By DataKnow Editorial team
Surely you’ve heard the phrase “divide and conquer” from Julius Caesar. Caesar was probably referring to political or military matters, but none of us are going to war—at least, I hope not. Even so, the phrase makes a lot of sense: divide what you want to do into smaller, more manageable parts. For example, a pizza is hard to eat if you don’t slice it. The same principle applies to work; if you’re overwhelmed, you can divide your tasks to manage everything without going crazy.
As we can see, the tip Julius Caesar gave us hundreds of years ago remains as relevant today as the day it was uttered. We’ve applied it in countless ways, but today we’re not here to talk about Caesar or phrases. The topic of the day is customer segmentation.
What is customer segmentation, and what is it for?
It follows the same principle of “dividing to conquer,” but in a more complex version applied to businesses. Simply put, customer segmentation—or, in some cases, “marketing segmentation”—is used to categorize your customers into groups that share similar characteristics.
Recycling the pizza example (because recycling is important), let’s imagine you have a pizzeria with two types of customers: the first group prefers traditional pizza—they like simple things and aren’t very adventurous. On the other hand, there’s a second group that’s hard to please; they’ll order pineapple pizza and might even ask for it with chocolate and gummies (very odd, if you ask me).
Knowing and segmenting your clientele is fundamental and likely one of the first steps you should take when you start attracting customers.
Customer segmentation not only allows you to offer the right product to each group, but it also helps you communicate better with them and focus on those who are most beneficial to your business. For instance, if your pizzeria isn’t the type to add a family-size chocolate-and-pineapple pizza to the menu, you might decide to focus on the first group instead.
Machine learning for customer segmentation
I have good news and bad news. The bad news is that the examples I’ve used so far are overly simplistic to explain the concept in an easy-to-understand way, but reality is much more complex. Customers and industries today are incredibly sophisticated and demanding.
Specifically, customers have become more complex and harder to categorize. Unless you have a very small business or a specific niche, it’s unlikely you’ll have a simple A Group and B Group scenario to base your marketing strategy on (if you even have one). You’ll probably have Groups A, B, C, D, E, and so on through Z. Collecting and processing data for each group is nearly impossible for a human who relies on common sense to identify patterns and shared characteristics among customers and then group them.
The good news is that technology is here to save the day. Clustering is a machine learning technique. One of the best-known clustering methods is K-Means because it’s easy to teach, learn, and apply. With these tools at your disposal, you no longer need to overwork your data analyst to process and group the massive amounts of data you might receive.
Data is key
We can’t say it enough: without data, we’re going nowhere. These are the most commonly used data types for customer segmentation:
Geographic location
Country, population density, and climate.
Demographics
Age, gender, marital status, education level, ethnicity, and family group.
Behavior
Pages viewed, product benefits sought, product attributes, etc.
Lifestyle
Hobbies, social values, cultural practices, and communities.
Identifying your best customer
Once your algorithm is running and segmenting customers, you’ll be able to identify your dream customers. Here’s a list of traits that can help you spot them:
- Frequent buyers
- High purchase values
- Customers with few or no returns
- Take the time to leave reviews (more data)
- Actively respond to offers
Focusing on the wrong customers won’t just waste money on poorly targeted marketing campaigns; it also increases the logistical costs of your value chain. Effective customer segmentation helps you implement the right marketing strategy, avoid the headache of losing money unnecessarily, and guide customers through the entire marketing funnel to retain them—and that sounds pretty great.
