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AI Product Recommendations

GreenPOS uses AI-powered recommendations to suggest products customers might like, helping increase average order value and customer satisfaction.

Where Recommendations Appear​

Point of Sale​

When items are in the cart, a "You Might Also Like" section appears showing up to 4 recommended products. Each recommendation displays:

  • Product image and name
  • Category badge and brand
  • Price
  • Reason tags (e.g., "Frequently bought together", "Similar category")

Click a recommendation to add it to the cart.

Online Store​

Product pages on your GreenPOS-powered website show related products based on similarity and purchase patterns.

How It Works​

The recommendation engine considers multiple factors:

Purchase Patterns​

  • What did other customers buy with these items?
  • What do customers with similar purchase patterns prefer?

Product Similarity​

  • Category — Same product type (flower, edibles, etc.)
  • Strain Type — Indica, Sativa, Hybrid matching
  • Price Range — Similar price points

Customer History​

When a customer is attached to the sale, recommendations can be personalized based on their past purchases.

Setting Up Product Data​

For best recommendations, ensure your products have complete data:

  • Category — Assign accurate product categories
  • Brand — Fill in brand/manufacturer
  • Effects — Add effect tags (Relaxed, Uplifted, Creative, etc.)
  • Terpene Profiles — Add terpene data when available from lab results

The more complete your product data, the better the recommendations.

Tips​

  • Complete product data — Fill in effects, terpenes, and descriptions for better matching.
  • Accurate categorization — Ensure products are in the right categories.
  • Customer accounts — Encourage customers to create accounts for personalized suggestions.
  • Sales data — The system learns from purchase patterns, so recommendations improve with more sales data.

Next Steps​