In the last few months, especially after the events that occurred in Charlottesville, VA, pundits have discussed the topic of “political segmentation” on most of the cable news channels. Regardless of one’s political views, the 2016 Presidential election cycle did focus on multiple population segments and their preponderance to support various candidates. From the outset, the votes of white working class vs. black vs. Hispanic vs. female vs. LGBTQ segments were analyzed and election outcomes were predicted based upon how various analysts believed these individuals were going to vote.
In the end, they were basically wrong. Donald Trump won the election despite predictions that Hillary Clinton would win by a landslide. People didn’t necessarily vote as predicted and the various market analysts, instead of figuring out what went wrong (obviously it was their survey methodology), are still segmenting individuals and applying those beliefs to various groups. That’s why we hear outrageous statements from multiple networks, pundits and others such as “Antifa represents the Democratic party” to “Anyone who voted for Donald Trump is racist”.
Market segmentation was originally developed for marketing. The goal was to determine how companies could tailor messaging and products to specific groups. Market segmentation has never been meant to discriminate. It merely identifies traits by groups….and sometimes those groups are easier to identify in demographic terms such as age, race, gender and others. But, as those of you who use market research know, sometimes those factors are irrelevant. It may be personality characteristics that define whether someone uses your product or not. Or other more general traits - someone with dry skin, for example, could fall within any age group, and could cross gender and races.
That being said, sometimes simple demographics help in marketing. Who could argue that Millennials are probably more technologically proficient than individuals who fall within the WWII demographic? Of course there will be exceptions, but sometimes it’s ok to make some assumptions. But it gets tricky when you apply some traits to specific groups, and the risk is that we negatively condone others by making generalities.
Here are some tricky examples from my market research background. Several years ago we did some research and segmented by religious affiliation. We found that Jewish households were better savers than those in other religions. We found that Catholics were more likely to be small business owners. Now, were those findings discriminatory? Did they promote stereotypes of various religions? Yes and no. Financial beliefs and habits are cultural. Some families pass along various beliefs differently than others. Thus, these findings actually provided important findings on how some households could learn from others.
My second example has to do with another tricky segmentation. We analyzed financial habits, investment knowledge and portfolios by ethnicity. We found that some ethnicities preferred online investing rather than meeting face-to-face with an advisor. We also found that others professed less overall knowledge about investments than others. Is this research racist? Not at all. It helps financial providers located in various communities to focus on products and services that might be attractive to their customer base.
Since the early part of this century the concept of the “Market of Me” has been promoted. Each person, regardless of their age, gender, work status or other demographic will have values based on their own needs. While gender, age, occupation, religion and other demographic factors may apply to a person – each person is made up of multiple demographic factors. Market segmentation, especially demographic segmentation, just helps marketers try to focus on larger groups that sometimes think similarly. It has nothing to do with racism, discrimination, or other ugly concepts.
Spectrem is developing some dashboards that will allow you to apply multiple filters on groups and discover core values and investment intentions. For example, if you are meeting with a Hispanic household with more than $100,000 of net worth, over the age of 50 you can identify how they might want to invest. This tool would allow you to be prepared somewhat….you might note that these households prefer annuities, and don’t like to be involved in the investing process. Of course, your individual client may not fit the parameters….but the tool is a good place to start.
Segmentation needs to be used to understand cultures and behaviors, but not to discriminate against them. Most marketers know how to effectively use demographic segmentation. They also understand that sometimes other behavioral segmentation is more important.
So let’s stop making huge generalizations based on factors that don’t apply to everyone in a segment. Not all of those who voted for Hillary Clinton wear black masks and carry clubs to a riot, and not all Donald Trump voters are racist. (They may all, however, like red ball caps that say MAGA…..just kidding….)