The definition of customer segmentation
Customer segmentation is a marketing technique that involves grouping customers into segments that have certain variables in common. Analyzing segmented customer data generates quality insights that can be further used for advanced personalized targeting, leading to an increase in conversions, revenue, customer retention, and other important indicators.
Segmentation allows you to look at the relevant segments in your customer base and get actionable information that you can use in your marketing campaigns. The end goal of effective segmentation is making the most out of every dollar you spend, by optimizing your marketing messaging.
Think about it: the human mind is wired to better process information by classifying it. So it should be no wonder that well designed, relevant, and reliable segments can definitely increase the quality of your decision making process in a business.
Why should you segment your customers?
If you’re wondering why you should segment your customers, the answer is simple. By not looking into segmented data about your customers, you’re missing out on a goldmine of conversions and revenue opportunities from your target market and beyond.
I’ll explain briefly the importance of customer segmentation and why you should start treating your customers differently in all the possible marketing touchpoints.
First of all, segmentation helps you find out who your customers are, and the most relevant types of customers. You’ll get to compare segments between one another and see where most of your sales are coming from. This will make it easier for you to dig into each segment more and create customers personas based on the statistics that you have.
Then, having the right segments and personas defined helps you speak their language. This way your marketing messages will be much more persuasive.
Let’s say that one of your personas for your natural therapy products is the 50+ lady living in the countryside who believes in natural cures. You’ll target her with a different message and on a different channel than the ones you’ll use to reach a young mother living in the big city. Different lifestyles, different habits, different channels and messages.
Also, proper segmentation gives you a lot of room for personalization. Using the right tools, you can personalize the offers, the messages, the ads, the landing pages, and so on.
In the end, all these steps will lead to more conversions, more revenue and a better retention rate. Plus, they can even contribute to an improved customer satisfaction rate. When you show your customers that you care about their specific case, they’re much more likely to return and become loyal.
Segmentation is used in B2B just as it is in B2C. The main differences are the variables you’ll consider when creating the categories you want to reach.
For example, B2B customer segmentation usually takes into consideration job titles.
In this case, if you sell software, you will draft your segments based on the job description – CTO, IT Managers or Tech leads could be some of your segments. To further refine them, you can give a score to each job title according to the decision making power that each segment has. So you know who you should try to reach prioritarily.
When you’re targeting businesses, your segments will take into consideration the size of the business, the estimated or reported yearly turnover, the business location, or even how the decision-making process happens.
But it’s not just about the Whats and the Whos. The timing is also important. For example, some companies have a limited timeframe for contracting new services.
In this case, you can segment the businesses you want to target based on how often you have a selling opportunity window with them, such as at the beginning of each business quarter or year.
Benefits of B2C customer segmentation
If we look at B2C businesses, the main benefit of customer segmentation is knowing the people that keep your business alive. Once you know specific information about each segment, you’ll not only know their habits, but you’ll be able to predict their needs and expectations, leading to a more coherent market management, as well as optimized acquisition.
When you have your main segments in place, you will also reduce your wasted advertising money. You’ll be able to adjust ad spend based on what you know about your relevant segments, their LTV, and maximize the ROI of your performance campaigns.
Another great benefit of customer segmentation is being able to personalize the way you address them. You’ll not only get a better chance of conversions and more revenue, but this might also have a positive impact on the way they perceive your brand and business.
Speaking the same language as your customers will make you less of a talking head type of brand, and more of a friendly voice.
Besides, analyzing qualitative data from your customer segments can result in essential insights regarding what they need, expect, how likely they are to be retained, whether your products, website, or purchasing process has any flaws you don’t know about, and much more.
Types of segmentation variables
Segmentation variables fall into a few big categories, and they include demographic, geographic, psychographic and behavioral data.
- Demographic segmentation is based on variables such as gender, age, marital status, education, occupation, income, family size etc. Based on demographic data that you have about your customers you’ll be able to target them with different products and offers based on their gender and age. This type of segmentation is essential in fashion, cosmetics, and even electronics because the needs and preferences of your customers can be very different according to their age and gender.
Most e-commerce analytics tools have predefined reports for these segments. But you can take things up a notch by creating custom reports that are even more relevant to your business. Such a custom report based on demographic data can be something like “women between 30-40 with a high income”.
- Geographic segmentation is simply looking at clusters based on where your customers are located: urban vs rural, specific cities, cities grouped by the number of inhabitants, international customers, and so on.
This can help you refine even more your existing segments, turning the example above into two segments – “women between 30-40 with a high income, who live in cities with more than 300.000 inhabitants” and “women between 30-40 with a high income who live in cities with less than 3000.000 inhabitants”.
If you have an online business, based on geographical segmentation you’re able to display personalized testimonials. By showing visitors from a specific city or area the opinion of a current customer in their area you will increase their trust and likelihood to purchase from you.
- Psychographic segmentation looks at the lifestyle of your customers, their social class, and personality traits. An example of psychographic segmentation (that also has a demographic basis) are the generations known as millennials, boomers, or X, Y, Z. Usually, when we talk about these generations, the demographics matter less than the psychographics and behavioral aspects that they have in common.
Let’s say you sell electronics and you have a brand new device in your inventory. The first ones to break the news to are the customers in your “early adopters” segment, because they’re always searching for the newest products.
And lastly, behavioral segmentation is a way of segmenting your customers based on the way they use your product, how often they buy it, the reasons why they buy it, and the perceived value of your brand.
- Behavioral segmentation also sheds some light on your consumer segmentation, and the relation between your brand, product, or service and the people who actually use it, who can be different from those who make the purchase decision.
Based on their behavior, you could segment your e-commerce customers into clusters such as frequent buyers, heavy users, light users, occasional buyers and so on. This will help you create tailored offers for them, knowing how often or how much of your product they usually buy and use.
Types of data you should analyze in your marketing segmentation
One type of data you should look into in order to learn more about your customers and their needs is the quantitative data.
If you’re working for an e-commerce business you can start doing a thorough analysis of your Google Analytics account and identify some relevant segments.
You can start with basic demographic segmentation by age, gender, marital status, then geographical location, and then move to behavioral variables.
You can even create some custom segments based on other KPIs such as your business costs.
For example, if you offer free shipping, but it costs you more to ship in certain geographical areas, then you can group the customers and visitors in those areas in specific segments. After an analysis of their specific LTV, you can decide whether adding a shipping fee for some of your geographic segments is a good idea or not.
A smarter level of segmentation is based on intersecting various variables with the information you store about your visitors and customers and then generating a more complex segmentation analysis. For example, you can create a segment only with the visitors who have seen a certain campaign landing page or have reached the middle of the funnel but didn’t convert. This will help you target them accordingly to persuade them to take the next step.
The second type of data you can look into is qualitative data. You can gather this through customer surveys, by reading product or company reviews or even listening to call center recordings.
Qualitative data will take your insights to a more refined level. In most cases, they’re a great source of information based on meeting customers’ expectations and the extent to which you are meeting those expectations.
Looking into qualitative data can tell you whether a specific segment considers your product too expensive, or have a specific need that your product solves, maybe different from what you’re advertising now.
It’s safe to say that analyzing qualitative data is an effective way of measuring customer success and can impact not just your marketing segmentation, but your entire business strategy.
Segmentation methods and strategies
Now that you’ve defined your potential segments based on demographic, geographic, behavioral, and psychographic aspects, you can build your customer segmentation strategy.
Proper customer segmentation starts with deciding on the data points that you want to collect and how you will collect it. This is based on the primary segments that you’ll want to have. Also, this first step will make it easier for you to choose the most relevant option out of all the potential segmentation models you could work with.
Then, the next step is the actual gathering data. The more data, the more types of data and the more sources you have, is usually the better. Just start with what you have, and try to identify potential new ways and tools for segmentation as you get more experienced at this.
After you’ve collected sufficient data, you will start defining clearer segments, and even more advanced ones. The trick here is to focus on segment relevance. This can be determined based on segment size and value.
Looking at segment size will help you find and analyze information such as where most of your customers live, to notice trends, or whether the marketing campaigns in the past have had any impact in the segments they were targeting.
Segment value will tell you how much revenue your business is getting from a specific group of customers. Don’t be surprised if you see that the biggest segment doesn’t also have the biggest value.
Based on segment size and value, you’ll be able to prioritize your resources in your next marketing campaigns.
The final step of your customer segmentation strategy, after looking into the numbers, is taking marketing and business decisions based on the insights you have.
Thanks to the segmentation model above, you’ll be able to optimize your marketing strategy and improve customer retention.
Examples of customer segments
Understanding and using the variables in the customer segments can help you create customer profiles or personas.
Depending on the segmentation research you’ve done and the variables you decide to use, you can get a specific type of customer segmentation that is most relevant to your business.
For example, based on their behavior and your relation with them, you can create segments such as “deal hunters” – groups of customers who shop only on sales (so they have a relatively low frequency), but if you notice repeated purchases, you can assume that they are loyal deal hunters.
For such a segment, you could run specific offers through a dedicated newsletter or ads, to make them come back more often instead of waiting for the sales periods.
Also, from a demographic point of view, you can filter things even more and see where most of the deal hunters come from – are they in the same city? Rural vs urban? Are they men or are they mostly women? You can get a lot of insights for a more personalized approach, increasing your chances to reach them with a message that they resonate with and getting more conversions.
Timing is also important, just like in B2B targeting. Let’s say that you have a baby food e-commerce. You can have a segment of mothers who gave birth very recently and you’ll know what their needs are: the smallest size of diapers and clothes, maybe very soft toys. But after a few months, the mothers in this segment will have different needs for their children: toys for the teething period, solid baby food appropriate for diversification, and so on.
Knowing all these variables will allow you to personalize your messages across channels, reach the customers where they are, and make it easy for them to find and order what they need.
A type of segmentation worth doing by any business is one based on the Recency, Frequency, and Monetary Value of its customers.
We’ve talked before about RFM and why it’s important to group your customers based on how recently their last order is, how frequently they order, and how much they spend.
By analyzing your customers based on the RFM model, you could realize who are the 20% of the customers who bring you 80% of the revenue are.
Once you know what your VIP segment looks like (the segmentation according to the monetary value), you can address those customers differently, maybe more personalized, or with tailored offers.
Then, you can go and look for other defining characteristics of the VIP customers. You’ll be able to use those traits to draft an extended audience that fits the profile, and that you can target in order to expand the pool of top revenue customers.
Don’t overcomplicate your segments
As you start experimenting and creating your first customer segments, you might find yourself attracted by the idea of cross-checking different variables and hypotheses and creating an enormous number of potential groups.
However, creating segments that are too narrow or simply provide information that you can’t use is just a waste of resources.
Be creative, but don’t force it. Just focus on what actionable and impactful insights that you can get from a segment that is big enough to matter. Effective data management is an important aspect to keep in mind when you start segmenting your customer information. Otherwise, you’ll just end up with reports crowded with small irrelevant segments, and your actions won’t have a real impact.