Everything You Need to Know About Behavioral Segmentation [+ Examples]

As marketers, we‘re on an endless quest to understand what makes our customers tick. We slice and dice by demographics, study their social media habits, and survey them relentlessly. But in our obsession with who our customers are, we often neglect to consider what really matters—how they behave.

Enter behavioral segmentation: the practice of dividing consumers into groups based on their actions. Rather than focusing on static attributes, this approach looks at the dynamic patterns in how customers interact with your brand across channels and over time.

The result is a crystal-clear picture of your customers‘ needs, motivations and preferences. And in a world where 91% of consumers are more likely to shop with brands that provide relevant offers and recommendations, that understanding is pure gold.

In this comprehensive guide, we‘ll dive into everything you need to know about behavioral segmentation, including:

  • Why it‘s a critical piece of any data-driven marketing strategy
  • The four key types of behavioral data to analyze (with examples)
  • How to use behavioral insights to power personalization at scale
  • Tips, tools and best practices for getting started

By the end, you‘ll be equipped with a solid understanding of behavioral segmentation and actionable ideas to begin applying it to your own marketing. Let‘s get started!

Why Behavioral Segmentation Matters

Consumer behavior has always been important to marketers. But in the digital age, it‘s become our most valuable source of customer insight. Every click, download, and purchase tells a story about what that person needs or desires.

The problem is, those signals are scattered across a dizzying array of channels and platforms. Behavioral segmentation is about gathering all of that data into a centralized view, uncovering the patterns, and grouping customers based on meaningful shared behaviors.

And it‘s incredibly effective. Research from McKinsey found that behavioral segmentation can increase marketing ROI by 30% or more:

Behavioral segmentation increases marketing ROI

Specifically, analyzing customer behavior empowers you to:

  • Deliver more relevant experiences. Tailor messaging, offers, and recommendations to align with each group‘s demonstrated interests and preferences.

  • Identify your most valuable customers. Spot the "power users" or frequent purchasers that drive a disproportionate amount of revenue.

  • Anticipate customer needs. Use past behaviors and predictive analytics to surface the right products or content at the perfect moment.

  • Optimize marketing spend. Focus acquisition efforts on the audiences and channels that consistently produce high-value behaviors.

  • Proactively reduce churn. Take action when customers show signs of fading engagement or purchase frequency.

The more you understand what motivates different groups of customers to act, the better you can design experiences that drive results. Which leads us to…

The 4 Types of Behavioral Segmentation

What specific actions should you track and analyze for behavioral segmentation? While the exact data points will vary for every company, most can be grouped into four key categories:

1. Purchasing Behavior

How much customers spend, how often, and on what offers deep insight into their relationship with your brand. Examining patterns in metrics like these can uncover actionable segments:

  • Products or categories purchased: Do certain customers heavily favor a particular product line, collection, or department? For example, a sporting goods retailer might find one group primarily buys running gear, while another spends big on camping equipment.

  • Average order value: Grouping customers by how much they typically spend per purchase can inform personalized offers, tiered discounts, and more.

  • Purchase frequency: How often are customers buying—daily, weekly, monthly, annually? A subscription business might segment by number of monthly orders, while a car dealer could categorize leads by replace-or-repair cycle.

  • Discount usage: Some shoppers routinely buy items on sale, while others are happy to pay full price. Segmenting by price sensitivity and discount responsiveness allows you to optimize promotions.

  • Lifetime value (LTV): Knowing a customer‘s total worth over their lifespan with your brand highlights VIPs and opportunities to boost loyalty.

Example: RFM Analysis

A powerful framework for segmenting by purchase behavior is RFM analysis, which scores customers based on the recency, frequency and monetary value of their transactions:

  • Recency: When was the last purchase?
  • Frequency: How many purchases in a given time period?
  • Monetary: How much have they spent in that time?

Each customer is assigned a score from 1-5 (with 5 being highest) for each factor. Grouping customers with similar scores creates highly actionable segments.

For instance, frequent, high-value buyers (5-5-5) are prime candidates for a loyalty program. A customer with high recency and monetary scores but low frequency (5-2-5) could be enticed to purchase more often with an exclusive discount.

2. Occasion or Timing

When key customer actions occur can be just as insightful as what those actions are. Do certain days, times or seasons correlate with spikes in purchases or engagement? Analyzing behavioral patterns through this lens often reveals:

  • Time of day: Looking at conversion rates by hour and daypart can help optimize ad delivery, email send times, sales outreach and more. A restaurant might find lunchtime diners spend less per check than evening patrons.

  • Day of week: Do some promotions or products drive more action on weekdays versus weekends? Segmenting audiences by when they‘re most likely to interact ensures you‘re delivering the right message at the optimal time.

  • Seasonality: Many businesses have a clear busy season, like the holidays for retailers or summer for a surf shop. But diving into less obvious seasonal trends in your data can unlock hidden opportunities.

  • Purchasing occasions: Amazon has clearly defined occasions like Prime Day that spur massive activity. Digging into your customers‘ unique buying triggers and creating occasions around them can produce similar results.

Example: Birthday Emails

One occasion-based tactic rising in popularity is the birthday email. Many brands now send a special offer or freebie to customers on their big day as a loyalty perk.

Starbucks gives its Rewards members a free food or drink item on their birthday. Sephora offers extra loyalty points, while Nike serves up limited-edition products.

By reaching out at a time that feels personal and celebratory, these brands make customers feel valued—and give them a reason to engage. Birthday emails have 481% higher transaction rates than promotional emails.

3. Benefits Sought

Why do customers ultimately choose your product or service? What are they really trying to accomplish? Uncovering the primary problems you solve for different groups provides endless marketing fodder.

Consider segmenting by:

  • Use cases: How are customers putting your product to work in their lives or businesses? A project management app might have users focused on task tracking, team collaboration, file storage, or workflow automation.

  • Key features: Which elements of your product do customers engage with most? Some may only scratch the surface, while others wring value out of every feature. Segmenting by feature usage can spotlight power users and help troubleshoot churn risks.

  • Customer jobs-to-be-done: What‘s the underlying task or goal customers "hire" your product for? Accounting software buyers, for example, might be trying to organize business finances, prepare for tax season, or sync multiple bank accounts.

  • Emotional benefits: Sometimes the value is less tangible, like reducing buyer‘s remorse or providing peace of mind. An extended warranty provider could segment customers by their top concern, whether that‘s budget, convenience or protecting their investment.

Example: Beneficiaries vs. Intermediaries

Another way to think about benefits sought is whether your customer is an end beneficiary or intermediary. Weight loss programs are a classic example.

The paying customer is often the dieter, motivated by personal appearance, health or wellness benefits. But sometimes a spouse or loved one makes the purchase, driven by a desire to see that person succeed. Slightly different use cases and benefits.

The intermediary‘s perspective is different from the end user, so messaging should be tailored accordingly. Nutrisystem‘s website reflects this with a section on helping a loved one lose weight.

4. Customer Journey Stage

Behavioral data is also a powerful indicator of where a prospect or customer is in their relationship with your brand. Common journey stages to segment by include:

  • Awareness: Browsers who have landed on your site for the first time. High bounce rates and low time on site may indicate they‘re not finding what they need.

  • Consideration: Visitors comparing solutions and consuming educational content like blog posts or webinars. Looking at which content drives them closer to conversion can inform lead nurturing strategy.

  • Purchase: Ready to become a customer, often requesting a demo or starting a free trial. Tracking completion rates and time-to-purchase helps pinpoint obstacles in the process.

  • Adoption: New customers in the first 30/60/90 days. Engagement with onboarding materials, documentation or support channels provides an early signal of future success.

  • Advocacy: Loyal customers who leave glowing reviews, refer friends and follow you on social media. Tap into their enthusiasm to amplify your reach.

Example: Acme Adoption Dashboard

Acme Co. sells business intelligence software. To reduce churn, they segment new customers into four tiers based on adoption behaviors in the first 90 days:

Tier Behaviors 90-Day Retention
1 <10 logins, 0 reports created 30%
2 10-25 logins, 1-3 reports 55%
3 25-50 logins, 3-5 reports, 1+ dashboard 75%
4 >50 logins, >5 reports, 2+ dashboards, invited team 95%

Identifying these behavioral thresholds helps Acme create targeted onboarding flows to move customers into higher tiers and drastically improve retention.

Measuring Behavioral Segmentation Success

Once you start grouping customers by shared behaviors, how do you know it‘s working? Establishing clear goals and KPIs upfront is crucial. Common objectives and metrics include:

  • Engagement: Open rates, click-through rates, and time on site. Are targeted audiences responding to your messaging?
  • Conversions: Purchases, leads generated, content downloads. Is each segment taking desired actions?
  • Average order value: Are high-value segments increasing their spend?
  • Customer lifetime value: Is behavioral targeting boosting loyalty and repeat purchases over time?
  • Churn rate: Are at-risk segments sticking around longer due to proactive outreach?

Keep in mind, the goal of behavioral segmentation is not just to identify meaningful segments, but to tailor experiences and optimize outcomes for each one.

How to Get Started

Now that you understand the types of behavioral data to track, how can you put segmentation into action? Follow these steps:

  1. Align on objectives. Get clear on your goals for behavioral segmentation. What needles are you ultimately trying to move?

  2. Assess your data. Audit the behavioral data you currently collect across web analytics, marketing automation, CRM and other platforms. Where are the gaps?

  3. Start small. Begin with 2-3 simple segments, like one based on LTV and another on product usage. Test offers or messaging targeted to each and see what performs.

  4. Build your tech stack. As you expand, tools like customer data platforms (CDPs) can help unify data into a single view and enable you to build sophisticated segments.

  5. Automate. Leverage machine learning and predictive analytics to process massive amounts of behavioral data in real-time and dynamically match customers to the right experience.

As you dive deeper into behavioral segmentation, remember it‘s an ongoing process. Customer needs evolve, so continuously monitor segments and adapt your approach.

Conclusion

In a hyper-competitive, customer-centric world, behavioral segmentation is a must. Demographics only tell part of the story. How consumers interact with your brand is the true window into their needs, preferences and value.

By grouping customers based on those behaviors, you can consistently deliver relevant experiences that drive action. It‘s the key to boosting conversions, building loyalty and maximizing lifetime value.