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Little Boxes on the Hillside, Little Boxes All the Same

Steve ManattOctober 30, 2014

Way back in my youth, before I knew what activists and hippies were, Malvina Reynolds wrote “Little Boxes.” You may not remember the original song, but perhaps you’ve heard one of your favorite bands cover it. Since she first wrote it in 1962, it has been covered by many artists in English, Spanish, Russian, and French including Pete Seeger, Donovan, Elvis Costello, Linkin Park, The Mountain Goats, Randy Newman, Death Cab for Cutie, and Rise Against just to name a few. It gained new popularity more recently when it became the theme song on Showtime’s series “Weeds.”

“Little Boxes” was a satirical commentary on the development of suburbia and conformist middle-class attitudes and behaviors. It reminds me of the neighborhood in Edward Scissorhands where all the women were housewives, except for the beautician and the “career gal” who sold cosmetics door-to-door. The houses in that neighborhood are pink, green, blue, and yellow, just like in the song.

According to the lyrics, everything was the same – the houses were the same, the people were the same, the children were the same. If you rely only on demographic data at the geographic level to identify new markets all your customers and prospects will look all the same and you’re liable to put them in little boxes, too.

Don’t get me wrong. There is a great deal of value marketing with geographic data. It helps many banks, retailers, restaurants, and other businesses decide where to open new stores and branches. It helps realtors identify new markets, but also helps them target markets for their clients. It helps anyone who is interested understand the behaviors and lifestyle characteristics of a neighborhood or area. But is that really all you need to know for your marketing campaigns?

Look out your front window. Take a walk through your neighborhood. As you take that walk think about how much like you all your neighbors are and how demographics at a geographic level accurately reflect all of you.

My neighborhood is a collection of 1940s through 1960s ranch homes. As a matter of fact I can easily imagine Malvina Reynolds looking at the neighborhood and thinking “ticky tacky!” The houses are not pink, green, blue, and yellow…well, maybe some are, but not nearly as colorful and bold as I imagine when I hear the song. The prices of houses in my neighborhood range from less than $100,000 for a house in need of updating to over $1,000,000 for houses with a view of the river. These little boxes are not all the same.

What is even more varied is the make-up of the people in the houses.  We are quite varied, which is fairly common in older neighborhoods. The people in my neighborhood include home owners and renters. Our ages range from 20-somethings all the way up to 90-somethings.  Some of us went to university, but not all of us.  Some even dropped out of high school. My neighbors are doctors and lawyers and business executives, but they are also marketers, teachers, landscapers, retail workers, restaurant workers, nurses, non-profit fundraisers, event planners, retirees, mechanics, construction workers, and a dog walker just to name a few.  There are people who are married, never married, widowed, and divorced.  Some households have young children, some have grown children, some have grandchildren, some have lost children, and some are childless. Our ethnicity, race, income, interests, and the make-up of our households is quite varied.  We do not all look just the same.

To effectively identify your audiences on a household level, you can’t rely only on geographic data.  The most effective targeting and understanding of households will come from your data combined with geographic data, demographic data, and the ability to identify households effectively. If you rely solely on geographic data, contrary to the description I have given you, you will be told that my neighborhood is white, married couples with college degrees. Our home value is higher than the average for the metropolitan area.  The median age is 40, we were born in the state, and we hold professional / white collar jobs. <Cue Malvina singing “…and they all look just the same”.>