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Customer Segmentation

Customer Segmentation Analysis inE-commerce: Definition & Methods

Published onMay 02, 2025

Have you ever noticed shoppers adding items to their carts only to disappear without making a purchase? It sounds frustrating, right?

You dig into the data and discover a pattern: many of these shoppers belong to a 'price-sensitive' crowd, hesitating to check out without a little extra push.

So, what do you do? Try to look at your customers' interests to give them offers that will let them complete a purchase.

Using a customer data platform, you can combine all the customer data to create personalised offers and discounts. This gives you complete visibility into your customers so that you can develop offers that appeal to them.

But, how do you ensure that the right incentives reach the right customers?

Enter customer segmentation analysis. You can approach your customers through personalised marketing by breaking down your audience and understanding this group’s behaviour.

Customer Segmentation Analysis

Let's understand customer segmentation analysis practically. Imagine an e-commerce store that sells everything from ordinary to luxury items. The store divides customer data based on shoppers who love high-end fashion and another filled with budget-conscious buyers who only shop during big sales.

With these insights, the store can create tailored marketing strategies—like exclusive sneak peeks for luxury lovers and special discounts for deal-seekers—making every interaction feel more personal and relevant.

This process is known as customer segmentation analysis. It’s dividing a customer base into different segments based on specific criteria.

What is The Aim of Customer Segmentation in E-commerce

  • Better Marketing Strategies : Customer segmentations help e-commerce businesses identify the specific needs of each targeted segment and create specific marketing strategies, making marketing more engaging.
  • Personalised Experiences : Customer segmentation offers personalisation by categorising customers and providing them with specific offers and experiences, enhancing customer engagement.
  • Customer Satisfaction and Loyalty : Customers are delighted when they get a personalised marketing experience that meets their needs. This leads to high customer satisfaction and loyalty.
  • Resource Allocation and Targeted Promotions : E-commerce businesses can save resources by allocating them appropriately to specific segments, which provides high return values.

Difference Between Customer Segmentation and Market Segmentation

Aspect
Customer Segmentation
Market Segmentation
Definition
Divide an existing customer base into smaller groups based on shared characteristics.
Splits the broader market into distinct groups based on specific criteria.
Purpose
To better understand and cater to current customers' needs and improve e-commerce customer retention.
To identify and target the most promising market segments for growth and expansion.
Focus
Existing customers who have already engaged with the business.
Potential customers and the overall market landscape.
Data Sources
Customer behaviour data, purchase history, engagement metrics, CRM data.
Market research, consumer surveys, industry trends, and general market data.
Criteria for Segmentation
Demographics, buying behaviour, preferences, engagement levels, psychographics.
Demographics, geography, psychographics, income levels, lifestyle, and needs.
Examples
  • Segmenting customers into high-spenders, seasonal buyers, and budget shoppers.
  • Targeting frequent buyers with loyalty rewards.
  • Segmenting the market into health-conscious, luxury, and budget consumers.
  • Launching a new product line for a specific age group or region.
Outcome/Goal
  • Improve customer satisfaction and increase repeat sales
  • Personalize marketing efforts to boost engagement.
  • Capture a larger market share and attract new customers.
  • Position products effectively for maximum appeal.
Marketing Strategies
Personalised email campaigns, exclusive offers, loyalty programs, and retargeting ads.
Broad campaigns for new customer acquisition, region-specific advertising, and new product promotions.
Benefits
  • Increased customer loyalty and retention.
  • Higher engagement and conversion rates.
  • Access to new market opportunities.
  • Improved targeting for new product launches.
Challenges
  • Requires constant data updates and analysis to remain relevant.
  • Risk of over-segmenting and complicating marketing efforts.
  • Needs extensive market research and can be costly.
  • Risk of misjudging market potential or trends.
Tools Used
CRM software, customer feedback platforms, and analytics tools.
Market research reports, industry analysis tools, and data analytics platforms.
Example Businesses
E-commerce platforms focusing on retention and repeat purchases.
New startups entering the market or established businesses launching new products.

What are Four Types of Customer Segmentation?

Cohort Analysis Graph
  • Demographic Segmentation : You segment customers based on simple but powerful details like gender, age, income, education, and occupation. This helps you create a clear profile and connect with them more effectively.
  • Geographic Segmentation : You group customers by their location—whether by country, city, or climate. This approach lets you offer products and promotions that perfectly match regional needs or seasonal trends.
  • [Behavioural Segmentation](https://techmonk.io/blog/behavioural-segmentation) : You analyse customers' shopping habits, such as purchase frequency, spending habits, brand loyalty, and product use. This lets you identify patterns and customise your marketing to match these habits.
  • Psychographic Segmentation : You get to know your customers personally by focusing on their interests, values, lifestyle, and personality traits. This helps you understand what drives them and personalise their experiences even more.

What are Four Types of Customer Segmentation?

Apart from the four main customer segmentation categories, these are a few more categories that companies follow:

  • Engagement Segmentation : You look at how customers interact with your brand—whether they open your emails, visit your website, or engage on social media. With this insight, you optimise your communication and keep customers engaged.
  • Needs-Based Segmentation : You categorise customers by the specific problems they’re trying to solve or their needs. This lets you develop targeted messaging and create products that directly address their concerns.

How Different Types of Customer Segmentation Benefits

1. Tailored Customer Experiences:

Segmentation helps businesses create personalised experiences that connect with targetted customer groups. Instead of a generic approach, you can customise everything from product recommendations to marketing messages to make each interaction more meaningful.

2. Increased Engagement and Conversions:

Engagement increases when you understand each segment's needs and deliver exactly that. People stick around longer, bounce rates drop, and conversions increase because you give customers what they want

3. Better Resource Management:

Segmentation makes spending your marketing and product development budgets easier. You can focus on strategies that impact each group most, saving money and maximising results.

Methods for Conducting Customer Segmentation Analysis

Collecting accurate and comprehensive data is the foundation of customer segmentation analysis. Here are some common techniques:

Methods for Conducting Customer Segmentation Analysis

1. Customer Surveys

Customer surveys are a common way to do customer segmentation. They ask questions about demographics, buying preferences, and other details.

Surveys ask customers about their likes, behaviours, and backgrounds. Businesses can send surveys by email, social media, or directly on the website.

  • Purpose : Surveys give insights into what customers need and expect. They help businesses understand what drives purchases. For example, a survey might show that some customers prefer eco-friendly products. This can guide future marketing.
  • Example : An online store could ask customers about their shopping habits, favourite products, and spending levels. This data helps the store offer products that fit each group’s interests.

2. Web Analytics Tools

Web analytical tools help businesses track and analyse user interaction with their websites. These tools collect data on page views, bounce rates, session duration, and user navigation paths.

  • Purpose : Web analytics tools provide insights into consumer behaviour, revealing which product pages are most popular or where customers drop off during the shopping process. This information helps identify segments based on browsing patterns.
  • Example : An e-commerce store might discover that a group of users consistently browses premium products but rarely makes purchases, indicating a potential “window-shopping” segment.

3. Analysing Data

CRM tools help e-commerce businesses organise and analyse customer data.

  • Purpose : CRM tools let businesses track customer interactions, group customers, and create reports. This helps them understand buying behaviours and engagement. Data analysis tools show trends, making it easier to find different customer groups.
  • Example : An e-commerce business can use CRM tools to identify high-value customers based on purchase frequency and order size. They can then create targeted AI-powered campaigns for their loyal customers.

4. Applying Machine Learning for Advanced Segmentation

CRM tools help e-commerce businesses organise and analyse customer data.

  • Clustering Algorithms : Algorithms like K-means clustering group customers by similarities, such as buying history, site activity, or product preferences. Clustering is unsupervised, so it doesn’t need preset categories.
  • Predictive Modeling : Predictive modelling uses past data to predict future behaviours. It helps find customer groups likely to respond well to specific campaigns or offers.

Customer Segmentation Examples For E-Commerce

1. Frequent Shoppers

Your frequent shoppers are your most valuable customers. They buy more often and bring in the most revenue. With behavioural market segmentation. you can easily spot these loyal customers and treat them with special offers during sales or new product launches.

You can use AI agents for e-commerce to send these offers automatically, making sure your best customers feel noticed. That means more customer loyalty and more sales.

2. Idle or Inactive Customers

Not all customers stick around. Some stop engaging over time. But how do you know who’s gone quiet?

Segmentation tools like TechMonk help you find those inactive customers so you can remove them from certain campaigns. Why waste time and money on the wrong crowd? Instead, focus your efforts on the ones who are still paying attention.

3. Milestones Achieved

Want to reward customers for reaching loyalty milestones like reward points or higher tiers? You can track these moments and send out exclusive rewards.

It’s a simple way to say, 'Thanks for sticking with us.' Plus, it motivates your customers to stay engaged and shop more often.

4. Customer Location

Your customers live in different cities or regions. Then why send everyone the same messages and offers?

With location-based customer segmentation marketing, you can send offers based on local events or holidays. That way, your customers get deals that matter to them. It helps you stand out—and makes them feel like part of a community.

Create Rich Customer Segments And Target The Right Customers In Your Campaigns With TechMonk

TechMonk homepage

TechMonk is a first-of-its-kind agent-as-a-service full-stack customer engagement platform. It has all the right tools for e-commerce businesses for exceptional sales operations, smarter support, and unparalleled marketing automation.

It’s a full-stack marketing toolkit with tools for segmenting your customers with the right customer data. Its CDP for e-commerce brings in data from CRMs, logistics tools, e-commerce platforms, customer support interactions, and ongoing events. Therefore, it gives you a 360-degree view of your customers. Moreover, it makes user segmentation precise and granular.

How does it manage to do all that without human input?

  • Segmentation : Static, Dynamic, and Drip segmentation of customers.Drip segmentation on TechMonk
  • Cohort Analysis : Segmentation of customers based on Events and duration.Cohort Analysis on TechMonk
  • RFM Segmentation :Segmentation of customers based on the Recency, Frequency, and Monetary Value of events.RFM Segmentation on TechMonk
  • AI-Powered Segmentation : Use the prompt bar to type in the customer segment you wish to create and segment customers with AI in seconds.AI-powered customer segmentation in TechMonk

Creating meaningful customer segments is simple with TechMonk. Here’s how you can segment your customers based on the events' Recency, Frequency, and Monetary value.

  • 1. Launch RFM from TechMonk's sidebar. Then, in the upper right corner of your screen, select the Create RFM button.
  • 2. In the corresponding field, give your segment a name.
  • 3. Select the event for which you want to create the RFM section under Select Recency & Frequency Event.
  • 4. Enter the Start Date and End Date based on your needs and complete the remaining fields.

You can also add these additional filters to your segments if needed.

  • 5. Click the Add Filter option. Next, choose the OR or AND option as needed. Fill in the following boxes as necessary.
    • Select Attribute: Choose Customer Attributes or Page Data attributes from the list.
    • Select Condition: Choose between Is, Contains, and Is Not.
    • Enter Value: Type in a value based on the conditions you selected before.
  • 6. In the ‘Do you want to use Existing Segment?’ field, you can choose any existing segment.

TechMonk also lets you micro-segment your customers with its Advanced Filters.

  • 7. From the bottom-left of the screen, choose Add Advanced Filter button.
  • 8. You can also choose any desired timeline for segmentation.
  • 9. On both the Customer and Event fields, you can add as many filters as needed.TechMonk's Advanced Filters For RFM Analysis
  • 10. From the lower right corner of your screen, select the Next button.
  • 11. The user segments based on the RFM event are displayed here. It segments your customers as follows.
    • • About to sleep
    • • Price-sensitive
    • • Loyal customers
    • • Promising customers
    • • Recent customers
    • • Customers who need attention
    TechMonk’s RFM Segmentation
  • 10. To save the user section, click the Save section button.

After detailed segmentation of customers, e-commerce businesses can target customers in their customers to reach them with the right offers and messages. As a result, the campaigns help convert and engage customers, maximising the ROI of campaigns.

TechMonk isn’t just a simple tool for customer segmentation. It also includes more features dedicated to e-commerce businesses.

Even though filled with exciting features, TechMonk is highly affordable. The pricing plans starting at just ₹30,000 per month.

Is TechMonk the right solution to your e-commerce business concerns? Get on a call with us to know!

Reach The Right Audience In Your Campaigns With Precise Customer Segmentation

FAQs

  • What is customer segmentation in e-commerce?

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  • What are the 4 types of customer segmentation?

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  • What are the benefits of customer segmentation analysis?

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  • What are Four Types of Customer Segmentation?

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  • What is the customer segment of e-commerce?

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