The Twitter Effect has been debated in both the academic community as well as by practitioners. The discussion’s locus is that tweets (or eWOM, or more specifically MWOM) have the ability to strongly effect consumer behavior — or “early product adoption behaviors”. I first came across this topic in relation to the release of Bruno, a Sacha Baron Cohen movie. It was argued that negative eWOM caused the movie to flop, and flop bad. The reasoning, early viewers ability to share their opinions. I do believe that there is real power in consumers having access to the post-consumption evaluations of early adopters. Furthermore, if this effect is prevalent then there certainly are economic implications for brands.
Much of the current literature on eWOM has examined the volume and valence of eWOM in relation to a brand’s performance. The environments used were communities, review sites and online forums.
For example, we find that:
- the positive feedback mechanism built into social media platforms have shown to have a positive effect on movie sales and total box office revenue.
- the amount of eWOM generated has a powerful and measurable effect on television ratings.
- both volume and valence impact the performance of book sales via online retailers.
- eWOM negatively influenced financial returns within the airline industry
- buzz surrounding the performance of a digital music device effected the pricing and placement
- referral eWOM (one person suggests a product to another), and not necessarily high-emotion eWOM, had a direct impact on a brand’s performance.
As we continue to see mobile-usage trends increase, the availability of post-purchase evaluations become more pervasive– most notably on social media sites. In general, 46 percent of online users count on social media to make a purchase (Nielsen, 2012). Consumers often report that it is the availability of opinions close to a purchase decision or during the purchase process that make it more effective.
Twitter and Consumer Behavior
Academics are beginning to study the effect Twitter, called MWOM (microblogging word-of-mouth), has on the decision-making process. We know that 53 percent of posts on Twitter recommend a product or a brand. Similarly, 48 percent of those who receive tweets report following through with a recommendation (Gottlieb, 2010). What must be clarified is that the Twitter Effect focuses on valence, not volume of tweets at the early stage of their cycle. That is, the positive or negative sentiments effect on behavior. As both Asur and Huberman (2010) and Wong, Sen and Chiang (2012) found, Twitter volume did have an effect on initial box office revenues.
I would surmise that there are three primary ways that the Twitter effect plays out. First, we are social beings. We tend to look toward others for what psychologist Robert Cialdini calls social proof. Hennig-Thurau, Wiertz and Feldhaus (2014) provided evidence that Twitter does “affect early product adoption behaviors by immediately disseminating consumers’ post-purchase quality evaluations”. Not only can we see how others react toward a product or service, but we are able to identify who are these early adopter and do they support or reject our idea of the end user? Similarly, early adopters provide a real-time feedback loop. Consumers have a digital archive of conversations surrounding products they may be interested in.
Second, Twitter has both a push and pull element built in. Users are both presented information within the Twitter feed and have the ability to activily search for information. Based on the relative ease of both active and passive search, branding decisions can be made more fluid. For example, Esch, Langner, Schmitt and Geus (2006) found that purchase behavior is more strongly affected by brand image. Brand awareness has an indirect effect on purchase behavior. While searching for a product, or as information is seen in the feed, posts are creating an association within the mind of the user. I see this effect primarily develop with television shows. Social conversations surrounding television, either live or post-broadcst, contribute to the show’s (brand’s) image. Whether seeking reviews or merely following along an image is being created. As more viewers chime in about a program both awareness and image are being created.
Third, users see their Twitter network as more trustworthy. Users perceive a sense of closeness, even with weak ties. Some believe this to be a consequence of how the platform has shaped communication. Gilpin (2009) argued that Twitter encourages the exchange of cultural norms, values and ideology creating a more binding system. This relational element has been discuss ad nauseam, as it relates to brand building.
Consumer Socialization Theory
We learn consumption-related skills through the observation of others in the marketplace. This process is known as socialization. The transmission of information between peers shapes attitudes and behaviors. Twitter not only provides a megaphone, but a virtual forum for such transmissions. What I believe is central to this “effect” is the communication of the early adopters. As DeGregorio and Sung (2010) argued, Twitter make the agent-learner relationship easier to establish. Not only does socialization occur on Twitter, but the establishment of perceived agent-learned relationships may evolve more quickly (Wang, Yu and Wie, 2012). Thus, the messaging to early adaptors and any subsequent influencer tactics become central to this effect.