AI Product Recommendations: Teaming Up with Top Japanese Data Provider
In a Nutshell
A Japanese data provider with 60M+ registered users partnered with us to implement an AI-powered product recommendation engine that delivers hyper-relevant suggestions based on real-time user behavior and purchase history.
In a Nutshell.
A Japanese data provider with 60M+ registered users partnered with us to implement an AI-powered product recommendation engine that delivers hyper-relevant suggestions based on real-time user behavior and purchase history.
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Inside the Opportunity
- Customers were overwhelmed by the sheer volume of 80 M+ products across 80+ categories.
- Generic product suggestions led to high bounce rates and low conversion.
- Users often drop off during lengthy product searches.
- Lack of personalization limited customer engagement and repeat purchases.
- The platform needed to stand out in Japan’s saturated e-commerce landscape.
Inside Innovature’s Thinking
- Designed and deployed a machine learning engine trained on customer browsing habits, sales history, and behavior patterns.
- Integrated advanced recommendation algorithms to dynamically suggest products based on real-time interest and purchasing signals.
- Enabled continuous learning to refine suggestions as new data streams in.
- Created a scalable architecture to handle high-volume customer interactions across millions of SKUs.
- Embedded recommendation modules across landing pages, product listings, and checkout to enhance discoverability.
Inside the Impact
46%
30%
70%
Client Overview
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.
Our 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.
Client Benefits
They experienced a notable 30% increase in website traffic, attracting a larger audience and expanding their online presence. Moreover, our solutions contributed to a remarkable 46% boost in overall sales, driving revenue growth and maximizing profitability. Through personalized interactions, we ensured that each user received tailored experiences, fostering stronger customer relationships and improving satisfaction. Additionally, our services brought more convenience to customers, making their interactions with the brand easier and more streamlined.
Overall, our solutions delivered increased website traffic, heightened sales, personalized interactions, and enhanced convenience, resulting in a highly successful outcome for the client.
