I recently bought a new (old) home in Atlanta. Temperatures have been, well, hot and the AC has not stopped running all summer long. But when my energy bill tripled for last month’s usage I had to wonder if there was something I should do. So, I reached out to my social circle; but neighbors, friends and family all gave me different opinions on what was “normal” for this time of year. I just wanted to know what normal energy consumption should be and understand how my home compared. While I’m sure there’s an app for that, I opted for a simple search which brought me to Microsoft-hohm.com where I could see how my home compared with my neighbors, the state and the nation. In fact, the site suggested that I could save quite a bit of money if I took steps to make my home more energy efficient. Decision made. Add more insulation, seal the windows and then reevaluate.
My point here is that while some decisions, like buying a pair of jeans, might require a couple thumbs up from your friends on Facebook, involved decisions, major behavioral changes and shifts in opinion may require an up-close and personal encounter with aggregated data from a substantial sample of “people like you.”
Access to other people’s information through social networks and aggregated data sites have made us more inquisitive about “how we compare.” Am I normal? Am I unique? This is the next generation of keeping up with the Joneses, just a bit smarter and less impulsive.
Conceptually, I like the ideas expressed in IBM Smarter Planet site (cl) that, “The planet has grown a central nervous system…we should instrument the world’s systems, interconnect them, make them intelligent.”
So, not only are we getting faster access to data, but that data is also being used to make faster more accurate and effective decisions. This cyclical relationship between data collection, aggregation, consumption and sharing will only expedite with time.
Advances in technology, analytics and computational modeling all in stride with the progression of social media – the possibilities for new engagement, connection and influence seem limitless.
The takeaway for communicators here is to know what data sources will influence your target audience to make a decision, change behavior or shift an opinion? And furthermore, what type of decision is your audience facing – Impulsive? Moderate involvement? High involvement?
In other words, is the individual buying a pretzel at the mall (impulsive), a pair of jeans (moderate), or buying a house(high)? And, who or what will motivate the individual? Will he be self motivated, directed, encouraged , or permitted to change behavior (consumption, purchase, perception, opinion)? Will this influence come from a single person, a group of friends or a substantial aggregate of data from a group of people “like him?”
When it comes to decision time will your target audience phone a friend or ask the audience?
Just a few examples to explore…
Phone a Friend
Shopping goes social:
blippy.com
swipely.com
Travel Advice gets personal:
TripAdvisor Trip Friends
Ask the Audience
Personal finance:
bundle.com
Home Purchase:
zillow.com
Energy Consumption
microsoft-hohm.com
Travel
tripadvisor.com
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