What Is Behavioral Targeting?

Think about a typical online shopping trip. You’re browsing a site for a new pair of hiking boots. You click on a few and read some reviews, but ultimately decide to wait. Then, a few minutes later, you see an ad for those boots on a completely different website.

That’s not a coincidence. It’s the direct result of behavioral targeting.

Behavioral targeting is a powerful marketing technique that uses your customers‘ actions to deliver a more and relevant . Instead of guessing what a customer might want based on age or location, it uses data about their behavior to understand their interests and . This could be anything from the pages they visit on a website to the products they've added to a shopping cart or the videos they've watched in a mobile app.

This approach matters because it transforms marketing from a into a precise, data-driven discipline. This isn’t about making a sale, but making a connection. By providing a more valuable, tailored experience, you build trust and loyalty that lasts.

The importance of behavioral targeting isn’t just a theory. It’s backed by solid data, and the numbers tell a compelling story.

The global behavioral targeting market was valued at approximately $10.5 billion in 2023 and is projected to reach around , representing a compound annual growth rate (CAGR) of 12.5%. This significant growth shows that companies increasingly recognize the value of avoiding generic marketing.

This shift is being driven by consumer demand. In a , 80% of consumers said they prefer brands that offer , and reported spending 50% more with such brands. The flipside is just as revealing. In a , 77% of customers said they get frustrated when they receive irrelevant promotional notifications. That affects not just customer sentiment, but your bottom line.

The desire for relevance is not just a preference. It’s now become a basic expectation.

Behavioral targeting operates on a simple but powerful principle: using the past to predict the future. The process can be broken down into three key steps.

1. Data is collected through various channels, from website cookies and mobile apps to email interactions.
2. This data is analyzed to create rich, individual user profiles.
3. Users are based on their shared behaviors, and these segments are used to drive personalized experiences.

This is where a platform comes in.

Instead of simply collecting data, an analytics platform allows you to move beyond basic demographics and create sophisticated user groups based on their actions. This process, known as , is the key to truly understanding the “why” behind user behavior. It enables you to define a group of users not by when they signed up, but by their actions.

For example, on a music streaming app, you could create a cohort of "power users" who have favorited at least 10 songs and created a playlist in their first week. You could then analyze this group to understand what other behaviors they share, and use that information to create a more effective flow for new users.

A truly effective analytics platform allows you to save these cohorts and apply them across different reports, such as and retention charts, providing a persistent and comprehensive view of your most valuable customers.

The basis of behavioral targeting is user data itself. It is not just about what people say they like but what their actions reveal. Various types can be used to create detailed user profiles and inform a powerful targeting strategy.

• Website and app : This is one of the most foundational data types. Beyond just pages visited and time spent, it includes the user’s specific navigation path, content they scroll past, mouse movements, and hover actions. It also tracks what they interact with on-site (such as form fields, calculators, or image galleries).
• Purchase and transaction history: This isn’t limited to what was purchased. It also includes purchase frequency, (AOV), products viewed but not bought, and items added to a shopping cart and then abandoned.
• Search queries and viewed products: What a user searches for on-site is a direct and powerful signal of their intent. This can be combined with the product filters they apply and the order of products they view to infer a high level of interest.
• Email and campaign engagement: This data shows how users interact with your marketing efforts. It includes email open rates, , which links they click within an email, and whether they've unsubscribed or marked a message as spam.
• Customer support interactions: The customer’s issues, how they interact with a chatbot or support agent, and the type of feedback they provide can all be used to understand their and areas of interest.
• Social media interactions: When users engage with your brand on social media—by liking, sharing, commenting, or clicking on ads—this strongly indicates their and interests. "Social listening" tools can also track mentions of your brand to understand public perception.
• Subscription and loyalty program data: For businesses with subscription models or loyalty programs, this data provides insight into user tenure, feature usage, points redeemed, and whether they've taken advantage of exclusive offers.

While often discussed in the same breath, behavioral, contextual, and demographic targeting are fundamentally different.

Contextual targeting

Contextual targeting relies on a webpage’s content to serve an ad. For example, an ad for gardening tools might appear on a blog post about planting a vegetable garden. The ad is relevant to the content but makes no assumptions about the person viewing it.

While contextual targeting is privacy-friendly, it’s also inherently impersonal. It can’t distinguish between a user actively seeking out a topic and one just passing through, which often results in lower engagement and a less effective return on investment.

Demographic targeting

This approach focuses on broad attributes such as age, gender, income, education, or location. Rather than relying on page content or individual browsing behavior, it assumes that people within a certain group are likely to share interests. For instance, a brand selling retirement planning services might target ads to users over 55, regardless of what site they’re visiting or what they’ve looked at online.

Behavioral targeting

This approach is all about the individual. It analyzes users‘ past actions to infer their interests and shows them a relevant ad, regardless of the webpage content. Using the earlier example, a person who has previously viewed a post about gardening tools would see a relevant ad for those tools on a completely unrelated news site.

While contextual and demographic targeting are valuable, behavioral targeting provides a level of personalization and precision that is far more effective at driving engagement and conversions. It’s about moving from a general-purpose message to a one-to-one conversation.

For both marketing and product teams, the benefits of a behavioral targeting approach are tangible and significant. Transitioning from a campaign-centric mindset to a one can be a game-changer.

• and : When marketing messages are highly relevant to users‘ past actions and interests, they are far more likely to engage with that content. This targeted approach dramatically improves campaign performance, leading to higher click-through rates and, ultimately, more conversions.
• Higher (ROI): By focusing marketing and advertising spend on specific audience segments with a demonstrated interest, businesses can significantly reduce wasted ad impressions and improve the efficiency of their budget. This strategic precision ensures that every dollar spent is working harder to reach customers who are genuinely likely to make a purchase.
• Enhanced and retention: A personalized experience shows customers that you understand their individual needs and value their time. This builds trust and strengthens the relationship between the customer and the brand, leading to higher and repeat business.
• Deeper customer insights: Behavioral targeting requires a deep dive into customer actions, which naturally uncovers valuable insights into the "why" behind user behavior. This deeper understanding helps product teams build more effective and user-friendly features, and allows marketing teams to craft more powerful and resonant campaigns.

Despite its many advantages, behavioral targeting is not without its challenges. Businesses must be aware of these limitations and address them head-on.

One of the most significant challenges is user privacy. An ad that feels too personal or intrusive can erode trust and lead to a negative brand perception. This is why transparency and consent are paramount. Users should always be aware of how their data is used and have control over it.

The shift away from third-party cookies is also forcing a new era of targeting based on , making it even more important for businesses to have a direct relationship with their customers.

Another challenge is . If your behavioral data is locked away in different departments or platforms, getting a full picture of the is impossible. Without a unified view, teams make decisions based on incomplete information, leading to disjointed and ineffective campaigns.

To maximize your behavioral targeting efforts, follow a few key best practices.

Start with your highest-value customers

Use behavioral data to identify your power users or most engaged customers. Understanding their journey can provide a for converting other users into loyal fans. Instead of targeting everyone at once, focus on the user segments that are already demonstrating high value. By analyzing their behaviors—from initial sign-up to their first and beyond—you can build a template for a successful user journey.

These insights can then be used to create targeted campaigns to guide new users along a similar path.

Be transparent and respect privacy

Clearly communicate what data you’re collecting and how you’re using it. Ensure your privacy policy is easy to find and understand. In an era of increased data privacy concerns, building and maintaining is paramount. Be proactive in your communication about data usage, and provide users with a clear and simple way to opt out of data collection if they choose. A transparent approach builds a foundation of trust that can lead to stronger, more lasting customer relationships.

Test, learn, and optimize

Behavioral targeting is not a “set and forget” solution. Continually test different , messages, and channels to see what works best. different messages for a single behavioral cohort can reveal powerful insights into what truly resonates with that segment. Similarly, testing different cohorts with the same message can help you uncover new, high-value audiences you might not have considered before. Use a growth-centric approach that views every campaign as an opportunity to learn more about your customers.

Go beyond basic demographic data

While age and location are useful, they don’t tell the whole story. Focus on what people do, not just who they are. Demographic data provides a static snapshot, but behavioral data provides a dynamic, real-time view of a customer’s interests and intent. A 25-year-old male from New York is just a demographic profile. But a 25-year-old male from New York who has visited your pricing page three times in the last 24 hours is a potential customer ready for a . Use actions as your primary guide.

Use product analytics to close the loop

The most effective behavioral targeting happens when marketing and product teams align on a for user data. Use a product analytics platform to create and save , and then use those cohorts directly within your marketing tools. This enables you to close the loop on the user journey, ensuring that the same behavioral insights that inform product decisions also power your targeted marketing campaigns.

Behavioral targeting is evolving fast, and artificial intelligence (AI) is accelerating the shift. What was once a manual process of segmenting users based on past actions is becoming a dynamic, predictive system that adapts in real time. Instead of reacting to what your users did yesterday, AI-powered targeting anticipates what they will likely do next.

This opens the door to using machine learning (ML). By analyzing not just behavior but context—device type, time of day, session depth, even inferred intent—you can tailor experiences with surgical precision. The result isn’t just more relevant messaging, but a smoother, more intuitive customer journey that feels designed for the individual, not just the segment.

But with greater precision comes greater responsibility. As targeting becomes more granular, transparency and ethical data use become non-negotiable. Your customers expect control over their data and clarity about how it’s used. The brands that thrive will be the ones that build trust into every interaction.

The era of generic, one-size-fits-all marketing is over. As consumers demand more relevant and personalized experiences, businesses must adapt or risk being left behind. Behavioral targeting is no longer a “nice to have” but a minimum requirement.

It represents a fundamental shift in philosophy—from focusing on broad campaigns to individual user journeys. Understanding the behaviors that drive engagement and conversion can build stronger customer relationships and achieve sustainable, data-driven growth.

This transformation requires a like Amplitude. It’s a powerful solution that allows you to collect, analyze, and act on behavioral data, unlocking a new era of precision marketing.