Personal Recommendations

This type of Recommendations widget personalizes product suggestions based on each customer's browsing history, ensuring relevant and engaging shopping experiences.

User Profile Development

As customers navigate your store, our system dynamically builds a profile based on their viewed products. This profile:

• Updates in real-time with each interaction
• Assigns greater weight to recent views
• Continuously adapts to reflect evolving interests

Note: To enhance the shopping experience & promote exploration, our system excludes recently viewed products from personal recommendations. While these products are technically relevant, we prioritize offering fresh suggestions that better align with the shopper’s evolving interests and preferences.

Recommendation Logic

Consider the following example:

If a customer views:

• A red hat
• White jeans
• A green t-shirt (most recent)

Our system may recommend:

• More t-shirts (emphasizing recent interest)
• Items in red, white, or green
• Products that bridge categories (hats, t-shirts, and jeans)
• Frequently purchased complementary items

Advanced Similarity Matching

Beyond basic attributes like color, size, and category, our algorithm:

• Analyzes over 100 product dimensions
• Identifies subtle relationships between products
• Learns from collective user behavior
• Recognizes non-obvious connections, such as formality levels