PIM Systems

Boost Your E-commerce Efficiency with AI-Powered PIM Systems

In the age of information, data is key. This is especially true for e-commerce. Since you don’t really get to interact with your buyers, you have no option but to decipher the trail of clues. Data can give you everything you need to know, provided you know how to harness it. 

Managing product data has become a critical challenge for large online brands and sellers. With thousands or even millions of products in their catalogues, it’s essential for them to ensure the information on each SKU (stock keeping unit) is accurate, up-to-date, and well-organised, as this will ensure a seamless shopping experience to their customers.  

This is where AI and automation come into play, revolutionising the way product data is managed and streamlining the entire process. Keep reading to find out about the potential of AI in the e-commerce space. 

What are product information management systems? 

Product information management systems are the central hub for storing and managing SKU and product data in e-commerce enterprises.  

For small e-commerce brands, it is easy to manage your product catalogue on your own. It is only when you scale up that the problems arise. When your product catalogue increases from a few hundred to a few thousand, manual handling becomes impossible.  

Product information management systems can handle all this data with ease. With advancements in AI and automation technologies, product management systems have evolved into powerful tools that automate various data management processes, leading to increased efficiency, accuracy, and overall business success. 

Benefits of an automated product information management 

  1. Automation 
    One of the most significant benefits of leveraging AI and automation within product information management systems is the automation of data entry.  

    Manually entering SKU and product information in the system is not only tedious, but prone to errors as well. AI-powered OCR technologies can scan and extract data from various sources, such as product images, labels, and specifications, and automatically populate the relevant fields within the system. This eliminates the need for manual data entry, reducing the risk of human errors and saving valuable time for employees to focus on more strategic tasks. 

  2. Categorisation
    Categorising products accurately is crucial for effective product discovery and navigation on e-commerce platforms. AI-powered image recognition and natural language processing algorithms can analyse product attributes, descriptions, and images to automatically assign the most appropriate categories and subcategories. This not only saves time but also ensures consistent and accurate categorisation across the entire product catalogue. 

  3. Search enhancement
    Robust search capabilities are vital for customers to find specific products quickly and easily. AI algorithms can analyse user search queries, historical data, and customer behaviour to deliver highly relevant search results.  

    By leveraging machine learning, the search functionality within a product information system can be improved continuously over time, drawing on the learning from user interactions. As a result, customers can discover products more efficiently, boosting conversion rates and customer satisfaction. 

  4. Accuracy
    Product or SKU data often needs to be updated regularly, whether it’s due to changes in specifications, pricing, or availability. Manually managing these updates across a large product catalogue can be a daunting task. AI algorithms can monitor and identify inconsistencies or errors in the data, automatically flagging them for review and correction. This ensures that the product information remains accurate and up to date, avoiding any potential misinformation that could dent the customer experience or erode trust. 

  5. Product performance
    By analysing vast amounts of data, including sales figures, customer reviews, and social media sentiment, AI algorithms can identify patterns and trends that enable you to make data-driven decisions.  

    For example, you can identify underperforming products that may require adjustments. These insights help optimise your product offerings and drive revenue growth. 


It’s important to note that AI and automation are not meant to replace human expertise, rather enhance it. While AI and automation offer significant advantages in streamlining product data management, human expertise remains crucial in overseeing and fine-tuning these technologies. 

Implementing AI and automation in PIM systems requires careful planning, integration, and ongoing maintenance. You must invest in robust infrastructure, data quality management processes, and cross-functional collaboration to ensure seamless integration. Check out Ordazzle’s product management system in action – speak to our experts today!