If you recall, Señor Lopez Lomong, last year we had some back and forth about curation. Courtesy of a curator I’ve been following recently, I came across a recent article about curation especially in the Tumblr and Pinterest context.
“Someone on Pinterest once posted a slide that read: ‘Pinterest: Where women go to plan imaginary weddings, dress children that don’t exist and decorate homes we can’t afford.’ But to focus on the ‘aspirational’ aspect is to miss the point. People don’t post stuff because they wish they owned it, but because they think they are it, and they long to be understood, which is different.”
You talked about surveys in your motivational misalignment post, but conflated them with observational data. In my view, surveys are very different from observational data. In my reckoning, surveys are explicitly carried out with explicit question-asking and elicitation, whereas observational studies try to implicitly elicit things just by watching things unfold as they normally do, with their inherent sample selection biases which should then be corrected. (In fact, the Anderson and Oliver (1987) paper I mentioned is empirically validated through surveys by Cravens, Ingram, LaForge, and Young (1993), whereas in this day of social media data and enterprise data collection, a validation based on that observational data could be attempted.)
The Zaltman metaphor elicitation technique is a survey method of sorts that tries to elicit consumer insight not from words, but from images. To understand the thoughts and feelings of customers about products or brands, Zaltman says that image-based elicitation is more effective than text-based elicitation. Rather than filling out a question-answering survey, a customer is tasked with taking several photographs representing their feelings on a product; researchers then interpret those photographs metaphorically in conjunction with conversations with the customer to draw conclusions on the voice of the customer. This is quite a costly and labor-intensive process.
Instead of the explicit photograph-taking to represent feelings on products, wouldn’t it be great if there were a ready source for such images that could be analyzed as observational data? Oh right, there now is: Pinterest. How could a machine analyze the images instead of a researcher? Couldn’t Torralba, Fergus, and Freeman’s 80 Million Tiny Images approach be used to find similar images and collect all the text surrounding and associated with the similar images, with that text information then being further analyzed by a machine good at natural language and evidence-based learning?
“At the heart of the Internet business is one of the great business fallacies of our time: that the Web, with all its targeting abilities, can be a more efficient, and hence more profitable, advertising medium than traditional media. Facebook, with its 900 million users, its valuation of around $60 billion (as of early June), and a business derived primarily from fairly traditional online advertising, is now at the heart of the heart of this fallacy.
“As Facebook gluts an already glutted market, the fallacy of the Web as a profitable ad medium will become hard to ignore. The crash will come. And Facebook—that putative transformer of worlds, which is, in reality, only an ad-driven site—will fall with everybody else.
“Facebook has the scale, the platform, and the brand to be the new Google. It lacks only the big idea. Right now, it doesn’t actually know how to embed its usefulness into world commerce (or even, really, what its usefulness is).”
He further states that the big idea will have to be something around the knowledge about people found inside the observational data that Facebook possesses. I couldn’t agree more. Along the same lines, the big idea for Pinterest should be image-based elicitation for consumer insight.