Organ Donation, Hickam’s Dictum, and the Power of Psychographic Data in Market Segmentation
In 2008, Duke University behavioral economist Dan Ariely gave a great TED Talk that explored the unpredictability and irrationality of consumer decision making. It’s a fascinating look into why we make the decisions we do and what those decisions are actually influenced by (Hint: It’s rarely self-will). If you’re struggling to understand why your emails, social ads, or other marketing campaigns aren’t converting, it’s worth watching the full talk.
That said, I’ve always been drawn to one anecdote from the presentation.
Around the 5-minute mark, Ariely shares a chart that shows organ donor program participation across a number of European countries. Here’s a screenshot:
What’s interesting about those numbers is the discrepancy of participation among countries that are demographically and geographically similar. For example, Germany and Austria, which are very similar in terms of ethnics, geographics, GDP per capita, and net disposable income per capita, vary widely in organ donor program participation — 12% for Germany versus 100% for Austria.
So, what gives?
As Ariely explains in his talk, the variance can actually be boiled down to a surprisingly simple factor: Germany includes a field on its DMV form that asks drivers to check a box if they want to participate in the organ donor program (opt-in), while Austria asks drivers to check a box if they don’t want to enroll in the program (opt-out). In both countries, the majority of people choose not to check the box at all because, as Ariely posits, it’s the easier decision to make — even if the decision leads to two very different outcomes.
What Organ Donation Has to Do With Email Segmentation
Welcome to consumer psychology and, more specifically, psychographics.
While demographic and geographic data would predict that the countries above should behave somewhat similarly, psychographics tell a different story — a story that can be influenced by something as binary as the language used in a box on a DMV form. This psychology-driven data digs into our subjective motivations, interests, and values, all of which tell marketers quite a bit about how and why we make decisions.
Now, it’s worth pointing out there were probably numerous other factors that influenced those countries’ donor program participation rates. But the anecdote from Ariely’s talk serves as an important lesson for ecommerce marketers. Most notably, while demographic data can be useful as a broad segmentation tool, it very rarely tells us everything we need to know about what inspires people to take action. Psychographic data can fill in some of those gaps.
Consider this scenario.
You run an ecommerce shop that sells men’s fitness apparel and accessories. It’s July and you’re running a sale, so you create a segment of 30-something men on the East Coast with household incomes of more than $150,000 who have gym memberships. Pretty specific, right?
Sure. But what if you could take that segment a few steps further by looping in psychographic data? Doing this might yield a customer segment that looks like this.
Self-employed, 30-something men who:
- Run 3-4 times a week
- Read and share articles about the latest fitness gear
- Don’t have kids (and don’t appear to want them)
- Are currently training for a marathon
- Only buy fitness clothing from brands that are perceived as “premium”
Of those two segments, which do you think would give you a better chance to create highly personalized marketing campaigns that drive higher conversion rates?
How to Use Psychographic Data to Create More Dynamic Segments
This isn’t to say that demographic and geographic data are relics of marketing’s past that must be banished for their vagueness. It’s still helpful to know that a particular customer is a married woman living in Berkeley, California, who also happens to be a lawyer. That information gives you a great starting point that can only be deepened by psychographic data.
The chart below (which I found in a great post on Neil Patel’s Crazy Egg blog), does an excellent job of showing how psychographics fit into broader market segmentation.
Now, here’s the million dollar question: How do you go about acquiring and applying psychographic information?
It’s not easy, but it’s also not as difficult as many marketers make it seem. Here are two easy places to start.
1. Broaden the questions you ask on a survey, quiz, review, or registration.
Surveys, quizzes, reviews, and profile registration aren’t new tactics for gathering information, but few marketers incorporate psychographics into them.
The good news: Doing this is relatively simple. If you run a fashion ecommerce store and a customer initiates the process of creating an account, you might throw in a few questions that ask the customer to list some of their favorite activities or interests. If you’re feeling really brave, you might even ask for their opinion on various social or political issues (be careful here).
Do they love to travel and cook, and consider themselves wine connoisseurs? If so, you might create custom promotions and offers that tap into their wanderlust, or forge partnerships with other brands that share those values. The goal here is to gain a deeper understanding of what makes your customers tick. What do they value? How do they think? What motivates them to take action?
2. Tap into social profile data to uncover key information about attitudes, personality, and values.
Mashable covered this one pretty well way back in 2011, but it’s even more relevant today as more and more people have grown comfortable with sharing information about themselves on social networks. Is someone married? Do they have kids? Where did they go to college? What are their favorite books, TV shows, and movies? What languages do they speak?
On their own, these data points may seem too subjective. But when they’re blended with the the more objective demographic and behavioral data you’re already collecting, they can reveal critical insight that allows you to more deeply understand and personalize each person’s experience.
For example, you might find that 30-something men who live in the Midwest and have kids in elementary school are more likely to care about education, support social businesses, and play golf (guilty). Having that information would undoubtedly help you refine your customer segments and deliver more relevant messaging. There are a number of social login tools you can use to pull this data and many of them integrate directly with sales and marketing platforms.
Occam’s Razor vs. Hickam’s Dictum
As a consumer, I’ll fully admit that some of this stuff creeps me out. But it’s the world we live in and, frankly, if it means that I’ll stop seeing Facebook ads about women’s lingerie because I once googled “best Valentine’s Day presents for my wife,” then sign me up.
Truth is, none of us are as generic or predictable as traditional segmentation would have you believe. We’re all unique. We have different opinions and values. And we’re all influenced and motivated by different things. Our age, income level, and geographics all say something about us, but that data doesn’t come close to telling our full story.
Which brings me to a final — and admittedly odd — metaphor.
In medicine, there are two conflicting theories about diagnosis. One — Occam’s Razor — suggests doctors should look for the fewest possible causes that account for all of a patient’s symptoms. The other — Hickam’s Dictum — argues that multiple symptoms can’t always be boiled down to one simple diagnosis. To quote the theory’s creator, Dr. John B. Hickam: “Patients can have as many diseases as they damn well please.”
As a marketer, I tend to subscribe to Hickam’s Dictum. In marketing parlance, consumers can have as many interests, opinions, and values as they damn well please.
Just because my wife is a 30-something mother of twin girls doesn’t mean she’s defined by her motherhood. It says a little bit about what she cares about and how she makes decisions, but it doesn’t mean she thinks and acts like all 30-something mothers of twin girls. As such, categorizing her only by that attribute — or, even worse, assuming that her interests and values are generally the same as all 30-something moms — is the quickest path to being ignored.
So, here’s my advice: Stop trying to be Occam’s Razor.
Instead, dig a little deeper. Try to understand more about who your customers are and what they’re influenced by. Collect and aggregate that information. Analyze it. And then use that insight to deliver messaging, content, emails, and ads that push us toward the destination we all want to reach: Truly personalized 1:1 customer experiences.
(Note: Thanks to the podcast Reply All for the Occam’s Razor/Hickam’s Dictum metaphor. If you’re looking for something to kill time during your commute, I highly recommend checking it out.)