Product-Recommendation-System-for-e-commerce

Inspiration

Product Recommendation System for e-commerce businesses A well developed recommendation system will help businesses improve their shopper's experience on website and result in better customer acquisition and retention

What it does

The recommendation system, I have designed below is based on the journey of a new customer from the time he/she lands on the business’s website for the first time to when he/she makes repeat purchases.

How we built it

The recommendation system is designed in 3 parts based on the business context:

Recommendation system part I: Product pupularity based system targetted at new customers

Recommendation system part II: Model-based collaborative filtering system based on customer's purchase history and ratings provided by other users who bought items similar items

Recommendation system part III: When a business is setting up its e-commerce website for the first time withou any product rating

Challenges we ran into

Accomplishments that we're proud of

When a new customer without any previous purchase history visits the e-commerce website for the first time, he/she is recommended the most popular products sold on the company's website. Once, he/she makes a purchase, the recommendation system updates and recommends other products based on the purchase history and ratings provided by other users on the website. The latter part is done using collaborative filtering techniques.

What we learned

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.

What's next for Product-Recommendation-System-for-e-commerce

Product Recommendation System for e-commerce businesses A well developed recommendation system will help businesses improve their shopper's experience on website and result in better customer acquisition and retention

Built With

• datascience
• ml
• python