Customer segmentation is the process of categorizing your customers based on shared characteristics like age, behaviors, spending habits, and preferences. Then, through customer segmentation analysis, you can learn more about your customers and tailor your campaigns, offers, and products to their specific desires and needs.
The more you understand your customers, the better you can sell to them and the more successful your business will be. Segmenting customers allows you to visualize major differences between different categories of customers, then finetune your marketing efforts to the behaviors of these various groups.
So what is customer segmentation? Put simply, it’s grouping your customers based on similarities that help you market to them effectively.
It might look like categorizing your audience by factors such as:
…and many more! Scroll down to the section on types of customer segmentation for additional details.
Once you’ve identified your customer segments, you can dig deep into the analysis of how these groups behave and why, with answers to the following questions, according to the National Institutes of Health Office of Management:
The next step of the customer segmentation process is creating hypotheses around why you observe these trends. This can help your campaigns evolve to more effectively target the right customers.
This customer segmentation definition is similar to but distinct from marketing segmentation. Marketing segmentation is a similar process of dividing consumers into segments. But it involves looking at everyone in a target audience or market. Customer segmentation deals solely with your brand’s existing customer base.
Customer segmentation is important because it improves your bottom line by increasing key marketing metrics like customer engagement and conversion rate.
Here are some of the benefits of customer segmentation that help you get there:
But consumer segmentation isn’t just about grouping your customers by their ages and hometowns. There are a number of different types of customer segmentation you can use, depending on your industry, the size of your business, and the data you have available. These are also sometimes called customer segmentation models.
Demographic segmentation is likely the type of segmentation that’s familiar to most people. It involves grouping customers by demographic characteristics such as:
For example, if you run a catering business and you segment your customers by families with school-age children, you can craft tailored marketing campaigns about graduation parties to send to this segment.
As the name implies, this type of customer segmentation involves grouping your customers by their physical location. This can be at any number of levels, such as:
For example, you might send push notifications with a limited-time offer to a segment of your app users currently located near your brick-and-mortar location.
Behavioral segmentation is a little more nuanced: Instead of segmenting customers by tangible facts about who they are and where they come from, this model groups them by their past interactions with your online brand, such as:
This might look like segmenting your users into those who have previously made purchases on certain days of the week and timing your marketing sends to them accordingly.
This approach groups customers by characteristics that are closer to personality traits, such as:
If you run an online apparel business, you might segment your customers by activity and send running-specific messaging to the runners and hiking-specific messaging to the outdoorsy shoppers, for example.
Then, there’s segmentation based on the technology your customers use. This segmentation strategy looks at how much a customer uses different:
To put it into practice, you might segment your customers by social media use and capitalize on trending topics in your messaging to those users on their preferred platforms.
RFM segmentation groups customers based on three vectors of their past purchasing behaviors: recency, frequency, and monetary value. Customers are ranked based on each of these three vectors and then divided into groups based on their scores. The groups might include new customers, high-risk customers, high-value customers, and low-value customers, for example.
While less commonly used than the tactics above, needs-based segmentation is still a valid approach. As the name implies, it involves grouping customers by their needs, such as:
You might discover a segment of your customers is turned off by your customer service chatbot and instead needs to be able to reach a representative over the phone before making a purchase. Clearly communicate the hours when someone will be available to this segment. Delivering compelling creative and successful solutions targeted to a segment’s needs builds trust, loyalty, and retention.
Using customer journey analytics, you can segment your users by their value to your business. Then, you can allocate more resources to the segments that generate the highest lifetime value, which can help you cut down on costs and increase efficiency.
This might look like offering special promotions only to your highest-value customers to encourage repeat purchases.
Before you can capitalize on customer segmentation, you need to lay the groundwork of segmenting your users and visitors.
No matter which type of customer segmentation you decide to use, the process begins with gathering data about your customers.
You can do this via many pathways, including:
Then, your brand will need to analyze this data, looking for the most valuable patterns that can be used to create your segments.
Once you’ve identified patterns among your customers, it’s time to gather the appropriate shoppers into the appropriate segments. This is often done using either rule-based or cluster-based segmentation.
Once you have your segments, it’s time to learn meaningful insights about those groups of shoppers. Customer segmentation analysis is what helps your brand understand each segment more fully and hypothesize about how best to market to them in the future.
Analyzing the behaviors of each segment will help you highlight patterns and trends so you can develop targeted marketing strategies that are more likely to be successful for each customer segment.
Triple Whale's Segment Builder and Cohort Analysis tools have helped a number of brands perform customer segmentation.
Here are some of our favorite customer segmentation examples.
We helped Dixxon gain insights into which customer segments delivered the highest lifetime value. Customers who purchased country music-themed flannels were worth more than $1,000 after one year, nearly double the $503 value of motorsports customers. This insight has directly informed Dixxon’s product development strategy.
"This helps us understand where we should start doubling down from a product development standpoint—what categories we should really focus on based on the true value we're getting from these specific cohorts," Austin Urlocker, a marketing strategist at Dixxon, told us.
Read the full case study.
This supplement brand relied on our Customer Cohorts to track first-order revenue and monitor spending patterns over time, providing insights into the lifetime value and behavior of different customer segments. They also compared customer acquisition cost to LTV for specific cohorts to gain clarity into the profitability of key customer segments. Along with other Triple Whale insights, Create scaled from $0 of revenue to $4.5 million in one year!
Read the full case study.
RFM segmentation helped this mattress, bedding, and sleep accessories brand improve their Meta ROAS by 30%. Triple Whale’s easy-to-use segmentation builder helped them better target high-value customers, improving both campaign targeting and CRM flows. “We synced our high-value segments to Meta and Google. It led to better targeting and higher AOV,” Jon Moore, Simba Sleep’s marketing and ecommerce director told us. This resulted in the highest ROAS return from all their Meta lookalike audiences.
Read the full case study.
Boutique digital marketing agency RSN8 Media partnered with Triple Whale to supercharge brand growth for the apparel business TALENTLESS. Understanding and segmenting customer behaviors became pivotal, so RSN8 employed Triple Whale’s Audience Builder tool to gather and analyze demographic and behavioral data.
They targeted very specific audiences, such as couples celebrating anniversaries. A curated creative approach using couple-focused copy and imagery led to a new customer ROAS improvement of 300%. This outcome underscored the value of tailored creatives for specific audience segments.
“It's been extremely helpful to understand and try to tell the full story as to why certain products actually drive better long-term value for each individual customer acquired,” Shayan Doosty, CEO and founder of RSN8 Media told us. “Just trying to dissect that and working backwards to reverse engineer the [customer] journey has been really effective for TALENTLESS.”
Read the full case study.
Of course, you can’t just create these segments out of thin air. Audience segmentation tools like the following can help you create and analyze your segments.
Increasingly, customer segmentation tools and software use artificial intelligence and machine learning to analyze larger amounts of data faster to more accurately and efficiently create and learn from customer segments.
Triple Whale’s AI Moby Agents work behind the scenes in our RFM segmentation process to identify your most valuable customers and prospects, then syncs them to your marketing channels automatically. This results in 50 to 100% larger segments than typical segmentation tools, meaning you’re reaching more of the right people.
Customer segmentation involves grouping your customers into categories based on their shared characteristics, then marketing to them differently based on their unique desires, needs, preferences, and behaviors.
This can help you increase customer retention, average order value, and lifetime value, as long as you’re constantly evaluating your segmentation process and tweaking it to make it work best for your brand. There are lots of different ways to segment your customers and various ways to analyze the data you gather from each segment. And Triple Whale can help with all of it, including building smarter segments and analyzing various cohorts of shoppers. Book a demo today!
Customer segmentation is the process of categorizing your customers based on shared characteristics like age, behaviors, spending habits, and preferences. Then, through customer segmentation analysis, you can learn more about your customers and tailor your campaigns, offers, and products to their specific desires and needs.
The more you understand your customers, the better you can sell to them and the more successful your business will be. Segmenting customers allows you to visualize major differences between different categories of customers, then finetune your marketing efforts to the behaviors of these various groups.
So what is customer segmentation? Put simply, it’s grouping your customers based on similarities that help you market to them effectively.
It might look like categorizing your audience by factors such as:
…and many more! Scroll down to the section on types of customer segmentation for additional details.
Once you’ve identified your customer segments, you can dig deep into the analysis of how these groups behave and why, with answers to the following questions, according to the National Institutes of Health Office of Management:
The next step of the customer segmentation process is creating hypotheses around why you observe these trends. This can help your campaigns evolve to more effectively target the right customers.
This customer segmentation definition is similar to but distinct from marketing segmentation. Marketing segmentation is a similar process of dividing consumers into segments. But it involves looking at everyone in a target audience or market. Customer segmentation deals solely with your brand’s existing customer base.
Customer segmentation is important because it improves your bottom line by increasing key marketing metrics like customer engagement and conversion rate.
Here are some of the benefits of customer segmentation that help you get there:
But consumer segmentation isn’t just about grouping your customers by their ages and hometowns. There are a number of different types of customer segmentation you can use, depending on your industry, the size of your business, and the data you have available. These are also sometimes called customer segmentation models.
Demographic segmentation is likely the type of segmentation that’s familiar to most people. It involves grouping customers by demographic characteristics such as:
For example, if you run a catering business and you segment your customers by families with school-age children, you can craft tailored marketing campaigns about graduation parties to send to this segment.
As the name implies, this type of customer segmentation involves grouping your customers by their physical location. This can be at any number of levels, such as:
For example, you might send push notifications with a limited-time offer to a segment of your app users currently located near your brick-and-mortar location.
Behavioral segmentation is a little more nuanced: Instead of segmenting customers by tangible facts about who they are and where they come from, this model groups them by their past interactions with your online brand, such as:
This might look like segmenting your users into those who have previously made purchases on certain days of the week and timing your marketing sends to them accordingly.
This approach groups customers by characteristics that are closer to personality traits, such as:
If you run an online apparel business, you might segment your customers by activity and send running-specific messaging to the runners and hiking-specific messaging to the outdoorsy shoppers, for example.
Then, there’s segmentation based on the technology your customers use. This segmentation strategy looks at how much a customer uses different:
To put it into practice, you might segment your customers by social media use and capitalize on trending topics in your messaging to those users on their preferred platforms.
RFM segmentation groups customers based on three vectors of their past purchasing behaviors: recency, frequency, and monetary value. Customers are ranked based on each of these three vectors and then divided into groups based on their scores. The groups might include new customers, high-risk customers, high-value customers, and low-value customers, for example.
While less commonly used than the tactics above, needs-based segmentation is still a valid approach. As the name implies, it involves grouping customers by their needs, such as:
You might discover a segment of your customers is turned off by your customer service chatbot and instead needs to be able to reach a representative over the phone before making a purchase. Clearly communicate the hours when someone will be available to this segment. Delivering compelling creative and successful solutions targeted to a segment’s needs builds trust, loyalty, and retention.
Using customer journey analytics, you can segment your users by their value to your business. Then, you can allocate more resources to the segments that generate the highest lifetime value, which can help you cut down on costs and increase efficiency.
This might look like offering special promotions only to your highest-value customers to encourage repeat purchases.
Before you can capitalize on customer segmentation, you need to lay the groundwork of segmenting your users and visitors.
No matter which type of customer segmentation you decide to use, the process begins with gathering data about your customers.
You can do this via many pathways, including:
Then, your brand will need to analyze this data, looking for the most valuable patterns that can be used to create your segments.
Once you’ve identified patterns among your customers, it’s time to gather the appropriate shoppers into the appropriate segments. This is often done using either rule-based or cluster-based segmentation.
Once you have your segments, it’s time to learn meaningful insights about those groups of shoppers. Customer segmentation analysis is what helps your brand understand each segment more fully and hypothesize about how best to market to them in the future.
Analyzing the behaviors of each segment will help you highlight patterns and trends so you can develop targeted marketing strategies that are more likely to be successful for each customer segment.
Triple Whale's Segment Builder and Cohort Analysis tools have helped a number of brands perform customer segmentation.
Here are some of our favorite customer segmentation examples.
We helped Dixxon gain insights into which customer segments delivered the highest lifetime value. Customers who purchased country music-themed flannels were worth more than $1,000 after one year, nearly double the $503 value of motorsports customers. This insight has directly informed Dixxon’s product development strategy.
"This helps us understand where we should start doubling down from a product development standpoint—what categories we should really focus on based on the true value we're getting from these specific cohorts," Austin Urlocker, a marketing strategist at Dixxon, told us.
Read the full case study.
This supplement brand relied on our Customer Cohorts to track first-order revenue and monitor spending patterns over time, providing insights into the lifetime value and behavior of different customer segments. They also compared customer acquisition cost to LTV for specific cohorts to gain clarity into the profitability of key customer segments. Along with other Triple Whale insights, Create scaled from $0 of revenue to $4.5 million in one year!
Read the full case study.
RFM segmentation helped this mattress, bedding, and sleep accessories brand improve their Meta ROAS by 30%. Triple Whale’s easy-to-use segmentation builder helped them better target high-value customers, improving both campaign targeting and CRM flows. “We synced our high-value segments to Meta and Google. It led to better targeting and higher AOV,” Jon Moore, Simba Sleep’s marketing and ecommerce director told us. This resulted in the highest ROAS return from all their Meta lookalike audiences.
Read the full case study.
Boutique digital marketing agency RSN8 Media partnered with Triple Whale to supercharge brand growth for the apparel business TALENTLESS. Understanding and segmenting customer behaviors became pivotal, so RSN8 employed Triple Whale’s Audience Builder tool to gather and analyze demographic and behavioral data.
They targeted very specific audiences, such as couples celebrating anniversaries. A curated creative approach using couple-focused copy and imagery led to a new customer ROAS improvement of 300%. This outcome underscored the value of tailored creatives for specific audience segments.
“It's been extremely helpful to understand and try to tell the full story as to why certain products actually drive better long-term value for each individual customer acquired,” Shayan Doosty, CEO and founder of RSN8 Media told us. “Just trying to dissect that and working backwards to reverse engineer the [customer] journey has been really effective for TALENTLESS.”
Read the full case study.
Of course, you can’t just create these segments out of thin air. Audience segmentation tools like the following can help you create and analyze your segments.
Increasingly, customer segmentation tools and software use artificial intelligence and machine learning to analyze larger amounts of data faster to more accurately and efficiently create and learn from customer segments.
Triple Whale’s AI Moby Agents work behind the scenes in our RFM segmentation process to identify your most valuable customers and prospects, then syncs them to your marketing channels automatically. This results in 50 to 100% larger segments than typical segmentation tools, meaning you’re reaching more of the right people.
Customer segmentation involves grouping your customers into categories based on their shared characteristics, then marketing to them differently based on their unique desires, needs, preferences, and behaviors.
This can help you increase customer retention, average order value, and lifetime value, as long as you’re constantly evaluating your segmentation process and tweaking it to make it work best for your brand. There are lots of different ways to segment your customers and various ways to analyze the data you gather from each segment. And Triple Whale can help with all of it, including building smarter segments and analyzing various cohorts of shoppers. Book a demo today!
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Body Copy: The following benchmarks compare advertising metrics from April 1-17 to the previous period. Considering President Trump first unveiled his tariffs on April 2, the timing corresponds with potential changes in advertising behavior among ecommerce brands (though it isn’t necessarily correlated).
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