AI-based solution built for Monger E-commerce
Monger is an e-commerce company based in the USA. The company provides a unique opportunity for its customers to pay back the education loans with the credits earned with each purchase they made through the platform.
Maintaining an up-to-date inventory is a big challenge for large retailers especially for online e-commerce stores. Product categorization is indispensable for e-commerce websites. A typical e-commerce platform lists hundreds of products from different vendors but they all need to be classified under various categories.
The vendors have to upload the product images in bulk and the e-commerce platform has to go through these bulk images to classify the images based on products. Monger had to assign many employees to work continuously to classify the images based on products. This process was very time-consuming and proved to be very costly. They wanted a system that would automatically classify the images. Accurate tagging for all products based on a standardized product taxonomy is vital so that customers can find and purchase what they’re looking for.
The client put forth requirements to build an efficient solution that will enable the classification of thousands of product images with a high degree of accuracy. The client also wanted to reduce the manpower required for the job and wanted to classify the products much faster.
We created an AI-powered image classification tool using machine learning algorithms. The AI-based Inventory Classifier tool can compare two different product images and find the degree of similarity between the two. The system does so by extracting key points and features from the images then it is matched together to calculate the degree of similarity.
Apart from that, the Inventory Classifier tool compares the names of the different products to calculate their differences. In the end, a final score is assigned by the system. Using this score, the system was able to classify the product. It can even conduct product name analysis and tag them with appropriate category names.
The AI-based Inventory Classifier tool was able to sort and classify thousands of product images with a high degree of accuracy. A job that takes weeks to complete was done in just an hour. With the implementation of the Inventory Classifier, the client was able to reduce the manpower required for the tedious job. The system also allowed to update the products in a much faster way. By using deep learning to categorize millions of products quickly and accurately, the client was able to deliver a better search experience to the users.
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Key points extraction
Product name analysis and tagging
Product family categorization