Behavioral Targeting Explained: How It Works for eCommerce Success
Behavioral targeting is a personalization strategy that uses data on how customers interact with a website—including purchase history, cart activity, and search queries—to deliver more relevant product recommendations, ads, and content. Key strategies include dynamic product recommendations, abandoned cart retargeting, and email segmentation.
Published June 23, 2025.
In eCommerce, behavioral targeting plays an important role in increasing relevance and conversion rates by showing shoppers what they are most likely to buy. For instance, a shopper who views several sneaker styles may later be shown similar sneakers or limited-time offers on footwear when they return, potentially increasing conversion rates by up to 76%.
Here's everything you need to know about using behavioral targeting in eCommerce to boost personalization efforts and conversion rates.
» Want to boost your behavioral targeting? Here's how Fast Simon's AI-powered personalization can help you
What Is Behavioral Targeting?
Behavioral targeting is a personalization strategy that uses data on how customers interact with a website to deliver more relevant product recommendations, ads, and content. This data includes actions such as:
- What users click on
- How long they browse
- What they abandon in their cart
- What they purchase
» Here are our top eCommerce personalization strategies & platforms
Behavioral Targeting vs. Other Targeting Methods
| Targeting Type | How It Works |
|---|---|
| Behavioral | Tracks real-time user actions such as browsing, clicking, and purchasing to personalize what each shopper sees |
| Demographic | Segments users by fixed traits like age or income |
| Contextual | Focuses on aligning content with the topic of a page |
| Psychographic | Categorizes people by values, interests, or lifestyle |
Behavioral targeting is uniquely effective for eCommerce due to its ability to act on intent signals. It detects purchase interest (e.g., abandoned cart, multiple product views) that other methods can't, making the experience more relevant.
» Learn more: Behavioral targeting vs. retargeting
Unlock Your eCommerce Potential
Fast Simon's advanced personalization technology harnesses the power of behavioral targeting, turning real-time shopper actions into conversions.
Schedule a Demo4 Key Types of Behavioral Data Typically Collected in eCommerce
» Worried about the ethics? Here's how to ethically collect customer data
1. Browsing Behavior
Browsing behavior helps uncover user interests, intent, and product affinity. It includes:
- Pages visited
- Time spent
- Scroll depth
- Navigation flow
By analyzing browsing patterns, eCommerce brands can segment users based on engagement and serve personalized product recommendations that reflect real-time behavior, not just past purchases. This data is typically collected through site tracking tools and session analytics.
» Learn more about customer segmentation in eCommerce
2. Purchase History
Purchase data builds the foundation for loyalty models and product affinity scores. It tracks all previous transactions, including:
- Items bought
- Order value
- Frequency
This enables precision in upsell and cross-sell campaigns by predicting what a customer is most likely to buy next based on historical patterns. This behavior also supports dynamic product bundling and post-purchase automations.
» Don't miss these upsell strategies and cross-sell strategies
3. Cart Activity
This data captures items added, removed, or left in carts without checkout and is key for identifying friction points in the buyer journey, including:
- Pricing
- Shipping cost
- Distraction
It powers automated retargeting flows like cart abandonment emails, real-time reminders, and tailored discounts. Cart behavior also helps refine checkout UX and test conversion triggers.
» Need help? Here are some techniques to personalize emails
4. Search Queries
This logs every on-site search engine term entered by users. eCommerce site search behavior is a direct signal of intent, often revealing what the user truly wants, especially when browsing behavior is scattered.
Analyzing this data improves product categorization, filters, and predictive search functionality, enabling merchandising teams to adjust inventory visibility based on high-intent demand.
» Don't believe us? Here's how site search data can revolutionize eCommerce optimization
How to Use Behavioral Targeting in eCommerce
4 Most-Effective Behavioral Targeting Techniques
1. Dynamic Product Recommendations
By analyzing browsing history, cart contents, and previous purchases, brands can deliver real-time product suggestions tailored to each user. These recommendations appear on homepage banners, product pages, or during checkout, increasing relevance and average order value.
For example, if a customer views several skincare products, the site may suggest complementary items like serums or moisturizers. Amazon attributes up to 35% of its revenue to this tactic.
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2. Abandoned Cart Retargeting
When a user adds items to a cart but does not complete the purchase, a retargeting flow is triggered via email or ads. These reminders often include product images, urgency messaging, or time-sensitive discounts.
This technique helps re-engage high-intent shoppers and recover lost sales. Abandoned cart flows drive the highest average revenue per recipient ($3.65) and the highest average placed order rate, or conversion rate (3.33%).
South African eCommerce store, Takealot, doesn't wait long before sending customers reminders about products they added to carts but never purchased.
» Don't get caught out: Remarketing vs. retargeting in eCommerce
3. Exit-Intent Offers
Exit-intent technology tracks mouse movement to detect when a user is about to leave the site. A targeted pop-up can then appear with an incentive, such as a discount or free shipping, encouraging them to stay or complete a purchase.
This method captures attention at the final decision point and is especially effective in reducing bounce rate and cart abandonment. A DiviFlash report from 2024 reported that pop-ups can increase conversions by 4%.
J.Crew makes use of exit-intent popups to offer customers an extra sign-up bonus the moment they try to leave the site.
4. Behavior-Based Email Segmentation
Rather than sending broad messages, brands segment email campaigns by behavioral triggers such as browsing activity, repeat visits, or time since last purchase.
For example, a user who regularly views a product but never buys may receive a tailored message with social proof or a limited-time bundle. This increases relevance and click-through performance across campaigns.
» Get started by understanding the science of effective email segmentation
Key Tools and Platforms to Boost Behavioral Targeting
Fast Simon
Fast Simon is a unified merchandising and personalization platform built specifically for eCommerce. It enables behavioral targeting through AI-powered search algorithms, smart collections, and product recommendations that adapt in real time to shopper behavior.
By analyzing browsing data, cart actions, and search queries, it delivers personalized experiences across the customer journey, boosting conversion rates, average order value, and engagement. Its no-code integration and deep analytics make it accessible for both marketing and merchandising teams.
Google Analytics 4
GA4 provides in-depth behavioral data like user paths, time on page, and event tracking. It’s a foundational tool for understanding what users do on-site, enabling more precise segmentation and funnel optimization.
Paired with eCommerce tools like Fast Simon, GA4 can help validate behavioral patterns and support continuous optimization.
Klaviyo
Klaviyo uses customer behavior such as browse abandonment, purchase frequency, and email interaction to automate personalized email flows. It segments users by intent and engagement, allowing brands to follow up with timely, behavior-triggered campaigns that drive conversions.
When combined with on-site personalization from Fast Simon, Klaviyo helps complete the behavioral marketing loop.
» Learn more about the Fast Simon & Klaviyo integration
Example of a Successful Behavioral Targeting Campaign
NRS World, a leading retailer of western and ranch lifestyle products, used Fast Simon’s AI-powered merchandising and online behavioral targeting. NRS world analyzed real-time actions like browsing behavior, search patterns, and product interactions, which shaped personalized product rankings, dynamic category pages, and relevant search results.
» Make sure you know the difference between categories and collections
By offering eCommerce personalization within site search, each user received a uniquely tailored shopping experience that created natural buyer inspiration and led to measurable improvements in key metrics. NRS saw increased engagement, a boost in average order value (AOV), and stronger conversion rates.
What made NRS World's campaign effective was the speed at which behavioral data was applied, along with seamless integration across the search and discovery journey. It wasn’t just about collecting data, it was about acting on it in real time to drive better shopping outcomes.
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FAQs
What are the most common missteps or blind spots eCommerce brands face when relying too heavily on behavioral targeting?
- Overpersonalization fatigue: When users see the same products or recommendations repeatedly, it can lead to decision fatigue or disengagement. This happens when behavioral data isn’t refreshed or diversified. To avoid this, brands should rotate content, introduce novelty, and blend in seasonal or trending products to keep experiences fresh.
- Ignoring broader context: Focusing only on behavioral signals may cause brands to overlook external factors like economic shifts, holidays, or regional events. Behavioral targeting should be paired with contextual data to create campaigns that reflect both individual actions and broader consumer trends.
- Privacy overreach: Heavy behavioral tracking without transparency can erode trust. Users are increasingly sensitive to data collection. Brands must provide clear opt-ins, explain how data is used, and ensure compliance with privacy laws to maintain credibility.
- Misinterpreting intent: Not all behavior indicates purchase readiness. For example, repeated page views may suggest interest, but also confusion or dissatisfaction. Brands should combine behavioral signals with feedback tools like surveys or session recordings to better understand user motivation.
How can eCommerce companies adapt their behavioral targeting as third-party tracking phases out?
As third-party cookies disappear and privacy regulations become stricter, eCommerce companies must focus on first-party data and consent-driven strategies. This means collecting high-quality behavioral data directly from your own websites, apps, and owned channels. Think about tracking on-site actions like search queries, page views, and cart behavior using privacy-compliant analytics.
What role does consent play in this new approach?
Consent is now critical. Clear opt-in prompts and transparent data usage policies are no longer optional. Companies should also focus on a value exchange, offering benefits like loyalty points, early access, or personalized experiences in return for user data.
How does behavioral targeting influence product development?
Behavioral targeting plays a critical role in shaping product development by tracking patterns such as frequent search queries that return no results, products with high engagement but low conversion, or features that draw repeated interaction. This helps brands identify gaps in their offerings and refine their inventory or pricing strategies accordingly.
What is the role of predictive analytics in behavioral targeting?
Predictive analytics adds another layer to behavioral targeting by using behavior patterns to forecast future actions, such as repurchase probability or churn risk. This allows eCommerce teams to act preemptively with tailored offers or messaging.
The Fastest Way to Smart Sales With Behavioral Targeting
In the dynamic world of eCommerce, connecting with shoppers on a personal level based on their real-time actions is key. This is where behavioral targeting shines, moving beyond static data to understand true shopper intent.
Stop guessing what your customers want. With Fast Simon, you can deliver exactly what they need, swiftly and smartly, making every interaction count. Our AI-powered platform helps you harness these crucial behavioral signals, turning insights into immediate action.
» Ready to get started? Schedule a demo with Fast Simon
