Fast forward to the third decade of the century, campaigns rooted in proper customer segmentation no longer knock our socks off. They’re nothing short of a necessity for any B2B or B2C company that wants to stay relevant.
The real question that stands for businesses, however, is how to choose from all the customer segmentation models we can read about online.
- What kind of data do they incorporate, and which model will work best for you?
- Can you run with an out-of-the-box solution?
- Is it worth working on a tailor-made one?
To help you find the answer to this question, we’ve put together a list of 5 common customer segmentation models, along with examples of what they can bring into your business.
We also shed light on the types of data and criteria that are used to create effective segmentation models.
We’re confident that by the end of this post you’ll know which direction is worth pursuing.
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Ready? Let’s get to it then!
Customer Segmentation – Types of Data
In the most simple terms, customer data can be divided into two groups – basic and question-based.
These types of data are exactly what they’re called – basic. Which doesn’t mean that they’re not important for establishing precise user segments?
In fact, most businesses that sell online track these data one way or another, regardless of whether they have an actual customer segmentation strategy in place.
These customer data types can be categorized as:
Demographic – a broad group that includes gender, ethnicity, age, and religion. We discuss the potential of these criteria further on in the post.
Geographic – ex. country of residence, timezone, and language used.
History of purchase – ex. returning vs new customers, frequency of purchase.
Behavioral – ex. how often the user logs in, how he/she uses the product, price sensitivity, spending pattern (for B2B businesses – renewal periods).
Psychographic – examples include attitudes, personality, and beliefs. We’ll pay more attention to these traits as we discuss customer segmentation models below.
Business lifecycle – if you’re selling to a business, how big the company is (startup, SMB, enterprise). This information can complement demographic data on your customers.
As mentioned above, you can find such information in your CRM, data enrichment, and analytics tools – but only to a certain degree.
If any of the above criteria are important for your business, it’s highly advised that you also dig a little deeper and run surveys among your customers.
This leads us to the second customer segmentation data group…
Answers to Precise Questions
These are the types of information you’ll have to be a bit more proactive about getting.
Once you do, you’ll see it was well worth the effort!
Running surveys among your customers mean you get to learn about what they actually think – not just do. Once you know all this, you can validate the assumptions you’ve made based on your CRM or analytics data.
Sounds good, doesn’t it?
Here are a couple of examples of customer segmentation surveys:
Reason for purchase
Not all services or product motivations are self-explanatory (remember the juice squeezer?).
For example, in a piece we wrote on business strategy, we spoke to a server company that thought they were selling to B2B companies only. In reality, after they’d run a “why did you buy this product” survey, it turned out that they were also being used by a huge gamer community.
See how much this can influence your thinking of customer segmentation?
Right next to purchase reasons, you can also collect data on how a product is used – especially if there are multiple options.
You can ask customers about their goals or if there’s more than one person using the product. Such data can trigger you to create a separate onboarding sequence for each use case scenario.
Reason for cart abandonment
Nothing frustrates a business like a cart that hasn’t been finalized, right? Plus, there’s only so much you can learn about those who haven’t completed their purchase from session recordings or an analytics tool.
One of Survicate’s customers, brand design company Looka, noted a 2400% rise in ROI after using a cart abandonment survey to segment and address their would-be customers’ concerns.
Sounds intriguing? You can read more about this customer segmentation strategy in our Looka case study.
How customers found you
If you ever thought the “how did you hear about us?” question is redundant, think again.
Knowing where one first learned about you means knowing what they expect from a brand like yours. If you’re a fitness club and got a couple of new signups from a pro-weightlifters’ competition, you won’t make them fall in love with your brand by onboarding them with content for fitness newbies.
Now that we’ve given you an overview of the various data types, it’s time to see how they are combined and applied in popular customer segmentation models.
5 Customer Segmentation Models and When to Use Them
In this model, you focus primarily on your customers’ demographics, which means that your CRM or Google Analytics data won’t be enough.
You’ll need to supplement the basic information you can find in these tools by running a demographic survey.
Depending on your niche, you can ask your customers about their marital status, income, ethnicity, or whether there are children in the household.
This type of segmentation can be used in countless ways – customers can be segmented into parents and singles, those who are willing to pay more for quality vs those who value a good bargain, etc.
Not to mention the options beauty brands have if they know a customer’s eye color and complexion!
Some companies benefit from segmenting customers based on a set of personality traits and attitudes that they represent. This helps them build accurate user personas that match specific lifestyles.
To create an effective psychographic-based customer segmentation model, you need to survey your customers.
Plain and simple, there’s no other way around it!
Specifically, you should focus on surveys that ask customers to evaluate a statement on a scale from ‘highly agree’ to ‘highly disagree’.
The psychographic model will let you adjust your brand’s tone of voice and offer per user segment.
Learning about a customer’s stance on veganism, the role of physical activity in their lives, or political preferences.
This one circle around three metrics (Recency, Frequency, Monetary [RFM]):
- When a customer last purchased;
- How many times he/she has bought so far;
- How much he/she has spent with your company.
This model helps identify your High-Value Customers (HVCs) (now, who wouldn’t want that?!).
When you define your ideal customer’s profile, you can focus your marketing and sales efforts on the segments that bring in more recurring revenue.
In this model, you use a mix of data – behavioral and psychographic from your CRM, analytics tool, and survey results.
You derive behavioral data on when customers purchase from you or take an action (think: logging into their accounts, adding an item to their cart, etc.).
Simultaneously, you run surveys among customers to make sure their goals or lifestyle haven’t changed in a way that could affect your business.
For example, let’s assume you’re an online grocery store.
If your customers are embracing a more eco-friendly life or ditching their sugar addiction, moving them to a new customer segment can make them appreciate your brand’s adaptability to their needs.
Last, but not least…
Similar to the customer goal-oriented model, this model helps you predict when and what your customers might purchase based on their previous orders.
You can divide your customers into those who engage with your brand and those who stopped coming back.
These segments are called active and lapsed customers.
What does this give you?
Most importantly, the opportunity to further strengthen customer loyalty or run a user activation campaign among idle customers.
Such a model also lets you create separate segments for new customers who need a helping hand in understanding your services vs those who are well accustomed to your brand.
There’s no one-size-fits-all customer segmentation model that can be used across all industries. However, regardless of the model you find most fitting for your business, we recommend that you use as many data points as possible to truly know your audience.
Firstly, make sure to analyze your sales and behavioral data diligently. Secondly, nothing is ever set in stone. You must be inquisitive and run customer surveys on an ongoing basis.
Only then can you create an effective customer segmentation strategy and come close to your customers to provide them with the solutions they need.
Good luck & Have fun!