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How to Boost Product Classification With AI

How to Boost Product Classification With AI

Here’s the golden rule for every online enterprise or marketplace: Your online catalog must always be up-to-date and search friendly, despite the rapid influx of inventory and fluctuation in product availability. That is easier said than done, especially if you handle a wide variety and large volume of products from different countries. 

Well-organized product categorization and classification are key to your website’s traffic and customer search engine, but also contribute significantly to your logistics and operations behind the scenes. In order to prevent costly errors due to faulty product classification, you need an AI-based platform that automatically and accurately categorizes merchandise. 

What is Product Classification

Product classification is a crucial process for any eCommerce business. It involves categorizing products based on their attributes, such as size, color, and material. However, manually classifying products can be time-consuming and prone to errors, which is where AI comes in. In this blog post, we’ll explore how AI can boost product classification and help eCommerce businesses save time and improve accuracy.

Use machine learning algorithms

One of the most effective ways to boost product classification with AI is to use machine learning algorithms. These algorithms can learn from existing product data and use that knowledge to classify new products automatically. For example, an algorithm could learn that a certain set of attributes is associated with a particular product category, such as shoes, and then use that knowledge to automatically classify new shoes based on their attributes.

Train your AI models

To get the most out of AI for product classification, it’s important to train your AI models on a large and diverse set of data. This can include product images, descriptions, and other attributes. The more data your AI models have to learn from, the more accurate they will be at classifying products.

Incorporate natural language processing

Natural language processing (NLP) is a branch of AI that can help improve product classification by analyzing and understanding text-based product descriptions. By using NLP, AI can automatically extract relevant product attributes from product descriptions and use them to classify products more accurately.

Use image recognition

Image recognition is another powerful AI technology that can be used to boost product classification. By analyzing product images, AI can automatically identify product attributes such as color, shape, and pattern. This can help improve the accuracy of product classification and reduce the need for manual intervention.

Integrate with your eCommerce platform

To get the most out of AI for product classification, it’s important to integrate it with your eCommerce platform. This can help automate the classification process and reduce the need for manual intervention. For example, an AI-powered product classification system could automatically categorize new products as they are added to your eCommerce platform, saving time and improving accuracy.

What are the benefits of AI-powered product classification? 

Empower accurate product mapping

In order to ensure accurate product mapping, you must first create organized product groups. This means forming macro-categories (dresses, for example) and micro categories that logically fall underneath the main category (casual dresses, summer dresses, etc). AI-powered product taxonomy enables accurate macro and micro categorization predictions based on category ID and taxonomy tags. Product classification using machine learning prevents costly manual mistakes.   

Optimize tariff classification and customs compliance

When dealing with a large volume of products from numerous countries and various retailers there is much room for error. An AI-based system has the ability to use data such as manufacturer, product description and other input to automatically ensure customized classification and accurate tariff codes. The machine-learning classification module can be modified based on each country’s code in the Harmonized Commodity and Coding System, facilitating faultless shipments to customers worldwide.  

Recommend products based on past customer experiences

AI-based classification can be used to recommend new products based on a customer’s past browsing and purchase history. Today’s customers desire personalized content and special offers based on their individual preferences. AI-categorization, which provides actionable insights, enables the delivery of individualized messages. This machine learning tool is used by large businesses like Netflix and Spotify. 

Correlate crucial data of different classes

Aside from the ability to match data within a given class, AI-based techniques also enable the correlation of data from different classes that share association. Machine learning integrates meta-data analysis to achieve a deeper understanding of data. This input enables more discerning automatic cataloging for easy discovery through search. By combining in-depth classification and correlation capabilities, AI provides enterprises with the tools to locate, inventory and map crucial data.

The days of manual categorization for online catalogs are long gone. With inventories counting tens of thousands or even millions of products, most large enterprises are transitioning to automated AI-based platforms to ensure consistency, prevent duplications, and increase customer traffic. 

Best Practices for Implementing AI in Product Classification

To successfully implement AI for product classification, consider the following best practices:

  1. Data Quality: Ensure that the data used to train and test your AI models is of high quality. Garbage in, garbage out still applies in the world of AI.
  2. Regular Updates: Continuously update your AI models to adapt to changing product catalogs and customer preferences.
  3. Human Oversight: While AI can automate much of the classification process, human oversight is crucial for quality control and addressing edge cases.
  4. Security and Privacy: Protect user data and sensitive information during the AI classification process. Comply with relevant data privacy regulations.
  5. Monitoring and Evaluation: Regularly monitor the performance of your AI classification system and be prepared to make adjustments as needed.
  6. Integration with Other Systems: Integrate your AI classification system with other e-commerce systems to ensure a seamless shopping experience for customers.


AI-driven product classification is a game-changer for e-commerce and online marketplaces. It not only enhances the user experience by making products more discoverable and organized but also improves the efficiency of operations and increases profitability. By leveraging AI technologies such as image recognition, NLP, and machine learning, businesses can stay competitive, scale effectively, and offer personalized shopping experiences in a dynamic and ever-evolving market. As AI technology continues to advance, the potential for even more accurate and efficient product classification is bound to grow, making it an exciting time for e-commerce and online retail businesses.  Book a demo with our eCommerce specialists today to see what Cluster can do for you.

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