Product recommendation engine

Step-by-Step Breakdown

Detailed explanation of each automated stage in the workflow.

1. 1

   Trigger

   Customer product interaction detected

   Customer views a product page, adds item to cart, or completes a purchase. This event captures the customer ID and product details to begin recommendation analysis.

   ShopifyWooCommerce
2. 2

   Action

   Retrieve customer purchase history

   Pull the customer's complete order history, browsing behavior, and demographic data from the e-commerce platform. Gather product categories, price ranges, and purchase frequency patterns.

   ShopifyBigCommerceWooCommerce
3. 3

   Action

   Analyze product catalog similarities

   Compare the viewed/purchased product against the entire product catalog using attributes like category, price, brand, and customer reviews. Generate similarity scores for potential recommendations.

   ShopifyBigCommerce
4. 4

   Decision

   Determine recommendation strategy type

   Branch workflow based on customer data richness - use collaborative filtering for returning customers with purchase history, or content-based filtering for new customers with limited data.

   n8n
5. 5

   Action

   Generate personalized product recommendations

   Create a ranked list of 3-8 recommended products based on the chosen strategy. Include complementary items, similar products, and trending items in the same category.

   ShopifyWooCommerce
6. 6

   Action

   Create targeted email campaign

   Build and send personalized email with product recommendations, including product images, descriptions, and special offers. Segment timing based on customer behavior patterns.

   Klaviyo
7. 7

   Output

   Display recommendations across touchpoints

   Show personalized recommendations on website product pages, cart page, and checkout flow. Track click-through rates and conversion metrics for optimization.

   ShopifyBigCommerceWooCommerce

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