Behavioral segmentation explained

What is behavioral segmentation?

Behavioral segmentation is the process of grouping customers based on their behavior rather than who they are. While most brands collect behavioral data, research shows that 42% of marketers don’t segment at all. By the time these insights are analyzed, customer behavior has already shifted. 

Behavioral segmentation closes this gap, enabling brands to respond immediately to high-intent actions such as cart abandonment or usage spikes and deliver relevant experiences at the right moment. 

Why behavioral segmentation matters

Airship research shows that 79% of consumers ignore or delete marketing emails from brands they’ve subscribed to at least half the time. Insights like these signal a clear disconnect between what brands send and what customers find valuable. 

Behavioral segmentation resolves this disconnect and is a strong predictor of when customers are likely to buy, driving business outcomes. With behavioral segmentation, brands move beyond generic messaging and deliver personalized experiences based on what customers actually do. 

Types of behavioral segmentation 

There are several approaches brands use to apply behavioral segmentation across the customer lifecycle. Unlike demographic segmentation — which focuses on who customers are — behavioral segmentation examines how customers interact with your brand, whether in a mobile app or a browser-based experience. 

Purchase behavior 

Purchase behavior segments customers based on when they’re ready to buy, how often they buy, and how much they spend. These transactional signals reveal what motivates customers to purchase and identify opportunities to increase lifetime value.

For example, you might segment customers in the following categories: 

• High-frequency buyers: Reliable customers who buy regularly with your brand
• Occasional purchasers: Sporadic customers who often buy during a sale or seasonal peaks
• First-time buyers: New customers who’ve made a purchase but have yet to return to make a repeat purchase
• High-value spenders: Customers who don’t shop often but have a large order that exceeds your baseline
• Inactive customers: Previously active customers who haven’t purchased in a while

Usage behavior

While purchase behavior is transactional, usage behavior focuses on sustaining the relationship by tracking how customers use your mobile app, product, or service. Segmenting by usage behavior enables you to personalize your messaging based on how often users engage with your brand.  

For example, you might segment usage behavior in the following categories:  

• Heavy users: Power users who utilize your product or service as part of their daily routine
• Medium users: Semiregular users who use your product on occasion but may not explore its full potential
• Light users: Casual browsers who only use your services from time to time and may be at a high risk for churn

Engagement behavior

Engagement behavior segmentation measures the quality and depth of your interactions with customers, not just how often they occur. By analyzing channel preferences, content engagement, and campaign response rates, brands can identify where customers are most receptive across the customer journey. 

Occasion and timing 

Occasion and timing segmentation groups customers based on when they’re likely to engage, such as seasonal peaks, event-driven purchases, or key life moments. Understanding these patterns helps brands tailor campaigns to these events. 

Loyalty and retention status

Behavioral segmentation is sorted by loyalty and retention status. Identifying who is loyal or at risk enables you to implement strategies to protect revenue and maximize customer lifetime value. 

For example, you might segment loyalty and retention status  in the following categories: 

• Active loyalists: Customers who consistently engage and buy often
• At-risk customers: Previously engaged customers who have slowed down in engagement
• Churned customers: Former customers who have stopped buying from your brand
• Win-back candidates: Churned customers whose history with your brand still suggests high recapture potential

Benefit sought 

Benefit sought segmentation groups customers by what they value most, whether that’s convenience, price, quality, or specific features. Unlike assumptions based on demographics, benefit-seeking segmentation is driven by actual behavior and patterns to tailor your messaging to the benefits customers prioritize. 

Where behavioral segmentation data comes from 

Behavioral segmentation data is collected across digital and physical touchpoints — capturing how customers interact through mobile apps, websites, email, SMS, push notifications, and in-store visits. 

Behavioral data is collected through the following methods: 

• App behavior: Tracking screen views, feature usage, in-app actions, session duration, and navigation patterns to understand how customers engage with your mobile experience
• Website behavior: Monitoring page visits, browse patterns, cart activity, search queries, and time on the site to identify purchase intent and content preferences
• Purchase data: Analyzing transaction history, order value, product categories, purchase frequency, and payment methods to segment by buying patterns and lifetime value
• Email/SMS engagement: Measuring opens, clicks, unsubscribes, and conversions from messages to identify which content and offers resonate with each segment
• Push notifications response: Tracking opt-in status, tap-through rates, dismissals, and timing preferences to optimize delivery and reduce notification fatigue
• Zero-party data: Collecting explicit preferences through surveys, quizzes, and profile centers where customers voluntarily share what they want to experience

How to segment customers by behavior

Understanding your customers’ behavior is just the first step. The next step is to turn those insights into segments to create personalized, mobile-first experiences and drive business outcomes. 

1: Define your segmentation goals (with measurable outcomes)

Clarify what business outcomes you’re looking to achieve — e.g., reducing churn, increasing repeat purchases, or improving customer retention. Define success up front and track it with metrics aligned with your goals. 

2: Identify relevant behavioral signals

Once you’ve identified your segmentation goals, identify the relevant behavior signals. For example, if your goal is to increase repeat purchases, check for behavioral signals such as timing, usage, and browsing patterns to understand when customers are likely to buy. 

3: Collect and unify your data

Gather behavioral data from your mobile app, website, email, SMS, and transaction system into a unified customer profile. You can store this data in a customer experience platform to update segments in real time as behaviors shift. 

4: Build your segments 

Create dynamic segments based on behavioral signals you’ve spotted, ensuring that they tie to your business goals. Prioritize segments that represent your highest-value opportunity and most significant revenue risks.

5: Activate across channels

Deliver segment-specific messaging across push notifications, SMS, email, and in-app messages based on behavioral triggers. For example, a cart abandoner might receive a push notification within an hour, an email the next day, and an SMS offer 48 hours later. 

6: Measure and optimize for real results

Track segmentation performance against your original goals. If you’re not hitting your goals, refine your segmentation criteria and continuously test new behavioral triggers to improve performance. 

RFM analysis: A proven behavioral segmentation framework

RFM (recency, frequency, monetary) analysis is a behavioral segmentation framework that gives customers a score based on how recently they purchased, how often they buy, and how much they spend. RFM analysis is commonly used in retail, e-commerce, and subscription services to help understand purchase behavior. Once a customer has received a score, they’re sorted into the following segments: 

• Champions: High scores across all three metrics — your most valuable customers
• Loyal customers: Frequent buyers, but might not be top spenders
• At-risk: Previously valuable customers whose RFM scores have dropped and are at-risk of churn
• Hibernating: Customers who used to buy frequently but haven’t made a purchase recently
• Lost customers: Low scores across all the metrics — your most disengaged customers

Behavioral segmentation strategies that drive results 

Behavioral segmentation is only as effective as the strategy behind it. The most common behavioral segmentation strategies you can use are as follows: 

• Lifecycle-based segmentation: Segmenting customers based on where they are on the customer journey
• Engagement tier segmentation: Identifying how actively customers engage with your brand
• Channel preference segmentation: Reaching customers on their preferred channel
• AI-powered predictive behavior segmentation: Using AI-powered predictive analytics to anticipate customer behavior
• Event-triggered segmentation: Responding to specific customer actions in real time, such as a recent purchase or card abandonment

Common types of behavioral segmentation campaigns

Behavioral segmentation strategies work best when mapped to specific business objections. Here are common types of behavioral segmentation campaigns to consider.

Behavioral segmentation examples by industry 

Every industry uses behavioral segmentation differently. Let’s take a look at a few examples.

Retail and e-commerce

Retailers and e-commerce brands use behavioral segmentation to convert browsing into purchases. For example, retailers may see a customer browsing a category, but they didn’t make a purchase. To encourage the customer to buy, the retailer could send a triggered email with product recommendations, which can drive up to 31% of e-commerce revenue. 

Media and entertainment 

Media and entertainment brands use behavioral segmentation to increase content consumption. For example, if a media brand notices users watched 80% of a series but didn’t finish, they can send a push notification to remind them when the next episode drops. 

Travel and hospitality 

Travel brands use behavioral segmentation to translate research into bookings by responding to price-sensitivity and destination-interest signals. For example, a travel brand might notice a customer searching for flights to Paris, France, and send a price-drop alert email to encourage booking. 

Common behavioral segmentation measurement and pitfalls to avoid

Measure the success of your behavioral segmentation efforts by tracking segment conversation rate, customer lifetime value by segment, retention rate, and segment migration over time to understand performance. 

At the same time, watch for these common behavioral segmentation pitfalls: 

• Over-segmenting
• Static segments
• Siloed data 
• Segments without an activation plan
• Tracking the wrong metrics 

Behavioral segmentation FAQ

Take behavioral segmentation further with Airship

Behavioral segmentation is only powerful if you can act on insights in real time.

With over 15 years of experience in mobile innovation and intelligent orchestration, Airship meets your customers where they are and guides them to where they want to go — all in one seamless platform. Schedule a demo today to learn more.