Labels Are Easy and Usually The Surest Path To Confusion and Wrong

 

By Ron Sellers

In research, it’s extremely easy to call someone a Democrat.  Or a customer.  Or a Catholic.  Or affluent.  Or a member of whatever subgroup you’re researching.

But we need to be extremely careful with these labels, because they’re often not accurate.  For example:  Teresa earns $70,000 annually.  She lives frugally, and has no spouse or children.  She’s amassed a nest egg of $400,000, and recently splurged on a BMW 3-series convertible and a trip to Venice.  Trevor, on the other hand, earns $150,000 annually.  He’s supporting three kids from his current marriage, along with two from a previous relationship.  He’s underwater on his mortgage, has almost nothing saved for retirement, and has over $50,000 in car loans and credit card debt.

Which one is really affluent?

Definitions are critical.  Grey Matter Research partnered with Russ Reid Company on a large-scale study of charitable giving in the US (Heart of the Donor).  We broke out self-identified Catholics from the rest of the population and looked at all sorts of things such as what proportion give to non-profits, how much they give, the causes they support, etc.  What we found is that people who consider themselves to be Catholic show almost no differences from the rest of the population on charitable behaviors.

However, we also found that people who actively attend a Catholic parish are quite different from those who call themselves Catholic but don’t regularly attend Mass – active Catholics are far more generous, give to more organizations and a wider variety of causes, give away a much higher proportion of their income, volunteer more, and are more charitable in a variety of ways than are inactive Catholics.

So the question is:  are you Catholic if you call yourself Catholic, or are you Catholic if you are actively involved in your faith?  This is not just an academic question.  Think about how many times you’ve heard that Catholics will be the swing vote in a particular election – who are they really talking about?

Similarly, there’s a lot of research out there about evangelical Christians.  Much of it is contradictory.  Part of the problem is that there are different organizations defining this group in different ways.  The Barna Group says evangelicals amount to about 7% of the US population.  Baylor University figures it’s closer to one out of every four Americans.  Pew Foundation says it’s closer to one-third (although two different arms of Pew define “evangelical” in two entirely different ways, further adding to the confusion).    There’s a pretty big difference between 34% and 7%, and the definitions that would create each figure.  (For more detail on this topic:  click here.)

Is someone Republican because she voted for McCain in the last election?  Because that’s what she calls herself?  Because that’s how she’s registered?

Is someone a “customer” because he bought from you once a few years ago?  Because he expressed interest in a product?  Because he’s a repeat buyer?  Is he a “lapsed customer” because he hasn’t purchased from you in six months?  Twelve months?  Two years?

There’s no blanket answer to what defines a Catholic, or a liberal, or most other subgroups.  But I frequently see situations where a client raises doubts about a study because the findings contradict other studies – only to find out that one study of “Hispanics” was among English-speaking people with a Hispanic surname in major Hispanic markets, while the other study of “Hispanics” was among self-identified Hispanics nationwide, conducted in Spanish and English.  Because both studies are among “Hispanics,” there is too often an expectation that the data will match.  Big surprise when it doesn’t.

Someone once said, “Going to church doesn’t make you a Christian any more than standing in a garage makes you a car.”  The same might also be said about voting for Obama and being a liberal, or buying a sample product and being a customer.

Labels are easy and definitions are challenging – but going simply by labels without a complete understanding of the definition is the surest path to confusion and wrong assumptions.