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Product Recommendations Magic

Develop by Shopify

$20

/ Month
14 Days Free Trial

Smarter product recommendations to increase sales and AOV

Machine learning recommendations
Customizable algorithm
Auto-pilot mode
8 data points
Shop-wide display

About Product Recommendations Magic

Launched Jul 30, 2020

Categories

Built by Shopify

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Description

Product recommendations from a highly customizable algorithm that you can setup easily.

Most product recommendation apps simply lump together the product that was most purchased with the current product. Product Recommendations Magic is different, completely different. Since no two stores are the same, neither should your recommendations algorithm! Install and set the app to auto-pilot, or tailor your product recommendations based upon 8 criteria including personalization of what the customer has clicked on, added to cart, what others have purchased, and more.

Most product recommendation apps simply lump together the product that was most purchased with the current product. Product Recommendations Magic is different, completely different. Since no two stores are the same, neither should your recommendations algorithm! Install and set the app to auto-pilot, or tailor your product recommendations based upon 8 criteria including personalization of what the customer has clicked on, added to cart, what others have purchased, and more. more
  • Harness machine learning to tailor recommendations to your customers.
  • Use Auto-Pilot, or customize recommendations algorithm based on 8 data points.
  • Recommendations display anywhere in your shop, after adding to cart, or both.

Pros

  • Smarter product recommendations tailored to increase sales and AOV
  • Customizable recommendations algorithm based on 8 different criteria
  • Harnesses machine learning to personalize recommendations for customers
  • Auto-Pilot option for easy setup and management
  • Recommendations can be displayed anywhere in the shop, enhancing user experience

Cons

  • Potential complexity in setting up and tailoring the recommendations
  • May require some understanding of data points to fully customize the algorithm
  • Effectiveness may vary depending on the quality and quantity of customer data

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