Demographics Meet Lifestyles: Psychographics in a Social World
In the late 1980's, the book, The Clustering of America by Michael Weiss had an immense impact on my career. It was a fascinating look at how people migrate to neighborhoods of similar background, interest and socio-economic status. Today it might seem obvious but in the late 80's mapping technology hadn't yet revealed the spatial aspects and relationships of lifestyle segmentation or psychographics. In the book, readers could look up their zip code and find the dominant lifestyle class in that area. Class labels such as Furs and Station Wagons or Guns and Pickups didn't just spur the imagination, it hit the nail on the head as to what you might expect if you ventured into that zip. Weiss followed that book with The Clustered World in 2000.
Today, nearly every advertising agency and market research firm uses some form of psychographics and are presented with better tools for visualizing spatial relationship. Last week, Esri unveiled its latest version of its lifestyle segmentation system, Tapestry. The company released a Story Map (image at right) that gives just a sampling of the lifestyle clusters now available. Many clusters have changed based upon the huge economic upheaval experienced in the US in the last six years or so. According to Esri:
Trends being seen in the United States today include reduced incomes, lower home values, and an increasingly diverse population. A steady shift in household types from traditional to nontraditional families and an aging population are also portrayed.
If you are really fascinated with who your neighbors really are and perhaps what it says about you, then try the interactive map to find your zip code and hence your unique cluster. If you are like me, you'll spend a significant amount of time trying to debunk how accurate the demographic data is only to find that they are embarrasingly spot on! As I said, Weiss' first book on psychographics, while based upon a competing segementation system originally, was influential in articles I published on the business applications of mapping and GIS. They were also quite accurate in its depiction of neighborhoods and zip code classifications. Today, though I wonder how frequently these clusters could change. We are a more mobile society in the wake of such a devastating economic downturn. Many people have migrated back to cities. But in the wake of social media, we are probably more segmented then the 60 odd clusters in most segmentation systems. We can be more defined by our online social habits and more precisely "clustered" by big data analytics.
Regardless, have fun playing with your cluster.