What is Behavioral Targeting: Key Differences, Tactics, and Future

Understanding user behavior is essential for crafting highly personalized customer journeys. In this context, behavioral targeting helps you serve the right message to the right user at the right time.

Behavioral targeting gives you solid insight into users' browsing habits, purchase intent, and interactions, enabling you to create hyper-personalized experiences that drive higher engagement and conversions. But how exactly does it work, and what tactics can you use to make it more effective? 

Here’s where Nudge proves to be effective through its use of behavioral targeting to deliver personalized prompts based on real-time user actions, preferences, and engagement patterns. 

This blog will explain the key differences in targeting approaches, the types of behavioral targeting, and how AI-driven tools like Nudge can drive the future of personalized marketing.

What is Behavioral Targeting?

Behavioral targeting is a personalization technique that is crucial for enhancing ad relevancy on websites and user experience (UX) in mobile apps. By analyzing user interactions, preferences, and in-app behavior, brands can deliver personalized content, intuitive navigation, and relevant product recommendations. This ensures a smooth and engaging experience that keeps users coming back, reduces friction, and improves overall satisfaction. 

Instead of relying solely on demographics or location, behavioral targeting helps you understand precisely what users are doing online and how their intent shifts over time. For instance, suppose a user frequently browses a fintech app's currency converter tool without completing a transaction. 

In that case, online behavioral targeting can trigger a personalized nudge, offering a cashback reward to encourage conversion. This approach creates one-to-one personalization at scale, making every interaction more relevant.

Why is Behavioral Targeting Important?

Did you know the behavioral analytics market is expected to be worth around 13.4 billion U.S. dollars by 2029 from the current 5.5 billion U.S. dollars?

Consumers today expect brands to anticipate their needs rather than bombard them with promotions that make no sense. Online behavioral targeting helps you meet these expectations by delivering the following.

• Higher Engagement: Personalized experiences drive more clicks and time spent on apps or websites.

• Better Conversions: Tailored offers based on real-time behavior increase the likelihood of conversions.

• Customer Satisfaction: Users feel understood when brands deliver messages that are in tune with their needs.

• Reduced Drop-Off Rates: Contextually relevant content makes users more likely to stay and explore.

With platforms like Nudge, you can take behavioral targeting even further by introducing gamification and personalized loyalty programs at critical touchpoints across the user journey.

Understanding Key Differences in Targeting Approaches

Not all targeting methods are created equal. Here's how online behavioral targeting compares with other popular approaches.

1. Behavioral Targeting vs. Contextual Targeting

Here's how Nudge can merge both approaches into a seamless user experience:

• Contextual Product Recommendations
  Automatically suggest products or services that align with the page content or feature users are currently viewing.
  Example: If a user is checking the currency converter tool in a fintech app, Nudge can display suggestions like "No-fee currency transfer on your first transaction."

• Recently Viewed Nudges
  Trigger subtle pop-ups that remind users of previously viewed products or services, without needing them to search again.
  Example: "Still thinking about converting USD to EUR? Today's rate is 2% better than yesterday!"

• Real-Time Personalization
  Combine live context signals with behavioral data to show hyper-relevant messages.
  Example: If a user spends more than 3 minutes on a pricing page, Nudge can prompt: "Lock this exchange rate for the next 10 mins with zero fees."

• Progressive Disclosure Nudges
  Unveil personalized recommendations gradually as users engage more with the app.
  Example: First-time users might see a simple nudge like "Compare rates easily," while frequent users might get "Save this rate for your next 3 conversions and earn cashback."

• Dynamic Incentives Based on Segments
  Nudge can automatically customize offers based on audience segments like new users, loyal customers, or high-value spenders.
  Example: "You're one step away from unlocking 1% cashback on your next currency conversion!"

2. Behavioral Targeting vs. Behavioral Retargeting

Behavioral targeting focuses on ongoing user actions across sessions, while behavioral retargeting involves re-engaging users who have interacted with your site or app but haven't converted.

Example:

• Behavioral Targeting: Suggesting relevant products based on browsing categories.

• Behavioral Retargeting: Displaying a personalized pop-up with a discount for abandoned carts.

3. Behavioral Targeting vs. Online Behavioral Advertising (OBA)

Online Behavioral Advertising (OBA) targets users across third-party websites, while behavioral targeting is often limited to your own platform.

Types of Behavioral Targeting

Online behavioral targeting can take different forms based on where and how the data is used.

1. Onsite Behavioral Targeting

Personalizes experiences within your own app or website based on user behavior.
For instance, Amazon excels at onsite behavioral targeting by recommending products based on past purchases, browsing history, and frequently bought-together items. This personalized approach enhances the shopping experience and drives repeat purchases.

Nudge utilizes personalized product suggestions as users engage more, using progressive disclosure techniques.

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2. Network Behavioral Targeting

Uses behavioral data collected across multiple websites or apps through third-party networks.
Example: For instance,  MakeMyTrip integrates with ZestMoney to offer instant no-cost EMI options within its mobile app, enabling users to book flights and hotels with flexible payment plans. This in-app fintech solution enhances affordability and boosts booking conversions.

3. Predictive Behavioral Targeting

Uses AI and machine learning to predict future user behavior based on historical patterns.
For instance, Netflix uses predictive behavioral targeting to recommend movies and shows based on viewing history, watch time, and user preferences. Its AI-driven algorithms anticipate what users will enjoy next, keeping engagement high and reducing churn.

Tactics in Behavioral Targeting

To make behavioral targeting truly effective, you need to execute the following tactics.

1. Data Collection

Data collection is the foundation of online behavioral targeting, enabling you to understand how users interact with your app at every stage. The more granular your data, the more personalized your campaigns can become.

Here's what to track:

• Page Visits: Identify which pages users are exploring most frequently to gauge interest in specific products or services.

• Session Duration: Longer sessions often indicate higher engagement, a signal of interest that can trigger personalized offers.

• Cart Activity: Track items added to cart, abandoned carts, and completed purchases to understand buying intent.

• Scroll Depth & Clicks: Measure how deeply users interact with content to identify high-value touchpoints.

• Search Queries: Capture in-app search behavior to uncover specific user needs.

Nudge utilizes these behavioral signals in real time using omnichannel tools like CleverTap, MoEngage, Braze, Firebase Developer, and Iterable to trigger dynamic nudges. For instance, if a user spends more than 2 minutes on a pricing page, Nudge can automatically prompt: "Need help choosing the best plan? Chat with us!"

Nudge’s in-app survey feature effectively uses both zero-party data and first-party data that are analyzed and cleverly adapted for use by the aforementioned omnichannel tools. This helps provide users with a deeply personalized experience, while ensuring that user privacy and data protection regulations are honored.

2. Audience Segmentation 

Not all users behave the same and that's where audience segmentation helps you deliver more relevant messaging. By grouping users based on their actions and intent, you can create micro-segments that align with different stages of the user journey.

Common behavioral segments include the following.

• First-Time Visitors: Users exploring the app for the first time, who might respond to educational content or welcome offers.

• Repeat Visitors: Users who have browsed multiple times but haven't converted yet are ideal for gentle reminders or limited-time offers.

• Cart Abandoners: Users who added items to the cart but dropped off, often needing incentivized nudges to return.

• High-Value Customers: Frequent buyers or power users who are prime candidates for exclusive rewards or loyalty programs.

• Infrequent Users: Dormant users who need reactivation campaigns to re-engage with the app.

Nudge uses dynamic segmentation to tailor messages automatically. For example, first-time visitors might see "Get 10% off on your first transaction," while high-value customers could reap VIP-only cashback offers.

3. AI-Driven Targeting

AI takes online behavioral targeting to the next level by predicting which users are most likely to convert and serve personalized content at precisely the right moment.

AI algorithms can do the following.

• Analyze historical data to score users based on intent signals.

• Detect patterns in user journeys, like repeat visits or price comparisons.

• Trigger proactive nudges when users display high purchase intent, such as returning to the same product page twice.

• Optimize incentive timing by offering personalized discounts only to users who are most likely to convert.

• Continuously refine targeting models based on real-time interactions.

Nudge's advanced behavioral analytics engine learns from user behavior over time, automatically refining in-app nudges to improve conversion rates. For example, if a user frequently abandons transactions during checkout, Nudge can serve a personalized message: "Complete your payment now and enjoy zero service fees!"

Benefits and Applications of Behavioral Targeting

Behavioral targeting enhances user engagement and conversions by delivering personalized content based on real-time actions and past interactions. It is widely applied in dynamic ads, in-app recommendations, and interactive formats like shoppable videos to optimize relevance and drive sales.

1. Creation of Detailed User Profiles for More Relevant UX

Behavioral targeting enables you to build rich, dynamic user profiles that reflect real-time interactions rather than static personal data. Instead of relying solely on demographics like age or location, you can map out user behavior patterns such as:

• Browsing history and frequently visited pages

• Products viewed vs. products purchased

• Time spent on different sections of the app

• Preferred communication channels

• Engagement with promotional offers or discounts

2. Improved App Engagement and Conversion Rates

Personalized experiences built around user behavior consistently drive higher engagement and conversion rates compared to one-size-fits-all campaigns. When users feel like your app understands their intent, they are more likely to stay longer, explore more features, and take action.

Behavioral targeting helps improve engagement in the following ways.

• Serving contextual recommendations like showing related products while browsing

• Sending proactive nudges when users hesitate during checkout

• Offering exclusive rewards based on recent actions

• Reducing decision friction with dynamic suggestions based on past preferences

• Using shoppable stories and videos to showcase products aligned with user interests.

Nudge’s Shoppable Stories & Videos create immersive, interactive shopping experiences by seamlessly integrating product discovery, storytelling, and one-tap purchasing within the app.

3. Enhancing Relevance of Messaging 

Traditional marketing often relies on demographic targeting, but two users of the same age or location may have completely different needs and buying patterns. Online behavioral targeting shifts the focus from who users are to what they do, making your messaging far more relevant and effective.

Behavior-based messaging helps you with the following.

• Recommend products or services based on past interactions

• Tailor incentives to match purchase intent

• Prioritize high-intent users with exclusive deals or limited-time offers

• Avoid overwhelming users with irrelevant promotions

With tools like Nudge, you can future-proof your marketing strategies by implementing behavioral targeting at four times the speed by using advanced AI-driven testing and analytics.

Conclusion

With growing privacy regulations like GDPR and CCPA, online behavioral targeting faces increased scrutiny. Ongoing trends include restrictions on third-party cookie usage, rise of contextual targeting that personalizes minimally, and focus on first-party data collection.

Nonetheless, perhaps the future of behavioral targeting will shift to balance growing privacy concerns with AI-driven, first-party data strategies, ensuring personalization remains effective while respecting user privacy. These strategies would include, among others, predictive algorithms that forecast user needs before they act and micro-segmentation based on real-time intent signals.

To stay ahead of these trends and maximize the impact of your behavioral targeting campaigns, Nudge is here to help you implement smarter personalization strategies that drive higher engagement.

Book a demo with Nudge today!