Exploring Demographics and Lifestyles with the Esri Tapestry Data

What is your neighborhood really like?  In 1988, Michael Weiss, in his fascinating book The Clustering of America, introduced the idea that neighborhoods can be grouped in terms of lifestyles, consumer spending, demographics, and socioeconomic variables. Part of a larger field of study known as Cluster Analysis, the descriptive names given to neighborhoods included “Furs and Station Wagons”, “Towns and Gowns” (college towns), and “Laptops and Lattes.” From this sprang geodemographics—the analysis of people based on where and how they live.  Some have argued that geodemographics had its roots in Charles Booth’s survey into life and labor in London during the 1890s.  However, it wasn’t until the 1990s when geodemographics became very important to businesses seeking to make wise decisions about where to locate.

I first wrote about the lifestyle cluster data available from Esri back in 2009, and since that time, the ways that the data can be accessed has become easier than ever.  In addition, the data itself has become more accurate and more detailed.  Tapestry segmentation provides an accurate, detailed description of America’s neighborhoods. U.S. residential areas are divided into 67 distinctive segments based on their socioeconomic and demographic composition, and then further classified into 14 LifeMode and Urbanization Groups.

If you are new to analyzing this type of data, I recommend starting with the introduction, reviewing the cluster segments, and examining the poster (you can even order your own paper copy of the poster here).

Now you’re ready for examining the data in live web maps.  Start by looking up the tapestry segments for your own zip code here.  Next, open the story map for a tour of the USA’s 14 LifeMode groups here.  You can also examine the data in an ArcGIS Online map, where at small scales, a single dot is shown for each ZIP Code, based on the predominant tapestry code.  As you zoom in, the map transitions to show dot density patterns for each tapestry segment found in the ZIP Code.  That’s not all!  You can also examine the tapestry data as a map layer, so that if you wanted to combine it with other data in ArcGIS Online, such as median household income, median age, the diversity index, or the growth rate, you could do so.

You can also examine the data inside two powerful applications–Community Analyst and Business Analyst (and its web counterpart, Business Analyst Online).  One advantage of using the tapestry data inside these applications is that you have the ability to easily create a wealth of maps and reports as well as attribute and location data on millions of business locations.

Space does not permit me to fully expand on the rich discussions that you can have with students with using the tapestry data, but they include discussing the differences between aggregated data and individual data, and whether you feel that the tapestry segment(s) for your neighborhood, region, or state accurately describe it, or why not.  Discussions could also include how your neighborhood compares with those adjacent to it, or to those across town, or to the neighborhood in which you grew up.  How do you believe your neighborhood is changing, and why?  What influence do specific industries, or natural resources, or universities or retirement communities have on your neighborhood?

Looking for this type of data outside the USA?  Some does exist; contact your local distributor for more information.

Please share in the comments section below how you are using this data in your instruction.

Tapestry data for a neighborhood in Washington DC

Tapestry data for a neighborhood in Washington DC.

Joseph Kerski

About Joseph Kerski

Joseph Kerski is a geographer who believes that spatial analysis through digital mapping can transform education and society through better decision-making using the geographic perspective. He serves on the Esri education team and is active in GIS communication and outreach, creates GIS-based curriculum, conducts research in the effectiveness of GIS in education, teaches online and face-to-face courses on spatial thinking and analysis, and fosters partnerships to support GIS in formal and informal education at all levels, internationally. He is the co-author of Spatial Mathematics, The Essentials of the Environment, The GIS Guide to Public Domain Data, and other books. Follow him on Twitter @josephkerski
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