As everyone has probably heard by now, the famous “Become a Fan” button on Facebook will soon change to a “Like” button. This seemingly insignificant label change is presumably aimed at helping lower the barrier for interaction among Facebook users. No longer are people posed with the internal question “Am I really interested in a page’s content so much as to  become a FAN of the page?” Rather, they probably only will ask themselves “Hey, I LIKE this content and I find it interesting.” The perception change for users probably encourages interaction with content. Facebook has been reportedly notifying agencies of the change and is recommending that they use “Find us on Facebook” or “Like us on Facebook” for the changed verbiage.

But what does it mean for Marketers within Facebook? One could argue this is Facebook’s attempt to better serve users and build user communities, thumbing its nose at what has likely become a key engagement measuring point for brands and companies. It seems people will generally be more inclined to “like” content than become a “fan” of content, because “liking” something is far less committal than becoming a “fan” of something.

This linguistic change poses some interesting depth-of-engagement questions. How does this simple label change affect key performance indicators for a company or brand? More importantly, how does it change the perception of their value to brands and companies? Does it have detrimental or positive effects on the engagement metrics used by Fan Page administrators? And for users, should “Fan Pages” now become “I Like” pages?

Last night I had the fortunate opportunity to attend the local UPA MN lecture where Susan Dray and David Siegel talked about some of the myths of user research.  Without getting into the details of the presentation, their main message was basically don’t always trust research outcomes, no matter how massive or sophisticated they appear.

We work hard to never stop questioning our approaches to defining customer or user experience problems, in addition to our methods in answering them. But as experience design strategists and designers in agency or consultancy settings like Bolin Digital, we often don’t have the luxury of large budgets to help us inform our design decisions for many projects.

In the methods of our work, we rely heavily upon activity-, user-, and system-centered approaches as models to guide us through the forest of decisions. We hope that one of them or a combination of them gets us to the answer quickly.  Paul and I have also chatted about the common sense approach to design: should we  sometimes  rely on our own experience or instinct to guide decision making (also referred to as Dan Saffer’s “genius” centered design approach)? It seems like even this cost-efficient “gut” check, however, can get us into deep water.

As we continue to grow up in a world of increasingly sophisticated interactions and product experiences, it’s important to understand how we arrive at conclusions about which design paths to take.

All this recent thinking provoked me to ask these questions about design research methods and tools: Wwhat’s the best mix of data and methods?  How much of it is driven by common sense? How do we know when we arrive at the best possible solution?