Pitching premium products to customers who rarely visit a store doesn’t work. Notify a customer who only ever buys cosmetics about men’s accessories, and the result is the same: no leads, just higher marketing spend for little or no return.
That’s the problem customer segmentation solves. Done well, a segmented campaign can drive up to a 760% increase in revenue, which makes it one of the highest-leverage moves in marketing.
This guide covers what customer segmentation is and how it sharpens your marketing.
What is customer segmentation?
Customer segmentation is the process of dividing customers into groups based on shared factors. Customers with similar characteristics or purchasing behavior get grouped together.
The purpose is to improve marketing by personalizing it. Instead of one message for everyone, each group gets an approach suited to it.
There are several ways to segment customers, and using more than one approach is usually better than relying on a single method. Here are the key ones.
What are the methods for carrying out customer segmentation?
Here are the main ways to segment your customers effectively.
Segmenting by value
Value-based segmentation groups customers by their economic value. Customers with similar economic standing are grouped together, and marketing is targeted accordingly.
Segmenting by needs
This groups customers by the specific needs they express for a product. For instance, customers who show interest in buying a particular product during a specific time form one group.
Priori segmentation
For something broader and more generic, priori segmentation is one of the simplest forms. It groups customers based on the size of the industry or organisation.
Lifecycle segmentation
Lifecycle segmentation groups customers by where they are in the buyer’s journey. Some are just learning about a product, others are considering it, and some have already bought and might buy again. Here’s how to give each group what it needs.
New customers
These customers have just made their first purchase. They’re interested but still unsure about your brand.
Strategy: Give them a warm welcome. Guide them through everything, build trust, and make them feel valued.
Active customers
These are your regulars. They like what you sell and keep coming back.
Strategy: Keep the momentum. Encourage them to explore more of your range and move them toward loyalty.
At-risk customers
These customers are showing signs of leaving. Their purchases are slowing and your emails are going unopened.
Strategy: Run a focused outreach campaign to re-engage them before they slip away.
Churned customers
These customers have gone quiet. No purchases, no engagement.
Strategy: Go for the win-back with a compelling campaign and an offer worth returning for.
Loyal customers
These are your best customers. They don’t just buy, they recommend your brand to others.
Strategy: Give them the VIP treatment and opportunities to spread the word.
Lifecycle segmentation isn’t set-and-forget. Watch for changes in behavior and adjust your approach as customers move between stages.
Following a similar logic, the customer segmentation process can include the following base factors.
What are the common types of customer segments?
Demographics
Demographic segmentation groups customers by age, occupation, gender, income, and similar traits. A group of female customers aged 18 to 28, for example, gets its own targeted strategy separate from other groups.
Geography
Geographic segmentation draws the line by state, city, region, or country.
Behavioral data
Behavioral segmentation is driven by customers’ purchase patterns and spending. Some lean toward premium products, others always look for the cheapest option. Tracking these patterns with user behavior analytics helps identify trends and build highly targeted campaigns.
Psychographics
Psychographic segmentation is based on lifestyle and personality. If a group orders organic products frequently, your store can build a personalised strategy around that segment.
These are the basics. For more examples and ideas, see the full guide to customer segments.
Knowing the methods is useful, but how does it help your business? Here’s the answer.
How segmentation saves marketing effort and generates higher ROI
Two questions come up here: why does customer segmentation analysis matter, and how does it affect marketing?
Segmentation groups customers so those with similar characteristics sit in the same segment. Once that’s done, the marketing team can build strategies specific to each group. Businesses that tailor their offerings to customer segments generate 10 to 15% more revenue than those that don’t, and that gap compounds at scale.
For example
Say you’re advertising an end-of-season sale with heavy discounts on books. Instead of pitching the offer to every customer, you can use the groups you’ve built.
A proper segmentation analysis identifies customers who are frequent buyers or have bought at some point, and you can create specific deals to target them. Getting the right product to the right customer leads to better sales, because you’re giving people what they already want.
Benefits of customer segmentation
Here are the main benefits.
- Improving your product: Segmentation helps you understand customers and their needs, which you can apply to improve your product and raise satisfaction for both existing and new customers.
- Sharper marketing messages: Segmentation lets you target marketing messages precisely, which lifts conversions. 80% of consumers are more likely to buy from a company that offers personalised experiences, and segmentation is what makes that personalisation possible.
- Better sales team performance: Understanding your segments lets your team build strategies for each one. Segmentation gives marketers what they need to pitch products, build sales pages, and write emails without trial and error, which saves time and money and lifts revenue.
In short, segment-based marketing personalises your offering, which drives higher sales and better results.
Want to dig deeper into what your customers actually want? See the guide to customer insights.
Real-world examples and case studies
Here’s how three well-known brands use customer segmentation, and what you can take from each. For more, here are additional examples.
Nike
Nike’s personalisation runs on segmentation:
- It groups customers by fitness level, favourite sports, and shopping habits.
- Its apps, like Nike Run Club, gather rich user data.
- It builds personalised product suggestions and workout plans.
How Nike acts on it:
- Tailored emails for different athlete types (runners get different content than basketball players).
- Personalised in-app challenges that keep users motivated.
- Product launches aimed at specific customer groups.
Results:
- Nike Plus membership rose by 30%.
- Users are more engaged with Nike’s digital platforms.
- Personalised recommendations are driving higher sales.
Grammarly
Grammarly uses segmentation to keep users on track:
- It groups users by writing style, usage frequency, and common mistakes.
- It looks at what users are trying to achieve (an essay versus a work email).
- It tracks which features users rely on most.
Grammarly’s approach:
- Weekly writing reports showing where to improve.
- Premium features suggested to solve a user’s specific writing problems.
- Emails tailored to the individual user.
Results:
- More free users upgrade to premium.
- Users stay longer and use Grammarly more often.
- More premium features sell because users see exactly what they need.
Airbnb
Airbnb uses segmentation to shape the whole travel experience:
- It groups travellers by preferences, booking history, and search behavior.
- It analyses host data to create property segments.
- It draws on user reviews and ratings.
Airbnb’s approach:
- Personalised property suggestions that match what the traveller was looking for.
- Travel guides and experiences tailored to interests, whether food, adventure, or history.
- Pricing suggestions for hosts based on property type and location.
Results:
- More bookings from accurate recommendations.
- Higher uptake of personalised Airbnb Experiences.
- Happier hosts who stay on the platform longer.
Want results like these? Start with behavioral segmentation.
Why is RFM the preferred customer segmentation method?
Whatever your business and marketing plan, a single factor isn’t enough to segment customers well. Say a customer made one high-value purchase. Segment by monetary value alone and they rank near the top.
But if that purchase was long ago and the only one they ever made, targeting them likely gets you nothing. That’s why the RFM method works better.
RFM stands for:
- Recency: When was the last purchase made?
- Frequency: How often does the customer buy?
- Monetary: What’s the value of what they’ve purchased?
RFM is the strongest method because it weighs all three parameters, recency, frequency, and monetary value, before sorting customers into groups.
Now that the best strategy is clear, here’s how to do it in practice.
AI-powered customer segmentation
Traditional segmentation relies on fixed rules: you define the criteria, you build the groups. AI-powered segmentation goes further by finding patterns in your data you might never think to look for.
Instead of manually deciding that “customers who bought X in the last 30 days” form a segment, machine learning models analyse hundreds of behavioral signals at once and surface the groupings with the highest predictive value.
The results back it up. AI-driven segmentation reaches around 90% accuracy, compared to roughly 75% for traditional methods, and companies using AI for marketing report a 37% reduction in costs and a 39% increase in revenue.
For eCommerce and SaaS businesses, that means smarter RFM scoring, better churn prediction, and more precise upsell targeting, without the manual overhead of spreadsheet-based segments.
Difficulties in doing segmentation manually
Segmentation sounds simple, but doing it by hand comes with real challenges.
- However careful your calculations, technical errors or irrelevant data can still creep in.
- The data you’re working from may be months old and no longer useful.
Carry out customer segmentation within seconds using Putler
When you have thousands of customers, segmenting them by hand isn’t practical. That’s where Putler comes in.
As a dedicated RFM analysis and segmentation tool, Putler helps you set up rules and charts to find your best-value customers. Its dashboard lets you pick the period you want the chart to cover.
But is it only RFM? What about segmentation by geography, product, or price?
Customer segmentation examples: how does Putler help segment customers?
Segment based on shopping behavior
Need to export a list of customers segmented by shopping behavior for targeted campaigns? Putler’s RFM segmentation handles it. Pitching email campaigns by hand is a lot of work; Putler cuts the process down. If you’ve built a holiday sale, it gives you a high-level view of the figures and conversion rates, so you can decide which segment to target and how.
For example
Putler is already integrated with your eCommerce store and payment gateways. It segments customers by how recently they bought, how often they buy, and how much they’ve contributed to your store to date.
From there, design your email content and either send the targeted RFM segment email directly from Putler or export the segment and send it from your ESP. No spreadsheets, no manual segmenting. You focus on strategy, reducing churn, and growing revenue. Next is the other type of segmentation Putler provides.
Product-based segmentation
Putler’s dashboard lets you easily locate customers who bought similar products.
For example
Say you need to email customers who bought a mobile phone in the last three months. Visit the dashboard, filter results to the last month, and search for the product. The results show customers who purchased it within that window.
Geography-based segmentation
Pitch products based on where customers are.
For example
Say you’re planning a 4th of July offer aimed only at US customers. The conventional method pitches it to everyone. Putler lets you segment by location, so you can filter results by country and target your offer to that list.
Price-based segmentation
Putler also lets you pitch products by price.
For example
Running email campaigns for higher-priced products like a laptop, fridge, or iPhone? Search by price range, and Putler filters everyone who bought within it. With that list of premium customers ready, targeted segmentation like this yields better results and higher sales.
6 practical ways to use customer segmentation in business
Now that you know how Putler segments customers by different parameters, here are ways to actually use those segments.
Send targeted emails based on shopping behavior
This uses Putler’s RFM segmentation, since RFM segments customers by buying behavior. You could send:
- Time-limited discount coupons to the hibernating segment to tempt a purchase.
- Store credits to at-risk segments that are about to lapse.
- Relationship-building emails to your loyal, champion segment.
Collect feedback
Feedback is a great source of insight. Two segments are worth asking: new customers and customers who requested a refund.
- New customers – Find them in Putler’s Customer Dashboard by setting the Customer Type filter to New (keep the date period at 90 days). Send a feedback email to those who’ve been with you at least 30 days.
- Refunded customers – In the Sales dashboard, set the Status filter to Refund. Email them asking the reason for the refund, hear their concerns, and address them.
Convert lost leads
Lost leads are customers whose subscription went into a Failed state. Find them in the Transactions Dashboard by setting the Status filter to Failed. Send them steps to reinitiate their subscription and close a few more sales.
Run festive discounts
Use location-based segmentation. In the Sales Dashboard, set the Location filter to a country with a festival coming up. Select Ireland, for instance, and send a festive discount to your Irish customers for St. Patrick’s Day.
Upsell relevant products
Say you have a new variant of product A or a complementary product. In the Customers Dashboard, set the Product filter to A and send an upsell email to everyone who bought it. Since it’s a relevant upsell, that segment is more likely to buy the new offering.
Welcome new customers
Like feedback emails, send welcome emails to new customers. In the Customers Dashboard, set the type to New, keep the period to a week or month, and send welcome emails to the new arrivals.
Conclusion
Customer segmentation isn’t a one-time task, it’s an ongoing process. Buying behavior keeps changing, so realising the full value means continually refining your segments and tailoring how you interact with each group.
FAQs
What is customer segmentation?
Customer segmentation is the process of dividing your customer base into groups based on shared characteristics. By grouping people with similar traits, you can tailor your strategies and communications to the specific needs of each group, so you can give customers what they want when they want it.
How do I measure the success of my segmentation strategy?
Track a few key metrics: conversion rates (are your targeted campaigns landing?), Customer Lifetime Value (are your segments becoming more valuable over time?), engagement rates (email opens, click-throughs, social interactions), and overall revenue and profitability. If these are trending up, your segmentation is working.
What tools can I use for customer segmentation?
There are several options. Google Analytics is good for understanding website visitor behavior and segmenting by demographics, interests, and activity. Mailchimp segments subscribers by engagement and purchase history. HubSpot offers segmentation for building targeted marketing lists. Putler makes it simpler with automatic RFM analysis plus filters for location, refund rates, quantity sold, and more, in one click.
How often should I update my customer segments?
A good rule of thumb is every 3 to 6 months. If you’re in a fast-paced industry or see sudden shifts in customer behavior, update more frequently.