Retail
❯
Personalization
❯Product recommandation
Product recommandation
Scope:
Shopping online from multi-store ecommerce platforms such as Amazon FR or Daraz, often has the same product with different criteria sold by different stores. The same product often has different prices, reviews and positive rates. The customer often get confused on which store to choose and looses track from the perfect product or store.
Goal:
Improved Customer Experience
Large Companies
Small Companies
Retail - Personalization
For:
Content marketers
Scope:
Personalizing marketing messaging using Natural Language Generation to increase marketing campaign return on investment.
Goal:
Improved Customer Experience, Increase Revenues
Product recommandation
Goal:
Improved Customer ExperienceProblem addressed
The recommendation system would search all the stores or similar with the same products(like the existing recommendation system) and on the basis of results would recommend.
Scope of use case
Shopping online from multi-store ecommerce platforms such as Amazon FR or Daraz, often has the same product with different criteria sold by different stores. The same product often has different prices, reviews and positive rates. The customer often get confused on which store to choose and looses track from the perfect product or store.
Description
By introducing a refined recommendation system that further analyze the similar and existing products from multiple stores and recommend better on the parameters such as reviews, price, number of orders, popularity, negative or positive ratings, comments, season/environment and most importantly user's personal characteristics. This recommendation is further refined form of an existing system.
Machine Learning
AI: Understand