Customer Segmentation

When businesses offer goods or services, customers either find their products desirable and useful or don’t like them. While this seems like a basic idea of how businesses thrive or shut down, the reality is more complicated, as clients are not an indiscrete crowd that has two mutually exclusive opinions on a given product. Hence the concept of customer segmentation.

What is customer segmentation?

Customer segmentation is the process of breaking down a customer base into groups that share similar characteristics. The customer segmentation meaning revolves around identifying patterns within a customer base to tailor business strategies effectively. In customer segmentation, you divide groups of customers into smaller sub-groups based on specific characteristics and various formal features such as gender, age, etc., thus coming up with a number of target groups, allowing for a more targeted marketing approach. As a result, companies can target these segments more efficiently with different approaches, which helps them maximize sales.

Common customer segmentation objectives

Customer segmentation analysis is used not only for marketing but for other objectives as well:

• Development of new products
• Adjusting marketing communication
• Developing different customer services and retention efforts
• Developing channel strategies
• Maximizing profits/ROI for existing products

Importance of customer segmentation for marketing

1. Increase revenue

Customer segmentation strategy allows businesses to carry out targeted marketing campaigns aimed at specific audiences. When properly executed, customer segmentation marketing ensures that potential customers are more likely to engage with the content if the right approach is chosen. This improves conversion rates in contrast with traditional mass marketing methods that target broad audiences, most of whom may show no interest in the product.

2. Reduce costs

Mаrket segmentation rеduсеѕ costs. Since a company doesn’t have to target ALL potential customers and can focus on a much smaller segment (with more potential), the cost of promotion goes down.

3. Build better customer relationships

By implementing customer profiling and segmentation, businesses can personalize communication for each segment. This helps improve customer loyalty by making them feel valued and appreciated.

How to build customer segmentation models?

Customer segmentation models can vary widely depending on the niche. However, the following types of customer segmentation are the most common:

1. Demographic customer  segmentation

This strategy divides the overall audience into segments based on age, gender, marital status, income level, education level, occupation, etc.

2. Geographic customer segmentation

This approach divides the target market according to specific locations where a given audience lives or works. This may refer to overall countries, ѕtаtеѕ, сіtіеѕ, neighborhoods, or even specific houses. 

3. Behavioral customer segmentation

When marketers divide audiences into segments based on behavioral patterns, they analyze how people make decisions: what kind of products they prefer, how much they’re ready to pay, whether they care about brands, and so on. Knowing how customers may react allows marketers to adjust their efforts accordingly.

4. Psychographic customer segmentation

This method is similar to customer behavior segmentation but focuses more on values, interests, and lifestyles. Companies leveraging customer segmentation machine learning can predict these behaviors more effectively.

The specific application of these segmentation types differs significantly, for example, retail customer segmentation might focus on in-store purchase behavior, while B2B customer segmentation prioritizes company size and industry. Furthermore, ecommerce customer segmentation, including Amazon customer segmentation, requires analyzing online browsing and purchasing patterns to personalize the digital shopping experience.

Choosing target customers with segmentation analysis

To conduct a proper customer segmentation analysis, marketers collect relevant data categorized into two groups – attributes and events:

• Attributes are static characteristics such as age, location, and language.
• Events are actions customers have taken, such as recent website visits or email engagements.

By combining attributes and events, marketers can construct customer segmentation examples such as “22-35-year-olds who visited the site from smartphones.” Businesses can use RFM customer segmentation and cluster analysis for customer segmentation to refine these groups further.

Implementing customer segmentation tools and AI

Advanced customer segmentation software and customer segmentation tools are available to help businesses analyze data effectively. Using AI for customer segmentation provides automated insights, improving decision-making processes.

If a customer segmentation tool supports integration, what is it able to do? It allows businesses to streamline their marketing efforts, ensuring seamless data synchronization between different platforms.

Customer segmentation in different industries

Different industries apply segmentation techniques in unique ways:

• Banking: customer segmentation in banking uses financial behaviors to determine target groups.
• SaaS platforms: customer segmentation SaaS platforms analyze user interactions to tailor services.
• Ecommerce (Magento 2): Magento 2 customer segmentation helps ecommerce businesses categorize customers for better marketing.
• General trend: dynamical customer segmentation and data-driven customer segmentation enable real-time adjustments based on market trends.

Closing thoughts

Customer segmentation is an important part of an effective advertising and marketing strategy. However, overly narrow segments may hurt your business. If a segment requires more than three adjectives to describe it, the segment is considered too complex.

By utilizing customer segmentation frameworks, customer segmentation analytics, and customer segmentation strategies, businesses can achieve better targeting, improve customer relationships, and increase profitability. Whether leveraging customer segmentation machine learning, automated customer segmentation, or customer segmentation platforms, companies must prioritize strategic segmentation to stay competitive in their respective markets.