Effects of Word-of-Mouth versus Traditional Marketing: Findings from an Internet Social Networking Site
By Michael Trusov, Randolph E. Bucklin, Koen Pauwels. 2009
2,578 citations recorded by the source corpus.
The authors study the effect of word-of-mouth (WOM) marketing on member growth at an Internet social networking site and compare it with traditional marketing vehicles. Because social network sites record the electronic invitations from existing members, outbound WOM can be precisely tracked. Along with traditional marketing, WOM can then be linked to the number of new members subsequently joining the site (sign-ups). Because of the endogeneity among WOM, new sign-ups, and traditional marketing activity, the authors employ a vector autoregressive (VAR) modeling approach. Estimates from the VAR model show that WOM referrals have substantially longer carryover effects than traditional marketing actions and produce substantially higher response elasticities. Based on revenue from advertising impressions served to a new member, the monetary value of a WOM referral can be calculated; this yields an upper-bound estimate for the financial incentives the firm might offer to stimulate WOM.
Subfields: Marketing, Sociology and Political Science, Strategy and Management
View Paper: https://www.semanticscholar.org/paper/4b42e7216977995de839cff4dda9f6df60b7c9b2
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Marketing
- Jonah A. Berger
- Andrew T. Stephen
- Peter C. Verhoef
- Koen Pauwels
- Ram Bezawada
- Philippe Duverger
- Thorsten Wiesel
- Evert de Haan
In Sociology and Political Science
- Jonah A. Berger
- Andrew T. Stephen
- Philippe Duverger
- Eric Wing Kuen See-To
- Kevin K. W. Ho
- Grant Packard
- Lauren Grewal
- Michael Trusov
In Strategy and Management
- Philippe Duverger
- Gerard J. Tellis
- Eric Wing Kuen See-To
- Kevin K. W. Ho
- Jonah A. Berger
- Andrew T. Stephen
- Koen Pauwels
- Reinhold Decker
Citations in the corpus
- Broadcasting and Narrowcasting: How Audience Size Affects What People Share (2014, background): “Word of mouth can generate awareness, encourage belief updating, or produce normative pressures (Van den Bulte and Wuyts 2009).”
- Creating Social Contagion through Viral Product Design: A Randomized Trial of Peer Influence in Networks (2011, neutral): “…have been proposed, including peer effects models and extended spatial autoregressive models (e.g., Oestreicher-Singer and Sundararajan 2008, Trusov et al. 2009, Bramoulle et al. 2009), actororiented models (e.g., Snijders et al. 2006), instrumental variable methods based on natural…”
- Promotional Marketing or Word-of-Mouth? Evidence from Online Restaurant Reviews (2013, background): “Trusov et al. (2009) present a model that enables marketing actions to be credited for their WOMgenerating abilities.”
- Social Networks, Personalized Advertising, and Privacy Controls (2013, neutral): “What changed was simply how easy it was for users to control access to their information by regular Facebook users.”
- Customer-to-Customer Interactions: Broadening the Scope of Word of Mouth Research (2010, methodology): “Based on vector autoregression modeling and Granger causality tests, Trusov, Bucklin, and Pauwels (2009) conclude that WOM leads to more new members and more new members lead to more WOM.”
- When Posting About Products on Social Media Backfires: The Negative Effects of Consumer Identity Signaling on Product Interest (2019, background): “Prior work has mostly addressed firm-level aspects, such as how social media influences sales and customer acquisition (Stephen and Galak 2012; Trusov, Bucklin, and Pauwels 2009).”
- Authentic assessment in business education: its effects on student satisfaction and promoting behaviour (2018, result): “Consistent with previous studies in the literature (Anderson 1998; Chevalier and Mayzlin 2006; Christiansen and Tax 2000; Trusov, Bucklin, and Pauwels 2009), satisfied customers are likely to spread positive messages about their experiences.”
- How Language Shapes Word of Mouth's Impact (2017, background): “Hearing that someone else likes something drives people to purchase (Chevalier and Mayzlin 2006; Liu 2006; Trusov, Bucklin, and Pauwels 2009), generating $6 trillion a year in economic value (WOMMA 2014).”
- Negative Reviews, Positive Impact: Consumer Empathetic Responding to Unfair Word of Mouth (2020, background): “Both types of reviews, negative and positive, greatly influence consumer decision making (Basuroy, Chatterjee, and Ravid 2003; Godes and Mayzlin 2009; Trusov, Bucklin, and Pauwels 2009), with negative reviews often being the most impactful (Chen and Lurie 2013; Mizerski 1982).”