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
- - 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.
- - 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.
- - Increased customer loyalty and retention.
- - Higher engagement and conversion rates.
- - Access to new market opportunities.
- - Improved targeting for new product launches.
- - 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.
What are Four Types of Customer Segmentation?
Type of Customer Segmentation
Demographic Segmentation
Geographic Segmentation
Behavioural Segmentation
Psychographic Segmentation
- • 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 : 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.
Some Other Types of 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 user 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
- • 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.
Create Rich Customer Segments And Target The Right Customers In Your Campaigns With TechMonk
TechMonk is an exceptional tool 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.
- • Segmentation : Static, Dynamic, and Drip segmentation of customers.
- • Cohort Segmentation : Segmentation of customers based on Events and duration.
- • RFM Segmentation : Segmentation of customers based on the Recency, Frequency, and Monetary Value of events.
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.
- 5. From the lower right corner of your screen, select the Next button.
- 6. 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
- 7. 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.
- • AI Customer Service : Assist your e-commerce customers with TechMonk’s AI that offers personalised recommendations and answers customer queries.
- • Gen AI Bot : TechMonk’s AI-powered bot can help improve WhatsApp commerce by letting users access your product catalogue, add products to cart, track orders, and more.
- • AI-Powered Campaigns : TechMonk lets you create targeted campaigns to re-engage customers who drop off and abandon carts.
Is TechMonk the right solution to your e-commerce business concerns? Get on a call with us now!
Reach The Right Audience In Your Campaigns With Precise Customer Segmentation
FAQs
What is customer segmentation in e-commerce?
What are the 4 types of customer segmentation?
