Editor’s note: This is part two of a series, Understanding Our Audiences, intended for anyone who does planning in the interpretive or visitor experience sectors. You can find the first instalment here.
It all sounds like marketing-speak. In fact, it’s pure old-school interpretation.
Market segmentation is based on the idea that your behaviour and your tastes are predicted, to some extent, by your life stage (age, family and marital status), your education, income, geography, and your values. And as much as we might hate to admit it, most of us behave true to type much of the time. Are you a twenty-something single urban cultural explorer? Are you part of a conservative rural family who seeks familiarity when you travel? Are you a facilitator, hoping to create a great experience for your visiting friends and relatives? Each of us belongs to one or several “tribes”; each of us can be described as the sum of the demographic, psychographic (values-based) and geographic qualities that define us in relation to a potential visit to a heritage/nature attraction.
It sounds like marketing-speak. In fact, it’s pure old-school interpretation: it’s a way of knowing your audiences so you can better help them make those vital emotional and intellectual connections to your resource.
Segmentation, Profiling and the Role of Free Will
I once had a heated discussion with an individual who refused to believe that his behaviour could in any way be predicted by his age, gender, income or education. He found the idea viscerally abhorrent. (He was even less pleased to learn that his refusal to be categorized actually helped place him into a category. What a hipster.)
I think what was at the heart of his distaste was the feeling that market segmentation appears to negate the role of free will. Aren’t we all individuals? Don’t we each have full responsibility for our choices, the places we go, the things we buy?
Of course we do. Market segmentation acknowledges free will; there are very few of us who don’t have some control over our day to day choices. The point of segmentation is that we tend to exert our free will in ways that are statistically predictable; the choices we make tend to correlate strongly with our demography, age, education, gender and values.
More prickly is the issue of profiling. What happens when we segment our audiences by race or sexual orientation or age? Isn’t that profiling? In a sense, it is. We are predicting people’s behaviour based on their demographic, geographic and psychographic attributes. And this can be controversial, particularly when we do a bad job of it. Segmenting by race, for example, is generally not productive. People don’t behave racially, as a rule. People do, however, behave culturally; all of us are influenced by our cultural upbringing. People also behave socio-economically, for better or worse. Therefore, to identify a segment called “Asians” is a little ham-fisted. But it is reasonable to acknowledge that people of Asian background do break down into different segments—influenced by where they live, their language, their cultural origins, their family composition, their social values, their degree of acculturation, their media habits, their income—and that some of these groupings might be unique enough to merit their own market segment, if we want to do business with them. Likewise gay people: targeting “the gays” is a bit naive. But in some markets, gay people are a substantial clientele, and among the many sub-groups of gay people (as segmented by cultural background, life stage, income, education, et cetera) may be some distinct groups that you want to establish a relationship with.
At the same time we acknowledge that these people will naturally be part of other market segments—cyclists or young mothers, say—and their Asian-ness or gay-ness is irrelevant in these cases.
If the perception of profiling is a risk for your organization, there are ways to mitigate that risk. One of the most effective is to actively reach out to the communities in question and invite them to work with you in an advisory role. They can help you “truth” your data, flag any potential sensitivities, and give you further insight into their community’s preferences. In this way, rather than saying to the world, “We are targeting Asians/gays/seniors based on Big Data,” you are effectively saying “These communities are important to us. We are doing our homework to learn more about them, and our community advisory panel is helping us along the way.”
NEXT: OK, how do we divide up all these different kinds of people?
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