A Whole New World of Information: How Valuegraphics is Different from Traditional Age-Based Data and What That Means

For years, marketers wishing to build profiles of their potential audiences have focused their efforts on a narrow set of variables.

You probably have experience of this phenomenon. Someone accosts you on the street, or you receive a survey in the mail. The questions are usually mundane. They’re about your age, job, family income, and various products that you may or may not purchase.

If you bother to respond at all, you give the interviewer a few dozen data points that you know they will later feed into a computer in the hopes of learning how better to sell you stuff. Or you fill in the survey and send it off, vaguely hoping that you might win whatever prize is on offer.

Now, here’s an insight into Valuegraphics. Unlike linear surveys, Valuegraphics uses a vast range of questions, which adapt to users’ responses. In other words, your answer to one question may actually affect which question you’re shown next. Naturally, this is far too complex to manage using paper surveys, so people fill in Valuegraphics surveys online.

Each survey consists of as many as 340 questions. So far, more than 100,000 people in Canada and the USA, and a half-million people around the world, have responded to Valuegraphics surveys, and the number of respondents continues to grow.

Trying to describe exactly how we extract meaningful information from the Valuegraphics Database is very difficult, unless you have an advanced degree in sociology and understand things like continuous dimensions, cultural cognition, and something called fuzzy data.

Which I don’t. At least not very well. But I do understand bubble baths. And that might be the next best thing.

Imagine yourself sitting in a big, frothy bubble bath, like an ancient god looking out over the bubble-based world in front of you. Every bubble in the bathtub is a Valuegraphics data point, and you are looking to see the patterns, how the data tends to clump together and form peaks in some areas and disperses to form valleys in others.

There are short mountains and tall mountains. Some have a broad base, and others are more like spires. The valleys come in all shapes and sizes too. The more you look, the more you see infinite types of mountains, hills, valleys, and plains, all made up of bubbles.

We’re all unique, so even the bubbles come in various shapes and sizes, and each bubble represents a valuable piece of information. But we’re also all similar to other people in measurable ways, so the groups of bubbles point to places where a large number of people agree. The larger and more dense the conglomeration of data-bubbles, the higher the number of people who think similarly about a particular variable.

We could explore the significance of every single data point, but that would be time-consuming and not particularly useful. To make Valuegraphics easier to talk about, I decided to identify and focus on the top ten spires of data, what you might call the Himalayas of the bubble-bath landscape. I named each of these ten spires after the powerful variable at its core.

These ten variables attract data points like a magnet. The stronger the variable, the more data is drawn toward it, and the bigger the spire becomes. We call these ten biggest, most influential data spires the Valuegraphics Archetypes.

Each Valuegraphics Archetype refers to a recognizable type of person. When you read about them, you’ll probably nod your head and think “yeah, I know someone like that.” They’re not infallible, but they’re a much more meaningful way to categorize people than with the outdated variables of age, income, and occupation.

Valuegraphics Archetypes tell us much more about groups of people than age-based demographic stereotypes do, and enable us to shape the way we live, work, and sell according to values, not merely age.

For more information and advice on Valuegraphics Archetypes, you can find We Are All the Same Age Now on Amazon.