Product Recommendation System

Our Experience developing an AI-enabled product recommendation solution for a leading e-commerce service provider.

Customer Profile:

Our client is one of the leading Data providers based out of Japan. With a registered customer base of over 60 million and offers over 80 million products across 80+ categories, they are well known for pioneering services such as Cash on Delivery, No Cost EMI and easy returns. Their major focus is on customer-centric innovations that elevate the user experience.

Problem Statement:

With the abundance of eCommerce businesses nowadays, each company is trying to add more value to the platform to ensure an elevated customer experience and increased customer retention. Searching through thousands of products is one of the major contributing factors for customers dropping off before purchase. Using a product recommendation system that allows customers to find the products relevant to them quicker and easier will directly contribute to increased retention rate, achieve better sales, and reduce the customer buying cycle.

Project Background:

Companies like Amazon, Netflix, and Spotify are using recommender systems, which allow customers to find the products relevant to them quicker and easier. Our client wanted to create a product recommendation engine to increase the retention rate, achieve better sales, and make the buying process more convenient for its customers.

Challenges:

  • Lack of structured data
  • Changing user preferences
  • Unpredictable items
  • Optimizing time of responding
  • Predicting unseen information

Technology:

Development language: Php, Python Database Server: MySQL File Storage: AWS S3 Hibernate Content Delivery: AWS CloudFront

Solution:

The solution equipped the client to collect and analyze shopping behaviors from all customers, including the store’s sales history, and enabled them to study what the customers are interested in and most likely want to buy, using machine learning. With advanced recommendation algorithms, the application automatically suggested the right products to the right customers.

Achievements:

  • Create and maintain a consistent Brand and User Experience.
  • Avoid Customer Frustration
  • Personalized Interactions for each user
  • Customized and Relevant Content

Return on Investment:

Increased the traffic to the site by around 30% and overall sales by 46%.