What is Behavioral Data in Marketing and How Your Online Store Can Benefit From It

Behavioral data marketing focuses on understanding what your customers do rather than what they say they’ll do. It analyzes customer actions, such as clicks, browsing history, purchases, or time spent on specific pages, to uncover valuable customer behavior insights and help you predict and create more personalized marketing campaigns.

Imagine being able to predict a customer's next purchase based on their browsing habits and use that data to deliver personalized recommendations that convert. This approach is proven to drive 85% more sales growth and 25% higher margins (McKinsey).

Each action is called an “event,” representing the "what" of user behavior. When combined across touchpoints, these events reveal a user's journey toward a specific outcome. Behavioral data marketing also uncovers the “why” by identifying user intent, which helps deliver relevant and engaging experiences that improve conversion rates and build loyalty.

For example, if a customer browses sectional sofas but doesn't complete a purchase, behavioral data can reveal their intent to buy a sofa, allowing businesses to re-engage them with tailored offers.

However, how do you gather these insights? Simple, behavioral data in eCommerce relies on three main types of customer data:

• Direct Insights (First-Party): These are the behaviors and preferences you track firsthand from your website, app, or store—everything from browsing habits to past purchases.
• Shared Intelligence (Second-Party): Data exchanged through trusted partnerships, giving you access to relevant customer behaviors from businesses with a similar audience.
• Market-Wide Trends (Third-Party): Aggregated data collected from various sources, offering a broader view of customer behavior across industries and platforms.

In a world where customer expectations are at an all-time high, behavioral data marketing allows online store owners to meet these expectations by offering personalized experiences, improving campaign performance, and building lasting customer loyalty. Here are some behavioral data benefits:

It Improves User Experience

Behavioral marketing in eCommerce refines offers, improves customers' understanding of their digital behavior, and tailors experiences to their habits. Every interaction reveals more about shoppers' preferences, enabling more targeted messaging across platforms, as 75% of consumers expect a consistent experience across all channels (SalesForce).

It Helps Attract and Retain Shoppers

Not all visitors come with a clear intention to buy, but understanding what they browse or add to their cart can help re-engage them. Loyal customers are 60-70% more likely to buy again compared to only 5-20% for new ones (Marketing Metrics). It’s one of the major benefits of behavioral marketing.

It Drives Personalization in Ecommerce

Behavioral data in eCommerce allows for hyper-targeted experiences, such as personalized product recommendations, tailored email content, or location-based offers. This is critical since 9 in 10 of customers prefer brands that personalize their shopping experience (Accenture).

It Boosts Conversions and Revenue

By delivering relevant offers at the right time, behavioral data marketing leads to conversion rate optimization. Merchants using customer behavior insights experience 85% higher sales growth and lower customer acquisition costs by optimizing campaigns (Gallup).

Curious about how personalized search can transform your online store? Discover the secrets to delivering tailored shopping experiences that boost engagement and sales in our latest blog post!

What is Personalized Search in Ecommerce and How to Excel

Unlocking the full potential of behavioral data in eCommerce requires smart strategies to reach customers with timely and relevant messaging. Below are some powerful techniques that can take your marketing to the next level:

Product recommendations are one of the most famous marketing personalization techniques, using behavioral data marketing to drive higher engagement and sales. By analyzing online store behavioral data like previous purchases, items viewed, and interaction patterns, you can craft tailored suggestions that align with each shopper’s unique preferences, significantly boosting conversion potential.

A great tool for implementing personalized recommendations is, for example, the Recently Viewed product widget from the Searchanise Upsell & Marketing app. This widget shows products customers recently browsed on home or product pages, helping to remind them of items they’ve already explored and encouraging conversions.

For instance, a clothing retailer could use this widget to display dresses, shoes, or accessories that a customer previously viewed. If the customer left without purchasing a pair of sneakers, seeing them featured again could encourage them to complete the purchase.

Actionable Tips

Analyze Browsing and Purchase History. Track and analyze a customer’s past interactions, such as products viewed or purchased, to suggest items they’re likely to be interested in.

Use Collaborative Filtering. Recommend products based on the behavior of similar customers. If one customer buys a certain item, show that item to others who have purchased similar products.

Case in Point

Amazon

Amazon perfectly illustrates how to use behavioral data for online store growth by displaying the “Previously Viewed” section. By showcasing items customers have interacted with but not purchased, Amazon encourages them to revisit and complete transactions.

Behavioral segmentation in marketing helps you categorize customers into specific groups based on their actions, enabling you to send more tailored and impactful messages. By analyzing behaviors like click patterns, purchase frequency, or interest in certain products, you can craft offers that truly resonate with each segment’s needs.

Unlike broad demographic strategies, segmentation targets specific behaviors. For instance, if a customer frequently views specific products but doesn't buy them, you can send a personalized email offering a limited-time offer on those items. Or, for loyal customers, you can offer rewards to encourage repeat purchases.

For instance, an online bookstore could segment customers into groups like "bestseller readers" and "mystery lovers," sending tailored promotions based on their interests.

Actionable Tips

Start with a few key groups. Begin by creating basic customer groups based on common behaviors, such as:

• Cart Abandoners: People who added items to their cart but didn’t check out.
• Frequent Buyers: Loyal customers who shop regularly.
• Inactive Users: Visitors who haven’t interacted with your site for a while.

Focusing on a few groups helps you take action faster without feeling overwhelmed.

Use Behavioral Triggers in Marketing. Set up automated campaigns that respond to specific actions. For example:

• Send a discount code to cart abandoners to encourage them to complete their purchase.
• Share "We miss you!" emails with inactive users to bring them back.

Combine Data for Better Results. Mix behavioral data in eCommerce (e.g., browsing habits) with demographic data (e.g., location or age) to create more targeted campaigns.

Case in Point

Airbnb

Airbnb is one of the most effective behavioral marketing examples to help you understand segmentation. The platform uses behavioral segmentation to tailor experiences to its users. By analyzing user interactions, such as search preferences (e.g., city, type of accommodation), booking history, and trip duration, Airbnb creates targeted recommendations for future stays. For instance, if a user frequently books weekend stays in urban areas, Airbnb might segment them into a “City Explorer” group and send email campaigns featuring top-rated apartments in cities they showed interest in but haven’t visited yet. This level of personalized segmentation keeps users engaged and more likely to book.

Sephora, a prominent name in beauty and cosmetics, leverages behavioral marketing in eCommerce to boost customer engagement and sales. By analyzing user actions, Sephora tailors personalized experiences across its website, mobile app, and email campaigns, ensuring a seamless and relevant shopping journey.

Triggered campaigns send automated, personalized messages based on specific customer actions like signing up, abandoning a cart, or browsing a product. These campaigns make your marketing feel timely and relevant. They can be used in automated emails or retargeting ads.

Emails

Email marketing is an effective tool for delivering targeted messages based on behavioral data in eCommerce. By tracking actions like opening an email, clicking links, or using promo codes, you can send personalized follow-ups. For example, if a customer browses pasta products but doesn't make a purchase, a follow-up email can offer a discount on popular pasta items. The email could also include a recipe suggestion, making the offer more relevant and compelling. Using segmentation, businesses can tailor emails based on past behavior, such as frequent shoppers receiving loyalty rewards or those with specific interests getting curated offers.

Targeted Ads

Retargeting ads work like a gentle reminder, bringing potential customers back to your store by highlighting the products they are interested in. For instance, if a shopper spends time browsing your online shoe collection but doesn’t check out, they could later be greeted by an ad on social media showing those same shoes, along with a special discount or an added perk like free shipping. It’s a smart way to rekindle interest and spark action, nudging customers closer to completing their purchase.

Actionable Tips

Create Welcome Series for New Subscribers. When a customer subscribes to your email list, automatically send them a series of emails over the next few days or weeks.

Leverage Time-Based Retargeting. Timing is key in retargeting. After a customer abandons their cart, you can show them an ad within a specific time window (e.g., within 24 hours) reminding them of their abandoned items.

Case in Point

Asos

ASOS is a pro at utilizing triggered email campaigns driven by customer actions. For example, when a shopper abandons their cart, ASOS automatically sends a reminder email showcasing the items left behind. They might even sweeten the deal with a discount or free shipping to encourage the purchase. If someone leaves a workout outfit in their cart, they might get an email with the subject line, 'This yours?' This strategy helps ASOS recover potential sales and keeps customers coming back.

Netflix

Netflix is a prime example of how behavioral marketing in eCommerce can help personalize email marketing. For example, they analyze viewer habits like which genres a user watches most and tailor the subject lines and content of their emails accordingly. These emails often include recommendations for similar shows or movies, encouraging subscribers to continue exploring the platform.

To manage behavioral data in eCommerce, online merchants need the best tools for behavioral marketing. Below, we’ve grouped tools into categories based on their primary purpose.

Monitor user behavior, engagement, and conversion journeys on your site.

Tools:

• Google Analytics: Dive into detailed user behavior, from session lengths to drop-off points, and discover where your site excels or needs attention.
• Hotjar: See your site through the eyes of your visitors with heatmaps and session recordings, turning data into visual insights for a smoother experience.
• Crazy Egg: Take your optimization to the next level with heatmaps and A/B testing, helping you identify exactly what grabs attention and what doesn’t.

Tools for tracking behavioral data in marketing are essential for understanding intricate customer behaviors, spotting trends, and predicting future actions. These insights empower store owners to optimize customer experiences, personalize strategies, and boost conversions.

Tools:

• Mixpanel: Monitors user behavior across both websites and mobile apps, offering deep insights into customer actions, helping businesses make data-driven decisions to refine their marketing efforts.
• Amplitude: Provides a comprehensive view of the entire customer journey, enabling businesses to understand user interactions, detect emerging trends, and assess the impact of new features or marketing campaigns.
• Searchanise Search & Filter: A search app that enhances the customer experience with advanced search and filtering features, coupled with on-site analytics.

Customer Data Platforms (CDPs) help businesses gather and organize data from multiple sources into one unified view. Instead of piecing together customer info from different tools, CDPs give you a clear, 360-degree profile. They help with segmentation and enable you to activate marketing campaigns that speak directly to your customers’ needs.

Tools:

• Segment: Offers seamless data collection and unification, allowing you to connect various marketing tools for consistent, customer-centric campaigns.
• Tealium: Helps you collect real-time customer data and segment audiences, providing the foundation for timely, personalized marketing actions.
• Adobe Real-Time CDP: Advanced real-time data processing helps businesses activate segmented data across multiple channels for immediate, personalized communication.
• Piwik PRO CDP: A privacy-conscious solution that ensures data compliance while helping you segment and personalize experiences, making it suitable for GDPR-driven markets.

Email marketing platforms help businesses send the right message at the right moment. By automating emails based on customer actions, such as browsing a product or making a purchase, you can stay top-of-mind and drive higher engagement and sales.

Tools:

• Klaviyo: Targets customers with personalized emails after actions like adding items to their cart or making a purchase.
• Mailchimp: Uses customer interactions to trigger timely emails, keeping potential buyers engaged and moving through the sales funnel.
• ActiveCampaign: Combines email with automation and CRM to guide customers smoothly from one stage to the next.
• Omnisend: Perfect for eCommerce, it offers pre-built flows like cart recovery and order confirmations to simplify the customer journey and boost revenue.

Deliver personalized ads to customers based on their online behaviors, like browsing history or abandoned carts.

Tools:

• AdRoll: Creates dynamic retargeting ads across web, social, and email.
• Google Ads: Targets customers with display or search ads tailored to their behavior.
• Facebook Ads Manager: Allows retargeting website visitors or creating lookalike audiences to attract new customers.
• Criteo: A specialized platform for personalized retargeting with dynamic ad creatives.

Automating marketing campaigns are triggered by customer actions, such as cart abandonment or browsing activity.

Tools:

• HubSpot: Automates email campaigns, workflows, and audience segmentation.
• Marketo (by Adobe): Offers behavior-based automation for email, ads, and lead scoring.
• ActiveCampaign: Combines automation with CRM functionality for seamless customer targeting.
• Drip: Specifically designed for eCommerce stores to build and automate personalized campaigns.

Online store owners often face hurdles in using behavioral data marketing effectively, such as ensuring data accuracy, following regulations, and keeping customer trust intact. The vast amount of data across various platforms can create confusion and mistakes if not managed carefully.

If not properly managed, the collection, resolution, storage, analysis, and activation of this data can lead to ethical and governance issues, jeopardizing customer relationships and the efficacy of the data itself.

The Challenge

As regulations like GDPR and CCPA tighten, handling customer data responsibly becomes more complex. Customers want to know exactly how their information is being used, and any missteps can erode trust.

The Fix

Implement tools that ensure you’re following privacy laws and keeping data secure. Be transparent with customers—make your data policies clear and easy to understand. Use data anonymization to keep identities safe, and track user consent with a reliable consent management system.

The Challenge

With so much behavioral data marketing coming in, it’s easy to feel overwhelmed. Turning massive amounts of data into meaningful insights can be time-consuming and complex.

The Fix

Tap into powerful analytics tools like Mixpanel or Amplitude to keep your data organized and accessible. Focus on tracking only the most relevant metrics that align with your specific business objectives, avoiding unnecessary clutter. Use customized dashboards to get real-time insights at a glance, streamlining decision-making so you can take action faster.

The Challenge

With data streaming in from so many places, websites, apps, social media, and email, it’s like trying to piece together a jigsaw puzzle where the pieces don’t quite fit.

The Fix

Use Customer Data Platforms (CDPs) like Segment or Tealium to unite all your data into one clear, cohesive picture. Keep everything in check with regular audits, ensuring the flow is steady and accurate. Standardize your formats and connect your tools, so they play well together, creating smooth, real-time insights that help you make quick decisions.

The Challenge

Collecting and analyzing behavioral data in eCommerce is one thing, but turning those insights into real, impactful marketing strategies is a whole other challenge for many eCommerce businesses.

The Fix

To make the most of your data, use tools that not only analyze but also automate actions - like personalized product recommendations or emails that trigger based on specific customer behavior. It’s equally important to establish clear workflows, ensuring that insights lead to tangible changes such as modifying landing pages, refining ad targeting, or activating retargeting campaigns. Start with small adjustments, using A/B testing to see what works best, and continuously iterate to refine your strategy for the best results.

Trends like AI-powered predictive analytics, hyper-personalization, data privacy, and cross-channel integration shape the future of behavioral data marketing. These advancements will help merchants better understand customers, deliver more personalized experiences and stay compliant with regulations.

As AI continues to evolve, it’s set to revolutionize predictive analytics in marketing. With the ability to analyze large data sets, AI can more accurately forecast customer behavior—predicting what products they’ll be interested in, when they’re likely to make a purchase, and even when they might churn. This shift allows businesses to move from reacting to customer actions to proactively anticipating their needs, ultimately optimizing marketing efforts and boosting customer retention.

Real-time behavioral data in eCommerce will take personalization in eCommerce to the next level. By tracking live interactions such as browsing behavior or social media engagement, online businesses can instantly offer personalized recommendations or promotions. For example, a shopper browsing a product could receive a tailored discount in real time, making the experience more relevant and timely, which increases the chances of conversion.

With data privacy regulations evolving rapidly, merchants must take a proactive stance. It’s not just about staying compliant—it’s about creating an environment where customers feel secure and valued. As regulations like GDPR and CCPA gain momentum, the spotlight is on providing clear, transparent privacy policies and obtaining explicit user consent. This growing focus on data protection is more than just meeting legal standards—it’s about building lasting trust and loyalty. By prioritizing transparency and ethical data practices, businesses can strengthen customer relationships and foster greater engagement.

As customers move between sites, apps, social media, and even physical stores, integrating their behavior across all platforms is essential. It’s not just about collecting data, but creating a seamless, connected experience. Imagine a shopper adding items to their cart on the phone and getting a personalized reminder when they return on the desktop. This cross-channel integration helps deliver smooth, personalized interactions that keep customers engaged and coming back.

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Behavioral data marketing is revolutionizing how online merchants enhance customer experiences and drive conversions. Data-driven insights from user interactions help businesses create highly personalized shopping journeys, deepen customer engagement, and build lasting brand loyalty.

Searchanise Search & Filter empowers merchants with advanced behavioral analytics, transforming raw data into actionable strategies. Don’t let valuable customer insights go untapped. Harness the power of behavioral data with Searchanise to refine your marketing strategies, increase conversions, and deliver exceptional shopping experiences.

Try Searchanise today and see the impact of data-driven decision-making on your store’s success!