In the past, I have argued against trying to compile lists of sociopolitical groups, or against targeting them in a strategic sense. I still think this is perhaps dangerous and slippery ground. Nevertheless, I have been thinking about this today, as three different systems for identifying sociopolitical groups came together in my head.
The danger of sociopolitical groups is simply this: of the making of sociopolitical groups, there is no end. One can start with “Taxi cab drivers in New York” and end up with “The Royal Family of England.” There could literally be a billion or more sociopolitical groups, and we can all argue about whether they are unreached or not. So from the perspective of monitoring the remaining task, I don’t think researching or measuring groups has significant value.
But the benefit of sociopolitical groups is this: they are a smaller and more engageable group. If I tell you that there are 332 million Bengalis and ask if you are called to reach them, your immediate answer is simple—no. No one can reach 332 million people. In fact, it could be argued that no single group of individuals, or even a single group of agencies, could reach 332 million Bengalis. After all, it’s like trying to evangelize, make converts of, and disciple, everyone in America.
The challenge, in my mind, is how to identify sociopolitical groups. I’m sure out “there” in the wide world of academia, there is a time-honored way of identifying groups within a given ethnicity and culture. But I’ve not run across it, and in the absence of some formal training, I’m here going to make a few simple suggestions that I’ve been reflecting on. If you have an improvement or an alternative please feel free to pipe up in comments below.
1.
First, let me point out the very interesting book Microtrends: The Small Forces Behind Tomorrow’s Big Changes, which was written by Mark Penn. He was an advisor to Hillary Clinton during her Presidential campaign. Now, admittedly some can argue that his strategy of targeting microgroups was part of her campaign’s downfall, but that doesn’t really detract from the very interesting research in this book. Microtrends is all about identifying small, intense subgroups and communicating with them about their individual needs and wants. Penn theorizes, “In today’s mass societies, it takes only 1% of people making a dedicated choice—contrary to the mainstream’s choice—to create a movement that can change the world.” Then he goes about to identify specific niche groups in America that make up 1% of the country’s population.
The very first example is “Sex Ratio Singles.” These are women left out of the institution of marriage because there are not enough males to marry. The reason is simple: homosexual males in America outnumber lesbian females by 2:1. This means there are more heterosexual females than heterosexual males—so unless we make polygamy the rule of the day, some females are going to be left out. They apparently make up more than 1% of the population. Single women are the second-largest group of home buyers, and they bought more than twice as many homes as single men.
Obviously, reaching out to a “Sex Ratio Single” woman requires a different strategy than reaching out to someone who is intentionally single or who is a lesbian. These women would prefer to be married. They may be more interested in a megachurch than a smaller church—simply because, honestly enough, they want a bigger pool of potential husbands.
There are a number of other groups that Penn identifies (and I’m not sure by any stretch that he has identified all of them). There are the Working Retired, the Ardent Amazons, the Pro-Semites, the Sun-Haters, the Old New Dads, the Militant Illegals, the Christian Zionists, the Young Knitters, and more. While many of these are “red, yellow, black and white,” each would need a different strategy.
Moving beyond Microtrends, let me point out a different resource which is available. Nielsen’s “Prizm” segmentation system segments the consumer market in American society using demographic data and customer data. You can look up the segments for your zip code here. It’s an interesting system: there are some 67 segments, a variety of which can be found in any given zip code. In my own zip code, you can find the Blue-Chip Blues, Home Sweet Home, Kids & Cul-de-Sacs, Suburban Sprawl, and Young Influentials. Each of these groups are further broken down with a brief description, some statistics, lifestyle traits, and demographic traits. For example, the Young Influentials are:
Midscale Middle Age without Kids: Once known as the home of the nation’s yuppies, Young Influentials reflects the fading glow of acquisitive yuppiedom. Today, the segment is a common address for younger, middle-class singles and couples who are more preoccupied with balancing work and leisure pursuits. Having recently left college dorms, they now live in apartment complexes surrounded by ball fields, health clubs, and casual-dining restaurants. US Households: 1.7 million. Median HH Income: $51k. (Plus a bunch of other traits.)
Just as in Microtrends, most of the PRIZM segments are designed to take up about 1 to 2 percent of the US population. In addition, these are grouped into Social Groups (e.g. Young Influentials are in the Middleburbs) and Lifestage Groups (Young Achievers). The “Middleburbs” are made up of Domestic Duos, Blue-Chip Blues, Suburban Sprawl, Young Influentials and Gray Power.
2.
I’ve known about these two segmentation systems for a while now. I bought Microtrends a few years ago, and PRIZM is older than that. What closed a circuit in my brain, I guess, was watching my kids working on prime factorization.
Prime factorization, if you don’t know or don’t remember, is a mathematical system for figuring out the primes within a given number. I didn’t learn it myself in school (or at least I don’t recall it), and you may not have either. If not, you can watch a great Khan Academy video on this. It’s a 4 minute video and the part that concerns us here starts about 2:30. So watch it, and you’ll learn something that’s maybe new, and then we’ll move on. Right?
Ok, now that you’ve gone through the whole factorization thing, here’s the point. What clicked in my brain was that a large number can be broken up into its primary components. A larger group can be broken up in the same way. I was thinking about the PRIZM segments, and it struck me that they are in some ways segmented based on (1) marital status, (2) economic position, (3) age, and (4) geographical location (e.g. inner city, suburbs, farms, etc).
It might be possible, then, to take any ethnic or linguistic group (or urban group, or whatever), and consider it in the same way. Segment the group first according to binary conditions—things you answer yes or no to. For example: married or not, divorced or not, widowed or not, urban or rural, etc. These “Yes/No” questions could be considered the “factors.” Next, we might move on to consider gradations of a particular status—e.g. wealth could be measured on a 5-part scale: very poor, relatively poor, middle class, wealthy, very rich.
It’s easier to apply it than to talk about it, probably.
3.
Let’s take a given people group—for example, let’s say the Han Chinese. There’s a lot of them—many millions of them. But it’s fairly easy to first divide the Han Chinese between urban and rural. We could also look at those who have advanced degrees, and those who do not. And, those who speak English and those who do not. Possibly, we could look at government employees, soldiers, businesspeople, small business owners, migrant workers, and unemployed. Certainly, age brackets can also be something to explore, in addition to marital status.
These sociopolitical segments are easier to identify than, say, “taxi drivers” or “market stall owners.” And, clearly, a different strategy can be articulated for each of these groups. The strategy itself does not need to be significantly different in each case, but you might consider your Teachable Behaviors and Repeatable Processes and how you would have to “riff” differently on these standards for each of these sociopolitical groups. In this case we are not necessarily trying to measure all of the sociopolitical groups, but rather find the natural social boundaries that the Gospel would have a hard time crossing, even within a common ethnicity and language. It might be easier to cross-pollinate the Gospel from the context of a missionary vocation, manually seeding it across these boundaries, rather than waiting for it to jump across automatically (although it can and I’ve seen many examples where it does).
So what do you think? Does this make sense? What sorts of natural sociopolitical subdivisions can you see in the people group that you are focused on – and how do you vary your strategy for these natural subdivisions? Write your comments below.
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