recommendations on how to manage tweeting as a marketing tool.
AnandBharat N., and ShacharRon (2011), “Advertising, the Matchmaker,”RAND Journal of Economics, 42 (2), 205–45.
2.
AndrewsMichelle, LuoXueming, FangZheng, and GhoseAnindya (2016), “Mobile Ad Effectiveness: Hyper-Contextual Targeting with Crowdedness,”Marketing Science, 35 (2), 218–33.
3.
AralSinan, and WalkerDylan (2011), “Creating Social Contagion Through Viral Product Design: A Randomized Trial of Peer Influence in Networks,”Management Science, 57 (9), 1623–39.
4.
ArellanoManuel, and BondStephen (1991), “Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations,”Review of Economic Studies, 58 (2), 277–97.
5.
BenYishayAriel, and Mushfiq MobarakA. (2015), “Social Learning and Incentives for Experimentation and Communication,”working paper, College of William & Mary.
6.
BlakeThomas, NoskoChris, and TadelisSteven (2015), “Consumer Heterogeneity and Paid Search Effectiveness: A Large-Scale Field Experiment,”Econometrica, 83 (1), 155–74.
CulottaAron, and CutlerJennifer (2016), “Mining Brand Perceptions from Twitter Social Networks,”Marketing Science, 35 (3), 343–62.
10.
DinnerIsaac M., Van HeerdeHarald J., and NeslinScott A. (2014), “Driving Online and Offline Sales: The Cross-Channel Effects of Traditional, Online Display, and Paid Search Advertising,”Journal of Marketing Research, 51 (5), 527–45.
11.
FossenBeth L., and SchweidelDavid A. (2017), “Television Advertising and Online Word-of-Mouth: An Empirical Investigation of Social TV Activity,”Marketing Science, 36 (1), 105–23.
12.
GhoseAnindya, GoldfarbAvi, and HanSang Pil (2012), “How Is the Mobile Internet Different? Search Costs and Local Activities,”Information Systems Research, 24 (3), 613–31.
13.
GodesDavid, and MayzlinDina (2009), “Firm-Created Word-of-Mouth Communication: Evidence from a Field Test,”Marketing Science, 28 (4), 721–39.
14.
GoelSharad, WattsDuncan J., and GoldsteinDaniel G. (2012), “The Structure of Online Diffusion Networks,” in Proceedings of the 13th ACM Conference on Electronic Commerce. New York: Association for Computing Machinery, 623–38.
15.
GoettlerRonald L., and ShacharRon (2001), “Spatial Competition in the Network Television Industry,”RAND Journal of Economics, 32 (4), 624–56.
16.
GoldenbergJacob, HanSangman, LehmannDonald R., and HongJae Weon (2009), “The Role of Hubs in the Adoption Process,”Journal of Marketing, 73 (2), 1–13.
HairJoseph F.Jr., BlackWilliam C., BabinBarry J., and AndersonRolph E. (2010), Multivariate Data Analysis, 7th ed.Upper Saddle River, NJ: Prentice Hall.
19.
HinzOliver, SkieraBernd, BarrotChristian, and BeckerJan U. (2011), “Seeding Strategies for Viral Marketing: An Empirical Comparison,”Journal of Marketing, 75 (6), 55–71.
20.
HobanPaul R., and BucklinRandolph E. (2015), “Effects of Internet Display Advertising in the Purchase Funnel: Model-Based Insights from a Randomized Field Experiment,”Journal of Marketing Research, 52 (3), 375–93.
21.
JooMingyu, WilburKenneth C., CowgillBo, and ZhuYi (2014), “Television Advertising and Online Search,”Management Science, 60 (1), 56–73.
KumarAshish, BezawadaRam, RishikaRishika, JanakiramanRamkumar, and KannanP.K. (2016), “From Social to Sale: The Effects of Firm-Generated Content in Social Media on Customer Behavior,”Journal of Marketing, 80 (1), 7–25.
24.
KuppuswamyVenkat, and BayusBarry (2016), “Using Tweets to Generate Electronic Word of Mouth: An Analysis of the Kickstarter Crowdfunding Community,”working paper, University of North Carolina.
25.
LambrechtAnja, and TuckerCatherine (2013), “When Does Retargeting Work? Information Specificity in Online Advertising,”Journal of Marketing Research, 50 (5), 561–76.
26.
LambrechtAnja, TuckerCatherine, and WiertzCaroline (2017), “Advertising to Early Trend Propagators: Evidence from Twitter,”Marketing Science, forthcoming.
27.
LewisRandall A., and ReileyDavid H. (2014), “Online Ads and Offline Sales: Measuring the Effects of Retail Advertising via a Controlled Experiment on Yahoo!”Quantitative Marketing and Economics, 12 (3), 235–66.
28.
LiaukonyteJura, TeixeiraThales, and WilburKenneth C. (2015), “Television Advertising and Online Shopping,”Marketing Science, 34 (3), 311–30.
LiuXiao, SinghParam Vir, and SrinivasanKannan (2016), “A Structured Analysis of Unstructured Big Data by Leveraging Cloud Computing,”Marketing Science, 35 (3), 363–88.
31.
LovettMitchell J., and StaelinRichard (2016), “The Role of Paid, Earned, and Owned Media in Building Entertainment Brands: Reminding, Informing, and Enhancing Enjoyment,”Marketing Science, 35 (1), 142–57.
32.
MaLiye, SunBaohong, and KekreSunder (2015), “The Squeaky Wheel Gets the Grease: An Empirical Analysis of Customer Voice and Firm Intervention on Twitter,”Marketing Science, 34 (5), 627–45.
33.
ManchandaPuneet, DubéJean-Pierre, GohKhim Yong, and ChintaguntaPradeep K. (2006), “The Effect of Banner Advertising on Internet Purchasing,”Journal of Marketing Research, 43 (1), 98–108.
34.
Miklós-ThalJeanine, and ZhangJuanjuan (2013), “(De)marketing to Manage Consumer Quality Inferences,”Journal of Marketing Research, 50 (1), 55–69.
35.
MilgromPaul, and RobertsJohn (1986), “Price and Advertising as Signals of Product Quality,”Journal of Political Economy, 94 (4), 796–821.
36.
MochonDaniel, JohnsonKaren, SchwartzJanet, and ArielyDan (2017), “What Are Likes Worth? A Facebook Page Field Experiment,”Journal of Marketing Research, 54 (2), 306–17.
37.
MoshkinNickolay V., and ShacharRon (2002), “The Asymmetric Information Model of State Dependence,”Marketing Science, 21 (4), 435–54.
38.
NickellStephen (1981), “Biases in Dynamic Models with Fixed Effects,”Econometrica, 49 (6), 1417–26.
39.
OnishiHiroshi, and ManchandaPuneet (2012), “Marketing Activity, Blogging, and Sales,”International Journal of Research in Marketing, 29 (3), 221–34.
40.
PetrovaMaria, SenAnanya, and YildirimPinar (2016), “Social Media and Political Donations: Evidence from Twitter,”working paper, Barcelona Institute for Political Economy and Governance.
41.
RuiHuaxia, LiuYizao, and WhinstonAndrew (2013), “Whose and What Chatter Matters? The Effect of Tweets on Movie Sales,”Decision Support Systems, 55 (4), 863–70.
42.
SahniNavdeep S., ZouDan, and ChintaguntaPradeep K. (2017), “Do Targeted Discount Offers Serve as Advertising? Evidence from 70 Field Experiments,”Management Science, 63 (8), 2688–705.
43.
SeilerStephan, YaoSong, and WangWenbo (2017), “Does Online Word-of-Mouth Increase Demand? (and How?) Evidence from a Natural Experiment,”Marketing Science, forthcoming.
44.
ShacharRon, and EmersonJohn W. (2000), “Cast Demographics, Unobserved Segments, and Heterogeneous Switching Costs in a Television Viewing Choice Model,”Journal of Marketing Research, 37 (2), 173–86.
45.
ShiZhan, RuiHuaxia, and WhinstonAndrew B. (2014), “Content Sharing in a Social Broadcasting Environment: Evidence from Twitter,”Management Information Systems Quarterly, 38 (1), 123–42.
SimesterDuncan (2017), “Field Experiments in Marketing,” in Handbook of Economic Field Experiments, DufloEsther and BanerjeeAbhijit Vinayak, eds. Amsterdam: North-Holland, 465–98.
48.
StephenAndrew T., DoverYaniv, MuchnikLev, and GoldenbergJacob (2014), “The Effect of Source Activity on the Decision to Retransmit Content in Social Media,”working paper, University of Oxford.
49.
StephenAndrew T., and GalakJeff (2012), “The Effects of Traditional and Social Earned Media on Sales: A Study of a Microlending Marketplace,”Journal of Marketing Research, 49 (5), 624–39.
50.
TobinJames (1958), “Estimation of Relationships for Limited Dependent Variables,”Econometrica, 26 (1), 24–36.
51.
ToubiaOlivier, and StephenAndrew T. (2013), “Intrinsic vs. Image-Related Utility in Social Media: Why Do People Contribute Content to Twitter?”Marketing Science, 32 (3), 368–92.
TrusovMichael, BodapatiAnand V., and BucklinRandolph E. (2010), “Determining Influential Users in Internet Social Networks,”Journal of Marketing Research, 47 (4), 643–58.
54.
TuckerCatherine, and ZhangJuanjuan (2010), “Growing Two-Sided Networks by Advertising the User Base: A Field Experiment,”Marketing Science, 29 (5), 805–14.
55.
WattsDuncan J., and DoddsPeter Sheridan (2007), “Influentials, Networks, and Public Opinion Formation,”Journal of Consumer Research, 34 (4), 441–58.
56.
WilburKenneth C. (2008), “A Two-Sided, Empirical Model of Television Advertising and Viewing Markets,”Marketing Science, 27 (3), 356–78.
57.
WooldridgeJeffrey M. (1999), “Distribution-Free Estimation of Some Nonlinear Panel Data Models,”Journal of Econometrics, 90 (1), 77–97.
58.
YeoJungwon (2014), “The Day of the Week Effects in Television Viewership and Primetime Television Scheduling,”working paper, Singapore Management University.
59.
ZamanTauhid, FoxEmily B., and BradlowEric T. (2014), “A Bayesian Approach for Predicting the Popularity of Tweets,”Annals of Applied Statistics, 8 (3), 1583–611.
60.
ZhangTongdao, and ZhifengHu (2013), “ 2012 Research Report on China's Documentary TV Industry,”Modern Communication, 201 (4), 81–89.
61.
ZhangYuchi, MoeWendy W., and SchweidelDavid A. (2017), “Modeling the Role of Message Content and Influencers in Social Media Rebroadcasting,”International Journal of Research in Marketing, 34 (1), 100–119.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
