The end goals of segmentation is personalization. The idea is that you can better communicate with and serve people based on treating them like, you know, people.
Some common categories of segmentation are as follows:
In B2B you’ll also see “firmographic,” and if you Google around, you’ll see a lot of different frameworks for how to think about segmenting.
As a primer, the easiest way to automate list segmentation is based on behavior (user events) and depending on your email setup, geography (ip address = approx. location).
Geography is good to pay attention to for brick and mortar chains, but for our purposes, we can ignore it.
Demography is concerned with the study of populations, typically using statistics. When marketers talk about demographics, they’re referring to things like age, gender, marital status, income, or education level.
Behavioral segmentation is concerned with user behaviors. If someone makes a purchase, you can tag them as a buyer. If they comment frequently on your blog, you can tag them as highly engaged.
Psychographics is (in my opinion) the most powerful way to segment your list. Psychographics is concerned with understanding what people are thinking.
Here’s the cool part: we can use behavior to unlock psychographics.
Geographic and demographic vs behaviorally inferred psychographics
AKA invading someone’s privacy vs. being cool and helpful
Mailchimp found that most people with email lists were segmenting based on demographics. They also found that that was a less effective way to go about personalization based on results.
Go figure. Knowing that someone is a young Jewish female from New York or an older black man from Alabama is not going to help you better communicate and sell that person.
If you want to stereotype your users and introduce a bunch of bias into how you think about your list makeup, focus on location and demographics.
But if you want to be cool because you’re a thought leader cultivating expertise, authority, and trust with a growing base, you’re much more concerned with your users’ needs. So let’s move on to the better way.
Segmenting by mindsets
The American Press Institute did a bunch of research to understand the mindsets behind users who purchase online subscriptions and found:
[…] there is not one revenue strategy or funnel that can apply to an entire audience. Further, segmenting news subscribers by mindsets [is] a considerably different way of thinking about acquisition and monetization […][There are] distinctly different mindsets about paying for news and information.American Press Institute, 2017
It might seem obvious, but in a lot of industries doing the deep work to recognize that people buy for different reasons and figure out what those reasons are is new territory.
Let’s dive into an example of how some really simple behaviorally inferred psychographic segmentation can be super powerful.
Pretend you’re the god of habits
Let’s say you’re James Clear (get. his. book.). A user, let’s call her Sarah, lands on a post on your site called, “Motivation: The Scientific Guide on How to Get and Stay Motivated,” from the Google and signs up for your newsletter.
We know what page she signed up on and can therefore tag her with “motivation.” We are now already 1000% ahead of where we were and here’s how:
Without even looking at what that page ranks for in Google, you know that Sarah is likely looking for motivation.
As a pro tip, we can take that a step further and look at what kinds of phrases a landing page is ranking for in Google to get a better idea of what searchers are thinking about and looking for when they get to that page.
But even just with the information that Sarah landed on the motivation post, I can think of multiple ways to more effectively communicate what content, products, and messaging on jamesclear.com would be most helpful to her, as well as the army of subscribers that come after her on a journey to improve their motivation.
What’s the lesson?
We could combine location and predicted demographics to pretty accurately discern that Sarah is a Millenial Jewish girl in the Big Apple. We could even pay pennies per email for email intelligence data scraped together by a big data broker and find out a bunch of invasive stuff about her.
Or we can simply pay attention to how she found the page she signed up on to get some context on where she’s coming from.
In terms of serving Sarah, what’s more useful? What data would you feel better about having?
Next, we’ll talk about some ways we can leverage insights from what I call these types of “mindset segments,” for better personalization.