The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.
Firm-Created Word-of-Mouth Communication: Evidence from a Field Test
Abstract
In this paper, we investigate the effectiveness of a firm's proactive management of customer-to-customer communication. We are particularly interested in understanding how, if at all, the firm should go about effecting meaningful word-of-mouth (WOM) communications. To tackle this problem, we collect data from two sources: (1) we implement a large-scale field test in which a national firm created word of mouth through two populations: customers and noncustomers, and (2) we collect data from an online experiment. We break our theoretical problem into two subproblems. First, we ask: “What kind of WOM drives sales?” Motivated by previous research, we hypothesize that for a product with a low initial awareness level, WOM that is most effective at driving sales is created by less loyal (not highly loyal) customers and occurs between acquaintances (not friends). We find support for this in the field test as well as in an experimental setting. Hence, we demonstrate the potential usefulness of exogenously created WOM: conversations are created where none would naturally have occured otherwise. Then, we ask: “Which agents are most effective at creating this kind of WOM?” In particular, we are interested in evaluating the effectiveness of the commonly used opinion leader designation. We find that although opinion leadership is useful in identifying potentially effective spreaders of WOM among very loyal customers, it is less useful for the sample of less loyal customers.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Citations
Cites
An Introduction to the Bootstrap
Efron, B., & Tibshirani, R. J. (1994) · doi:10.1201/9780429246593 · Cited by 40,500
Granovetter, M. S. (1973) · American Journal of Sociology · doi:10.1086/225469 · Cited by 40,491
Rogers, E. M., Singhal, A., & Quinlan, M. M. (2019) · Routledge eBooks · doi:10.4324/9780203710753-35 · Cited by 37,670
(2025) · doi:10.53555/acr.v2i2 · Cited by 13,486
Chaudhuri, A., & Holbrook, M. B. (2001) · Journal of Marketing · doi:10.1509/jmkg.65.2.81.18255 · Cited by 6,674
Regression Analysis of Count Data
Cameron, A. C., & Trivedi, P. K. (2013) · doi:10.1017/cbo9781139013567 · Cited by 6,640
Regression Analysis of Count Data: Author Index
Cameron, A., & Trivedi, P. (1998) · Cambridge University Press eBooks · doi:10.1017/cbo9780511814365 · Cited by 6,406
The Effect of Word of Mouth on Sales: Online Book Reviews
Chevalier, J. A., & Mayzlin, D. (2006) · Journal of Marketing Research · doi:10.1509/jmkr.43.3.345 · Cited by 6,003
Self-citationZero defections: quality comes to services.
Reichheld, F. F., & Sasser, W. E. (1990) · PubMed · Cited by 5,373
The antecedents and consequences of customer satisfaction for firms
Anderson, E. W., & Sullivan, M. W. (1993) · Marketing Science · doi:10.1287/mksc.12.2.125 · Cited by 4,610
Research works printed but not linked: 15
- Cialdini R., 2005, Persuasion: Psychological Insights and Perspectives, 143
- Engel J. E., 1969, J. Advertising Res., 9, 3
- Godes D., 2004, Case Study: Hasbro Games—POX
- Holmes J. H., 1977, J. Advertising Res., 17, 35
- Katz E., 1955, Personal Influence
- Keller E., 2003, The Influentials
- Khermouch G., 2001, Bus. Week, 50
- McConnell B., 2003, Creating Customer Evangelists
- O'Malley G., 2005, MediaPost
- Neff J., 2006, Advertising Age
- Petty R. E., 2005, Persuasion: Psychological Insights and Perspectives, 81
- Reichheld F. F., 1990, Harvard Bus. Rev., 68, 105
- Swan J. E., 1989, J. Retailing, 65, 516
- Verlegh P. W. J., 2004, Adv. Consumer Res., 31, 304
- Walker R., 2004, New York Times
Cited by
Sorted by citations
Items 701–800 of 832
Sequential Social Media Advertising: An Empirical EvidencePreprint
Hotkar, P., & Garg, R. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3287476 · Cited by 1
Thomas, L. J. (2018) · Cronfa (Swansea University) · doi:10.23889/suthesis.50777 · Cited by 1
Value co-creation in multi-actor ecosystems
Weretecki, P. (2021) · doi:10.3990/1.9789036552462 · Cited by 1
Quantity vs Variety: Non-Cooperative Content Production on Online Knowledge Sharing PlatformsPreprint
Guo, M., Ni, J., Shen, Q., & Xu, Y. (2021) · SSRN Electronic Journal · doi:10.2139/ssrn.4046286 · Cited by 1
“To make calculations feasible, we use ten-word negative sampling to approximate the denominator in the conditional probability function (see Equation(C2) and Mikolov et al., (2013b) for details on negative sampling).”
BackgroundMethodInfluentialComplex Contagion in Viral Marketing: Causal Evidence from a Country-Scale Field ExperimentPreprint
Lee, J., Lazer, D. M. J., & Riedl, C. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4092057 · Cited by 1
Absent Ties in Product Diffusion: Evidence from MicrotransactionsPreprint
Goetz, D., & Lu, W. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4116806 · Cited by 1
Roks, T. (2015) · Cited by 1
Does Rank Still Matter? Position Bias When AI Agents Shop on Our Behalf
Wadi, D., & Ma, Y. (2026) · arXiv · doi:10.48550/arxiv.2608.22697
“Sellers may therefore benefit more from strengthening these signals (e.g., by soliciting reviews; Godes and Mayzlin, 2009; Wadi et al., 2026c,a; Burtch et al., 2018) than from improving their placement.”
Buzz-Marketing als Guerilla-Variante des Word-of-Mouth
Hutter, K., & Hoffmann, S. (2013) · Springer eBooks · doi:10.1007/978-3-658-02268-6_7
Examples of Database Marketing Models
Leeflang, P. S. H., Wieringa, J. E., Bijmolt, T. H. A., & Pauwels, K. H. (2014) · International series in quantitative marketing · doi:10.1007/978-1-4939-2086-0_9
Swani, K. (2020) · ScholarWorks@UMassAmherst (University of Massachusetts Amherst) · doi:10.7275/6tdq-wm05
New Product Diffusion: A Dual Word-Of-Mouth Perspective
Zhang, J., & Huang, L. (2011) · Journal of the Association for Information Systems
Three Essays on Social Learning
Lee, J. Y. (2014) · ScholarlyCommons (University of Pennsylvania)
Podejście agentowe w modelowaniu zachowań konsumentów na rynku oligopolistycznym
Kowalska-Styczeń, A. (2014) · Digital Library of the Silesian University of Technology (Silesian University of Technology)
Pinto, C. S. (2013) · Pecvnia Revista de la Facultad de Ciencias Económicas y Empresariales Universidad de León · doi:10.18002/pec.v0i16/17.1340
Huifan, L., & Jian-hua, L. (2015) · International Conference on Service Systems and Service Management · doi:10.1109/icsssm.2015.7170260
“…has increasingly been considered as a useful marketing tool to acquire new customer (e.g., Berger and Schwartz, 2011; Chevalier and Mayzlin, 2006; Godes and Mayzlin, 2004, 2009; Goldenberg, Libai, and Muller, 2001, 2004; Hinz, Skiera, Barrot, and Becker, 2011; Schmitt, Skiera, and Van den…”
MethodChen, Q., Phan, T., & Goh, K.-Y. (2012) · International Conference on Interaction Sciences · doi:10.2139/ssrn.2163314
Social Networks and the Choices People MakePreprint
Chen, J. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1402.3138
“In a recent study, Godes and Mayzlin (2009) used data from a large-scale field test and an online experiment to study the efficacy of the proactive management of customer-to-customer communication by firms.”
BackgroundMethodResultInfluentialStructural analysis of large networks: observations and applications
Faloutsos, C., Montgomery, A. L., & McGlohon, M. (2010)
Exploring Word-of-Mouth Communication in Business-to-Business MarketingPreprint
Dash, M., & Havaldar, K. K. (2011) · SSRN Electronic Journal · doi:10.2139/ssrn.1934172
The Study Of Properties Of The Word Of Mouth Marketing Using Cellular Automata
Kowalska-Styczeń, A. (2014) · Foundations of Computing and Decision Sciences · doi:10.2478/fcds-2014-0003
“Particularly interesting results which are presented in [15] indicate, that w-o-m is the most effective channel of sales growth, if it is created by not very loyal consumers, but also”
BackgroundDou, Y., & Liu, T. (2013) · Journal of Systems Science and Systems Engineering · doi:10.1007/s11518-013-5224-7
“…literature has characterized the peer influences in different ways such as word-of-mouth effects (Chen & Xie 2008, Forman, Ghose & Wiesenfeld 2008, Godes & Mayzlin 2009), network effects (Katz & Shapiro 1994, Sun, Xie & Cao 2004, Parker & Van Alstyne 2005, Deishin & Mendelson 2008, Dou, Niculescu…”
BackgroundRetracted¿QUIÉN HABLA DE TI EN INTERNET? UNA EXPLORACIÓN DE LA 'BLOGOSFERA' AFÍN A TEMAS ALIMENTICIOS
Pinto, C. S. (2013) · Dialnet (Universidad de la Rioja)
Editorial—People of Marketing Science
Desai, P. S. (2012) · Marketing Science · doi:10.1287/mksc.1120.0709
“Table 3 Most Cited Marketing Science Articles by Year for 2009–2011 with ISI Web of Science Data Year of Rank publication (1= best) Reference 2009 1 Godes and Mayzlin (2009) 2009 2 Hauser et al. (2009) 2009 3 Luo (2009) 2009 3 Sood et al. (2009) 2009 5 Anderson et al. (2009) 2010 1 Fiebig et al.…”
BackgroundEmbedded but not Enchanted: How Social Network Predicts Response to Product RecommendationPreprint
Gong, S., & Huang, J. (2014) · SSRN Electronic Journal · doi:10.2139/ssrn.2529634
“Recent studies in this domain mainly focus on how firms propagate systematic WOM through consumer population (Dellarocas 2006; Godes and Mayzlin 2009; Kumar et al. 2013), target social "hubs" or "influentials" in marketing campaign for efficient WOM (Watts and Dodds 2007; Goldenberg et al. 2009;…”
BackgroundEssays on social media, social influence, and social comparison
Tang, Q. (2013) · Texas ScholarWorks (Texas Digital Library)
Three Essays on Networks and Public Economics
Amant, P.-A. B. S. (2013)
Managing negative electronic word of mouth: a study of British hotels
Tawat, S. (2026) · e-space (Manchester Metropolitan University) · doi:10.83056/mmu.32436114
How e-wom contributes to new product adoption. Testing competitive communication strategiesPreprint
Piñero, M. S., & López, M. (2011) · RePEc: Research Papers in Economics
Sensegiving Word-of-Mouth and Collective Sensemaking About Epistemic Objects
Smith, A. N. (2014) · YorkSpace (York University)
Consumers’ Response to Out-of-Stock Situations
Metzger, T. (2015)
The Impact of Gratitude-Embedded Messages on Online Pro-Social BehaviorsPreprint
Yim, D., Viswanathan, S., & Lucas, H. C. (2015) · SSRN Electronic Journal · doi:10.2139/ssrn.2694084
Looking Ahead to New Product Diffusion
Gatignon, H., Gotteland, D., & Haon, C. (2016) · Palgrave Macmillan UK eBooks · doi:10.1007/978-1-137-57264-6_6
Stephen, A. T., & Lehmann, D. R. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2772610
Methods for Selecting Nodes for Maximal Spread of Influence in Recommendation Services
Gliwa, B., & Zygmunt, A. (2016) · Communications in computer and information science · doi:10.1007/978-3-319-34099-9_8
— EMPIRICAL EVIDENCE FROM COMMUNITY -BASED CONFIGURATION SYSTEMS
Hildebrand, C., Landwehr, J. R., & Herrmann, A. P. (2011)
Managing Social Media Communities for Better Social Media Intelligence
Moe, W. W., & Schweidel, D. A. (2014) · Cambridge University Press eBooks · doi:10.1017/cbo9781139381338.012
Social Media Performance Measurement
Greve, G. (2015) · Advances in marketing, customer relationship management, and e-services book series · doi:10.4018/978-1-4666-8459-1.ch011
“In today’s connected world, online content is an integral part of a customer, and sharing online content can have a big impact on sales and the development of customer relationships (Chevalier & Mayzlin, 2006; Godes & Mayzlin, 2009).”
BackgroundIII Social Media Effects Along The Value Chain – A Narrative Review
Kick, M. (2015) · Springer eBooks · doi:10.1007/978-3-658-08837-8_3
The invisible force that shapes our world
van Eck, P. S. (2013)
López, M., & Piñero, M. S. (2015) · IGI Global eBooks · doi:10.4018/978-1-4666-7357-1.ch032
“This spontaneously generated WOM is referred to as endogenous WOM (Godes & Mayzlin, 2009) (see Figure 1).”
BackgroundA social perspective on S-D logic
Nijboer, J. F. (2011) · Nottingham ePrints (University of Nottingham)
Lee, J., & Hansen, S. S. (2013)
Consumer Information Sharing : Understanding Psychological Drivers of Social Transmission
Akpınar, E. (2013) · RePub (Erasmus University Rotterdam)
The Impact of Negative Online Review on Consumer's Purchase Intention: A Dual-Process Perspective
Xiao, Q. (2016) · International Journal of u- and e- Service Science and Technology · doi:10.14257/ijunesst.2016.9.12.13
“Factors such as the expert role, knowledge level and activeness would also be influential [21-22].”
BackgroundMethodThe heterogeneity of crowdfunders
Lin, Y. (2017) · DR-NTU (Nanyang Technological University) · doi:10.32657/10356/69547
Chinese Retailers’ Use of Brand-Consumer Communications: Mobile Instant Messaging (MIM) in Wechat
Nguyen, B., Melewar, T. C., & Schultz, D. E. (2017) · doi:10.1057/978-1-137-48996-8_7
The Marketing/Operations Management Interface:Toward a Science of Delivering Value
Li, S. (2010) · eScholarship (California Digital Library)
Managing Risk And Uncertainty In Supply Chains In The Face Of The Current Global Realities
Akalin, G. I. (2016) · UTA ResearchCommons (University of Texas Arlington)
Saito, K. (2014) · International Journal of Marketing & Distribution · doi:10.5844/jsmd.16.2_119
“研究 1 研究 1では,サンプル試用直後に形成さ れるWOM意図の先行要因を検討する。前 述のように,サンプルを 1回試用しただけ で消費者が利ブランド目標を持つことはほ ぼない。そのため,サンプル試用直後に形成 されるWOM意図は,利己目標や利他目標 を達成する手段としての他者やブランドの 有用性に依存する。”
InfluentialIs “proof” the Eighth “P” of Service? A Conceptual Model and Propositions
Moorthi, Y. L. R., & Roy, S. (2017) · Services Marketing Quarterly · doi:10.1080/15332969.2017.1363586
Designing Networks for Nudges: Using Social Conformity to Optimize Consumer BehaviorPreprint
Wei, Y. “., & Lu, J. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2791781
The impact of online word of mouth on fund sales
Liu, J.-W., Zou, P., & Li, X. (2016) · International Conference on Management Science and Engineering (ICMSE) · doi:10.1109/icmse.2016.8365611
엄금철 (2015) · Seoul National University Open Repository (Seoul National University)
Stumpf, C. (2018) · Publication Server of Kaiserslautern University of Technology (Kaiserslautern University of Technology)
Creating Consumer-Based Brand Equity With Social Media Content Marketing
Weitzl, W. (2018) · Advances in business strategy and competitive advantage book series · doi:10.4018/978-1-5225-6307-5.ch018
Deats, J. R. (2017) · Routledge eBooks · doi:10.4324/9780203786260-19
Identifying potential change leaders through social network visualizations
Andrzejak, P. (2019) · Management Sciences · doi:10.15611/ms.2019.1.05
The Role of the Level of Consumer on the Effect of Persuasion Knowledge on the Online Reviews
Son, Y., 송시연, & 남아영 (2017) · Journal of Product Research · doi:10.36345/kacst.2017.35.2.005
Nhi, N. X., Thong, B. Q., Khương, M. N., & Linh, L. T. T. (2018) · Journal of Economics Business and Management · doi:10.18178/joebm.2018.6.3.558
Kuznechikova, A. (2019) · Theseus (Ammattikorkeakoulujen)
The Roles of Emotional Cues and Purchasing Incentives in WeChat Commerce: A Content Analysis
Hao, X. (2020) · Digital Commons - University of South Florida (University of South Florida)
What Happens with the New Guy? Tackling the Problem of Tacit Knowledge through Social Networks
Galli-Debicella, A. (2020) · Journal of Management Research · doi:10.5296/jmr.v12i4.17696
“…on the market-level spread, while strong ties have a greater impact on interpersonal influence (Brown & Reingen, 1987; Frenzen & Nakamoto, 1993; Godes & Mayzlin, 2009; Hu, et al, 2019). www.macrothink.org/jmr 11 The majority of relationships at an organization are weak, since employees have…”
BackgroundCommunication Networks in Games with Asymmetric Information
Campbell, J. D. (2010) · doi:10.7301/z08c9thd
Competition, Politics, & Social MediaPreprint
Leung, B. T. K., & Yıldırım, P. (2020) · RePEc: Research Papers in Economics · doi:10.48550/arxiv.2012.03327
“While empirical marketing literature on social media has been growing (e.g. Godes and Mayzlin, 2009; Schweidel and Moe, 2014), there have been fewer theoretical examinations on the impact of social media channels (e.g., Joshi, 2015; Bart, 2017).”
BackgroundThinspiration from the 'Biggest Loser': Social Interactions in a Weight Loss ProgramPreprint
Uetake, K., & Yang, N. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2838279
Measuring Information Diffusion in an Online CommunityPreprint
Garg, R., Smith, M. D., & Telang, R. (2011) · SSRN Electronic Journal · doi:10.2139/ssrn.1864899
Designing digital marketing strategy process base on customer in Digital Service Provider Business
یزدانفر, ش., نعامی, ع., & آزاد, ن. (2019) · چشم انداز مدیریت دولتی · doi:10.29252/jbmp.18.37.99
Dimension 4: Customer Management
Staudacher, J. (2021) · Springer eBooks · doi:10.1007/978-3-658-20176-0_6
Leveraging Malicious Joy to Influence Consumer Word-of-Mouth Transmittal in Social Networks
Pacheco, B. G., & Paniculangara, J. (2021) · Springer proceedings in business and economics · doi:10.1007/978-3-030-76520-0_26
Determinants of influence in electronic word of mouth communication within Facebook
Stone, R. J. (2020) · University of Birmingham Institutional Research Archive (University of Birmingham)
Social Media as a Channel of Communication with Customers in the Hospitality Industry
Surdu, A. C. (2014) · Research Repository (Delft University of Technology)
Marketing research in foreign markets: information support
Кузняк, Б. Я., Добрянська, В. В., & Vasiuta, V. B. (2021) · Galician economic journal · doi:10.33108/galicianvisnyk_tntu2021.06.070
Managing Brands Through Social Media
(2017) · Advances in marketing, customer relationship management, and e-services book series · doi:10.4018/978-1-5225-5143-0.ch003
Kucuk, S. U. (2016) · Springer eBooks · doi:10.1007/978-3-319-48027-5_8
Lee, C. H., & Zhao, J. L. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3446714
“namely, awareness and persuasiveness [38].”
Re-Conceptualizing Relational Integrated Marketing Communications from the Perspective of Social CRM
Yoon, K., & Sims, J. D. (2015) · IGI Global eBooks · doi:10.4018/978-1-4666-7357-1.ch104
Social Media Performance Measurement
Greve, G. (2017) · IGI Global eBooks · doi:10.4018/978-1-5225-1837-2.ch017
豊, 濱. (2012) · Quarterly Journal of Marketing · doi:10.7222/marketing.2012.029
Integrating Social Media and Traditional CRM
Yoon, K., & Sims, J. D. (2015) · IGI Global eBooks · doi:10.4018/978-1-4666-7357-1.ch028
Using NPS Open-Text Responses to Uncover the Voice-Of-The-Customer
Sievert, J. (2023) · Springer eBooks · doi:10.1007/978-3-658-39072-3_11
Kucuk, S. U. (2023) · Palgrave studies in marketing, organizations and society · doi:10.1007/978-3-031-18215-0_11
Luna-Cortés, G. (2023) · International Journal of Event and Festival Management · doi:10.1108/ijefm-12-2022-0097
Ahrholdt, D. C., Greve, G., & Hopf, G. (2023) · Springer eBooks · doi:10.1007/978-3-658-40599-1_12
Testable Implication of Pairwise Stability in NetworksPreprint
Chiong, K. X. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4436491
An Experimental Analysis of The Negative Effect of Video on App DownloadsPreprint
Somech, I., Reichman, S., & Oestreicher-Singer, G. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4533039
Promotional Campaign Duration and Word-of-Mouth in Solar Panel AdoptionPreprint
Bollinger, B. K., Gillingham, K. T., Lamp, S., & TSVETANOV, T. G. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4546332 · Cited by 1
“Godes and Mayzlin (2009) face a similar challenge and thus study the impact of WOM across 15 markets by incentivizing WOM at the individual level instead of using market-level randomization.”
BackgroundInfluential
Metadata
- Authors
- Godes, D., & Mayzlin, D.
- Affiliations
- Harvard University (US)
- Yale University (US)
- Venue
- Marketing Science
- Published
- 2009-07
- Volume
- 28
- Issue
- 4
- Pages
- 721-739
- ISSN
- 0732-2399 (ISSN-L)
- 1526-548X
- OpenAlex
- W2132559268
- Cited by
- 837
- References
- 59
- Citations by year
- 2026: 11 · 2025: 22 · 2024: 24 · 2023: 52 · 2022: 41 · 2021: 46 · 2020: 54 · 2019: 55 · 2018: 52 · 2017: 50 · 2016: 57 · 2015: 72 · 2014: 73 · 2013: 81 · 2012: 53
- FWCI
- 155.67
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Marketing Science (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › Digital Marketing and Social Media
- Social Sciences › Business, Management and Accounting › Marketing › Marketing and Advertising Strategies
- Physical Sciences › Physics and Astronomy › Statistical and Nonlinear Physics › Complex Network Analysis Techniques
- Keywords
- word of mouth, opinion leadership, customer loyalty, sales effectiveness, customer awareness
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review