What is Behavioral Marketing and Why is it Important

Reading Time: 10 minutes

Most marketers still rely on surface-level tactics; demographics, gut instinct, and scheduled campaigns. But that’s no longer enough since customers now expect instant relevance. 

A behavior-based marketing strategy flips the script. Instead of guessing what customers want, it watches what they do and responds in real time. Behavioral data helps you identify your audience’s behavioral patterns, browsing history, and abandoned carts, tailor marketing efforts, and reach out to them with targeted ads and email marketing campaigns. 

This guide explains how behavioral marketing works step-by-step (along with behavioral triggers), why it outperforms traditional targeting, and provides behavioral marketing examples from top brands. 

Let’s start with the behavioral marketing definition first.

What is Behavioral Marketing?

Behavioral marketing is a strategy that uses data about users’ actions—like what they click, how long they stay, what they abandon, and what they revisit—to personalize experiences in real time. It’s not about who the customer is (age, gender, location) but what they’re doing and what those actions reveal about their intent.

Think of it as the difference between shouting in a crowd vs. whispering the right thing to the right person at the right moment.

In fact, Google’s shift to GA4 (Google Analytics 4) is largely a move toward behavioral measurement: it now emphasizes events and user journeys over traditional sessions and pageviews. This tells you that the industry is fully aligning around actions over attributes.

How Behavioral Marketing Works (Step-by-Step Guide)

In the 1960s Mad Men era, marketing was broad. You placed one ad and hoped it worked. Today, that’s laughable. 

In 2025, Fetch, an app where users snap photos of their receipts for rewards, became one of the most behaviorally rich marketing engines. 

With 11 million receipts scanned daily, Fetch gives brands access to real, item-level purchase data—what people actually bought, not just what they clicked. Campaigns run inside the app have led to a 5–15% increase in first-time purchases and up to 40% growth in repeat purchases, mainly because they respond faster than traditional ad channels.

This same approach—sending the right offer based on what someone does—is now driving better ecommerce, streaming, and travel results. The most effective marketers don’t wait around. They track real actions and respond quickly, with valid, relevant offers at the right time.

Here’s how behavioral marketing works step-by-step: 

Step #1: Collect Behavioral Data 

Behavioral marketing starts with collecting data about real user actions: what they click, where they scroll, what they ignore, what they buy, and how they leave.

Think of it like being a bartender at a busy local joint. You don’t ask every patron to fill out a form. You just notice: she always orders a martini, he checks the football scores before ordering, that couple only comes on Fridays. It’s the same online—watch, record, and learn from real behavior.

Here are the most common (and useful) types of behavioral data:

Pageviews & session time: 

This tells you what content or category pages attract attention, what paths users take through your site, and where they drop off. If 60% of users visit your homepage and then bounce in under 10 seconds, you’ve got a problem—likely messaging, loading speed, or visual hierarchy.

How to track it: Use tools like GA4 and FigPii to see average session duration, bounce rate, and user flows. Use exploration reports in GA4 or session recordings in FigPii to spot patterns, like users skipping key content.

For example, this session shows a user visiting a blog post, frequently switching tabs, and hovering over navigation and CTAs, which indicates distraction or low engagement. Session recordings like this help identify attention drop-off points and test areas for improving on-page retention.

FigPii session recording session to identify user behavior (Source)

Clicks & hovers: 

You can see what CTAs, product tiles, or filters users are drawn to and what they overlook. For example, if users hover over a “Size Guide” link but do not click, maybe it’s too small or unhelpful.

How to track it: Use heatmaps and click maps in FigPii, Hotjar, or Fullstory. FigPii’s heatmaps are scroll and device-specific, helping you compare behavior on mobile vs. desktop.

This heatmap visualizes where users move their mouse the most. Warmer colors (red, orange, yellow) show high activity—places users focus on or are likely to click. Cooler colors (blue, green) indicate low engagement.

In the example above, the top nav bar and “Contact Us” button (red spots) receive the most attention, while the body text and lower areas receive less. You can use this insight to reposition CTAs, fix ignored sections, or reduce distractions.

Purchase and cart activity: 

Behavior around cart activity reveals user intent. For example, someone adding three items and bouncing may be price-checking or confused about shipping. Tracking which items are abandoned often helps shape upsell, urgency messaging, or retargeting strategies.

How to track it:

Tools like GA4 enhanced ecommerce and Shopify’s native analytics let you track:

• Add to cart rates
• Checkout initiation
• Drop-off points in multi-step checkout
• Final conversion

Search queries: 

On-site search behavior reveals what users want, but can’t immediately find. If 200 people a week are typing “gift cards” and you don’t offer them (or hide the page), that’s missed revenue.

How to track it: Enable site search tracking in GA4, or use Shopify’s search analytics. For deeper insight, combine this with session recordings in FigPii to watch how users behave after searching. Do they convert? Bounce? Filter heavily?

Email & ad interactions: 

You’ll know who opened, clicked, converted, or bounced—critical for mapping behavioral segments like “engaged non-buyers” or “email loyalists.” This also helps test messaging effectiveness and CTA placement.

How to track it: Track email performance with your email service provider (like Klaviyo or Mailchimp), but pull that behavioral data into a central source for unified user profiles.

Device, location, time: 

Knowing when and where people browse (and on what device) helps you personalize UX and optimize send times. For instance, if 80% of late-night traffic is from mobile, your mobile experience better be airtight.

How to track it: GA4 provides these insights, but FigPii’s segmentation filters let you break test data down by device, location, or time of day. You can A/B test a mobile-only variant and isolate the results.

Step #2: Segment Users by Behavior 

Once you’ve collected behavioral data, it’s time to stop treating all users the same. Behavioral segmentation means grouping users based on their actions, not who they are. That way, you send the right message at the right time to the right person.

Think of it like a gym. One member comes daily at 6 AM and never misses leg day. Another shows up once a month and only uses the treadmill. Would you give both the same workout plan or offer? Likely not—and the same goes for your users.

Here are the most useful ways to segment based on behavior:

• New site visitors vs. returning visitors: The goal here is not to treat every visitor like they’re new. For example,
  • New users don’t know your brand yet. Focus on low-friction trust-builders: welcome popups, first-time discount codes, or a “Why choose us” section above the fold.
    
  • On the other hand, returning users already showed interest, so drop the hard sell and offer targeted messaging. Show recently viewed items, notify them of price drops, or greet them with “Welcome back” messaging that resumes where they left off.

• Cart abandoners: These users showed strong purchase intent but didn’t complete checkout, often due to price, distraction, or friction (e.g., forced account creation).
  • Pro tip: Send follow-up emails within 1–3 hours while interest remains fresh. Include visuals of abandoned items, stock urgency (“Only 2 left!”), or limited-time discounts.

For example, Joslin Studio sends a beautifully branded cart recovery email with the exact product left behind, a 15% discount code, and a copy that blends scarcity with emotional pull: “We only produce very small runs, don’t miss out… Are you in love?”

• High-intent browsers: These users engage deeply but haven’t converted. They might visit the same item several times, spend 5+ minutes on a product page, or explore size guides and reviews. Treat them like they’re in the “consideration” phase—retarget with product benefit callouts, third-party reviews, or price drop alerts.
  • Pro tip: Use behavior-triggered Facebook and Google retargeting ads that show, for example, “Still thinking about this?” or “Over 2,100 people bought this last week.”

• Purchase frequency: Not all customers are created equal. Segment by:
  • One-time buyers: Nudge them with customer loyalty incentives or replenishment reminders.
    
  • VIP/repeat buyers: Make them feel exclusive with early access, sneak peeks, or thank-you perks.
  • Churned customers (who have not purchased in 3–6 months): Win them back with “We miss you” offers or personalized product recommendations.

• Feature usage (for SaaS or product-based apps): This applies to users interacting with specific product features—some adopt fast, others don’t.
  • New users: Track where they drop off in onboarding. If they skip a key feature, trigger a walkthrough or help tooltip.
  • Power users: Identify what they use most and upsell add-ons or premium plans aligned with that usage.
  • Inactive users: Flag non-engagement and send reactivation nudges based on what they ignored.

Netflix is an oft-repeated example, but remains one of the best use cases of segmentation. The streaming platform is famous for recommending shows to its viewers based on their viewing history (aka customer’s online behavior). 

If you binge K-dramas, expect more of that genre. If you skip intros or rewatch a scene, that behavior gets noted. Their segmentation engine is so advanced that it runs 1,300+ recommendation clusters at any given time.

Netflix goes a step further and uses image recognition to personalize what you see. It tracks the scenes, moods, and types of visuals you watch or rewatch, then adjusts the artwork. 

So if you’re into thrillers, Stranger Things might show you a dark poster with Eleven’s bloody nose. But if you prefer nostalgic adventures, you’ll probably see the boys riding bikes. 

Using image recognition and behavioral data, Netflix shows different artwork for the same show based on what you’re most likely to click (Source). 

Step #3: Trigger Personalized Actions

Now that you’ve collected behavioral data and segmented users based on what they do, the next step is to act on it in real time. This is where behavioral marketing efforts turn into results: you trigger timely personalized messages and offers to appeal to your target audience. 

Here are some of the most effective types of behavioral marketing triggers you can use:

1. Abandoned cart reminder:

If a user adds an item to the cart but doesn’t complete checkout within X hours, trigger a follow-up based on behavioral targeting.

• Include a saved cart link, product image, and light urgency (“Almost sold out!”).
• Offer an incentive only if the user has shown high intent but hesitated.

Free People sends a stylish, emotionally driven reminder with the headline: “Something you love is going fast.”

It includes images of the products left behind and a clear “Shop Now” CTA. 

The design is calm but persuasive, and the tone matches their chic, light, and personal brand voice. There’s also a free shipping reminder to remove purchase friction.

2. Product browsing without purchase

If someone browses a category or product several times but doesn’t convert, send a follow-up highlighting:

• Reviews or UGC for that item
• Price drop alerts
• Similar alternatives

For example, Edmunds sends a clean, timely alert when a user’s previously viewed vehicle drops in price. The subject line is to-the-point (“Price drop on the 2015 Toyota Tacoma”), and the message highlights the exact car—Toyota Tacoma—plus the dealership’s name and distance. 

Price drop email example (Source)

A bold CTA button (“View This Offer”) creates urgency and makes it easy to return and act.

3. Time-triggered replenishment reminders

For products that run out (e.g., skincare, supplements, razors), track average repurchase cycles and nudge users before they realize they’re running low.

For example, Rockin’ Wellness sends a smart refill email about a month after purchase with the heading “Need a Refill?”

Time-triggered reminder example (Source)

It includes the exact product ordered, its price, and a bold CTA button (“Get Some More”)—all framed as helpful rather than pushy. The copy keeps it casual and warm: “We would hate for you to run out.” It’s a timely nudge that makes repurchasing frictionless.

4. Feature re-engagement (for SaaS)

If users stop using a key feature, or never activate it, trigger tooltips or emails that reintroduce it with short tutorials or examples of how others use it.

Step #4: Refine Using Real-Time Feedback

Behavioral marketing isn’t set-and-forget. Even with great segmentation and triggered actions, you must constantly adjust based on how people respond, in real time.

Real-time feedback doesn’t mean waiting for quarterly reports. It includes:

• Click-through rates on emails or push notifications
• Heatmaps and scroll depth on landing pages
• Conversion rates across personalized variants
• On-site behavior post-trigger (e.g., did they bounce, buy, browse?)
• Session recordings showing hesitation, drop-offs, or frustration
• A/B test results from personalized vs. default experiences
• Live chat transcripts that surface objections in the moment
  

Pro tip: Use tools like FigPii to run A/B or multivariate tests on different personalized flows and then adjust automatically based on winning variants.

Why Behavioral Marketing Matters for ROI and Growth

Personalized experiences driven by behavior consistently outperform broad, generic campaigns across industries, from ecommerce to SaaS. Here are some key reasons behavioral marketing drives higher ROI and growth: 

• It converts more of your existing traffic. You’ve already paid to bring users to your site through ads, SEO, influencer partnerships, or content. Behavioral marketing helps you keep them by responding to what they do on-site (browsing a category, abandoning a cart, or revisiting a product), so your follow-up feels timely and relevant, not random.

• It reduces churn and increases retention. Instead of blasting generic follow-ups, you send smart nudges—like refill reminders before someone runs out, or feature tips when a user stalls during onboarding. These small, behavior-based messages keep people engaged before they slip away.

• It improves ROI across marketing channels. You stop wasting budget on one-size-fits-all ads or emails. With customer behavior data, you only show discount codes to hesitant shoppers or upsells to high-intent buyers. That means better open rates, lower CPA, and more efficient spend, especially on retargeting.

• It builds trust and loyalty by showing users you’re paying attention. When someone sees product suggestions or offers that match their actual behavior, not just their demographics, they feel seen. This creates a feedback loop: more engagement, which leads to better personalization, which in turn leads to more profound brand affinity.

• It gives you a testing ground that teaches you something. Because behavioral marketing is dynamic, every segment, message, or offer becomes a live experiment. You learn which actions predict conversion, what sequence works best, and how different audiences behave—no waiting on quarterly insights.

Behavioral Marketing Tactics: Turn Real Actions Into Real Conversions

If there’s one takeaway from this guide, it’s this: the most effective marketing doesn’t rely on assumptions—it responds to behavior.

Behavioral marketing strategies help you make better decisions using real user activity. Instead of relying on assumptions, you use consumer behavior data from how and where site visitors click, scroll, drop off, and their search history to improve your marketing messages across different social media platforms and other marketing channels, along with the overall customer journey.

It helps you personalize based on actual behavior, recover abandoned carts, and send more relevant content and emails. When combined with a structured CRO process, it becomes a reliable way to increase sales and improve key metrics like revenue per visitor across different digital marketing channels. 

If you’re ready to stop guessing and start testing smarter, Invesp’s CRO experts can help you extract behavioral data and turn it into higher conversions.