Customer Segmentation 101 | What is Customer Segmentation

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Have you ever wondered why some brands seem to know exactly what you want?

Consider a scenario: a subscription-based nutritional supplement company that recognizes your unique health goals. When you log in, you receive personalized recommendations based on your past purchases, showcasing how customer segmentation delivers relevant products tailored to your wellness journey.

That’s the magic of customer segmentation!

By understanding their customers’ preferences, businesses can create personalized experiences that resonate deeply.

In fact, companies that excel at customer segmentation can see up to a 760% increase in revenue from targeted campaigns (HubSpot). So, let’s understand what customer segmentation is, how it works, and why it’s essential for your business.

What is Customer Segmentation?

Customer segmentation is the process of dividing a customer base into smaller groups of individuals with similar needs or characteristics. This allows a business to create targeted campaigns and tailor products or services to specific segments, thereby enabling data driven marketing.

There are many ways to segment a customer base, and the specific approach taken will depend on the business and its goals.  

Some common ways to segment customers include:

  • Demographic characteristics, such as age, gender, income, and education level
  • Geographic location, such as country, region, or city
  • Behavioral characteristics, such as purchasing habits and loyalty
  • Psychological characteristics, such as values, attitudes, and motivations

Why businesses need to segment their customers?

Well, by understanding the characteristics of different customer segments, businesses can tailor their products, services, and marketing efforts better to meet the needs and preferences of those segments. This can help businesses to attract and retain more customers and ultimately drive growth and success.

To perform customer segmentation, a company will typically gather customer data, and technology plays a pivotal role in shaping how businesses approach customer segmentation today. Advanced analytics tools and machine learning algorithms enable companies to process vast amounts of data quickly and efficiently.

This allows for more precise segmentation based on real-time insights into customer behavior and preferences. For instance, businesses can leverage CRM systems to analyze purchasing patterns or social media interactions, leading to more informed marketing decisions.

customer senmentation
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Customer Segmentation vs Market Segmentation  

Customer segmentation and market segmentation are closely related concepts in marketing that involve dividing a market into smaller groups of consumers based on common characteristics or needs. However, there are some key differences between the two concepts.

Market segmentation involves dividing a larger market into smaller groups of consumers with similar needs or characteristics. This can be used to identify opportunities for new products or services, or to target marketing efforts to specific groups of consumers.

On the other hand, customer segmentation is focused on understanding and meeting the needs of a company's specific customer base.

Overall, customer segmentation and market segmentation are both useful tools for understanding and meeting the needs of customers, but they are used for different purposes and at different stages of the customer journey.

For instance, if a fitness brand uses customer segmentation, it might find that its existing clients are primarily health-conscious millennials who prefer organic products. In contrast, through market segmentation, the same brand could discover that there’s a growing interest among older adults in fitness solutions tailored to their age group.  By leveraging both strategies effectively, businesses can create targeted marketing efforts that resonate with their audiences and drive better results.  

Types of Customer Segmentation  

Customer segmentation can be categorized into these types:

  1. Demographic segmentation
  1. Behavioral segmentation
  1. Geographical segmentation
  1. Psychographic segmentation
  1. Interest-based segmentation

Also, read – RFM Analysis

Segmentation Type Characteristics Example
Demographic Segmentation Dividing customers based on characteristics such as age, gender, income, education, and occupation A fashion retailer might target young, fashionable women with high disposable incomes, while a home improvement store might target middle-aged men focusing on DIY projects.
Behavioral Segmentation Dividing customers based on their behaviors and preferences, such as their purchasing habits, loyalty to the brand, and engagement with the company A gym might target customers who are regular attendees and have a history of signing up for multiple classes, while a coffee shop might target customers who visit frequently and spend more on specialty drinks.
Geographical Segmentation Dividing customers based on where they live, such as by country, region, or city A clothing company might target customers in urban areas with a focus on trendy fashion, while an outdoor gear retailer might target customers in rural areas with a focus on outdoor activities.
Psychographic Segmentation Dividing customers based on their attitudes, values, lifestyles, and personality traits A luxury car dealership might target customers who value exclusivity and status, while a natural food store might target customers who prioritize health and wellness.
Interest-Based Segmentation Dividing customers based on their interests or hobbies A sports apparel company might target avid runners, while a home decor store might target customers interested in interior design.

Benefits of Customer Segmentation  

Understanding your customers is key to business success. By segmenting your audience, you can tailor strategies that not only keep them coming back but also boost revenue and create personalized experiences. Here is how this approach can transform your business:  

  • Improved Retention: When businesses segment their customers, they can craft tailored retention strategies that resonate with each group. This personalized approach helps keep customers happy and encourages them to stick around longer.
  • Reduced Churn: Customer segmentation allows companies to spot at-risk segments before they leave. By targeting these groups with specific retention efforts, businesses can effectively lower their overall churn rates.
  • Increased Revenue: By concentrating on high-value segments, businesses can boost their sales. Identifying and focusing on the most profitable customers ensures that marketing efforts yield better results.
  • Improved Marketing Efficiency: Tailoring marketing campaigns to specific customer segments enhances the efficiency of ad spend. In fact, companies that excel in segmentation can generate 77% more ROI from personalized (email) marketing.
  • Better Product Development: Understanding different customer segments helps inform product development. This insight allows companies to create products that truly meet their customers' needs and preferences.
  • Increased Personalization: Knowing what different segments want enables businesses to personalize their interactions. This leads to better customer experiences and fosters stronger loyalty over time.

Tools like Saras Analytics allow you to leverage the power of customer segmentation, thereby refining and improving the ROI of your marketing campaigns.  Read more: Customer Analytics  

Prerequisite of Customer Segmentation  

To successfully implement customer segmentation, you need a solid foundation. Here are the key elements to consider:

  • Clean Data: Start with accurate, well-organized data. If your data is messy, your segmentation will be too, leading to poor decisions.
  • Robust Analytics: Strong analytics capabilities are essential. They help you uncover trends and insights that drive effective segmentation strategies.
  • Data Warehousing: A good data warehouse is like a central hub for all your information. It keeps everything organized and accessible for analysis.
  • Data Integration: Integrating data from various sources gives you a complete picture of your customers. This holistic view is crucial for meaningful segmentation.
  • Ongoing Analysis: Regularly revisiting and analyzing your segmented data ensures you stay aligned with evolving customer needs.

With Saras Analytics’ ETL and BI tools, you can streamline this process, making it easier to harness the power of customer segmentation.  

How to do Customer Segmentation  

Customer segmentation in six steps:

  1. Define your objective: Identify the specific group of customers you want to target with your marketing efforts. This will help you focus your segmentation efforts and ensure that you are reaching the right audience.
  1. Collect and integrate data: Use various methods, such as surveys, focus groups, and online analytics, to gather data about your customers. This information should include demographics, behavior, and preferences. You can use APIs, data pipelines to connect data sources to a central data warehouse. Also, read – Modern Data Stack
  1. Identify key variables: Use your gathered information to identify patterns and trends in your customer data. Look for common characteristics and behaviors among different groups of customers. Also, read – Customer Data Platform
  1. Use tools/analytics to segment customers: Select the variables that will be most relevant for your marketing efforts. These might include demographics, behavior, and preferences.
  1. Validate and refine segments: Use your identified segmentation variables to create detailed profiles of each segment within your target market. These profiles should include information about each segment's characteristics, behavior, and preferences.
  1. Develop targeted marketing campaigns: Use the segment profiles you have created to develop targeted marketing campaigns that speak directly to each segment's characteristics, behavior, and preferences. This will help ensure that your marketing efforts are more effective and resonant with your target audience.

Methods of Customer Segmentation

  1. Surveys and questionnaires: Surveys and questionnaires are a common customer segmentation method. They involve asking customers a series of questions about their demographics, preferences, buying habits, and satisfaction levels. This information can then be used to segment customers into different groups based on their responses. Surveys can be conducted in person, over the phone, or online.
  1. Focus groups: Focus groups involve gathering a small group of customers together to discuss a particular product or service. The group is usually led by a moderator who guides the discussion and asks questions. The information gathered from focus groups can be used to segment customers based on their opinions and attitudes towards a product or service.
  1. Behavioral tracking: Behavioral tracking involves collecting data on how customers interact with a company's website, social media pages, and mobile app. This data can be used to segment customers based on their online behavior, such as the pages they visit, the products they view, and their actions.
  1. Social media analysis: Social media analysis involves studying customer interactions and conversations on social media platforms. This can include analyzing comments, likes, shares, and other forms of engagement. The information gathered can be used to segment customers based on their interests, preferences, and opinions.
  1. Data mining and analysis: Data mining and analysis involves using software tools to analyze large amounts of data from a variety of sources, such as customer databases, sales records, and website logs. This information can be used to segment customers based on their demographics, buying habits, and other characteristics. Data mining and analysis can also be used to identify patterns and trends in customer behavior.

Overall, customer segmentation requires a combination of data gathering and analysis to identify and understand different segments within a customer base. By following these steps, companies can create targeted marketing campaigns that are more likely to resonate with their target audience and drive business growth.

Challenges in Customer Segmentation  

There are a few challenges that businesses may face when implementing customer segmentation:

  1. Data collection: To accurately segment customers, businesses need to have access to a large amount of data. This may require investing in tools and systems to track and analyze customer data, such as website analytics platforms or customer relationship management (CRM) software. Read more: Data Warehousing
  1. Changing demographics: Customer demographics can change over time, making it difficult to maintain accurate segmentation. For example, a young professional customer one year may become a young family the next year. Businesses need to continuously monitor and update their segmentation to ensure that it remains accurate.
  1. Overlapping segments: It is possible for customers to belong to multiple segments based on different characteristics. For example, a customer who is a high-income earner may also be a senior citizen. This can make it challenging to determine the most appropriate marketing and sales efforts for these customers.
  1. Limited resources: Segmenting customers requires significant time and resources. Businesses must carefully consider whether customer segmentation's benefits outweigh the costs before implementing it.
  1. Privacy concerns: Customers may be hesitant to share their personal information with businesses due to privacy concerns. This can make it difficult for businesses to obtain the data needed for customer segmentation. Businesses should strive to be transparent about how they collect and use customer data and to obtain customer consent when necessary.

Examples of Customer Segmentation  

OTP-Based Clothing Business

Let’s take the example of a clothing retailer that follows the one-time purchase business model. Based on customer segmentation, they realized that their customers can be divided into three distinct segments: fashion-forward young adults, eco-conscious shoppers, and budget-savvy families.

For the fashion-forward young adults, the retailer came up with collections featuring the latest styles and limited-edition pieces. They run social media campaigns showcasing influencers wearing their outfits, creating a buzz that resonates with this group.

Meanwhile, for the eco-conscious shoppers, they highlight sustainable materials and ethical production methods in their marketing. This segment appreciates transparency and values brands that align with their beliefs.

Lastly, for budget-savvy families, the retailer offers seasonal sales and family bundles, ensuring they feel valued without overspending. By tailoring their marketing strategies to each group, the retailer not only enhances customer satisfaction but also drives sales effectively.

The result: By identifying distinct groups, the retailer can personalize their marketing strategies to resonate with each segment. For instance, targeted social media campaigns for young adults featuring the latest trends can lead to higher engagement rates and increased sales. This focused approach not only enhances customer satisfaction but also leads to brand loyalty, as customers feel understood and valued. Ultimately, this results in a significant boost in repeat purchases and overall revenue.

Subscription-Based Nutrition Supplement Business

Now, let’s look at a subscription-based nutrition supplement company that caters to health enthusiasts. They’ve segmented their customers into three key groups: fitness fanatics, busy professionals, and wellness seekers.

For the fitness fanatics, the company offers high-protein supplements and pre-workout boosters. They send personalized emails featuring workout tips and recipes to keep this segment engaged.

For busy professionals, they promote convenient meal replacement shakes that fit seamlessly into hectic schedules, emphasizing quick delivery and ease of use. This group appreciates efficiency and often responds well to time-saving solutions. Lastly, for the wellness seekers, the company focuses on holistic health products like vitamins and herbal supplements. They create content around wellness tips and mindfulness practices to resonate with this audience.

The result: Using the same method, the health supplement company can create tailored product offerings and marketing messages. For example, sending personalized emails with workout tips to fitness enthusiasts can increase engagement and retention rates.  

Moreover, by addressing the specific needs of busy professionals with convenient meal replacements, the company can enhance customer satisfaction and reduce churn. This strategic segmentation not only drives higher conversion rates but also maximizes customer lifetime value, leading to sustained growth.  

Customer Segmentation as a pre-requisite for CRM

Customer segmentation is often a prerequisite for implementing a customer relationship management (CRM) system. Before implementing a CRM system, it is important for a company to have a clear understanding of its customer base and to have segmented its customers into different groups with similar needs or characteristics. This allows the company to tailor its marketing efforts and product offerings better to meet the needs of specific customer groups and optimize resource allocation.

Once the customer segments have been identified, a company can use a CRM system to track and manage interactions with each segment and analyze customer behavior, preferences, and needs. This can help the company to engage with its customers more effectively and to build stronger relationships with them.

Customer Segmentation and Machine Learning

Machine learning can be used to support customer segmentation by automating the process of analyzing customer data and identifying patterns and trends that may not be immediately apparent to human analysts. This can help companies to identify customer segments more accurately and drive their marketing campaigns more effectively.

Several machine learning techniques can be used for customer segmentation, including clustering algorithms, decision trees, and neural networks. These algorithms can analyze large amounts of customer data and identify patterns and relationships that can be used to create segments.

Also, read:

  1. Customer Analytics
  1. Realtime Analytics
  1. Marketing Analytics
  1. eCommerce Analytics
  1. Subscription Analytics

For example, a company might use a clustering algorithm to analyze customer data such as demographics, purchase history, and product preferences. The algorithm might identify several clusters of customers with similar characteristics, which could then be used to create customer segments.

Using a Data Warehouse for Customer Segmentation

Consolidating all data in a data warehouse can help with customer segmentation and various other use cases. By consolidating all of a company's data in a data warehouse, it becomes easier to analyze and understand customer behavior and preferences, which can be useful for customer segmentation.Having all data in a single location also makes it easier to create a holistic profile of a company's profitability, attribution, and ROI.

For example, a company could use data from multiple sources, such as sales, customer, and marketing data, to understand which products or marketing campaigns are the most profitable and where the best opportunities for growth lie.In addition, a data warehouse can help a company visualize the customer journey map and identify opportunities to improve the customer experience.

For example, a company could use data from a data warehouse to understand how customers interact with different channels (e.g. website, social media, email) and identify areas where the customer experience could be improved.

There are several benefits to consolidating all data in a data warehouse

  1. Improved data quality: By storing all data in a centralized location, companies can improve the quality of their data by standardizing data definitions, removing duplicate records, and ensuring data is accurately and consistently captured.
  1. Enhanced data security: A data warehouse can provide a secure, centralized location for storing data, which can help reduce the risk of data breaches and protect sensitive information.
  1. Increased efficiency: Consolidating data in a data warehouse can help streamline data management processes and reduce the time and resources needed to access and analyze data.
  1. Enhanced data accessibility: By storing all data in a single location, companies can make it easier for different teams and departments to access and analyze data, improving collaboration and decision-making.
  1. Greater scalability: As a company grows and generates more data, a data warehouse can scale to meet the increased data needs, ensuring that the company can continue to access and analyze data effectively.

Overall, consolidating all data in a data warehouse can provide many benefits to companies, including improved data quality, enhanced data security, increased efficiency, enhanced data accessibility, and greater scalability.

Conclusion

Undoubtedly, customer segmentation is a crucial strategy for identifying and targeting your most profitable customers. Partnering with a company like Saras Analytics can provide the necessary support and expertise to set up a strong data foundation, track and analyze customer behavior, and ultimately drive growth for your business.

At Saras Analytics, we offer a complete approach to customer segmentation that really makes a difference. From our ETL processes that help you integrate data from various sources to providing insights that lead to actionable segmentation, we help you create targeted marketing strategies that resonate with your audience. By knowing what each segment wants, you can tailor your offerings and communications effectively.  

Contact us today to learn how we can help take your customer segmentation efforts to the next level.

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