AI Recommendations and Discovery in Dynamics 365 Commerce
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This document discusses recommendations and discovery in Microsoft Dynamics 365 Commerce. It explains that recommendations are an important way for retailers to increase engagement and revenue using machine learning. It provides examples of different types of recommendations like "People Also Buy" and "Frequently Bought Together" that are powered by AI. It also shows how recommendations can be integrated and personalized in different parts of the commerce experience, including on product pages, carts, and in point of sale. Data is important for powering the intelligent recommendation systems.
AI Recommendations and Discovery in Dynamics 365 Commerce
- 1. Global AI Bootcamp 14 Diciembre del 2019
- 3. Microsoft Dynamics 365 Common application platform: PowerApps, Microsoft Flow, Common Data Model Microsoft AppSource Dynamics 365
- 4. Agenda Why Recommendations? What Recommendations? How Recommendations (in Dynamics 365 Commerce)? Demos Q & A
- 6. Across the Industry https://www.mytotalretail.com/article/4-ways-ai-is-transforming-e-commerce-businesses/ https://www.mckinsey.com/industries/retail/our-insights/how-retailers-can-keep-up-with-consumers Retailersare leaning stronger than ever towardsRecommendationsand Machine Learning intelligentsystems to drive more consumer engagement and higher revenue.
- 8. Microsoft’s Approach Present shoppers with great choices for a satisfying experience that increases revenue, increases repeat visits, and grows average order values for Retailers
- 9. Recommendations in action in Microsoft Landing Page Product Details Page Cart / Checkout User behavior is used to drive relevant discovery. Includingcross-selland upsell, in any UX context.
- 10. World Class AI-ML Research Team
- 12. Omni-Channel Recommendations Lists • “People also buy” AI-ML list based on transactions • “Frequently bought together” AI-ML list based on orders • “Picks for you” AI-ML list based on transactions • “New” chart based on assorted date field • “Best Selling” chart based on transactions • “Trending” chart based on transactions and assorted date field
- 13. People Also Buy Machine Learned list using consumers transactions to show recommendations in the context of a single product. Driving comparison shopping and increase in consumer engagement.
- 14. Frequently Bought Together Machine Learned list using consumers multi-item orders to provide recommendations in the context of the current consumer’s cart. Driving increase in average order value.
- 15. Picks For You Machine Learned list based on consumers transactions provides personalized recommendations for the signed in consumer. GDPR compliant, including support for consumer opt out. Model allows for personalization of any Chart and ML list.
- 16. New Chart shows all newly available products in an environment, ordered from most to least recent. Driving novel discovery.
- 17. Bestselling Chart shows the all-time best-selling products in an environment, ordered from most to least performing. Driving discovery via popular content.
- 18. Trending Chart shows the best-selling products in a recent period, ordered from most to least performing. Driving discovery with in-vogue content.
- 19. Additional Capabilities • Respects Assortments, Channel, Category, and Catalog out of the box • Customers can adjust algorithms’ configuration • Support for Algo / ML List manual modifiers
- 20. Seamlessly integrated in Dynamics 365 HQ • Enable / Disable Product Recommendations • Enable / Disable Personalized Recommendations • Create and manage Editorial lists
- 21. Expressive User Experience in E-commerce • In E-commerce: • Discovery Pages • Product Display Page • Cart Pages
- 22. Expressive User Experience in E-commerce • In E-commerce: • Discovery Pages • Product Display Page • Cart Pages
- 23. Expressive User Experience in E-commerce • In E-commerce: • Discovery Pages • Product Display Page • Cart Pages
- 24. Bonus Examples • Newest Hats → New Chart with applied Category • Bestselling Menswear for You → Personalized Bestselling Chart with applied Category • Like 2014 Col Solare Cabernet Sauvignon wine → People Also Buy with specified seed product
- 25. Compelling Recommendations in Point of Sale • In Point of Sale: • Product Details Screen • Transactions Screen • Customer Details Screen
- 26. Compelling Recommendations in Point of Sale • In Point of Sale: • Product Details Screen • Transactions Screen • Customer Details Screen
- 27. Compelling Recommendations in Point of Sale • In Point of Sale: • Product Details Screen • Transactions Screen • Customer Details Screen
- 28. Importance of Data “People also buy” AI-ML list based on transactions “Frequently bought together” AI-ML list based on orders “Picks for you” AI-ML list based on transactions “New” chart based on assorted date field “Best Selling” chart based on transactions “Trending” chart based on transactions and assorted date field
- 30. Everything to buildand run digital commerce
- 31. Build loyalty and exceed customer expectations
- 32. Scalable, reliable, secure, and compliant