Segmentation analysis is a marketing technique that can be used to identify and analyze different groups and categories of customers. Segmentation analysis can help marketers and product managers to better understand their target market. By segmenting customers, markets can also predict the future needs of customers, thus helping develop new and optimized strategies.

There are four main types of segmentation analysis:

1: Demographic segmentation

Demographic segmentation is the easiest to execute and is useful for segmenting customers by gender, age, and location. Demographic segmentation involves some of the following characteristics: 

• Age
• Education
• Ethnicity
• Gender
• Income
• Location

In B2B, it might also include: 

• Industry 
• Company size 

2: Psychographic segmentation 

Psychographic segmentation is more complex than most other forms of segmentation and usually requires in-depth qualitative research. Psychographic segmentation involves some of the following characteristics: 

• Attitudes
• Influences
• Interests
• Lifestyle
• Motivations
• Personality traits
• Political beliefs
• Priorities
• Subconscious and conscious beliefs
• Values, ethics, and morals

3: Behavioral segmentation 

Behavioral segmentation pertains to users’ behaviors and interactions with the brand or product. This usually includes value-based segmentation, which means sorting customers by the value they present to the brand and their customer lifetime value (CLV). It includes some of the following characteristics: 

• Brand interactions
• Purchasing habits
• Returning vs newer buyers
• Spending habits

4: Geographic segmentation

Similar to demographic segmentation, but more granular with regards to location. Geographic segmentation includes some of the following characteristics: 

• Postal or ZIP code
• City or town 
• Country
• Radius around a certain location
• Urban, suburban or rural

How do you segment customer data?

It’s possible to segment customers with Google Analytics or customer data platforms such as Segment and mParticle. You can also segment costumes in various ways using Python. Some CDPs use machine learning to automatically sort customers into segments, centralizing data from multiple channels. It’s also possible to sort customers using unsupervised learning, e.g. K-means clustering. 

The benefits of segmentation analysis

The benefits of segmentation analysis are:

• Understanding who your customers are in a more general or top-down sense
• Understanding different segments of customers in a more specific bottom-up sense
• Predicting the future needs of customers
• Developing new products to meet the requirements of different customers
• Target effective marketing and promotions 
• Informs brand messaging and visual branding
• Content creation, where content can be tailored and optimized for different segments

The disadvantages of segmentation analysis

Segmentation analysis can be time-consuming and costly. It requires a lot of data to determine which segments are profitable and worth targeting, which can be difficult when there is not enough data available. Segmentation analysis also relies on the assumption that all customers within a segment have similar needs, but this may not always be true.

Three practical examples of segmentation analysis

1. Segmenting the market by age: When a company has a product targeted at children, they might want to segment their marketing campaign to target different age groups within that demographic, such as toddlers, pre-teens, and teens (for their parental buyers). If a company is targeting an older demographic, they might want to segment their marketing campaign with different lifestyle segments such as families with children, singles or empty nesters for example. 
2. Segmenting the market by income level: Companies will often segment their customer base into various income levels when determining what type of products or services they offer and how much they charge for them. This is done because people in higher income brackets are more likely to spend more on luxury items than those in. This also applies to B2B where company budgets and turnovers affect marketing strategies. 
3. Segmenting the market by interests: By discovering affinity categories for different groups of customers, it’s possible to deliver them marketing promo and content which aligns with their interests. Google Analytics allows for affinity segmentation. 

The importance of segmentation analysis

Segmentation analysis is a type of marketing research that divides the market into different segments, or groups. These segments are then analyzed to determine which groups have the most potential for growth. Without segmentation, it’s far too easy to generalize over who your customers are and some of your assumptions are likely incorrect. 

For example, you might feel that you’re marketing your brand to 15 to 17-year-olds, when actually it’s their 40 to 50-year-old parents who are making the buying decisions some of the time. You could segment these into two groups and market to the kids separately from the adults. 

How you can easily achieve segmentation analysis

The key to achieving segmentation analysis is to first identify the segments of your market. This can be done by identifying the different needs and wants that each segment has. Once you have identified these, you will be able to create a product or campaign for each segment. The next step is to get feedback from customers on what they like about your products and what they don't like about them. This will allow you to improve your products in order to make them more appealing for all of the different segments that you are targeting.

Most advanced segmentation requires some level of qualitative analysis via feedback, surveys, etc. However, if you dig down into your customer data, you’ll find plenty of information that can be used for segmentation already (particularly demographic segmentation). Google Analytics has lots of excellent segmentation features and allows for campaigns to be targeted at the following:

• Detailed demographics: Targeting based on demographic information. 
• Life events: Target users based on potential life milestones.
• In-market: Target users based on their recent purchase intent.
• Your data segments: Target users that interact with your business.
• Affinity: Target users based on passions, hobbies, and interests. 

How to create a market segmentation strategy

1. Analyze your customers‍

Start with your current customers. If you use a CRM, this is the best place to start. If you keep some form of customer database, analyze that. Importing data into CDPs or segmentation studios is a good idea if you have vast quantities of customer data from different channels. ‍

2: Interview customers and collect qualitative data‍

Traditionally, focus groups and surveys were the primary means for businesses to understand their audiences. These techniques are still valid today. Contact your customers with a feedback form or survey and request their opinions.

‍3: Interview marketing and sales teams‍

Your marketing and sales teams will likely have some insight into your typical buyer personas. This is especially the case in compact B2B sales teams that communicate with a small set of high-value customers. Additionally, asking your marketing team to analyze social media traffic provides insight into who is interacting with your social campaigns. ‍

4: Use website analytics‍

Your web users are relatively simple to segment and analyze in Google Analytics. You can create segments in Google Analytics and analyze your website data for that segment only. This also provides insight into who your audience is if you’re not actually selling a product and therefore don’t have customer data. This might apply if you’re a blogger, affiliate marketer, news site, or similar. ‍

5: Action findings‍

Once you’ve segmented your customers with a handful of solid, high-confidence segments, it’s time to build some targeted campaigns for those segments. Examples of segment-specific marketing include emails, push notifications, SMS and even direct mail. You can also use segment data to build recommendation engines, as Segment describes here. 

Customer Segmentation Software

Some software applications designed specifically for segmentation include: 

• MailChimp, for email segmentation 
• Qualitrics, which integrates advanced machine learning customer exploration tools
• SproutSocial, great for segmenting social media content 
• Experian, enterprise-level segmentation 
• HubSpot, which combines a CRM with segmentation 
• Segment and mParticle, for advanced multi-channel segmentation and customer data automation 

Segment analysis in B2B

In contrast to B2C, where the focus is typically on broader segmentation, B2B environments demand more granular segmentation. In B2B, segments are often called buyer personas, which is basically the same thing as a customer segment, but slightly more individualistic and detailed. 

Buyer personas are incorporated into many CRMs, allowing sales teams to communicate with buyers based on their persona and related guidance. 

Summary: Segmentation Analysis

Segmentation analysis is the process of discovering customers that have certain characteristics in common. There are four main areas of segment analysis; demographic, psychographic, behavioral, and geographic. 

By segmenting customers, it’s possible to build targeted and bespoke marketing and sales strategies. The segmentation process is also valuable for understanding your audience in greater detail.