The recommendation system is designed in 3 parts based on the business context:
- Popularity based are a great strategy to target the new customers with the most popular products sold on a business's website and is very useful to cold start a recommendation engine.
- **Dataset : **Amazon product review dataset
- Recommend items to users based on purchase history and similarity of ratings provided by other users who bought items to that of a particular customer.
- A model based collaborative filtering technique is closen here as it helps in making predictinfg products for a particular user by identifying patterns based on preferences from multiple user data.
- For a business without any user-item purchase history, a search engine based recommendation system can be designed for users. The product recommendations can be based on textual clustering analysis given in product description.
- **Dataset : **Home Depot's dataset with product dataset.