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All CollectionsRelevic: A Step-by-Step GuideMastering Campaign Filters
Cookie-Based Filters
Cookie-Based Filters

How to use pre-existing cookie data to track and deliver advanced personalization experiences

Updated over 3 weeks ago

Overview

Cookie-based filters in Relevic allow you to personalize website content by leveraging data stored in cookies on a visitor’s device. By extracting specific variables from these cookies, you can create precise audience filters and deliver hyper-relevant experiences. Whether targeting users based on cart details, browsing behavior, or purchase history, cookie-based personalization is a powerful way to drive engagement and conversions.

How Cookie-Based Filters Work in Relevic

Relevic enables you to access pre-existing cookies stored on a user’s website. By specifying the cookie name and its variable, you can create conditions to match or compare stored values and use these insights to trigger personalized content.

Key Features:

  • Define the cookie name (e.g., cart_data, user_status).

  • Specify the variable within the cookie to target (e.g., total_cart_value, user_role).

  • Match or compare the value using conditions like equal to, not equal to, includes, or count-based comparisons.

For instance, you could target users with a cookie variable user_role set to subscriber or a cart_value greater than 100.

Use Cases for Cookie-Based Personalization

1. Abandoned Cart Recovery

  • Example Cookie: cart_data with a variable cart_value.

  • Filter Condition: cart_value > 0

  • Personalization Idea: Show a dynamic banner or pop-up saying, “You left items in your cart! Complete your purchase now and get 10% off.”

2. Loyalty Program Highlights

  • Example Cookie: user_status with a variable loyalty_points.

  • Filter Condition: loyalty_points >= 1000

  • Personalization Idea: Display a notification, “Congratulations! You’ve earned enough points for a $10 reward. Redeem now!”

3. Paid Customer Upsell or Cross-Sell

  • Example Cookie: user_data with a variable plan_type.

  • Filter Condition: plan_type = premium

  • Personalization Idea: Suggest a complementary service or product upgrade. For instance, “Premium users get 20% off on advanced analytics tools. Upgrade now!”

4. Recently Viewed Items

  • Example Cookie: recently_viewed with a variable last_viewed_category.

  • Filter Condition: last_viewed_category = electronics

  • Personalization Idea: Highlight popular products in the “Electronics” category or provide recommendations like, “You recently viewed electronics. Check out these trending items!”

5. Returning Visitor Welcome

  • Example Cookie: visit_data with a variable visit_count.

  • Filter Condition: visit_count > 1

  • Personalization Idea: Create a personalized greeting, “Welcome back! Let’s pick up where you left off.”

How to Set Up Cookie-Based Filters in Relevic

  1. Access the Campaign Canvas:

    • Navigate to the Campaigns section in your Relevic dashboard.

    • Click Create New Campaign to start.

  2. Add a Cookie Filter:

    • In the Filters menu, select the Cookie Data filter.

    • Enter the cookie name (e.g., cart_data) and specify the variable within the cookie (e.g., cart_value).

  3. Set Conditions:

    • Choose the condition for the variable:

      • Equal to: Matches an exact value (e.g., user_role = premium).

      • Not equal to: Excludes users with a specific value (e.g., plan_type != basic).

      • Includes: Targets users where the variable includes a specified substring (e.g., recently_viewed = electronics).

      • Count-Based Comparisons: Set conditions like greater than, less than, or equal to for numeric variables (e.g., cart_value > 100).

  4. Create a Page Variation:

    • Use Relevic’s editor to build a personalized variation tailored to the filtered audience.

    • Customize banners, CTAs, or content based on the cookie data.

  5. Publish the Campaign:

    • Assign the cookie filter to the campaign and publish it. Relevic will dynamically show the personalized variation to users who meet the filter criteria.

Best Practices for Cookie-Based Filters

  • Focus on High-Value Data: Prioritize cookies that store meaningful data, like purchase history, user preferences, or cart details.

  • Ensure Privacy Compliance: Always respect user consent and comply with data protection regulations like GDPR or CCPA.

  • Test Filter Accuracy: Regularly test the filters to ensure they match the intended audience based on the cookie variables.

  • Combine Filters for Precision: Enhance cookie-based targeting by combining it with other filters like location or UTM parameters.

Conclusion

Cookie-based filters in Relevic unlock advanced personalization opportunities by leveraging pre-existing data stored on a visitor’s browser. From abandoned cart recovery to cross-sell opportunities and loyalty program highlights, this filter empowers you to deliver tailored content that resonates with your audience. By using cookie variables creatively, you can enhance user experiences, drive engagement, and boost conversions.

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