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What is customer segmentation analysis?

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Last editedOct 20202 min read

Understanding who your customers are and what they want is a fundamental part of any successful business. Yet as a business grows, so does the customer base, and it can become increasingly challenging to create a one-size-fits-all customer profile. This is where the concept of customer segmentation comes in. Find out everything you need to know about customer segmentation analysis with our simple guide.

Customer segmentation definition

Marketers now have access to more data than ever. Customer segmentation is a strategy that groups customers into smaller clusters, based on the characteristics they have in common. There are three main categories of customer segmentation types, which encompass a variety of client personas.

  • Market-based segments: Based on observable demographic, geographic, or other firmographic traits.

  • Needs-based segments: Based on business use and needs, including frequency of service interaction. These needs are verified through market research. 

  • Value-based segments: Based on economic value, revenue, and the customer's willingness to buy.

By dividing them into smaller groups or segments, it's possible to focus on each group's needs more effectively.

Why is customer segmentation important?

Particularly for businesses with customers in far-flung locations, customer segmentation is an effective way to finetune your marketing approach. Different demographics exhibit different wants, needs, and buying behaviors. By breaking the larger customer base down into manageable groups, you can focus on a more targeted marketing campaign, product development strategy, and sales model for each segment.

Rather than focusing on the short-term, customer segmentation homes in on long-term customer lifetime value (CLV) for greater impact. Customers that spend more money over time have a higher CLV. Customer segmentation also allows the business to determine which segments are most profitable, which helps with resource allocation. Instead of shooting in the dark, segmentation addresses each group in a way most likely to maximize lifetime value.

How to design a customer segmentation strategy

The first step is to identify what your business hopes to achieve from customer segmentation. This could include developing more useful products, increasing loyalty rates, or improving sales flow. Defining the intended outcomes helps determine the types of segments you'll create. With your goals in mind, you can begin creating customer segments:

  1. Step 1: Gather customer data from internal and external sources. This includes factors like web traffic, revenue, demographics, and purchase frequency. Through customer surveys, you can find out more about product behavior as well. How often do they use your product or service?

  2. Step 2: Sort your customers using targeted variables that are either value-based, needs-based or market-based. The best choice will depend on the diversity of your customer base. When selecting variables, be sure that most of your customer base can be segmented into these categories.

  3. Step 3: Share customer segments with stakeholders. A customer segmentation analysis needs input from stakeholders across the business team, including Marketing, Engineering, Sales, Finance, and Product Development. Validate the initial segments with these professionals before turning to customers for further input. 

Analyzing customer segmentation data

Having grouped customers into logical segments, businesses can uncover new insights with a variety of analytical techniques.

A customer segmentation analysis works to assign long-term value to each segment, with the chief goal being to know how to allocate company resources better. Target high-CLV customers with time and resources while avoiding a high cost of sales on those segments with low frequency and recency scores.

Here are a few factors to track across your customer segments:

Machine learning is also an increasingly common way to track data and discover new segments, using highly advanced algorithms to create feedback loops. Tracking engagement over time helps you see which marketing actions are more profitable within each niche, providing you with greater efficiency overall.

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