Case study MercadoLibre

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Product categorization with Machine Learning

Categorization has become much more efficient and we implemented some automation of category creation and product classification.

Headquarters

Buenos Aires, Argentina

Founded

1999

Stock

NASDAQ, MELI

Efficiency and automation boost

MercadoLibre is the largest online retailer in Latin America with over 100M users. It is an e-commerce and auction platform that provides users with buying and selling mechanisms for e-transactions. We established a working relationship with them in order to solve issues related to the category tree of their product catalog.

-80% cost

item categorization

Challenge

E-commerce businesses spend a considerable amount of time and effort in organizing their products. MercadoLibre has a vast catalog, lots of data that needs to be archived and correctly analyzed. They wanted to explore a solution that makes that category tree more efficient and examine ways of automating this process.

Solution

An iteration based on specific goal achievement, ongoing development and progressive team scaling were the basis from which this solution was crafted. Classifying products into a set of known categories by using supervised learning.

approach

Discover our approach

The problem was faced in three stages: Research & Development, bringing the model into production, and exposing it through an API and Frontend development.

Data analysis

R&D implied a massive historical data analysis which later directed us to the hypothesis, trial & error circle until a fair solution was found.

Tryolabs has been a key piece in optimizing and extending our category trees at a much higher pace than we could achieve with our former tools and teams. Through the mastering and customization of state of the art Machine Learning techniques, we've been able to increase item "findability" and conversion rates. We are so glad to have them collaborating with us in the quest for the best e-commerce solution. I would absolutely recommend them.