Imagine you’re a tourist in a foreign resort town. You stroll down a seemingly lively street, looking for a bar to lodge yourself at for happy hour. There are two bars across the street from each other, clearly competing for business.
The exteriors are similar. Interestingly, they have very similar interior ambience, too. The drink menus are strikingly alike. Not knowing better, you and your friends choose one almost at random.
Shortly after, more tourists turn up on the street in search of a festive happy hour. They see one bar with what seems like a jolly group of people enjoying their drinks and an empty one across the street. They infer the bar with customers is better and more festive, so they walk into that one. A third group of tourists arrives and, not surprisingly, join the growing throng.
You know the ending. One bar is packed before the peak evening business hours even kick in, and the other is empty. This story probably happens more often than you realize. Perhaps it’s in our nature to be drawn to groups and exhibit group behavior.
To truly understand the full extent of behavioral targeting, planners must understand the emotional forces (e.g., peer-to-peer influence) behind group behavior.
The Emotional Effect of Social Proof
According to most economic theories, the aforementioned bar story shouldn’t happen. Not because it isn’t fair, but because it’s not rational. Economists assume people only make rational decisions after gathering the facts and weighing the evidence without bias.
“Social proof,” as social psychologist Robert Cialdini explains in his book “Influence, The Psychology of Persuasion,” refers to our inherent behavioral tendency to look at what others are doing before we decide. It’s a much more emotional process that rests on the connection with other people as opposed to a very rational one relying on price comparisons and product reviews.
It explains the bar example: “If everybody is drinking at this pub, it must be good and fun.” It demonstrates the emotional, and less rational, forces in our decision-making process. We’re all subject to a latent level of group thinking.
Social proof is the foundational instinct behind word of mouth and plays an instrumental role in the social computing phenomenon.
When the Web Mimics Life
Consider how many times you looked to buy the same piece of clothing after someone else tried it on in the store. While there’s a perceived level of voyeuristic nature in social proofing (it’s part of human nature to observe others), this type of basic human behavior is precisely what drives the convergence of real life and the Web.
What if we can enable all the real-life social behaviors in the virtual world? Imagine you could view someone else’s online shopping cart for inspiration, just as we do in real-life stores and shopping malls? What if you could see how many of your friends or people in general are on a particular Web site before you go in to explore, as in the bar example? What behavioral targeting tools can be developed to foster this type of Web 2.0 level of connectivity and interaction?
Old-timer powerhouses such as Amazon and eBay (with recommendation functions) are certainly steadily raising the bar, but it’s newbies such as Like (a visual search-based shopping engine) and weblin (software that enables people on the same Web page to see and communicate with each other) that are taking the power of social proof to the next level to bridge the gap between real-life and virtual behavior.
What This Means for Online Media
In his book, Cialdini highlights other emotional forces that shape our behavior. These include “reciprocity” (a sense of obligation to return and exchange), “liking” (if we like someone we’re more likely to trust them and buy from them), and many others that play a critical role in the behavioral equation.
These are insights into what marketing is all about, its insistence that we comprehend both the rational and emotional at the heart of communication. As consumers’ online behaviors continue to mature and diversify and to become more complex with the empowerment of digital channels, media planners must understand both sides of the equation to effectively construct the appropriate context to formulate clusters. There will inevitably be a convergence between media (conventionally, the more scientific side of marketing) and advertising (the emotional counterpart).
As we continue to explore the importance of behavior in the greater context of communications, a fundamental understanding of how to build emotional attributes will become critical in establishing the right parameters in behavioral targeting.
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