What is market segmentation? Benefits and examples

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Methods of market segmentation

There are two primary methodologies that are used in segmentation: the “a priori” method and the “post-hoc” method.

The “a priori” method (rule-based segmentation)

The “a priori” method, also known as rule-based segmentation, consists of manually dividing your audience into homogenous subsets according to predefined criteria. 

The criteria can be chosen based on the results of data analysis or research, or by making assumptions based on commonly held beliefs. If you were to create a customer segment based on 50 year-old men living in Canada, you would be using the “a priori” method.

Who is this method for? The “a priori” approach is best for companies with a good knowledge of their market and who can easily identify a priori criteria.

Where do you start? You need to have a good understanding of what is relevant in segmenting your audience to have this method be effective for you. 

You also need to have “a priori” information easily available to you. The more detailed your market knowledge, the better chance you have of achieving efficient segmentation.

Example: A clothing brand decides to segment its audience according to the gender and geolocation of its visitors. A  woman living in London and visiting the website on December 1st would be presented with winter coats, whereas a man living in Spain who visited the website in the month of June would be shown swimming trunks.

The biggest limitation with this method is it may prove inaccurate, since a woman living in London and visiting the website in December could very well be looking to buy swimming trunks for her son who swims.

The “Post-Hoc” method (cluster-based segmentation)

The “post-hoc” method, also known as cluster-based segmentation, doesn’t start with criteria or predetermined rules. Instead, you observe the similarities between visitors and then group them together according to those similarities. 

This could be:

• Buying behavior
• Visitor data
• Answers to surveys

The criteria is not fixed and can fluctuate widely. The greatest advantage of this approach is that it groups segments together based on actual behavior rather than assumed resemblances.

For example, instead of segmenting men with an interest in cars (“a priori”), you can segment people who have bought tires after being shown a specific promotion and who have stated that they own multiple vehicles. 

This will then provide a potential customer segment for the automotive market that is more relevant than a segment built “a priori”.

Who is this method for? The “post-hoc” approach is best for companies that have a limited knowledge of their market or are struggling to identify segments using “a priori” criteria.

Where do you start? For this approach, you need to collect information about the visitors to your website (via data analysis, research, surveys, etc.) so that those with similar characteristics can be grouped together. 

Example: Rakuten PriceMinister is an online marketplace where individuals and professionals meet to buy and sell. 

When a user first visits the site, it has no way of determining if they are a seller or a buyer. No a priori criterion would enable it to clearly identify between these two segments. 

For this reason, PriceMinister uses the post-hoc method: thanks to Kameleoon’s predictive algorithms the brand can distinguish between these two segments and adapt its campaigns.

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Segmentation vs targeting

Although segmentation and targeting are closely related, they are completely separate concepts.

• Segmentation is the act of dividing your market into subsets.
• Targeting is when you create specific marketing materials, products, or user journeys for that particular segment.

The two are often used in tandem with one another in a two-step process, beginning with segmentation. Targeting is often considered an occasional activity (a targeted marketing campaign), whereas segmentation is more evergreen.
 

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How to prioritize which segments to target

With so many different ways of segmenting, it can be heard to decide on where to begin. Here are a few factors that will enable you to identify your high-priority segments.

Relevance

First and foremost, your market or customer segment must have strategic value for your company. It is important that the segment you align on is highly relevant to the goal you are trying to accomplish.

Example: Allopneus, an online tire retailer, identified a “power user” segment. This segment represents only 10% of the traffic on their site, but it contributes to a large percentage of the brand’s turnover: it is therefore a target with high added value and is highly relevant to achieving their revenue goals.

Profitability

The segment must be profitable in order to be considered valuable. This means you need a clear idea of:

• The number of potential customers making up the segment. 
• Their purchasing power.
• Their buying behavior. 

By analyzing these elements, you will be able to measure the profitability of the segment. If you identify a segment made up of potential customers, but this only includes a small part of your audience, then it won’t be profitable to pursue this segment.

Example: An online retailer used behavioral criteria to identify customers that are most likely to convert when they have a sale. They named this segment “deal seekers”. They plan to send personalized marketing materials to them with special deals during the holiday season to drive more revenue. 

Accessibility

The segment must be accessible, meaning you must be able to reach them – whether by social media, email, search engines, or offline channels like broadcasts or direct mail or more. You also must be able to meet their needs or desires.

Example: A clothing brand wants to appeal to a younger audience. They use TikTok and YouTube to target their segment with personalized ads and offerings.

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 How to segment your market step-by-step

Here are four steps to apply what we’ve learned so far to get started with segmentation.

1. Set a goal

Effective segmentation begins with defining your goal and clearly outlining what it is you’re hoping to achieve. Do you want to:

• Improve your customer retention rate
• Increase your market share in North America
• Reduce your email unsubscribe rate

Your goal will drive how you segment your audience, so make sure it is clearly defined from the beginning.

2. Complete a data analysis

Analyzing the data you have available to you can help you identify interesting patterns and potential ways to segment your audience. 

Are there certain segments of customers that drive the most revenue? Are there any interesting patterns you notice about the data right off the bat?

This is where you take in all of the data you have available to you, from hot and cold data, across a variety of segmentation types, to see what you can do with it. 

3. Develop a segmentation strategy

A segmentation strategy clearly outlines how you hope to segment your market in order to reach your goal. 

For example, let’s say your goal is to increase the stickiness  of your product and boost retention. After completing a data analysis, you notice that customers who use the product everyday are 3x less likely to churn. 

Your strategy would then be to create a customer segment of individuals who log in to the product at least once a day based on behavioral data in your customer data platform (CDP).

4. Use this segment in your targeting efforts

Once you gather the data and identify a segment, you can then use this segment in your targeting efforts. 

These are some of the most common places where we see segments being used for targeting:

• Personalized ad creative and copy: target a segment of users with ad creative and copy that is tied to their previous interactions with your website.
• Landing pages: create landing pages that target a specific demographic of your user segment.
• Email sequences and workflows: create email campaigns that target a specific segment of your users, such as an ecommerce campaign for women under the age 35.
• Segmented product offerings: create different versions of a product or service that cater to specific customer segments, such as a premium version of its product for high-end customers, and a more basic version for budget-conscious customers.

This is where the real magic starts to happen, as you apply what you have learned about your customer to make impactful business decisions.

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 Market segmentation applications and examples

How do you use this segmentation information in practice? Below are a few applications and examples to put your segmentation to work.

Personalized advertising and communications

Using segmentation, you can design your advertising strategy based on the individuals that make up your segments and their needs or wants.

Marketers often use segments to create highly targeted ad campaigns. These often have a far higher ROI than a more broad approach.

Personalized discounts and incentive offerings

Suggest deals, such as discounts or promotional codes, depending on the user’s relationship with your brand.

You could offer unique deals to: 

• New visitors to encourage them to become customers.
• VIP customers to thank them for their loyalty.
• Undecided users to convince them to buy.

Product roadmap development

Customer research is an essential part of developing an effective product roadmap. Segmentation can help you better understand your customers and develop a better product suited to their needs.

For example, you can segment your customers based on power users and conduct customer research on how they use the product and what features they would like to see. Then, you can use that information to guide your product roadmap strategy.

Create differentiated products

You may use your customer segment research to develop different products entirely.

For example, Club Med identified two segments of customers in their product research: families and people without children. It used this information to design two different health clubs tailored to the expectations and requirements of each segment. 

Perhaps if a one-size-fits-all solution doesn’t work, it’s worth considering how you can create different products tailored to your customer segments.

Custom web journeys and browsing

Your website is your storefront. Offer your visitors personalized experiences based on their interests, geolocation, previous history, or even their browsing journey.

You can:

• Switch the image on the homepage according to their age or gender.
• Create personalized banners with individual discount offerings based on previous purchasing behavior. 
• Tailor product recommendations based on past purchase history.
• Highlight the categories most often viewed by visitors in that segment.
• Reorganize menu sections according to their preferences.

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 Segmentation with predictive targeting

We have now seen how crucial segmentation is to developing an effective business strategy. Even so, brands still encounter many difficulties implementing segmentation. 

72% of marketers said that they had difficulty translating and analyzing data collected about their visitors, while 62% had issues creating content and personalized recommendations for each user.

This is where predictive targeting comes into play.

Predictive targeting involves using a machine learning algorithm to analyze website visitor data and identify which visitors belong to a particular target segment. 

By observing visitor behavior and the correlations between them, the algorithm learns how to predict the behavior of each visitor. 

Eventually, it determines – with increasing accuracy over time – which visitor belongs to which segment.

Through machine learning, the predictive approach offers superior segmentation, since it is capable of learning from the behavior of visitors to offer them ever more relevant experiences depending on their browsing journey. And it can do this even if it’s their first visit to the website.

Why use predictive targeting?

Predictive targeting is used to identify segments that cannot be found using the “a priori” approach. It is essential when:

• The segmentation criteria are vague, ambiguous, or changeable (I want to know which of my visitors will be influenced by scarcity effects).
• The criteria is too numerous and dissimilar, and impossible to model manually.

In these situations, predictive targeting enables you to identify, with certainty, a greater number of visitors belonging to a segment that you’re seeking to target.

Learn more about AI-driven personalization on Kameleoon.

What results can you expect from predictive targeting

Predictive targeting can give you significant results when implemented correctly. Let’s take a look at an online tire retailer to see how they use predictive targeting.

Goal: To target “power user” customers and offer them a specific deal. Power users are defined as motorists who cover at least 24,000 km per year or who own several vehicles.

Implementation: With predictive targeting, the algorithm estimates which visitors have the highest probability of belonging to the “power user” segment. It does this by cross-referencing: 

• Hot data: browsing journey (brand, quality, budget, tire size), geolocation, source (SEO/SEM), time spent on each page and number of visits.
• Cold data: such as buyer profile (private individual, professional, type of vehicle owned), purchase history or form completion.

Results: This online tire retailer can identify 48% more “power user” customers than through manual segmentation, and has noted an increase of 16% in average cart value.

Predictive targeting can be highly valuable in these instances.

Visitor segmentation is thus a key stage in crafting your marketing strategy, and one that requires special attention. It will help you zero in on whom to target with your actions and give you an edge over your competitors.
 

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