Before you can effectively build customer personas that are an accurate representation of your market segments, you need to know what those segments are. This requires figuring out which segmentation variables are most appropriate for your industry, your target audience, and the goals of your business.
Here are a number of different segmentation methods to choose from, and you can decide to use one or more of them at the same time.
Here are a number of different segmentation methods to choose from, and you can decide to use one or more of them at the same time.
Segmenting an audience based on demographics is the most obvious and most commonly used method. It’s based on factual, statistical data such as age, gender, income levels, location, education, family situation, and ethnicity. These are typical for a B2C audience, while B2B demographics include company size, location, type of industry, number of employees, and others. In both instances, you can choose which factor to focus on as your lead criteria, with others as second or third-level criteria.
One way to pull demographics is by viewing the breakdown of the audience that visits your website. Google Analytics, for instance, is a way to see who is visiting your website, where they live, and what their interests are. If your website is new, consider installing an analytics tool right away to start capturing data now since these tools cannot retroactively pull website visits. At the same time, install your Facebook page’s widget onto your site so you can segment according to website visits and Facebook page visits as well.
This is the process of dividing the total marketplace into smaller, homogeneous groups based on the buying behavior of the people in the groups. Buying patterns used include frequency of use, loyalty to your brand, and the benefits they need as a result of using the product or service. Behavioral segmentation requires you to have knowledge or data about how the customer interacts with your brand.
For example, in the B2C space, this might mean a luxury car brand targeting customers who bought high-end vehicles in the past few years. In B2B, it could mean focusing on users who signed up for a free webinar in the past.
Firmographics are attributes that apply to business customers such as companies, non-profits, government departments, or any type of firm or organization. The data is to business organizations what demographic data is to individual consumers. By grouping business customers in terms of their shared needs and preferences, you can improve the insights your B2B marketing, advertising, and sales are based on. This will ultimately lead to more focused and effective campaigns.
This is when a business divides its target audience on the basis of geography. It’s used when people living in an area have similar problems and buying preferences as a result of their location. This kind of segmentation works well for businesses targeting a local audience. It can be broken down into countries, cities, towns, regions, urban, suburban, and rural areas.
This is one of the less common methods of segmentation, but it works in specific circumstances. Customers are segmented based on the different media used to reach them. For example, when a company targets personas that all consume media from a particular broadcaster or media house, they would most likely pour their budget into marketing with that broadcaster and any others the broadcaster’s audience follows.
Most types of market segmentation are based on capturing customer preferences at a single point in time. Many products and services need moving pictures, though, not snapshots, to help them gather data on unfolding trends and determine what customers are likely to want tomorrow (and why).
Ethnic or cultural segmentation is the economic and social resource accumulation of groups with a common background, either related to their nationality or to their traditions and beliefs. This is often a secondary option in two-factor cluster analysis. For example, you might want to create a segment consisting of consumers with Italian origins in the U.S. to market a new Italian-flavored product or a segment of people whose culture includes henna hand-painting to market a new type of tool to perform henna.
This form of segmentation means charging different prices to different types of customers buying the same (or similar) products or services. Examples include student pricing at movie theaters, senior pricing for transport tickets, and savings coupons available to certain groups.
Markets can be segmented in multiple ways using a variety of methods and tools. For most segmentation purposes, all the different variables are combined to identify those which apply most often. This determines how the audience is segmented. With multidimensional segmentation, however, variables are grouped into categories first. Each respondent then shows up as a member of several categories, which means they are segmented across multiple dimensions.
This is fairly self-explanatory in that it groups users according to their lifestyle types. These criteria are then used to plan marketing activities to ensure customers have the means, motive, and opportunity to consume them. It’s important for companies to deliver services that are customized, or better quality products based on consumer activities and interests.
The differences between value-based market segmentation and other methods are particularly important when it comes to pricing decisions. Most segmentation criteria overlook the customer needs that have the greatest effect on sellers’ costs to serve those needs. Costs are important to pricing decisions because the goal of most companies is to make a profit. To use value-based segmentation effectively, you need to find out why customers find particular product benefits (value) attractive. This opens up opportunities to develop new products and services based on that value.
Attitudinal segmentation, also called psychographic segmentation, is a method of grouping people based on factors such as their beliefs, attitudes, interests, opinions, daily habits, food preferences, and other lifestyle elements. It doesn’t matter whether these are visible traits or not, they help marketers to understand the goals, challenges, emotions, values, habits, and hobbies that drive customers’ purchase decisions.
When companies target customer groups based on a set of shared attitudes, it enables them to gain a deeper understanding of current and future customers. Companies recognize the impact of attitudes on buying behavior and target groups of customers with the same attitudes based on cluster analysis. This is also a good way to de-prioritize segments that don’t — and never will — be a good fit for your company. Attitudinal segmentation works most effectively when it’s combined with one of the primary methods, such as demographic, behavioral, or lifestyle segmentation.
In needs-based segmentation, you divide the market up into groups of people with similar needs. This enables you to offer them exactly the right products and services in precisely the right way to meet their needs. You can differentiate both the offering and the communications specifically for individual target segments. This gives your marketing higher impact and higher conversion rates and offers you benefits such as the chance to:
To achieve this type of segmentation, you’ll need to get hold of qualitative data about your audience in which consumers state what benefits matter to them when they choose a supplier. You can then create the segments mainly around these benefits, and group them into clusters.
This method of segmentation identifies chances for company growth based on the occasion or situation when consumers use their product or service. When you can identify the psychological need that drives the choice of drinks at particular times, you can segment the market in a way that matches how consumers use the product to fill the need.
Each of these different types of segmentation requires a different method of building personas. Whichever one you choose, it’s necessary to understand the life cycles of the customers based on their frequency or level of engagement. A persona who interacts with your brand only once a year might fall into a very different market segment than one who purchases from you monthly, and who will require a different approach to marketing as a result. You need to define feature sets for your segmentation process, which are based on the customer’s usage or the quest for a particular feature. Different people consume different media channels, which means building the right channel for each persona or segment, and individual personas — even those in the same segment — will often be at different stages in your sales funnel.
Consumers these days are being constantly bombarded by marketing communications. They’re tired of irrelevance and are looking for more meaningful messages than traditional marketing has delivered so far. People now want one-to-one marketing that addresses their specific issues and offers custom solutions for them. Data-driven segmentation makes this possible, with the use of clustering and the leveraging of pre-built segments.
Clustering is a mathematical way to discover similar groups of customers based on identifying the smallest variations among the customers in each group. It identifies the relationship between different data points from a statistical viewpoint.
Using machine learning algorithms for cluster analysis based on buying behavior can help you discover new segments of customer “archetypes,” such as:
A key factor in cluster analysis is defining what we mean by “similar” or “different” traits. It’s often necessary to split the data into segments that are analyzed independently to develop segment-specific insights.
There are three main benefits of a data-driven segmentation approach using cluster analysis:
The advantage of using clusters along with segmentation to create your personas is that each persona tells a different customer story. This gives you the means to target each customer grouping very specifically with personalized content and communications.
Segmentation can be complex and highly challenging to perform, but it’s so valuable marketers can’t afford to be without it. Studies show that while 72% of consumers in 2019 only engaged with marketing messages customized to their specific interests, up to 42% of marketers struggle with segmentation and message personalization. Pre-built segments offer a viable solution, particularly in email marketing.
A pre-built segment is when you use data to develop criteria for grouping the customers. Typical pre-built segments might appear to be superficial groupings. If you aren’t using any other form of segmentation, however, they still give you a basic platform to start from.
Establish the five primary strategic segments right from the outset. Depending on the type of business you have, these could be:
You can also choose other relevant criteria to create groupings or categories for your customers and use these as pre-built segments.
Pre-built segments enable you to hyper-personalize your marketing by making use of the behavioral data they show to discover customers’ consumption habits. By combining these pre-built segments with clusters and other segmentation methods, you can whittle your marketing down to a very specific set of persona identities.
With the amount of data you can now gather about your customers, you can use technology such as scoring tools to identify high-value or high-potential customers. You can also find out other information, such as which clients are the most likely to buy from you or to move to another supplier, and customize your communications accordingly. This is the benefit of hyper-personalization — the ability to target individual customers (or groups of individuals) with a specific message based on your knowledge about their activities and intent.
By combining your existing customer and transactional data, you can pinpoint the mix of common characteristics and product purchases that make up the best, most profitable customer relationships. You can retrace those customer journeys and discover how their relationship with you evolved to this point and use the data to define exactly what your target personas should look like. Based on this, you can determine how best to merge the segments with your marketing activities to make sure you’re delivering the right message to the right persona at the right time.
Before you can effectively build customer personas that are an accurate representation of your market segments, you need to know what those segments are. This requires figuring out which segmentation variables are most appropriate for your industry, your target audience, and the goals of your business.
Here are a number of different segmentation methods to choose from, and you can decide to use one or more of them at the same time.
Here are a number of different segmentation methods to choose from, and you can decide to use one or more of them at the same time.
Segmenting an audience based on demographics is the most obvious and most commonly used method. It’s based on factual, statistical data such as age, gender, income levels, location, education, family situation, and ethnicity. These are typical for a B2C audience, while B2B demographics include company size, location, type of industry, number of employees, and others. In both instances, you can choose which factor to focus on as your lead criteria, with others as second or third-level criteria.
One way to pull demographics is by viewing the breakdown of the audience that visits your website. Google Analytics, for instance, is a way to see who is visiting your website, where they live, and what their interests are. If your website is new, consider installing an analytics tool right away to start capturing data now since these tools cannot retroactively pull website visits. At the same time, install your Facebook page’s widget onto your site so you can segment according to website visits and Facebook page visits as well.
This is the process of dividing the total marketplace into smaller, homogeneous groups based on the buying behavior of the people in the groups. Buying patterns used include frequency of use, loyalty to your brand, and the benefits they need as a result of using the product or service. Behavioral segmentation requires you to have knowledge or data about how the customer interacts with your brand.
For example, in the B2C space, this might mean a luxury car brand targeting customers who bought high-end vehicles in the past few years. In B2B, it could mean focusing on users who signed up for a free webinar in the past.
Firmographics are attributes that apply to business customers such as companies, non-profits, government departments, or any type of firm or organization. The data is to business organizations what demographic data is to individual consumers. By grouping business customers in terms of their shared needs and preferences, you can improve the insights your B2B marketing, advertising, and sales are based on. This will ultimately lead to more focused and effective campaigns.
This is when a business divides its target audience on the basis of geography. It’s used when people living in an area have similar problems and buying preferences as a result of their location. This kind of segmentation works well for businesses targeting a local audience. It can be broken down into countries, cities, towns, regions, urban, suburban, and rural areas.
This is one of the less common methods of segmentation, but it works in specific circumstances. Customers are segmented based on the different media used to reach them. For example, when a company targets personas that all consume media from a particular broadcaster or media house, they would most likely pour their budget into marketing with that broadcaster and any others the broadcaster’s audience follows.
Most types of market segmentation are based on capturing customer preferences at a single point in time. Many products and services need moving pictures, though, not snapshots, to help them gather data on unfolding trends and determine what customers are likely to want tomorrow (and why).
Ethnic or cultural segmentation is the economic and social resource accumulation of groups with a common background, either related to their nationality or to their traditions and beliefs. This is often a secondary option in two-factor cluster analysis. For example, you might want to create a segment consisting of consumers with Italian origins in the U.S. to market a new Italian-flavored product or a segment of people whose culture includes henna hand-painting to market a new type of tool to perform henna.
This form of segmentation means charging different prices to different types of customers buying the same (or similar) products or services. Examples include student pricing at movie theaters, senior pricing for transport tickets, and savings coupons available to certain groups.
Markets can be segmented in multiple ways using a variety of methods and tools. For most segmentation purposes, all the different variables are combined to identify those which apply most often. This determines how the audience is segmented. With multidimensional segmentation, however, variables are grouped into categories first. Each respondent then shows up as a member of several categories, which means they are segmented across multiple dimensions.
This is fairly self-explanatory in that it groups users according to their lifestyle types. These criteria are then used to plan marketing activities to ensure customers have the means, motive, and opportunity to consume them. It’s important for companies to deliver services that are customized, or better quality products based on consumer activities and interests.
The differences between value-based market segmentation and other methods are particularly important when it comes to pricing decisions. Most segmentation criteria overlook the customer needs that have the greatest effect on sellers’ costs to serve those needs. Costs are important to pricing decisions because the goal of most companies is to make a profit. To use value-based segmentation effectively, you need to find out why customers find particular product benefits (value) attractive. This opens up opportunities to develop new products and services based on that value.
Attitudinal segmentation, also called psychographic segmentation, is a method of grouping people based on factors such as their beliefs, attitudes, interests, opinions, daily habits, food preferences, and other lifestyle elements. It doesn’t matter whether these are visible traits or not, they help marketers to understand the goals, challenges, emotions, values, habits, and hobbies that drive customers’ purchase decisions.
When companies target customer groups based on a set of shared attitudes, it enables them to gain a deeper understanding of current and future customers. Companies recognize the impact of attitudes on buying behavior and target groups of customers with the same attitudes based on cluster analysis. This is also a good way to de-prioritize segments that don’t — and never will — be a good fit for your company. Attitudinal segmentation works most effectively when it’s combined with one of the primary methods, such as demographic, behavioral, or lifestyle segmentation.
In needs-based segmentation, you divide the market up into groups of people with similar needs. This enables you to offer them exactly the right products and services in precisely the right way to meet their needs. You can differentiate both the offering and the communications specifically for individual target segments. This gives your marketing higher impact and higher conversion rates and offers you benefits such as the chance to:
To achieve this type of segmentation, you’ll need to get hold of qualitative data about your audience in which consumers state what benefits matter to them when they choose a supplier. You can then create the segments mainly around these benefits, and group them into clusters.
This method of segmentation identifies chances for company growth based on the occasion or situation when consumers use their product or service. When you can identify the psychological need that drives the choice of drinks at particular times, you can segment the market in a way that matches how consumers use the product to fill the need.
Each of these different types of segmentation requires a different method of building personas. Whichever one you choose, it’s necessary to understand the life cycles of the customers based on their frequency or level of engagement. A persona who interacts with your brand only once a year might fall into a very different market segment than one who purchases from you monthly, and who will require a different approach to marketing as a result. You need to define feature sets for your segmentation process, which are based on the customer’s usage or the quest for a particular feature. Different people consume different media channels, which means building the right channel for each persona or segment, and individual personas — even those in the same segment — will often be at different stages in your sales funnel.
Consumers these days are being constantly bombarded by marketing communications. They’re tired of irrelevance and are looking for more meaningful messages than traditional marketing has delivered so far. People now want one-to-one marketing that addresses their specific issues and offers custom solutions for them. Data-driven segmentation makes this possible, with the use of clustering and the leveraging of pre-built segments.
Clustering is a mathematical way to discover similar groups of customers based on identifying the smallest variations among the customers in each group. It identifies the relationship between different data points from a statistical viewpoint.
Using machine learning algorithms for cluster analysis based on buying behavior can help you discover new segments of customer “archetypes,” such as:
A key factor in cluster analysis is defining what we mean by “similar” or “different” traits. It’s often necessary to split the data into segments that are analyzed independently to develop segment-specific insights.
There are three main benefits of a data-driven segmentation approach using cluster analysis:
The advantage of using clusters along with segmentation to create your personas is that each persona tells a different customer story. This gives you the means to target each customer grouping very specifically with personalized content and communications.
Segmentation can be complex and highly challenging to perform, but it’s so valuable marketers can’t afford to be without it. Studies show that while 72% of consumers in 2019 only engaged with marketing messages customized to their specific interests, up to 42% of marketers struggle with segmentation and message personalization. Pre-built segments offer a viable solution, particularly in email marketing.
A pre-built segment is when you use data to develop criteria for grouping the customers. Typical pre-built segments might appear to be superficial groupings. If you aren’t using any other form of segmentation, however, they still give you a basic platform to start from.
Establish the five primary strategic segments right from the outset. Depending on the type of business you have, these could be:
You can also choose other relevant criteria to create groupings or categories for your customers and use these as pre-built segments.
Pre-built segments enable you to hyper-personalize your marketing by making use of the behavioral data they show to discover customers’ consumption habits. By combining these pre-built segments with clusters and other segmentation methods, you can whittle your marketing down to a very specific set of persona identities.
With the amount of data you can now gather about your customers, you can use technology such as scoring tools to identify high-value or high-potential customers. You can also find out other information, such as which clients are the most likely to buy from you or to move to another supplier, and customize your communications accordingly. This is the benefit of hyper-personalization — the ability to target individual customers (or groups of individuals) with a specific message based on your knowledge about their activities and intent.
By combining your existing customer and transactional data, you can pinpoint the mix of common characteristics and product purchases that make up the best, most profitable customer relationships. You can retrace those customer journeys and discover how their relationship with you evolved to this point and use the data to define exactly what your target personas should look like. Based on this, you can determine how best to merge the segments with your marketing activities to make sure you’re delivering the right message to the right persona at the right time.
iPullRank is a pioneering content marketing and enterprise SEO agency leading the way in Generative AI, Technical SEO, Audience-Focused SEO, and Content Engineering. People-first in our approach, we’ve delivered $4B+ in organic search results for our clients.
iPullRank is an NMSDC-certified Black-owned business. We support the NMSDC network in its mission to reshape the diversity landscape.
iPullRank is a pioneering content marketing and enterprise SEO agency leading the way in Technical SEO, Audience-Focused SEO, and Content Engineering. People-first in our approach, we’ve delivered $4B+ in organic search results for our clients.
iPullRank is an NMSDC-certified Black-owned business. We support the NMSDC network in its mission to reshape the diversity landscape.
