Artificial intelligence (AI) has revolutionized the way companies manage their product data. One area where AI has had a significant impact is product categorization within Product Information Management (PIM)-software. According to a report from Markets and Markets, the size of the PIM market is expected to grow from USD 7.0 billion in 2020 to USD 16.0 billion in 2025 at a compound annual growth rate (CAGR) of 17.3%. The increasing demand for efficient and accurate management of product data is largely driving this growth. With the integration of AI in PIM, the software has unlocked tremendous capabilities, including the ability to categorize products in ways that greatly enrich the customer experience.
WHAT IS PRODUCT CATEGORISATION?
Product categorization is the process of organizing and classifying products into categories based on specific characteristics such as size, color, material and price. A well-designed categorization system improves the accuracy, consistency and completeness of product data and is a must for any ecommerce store. Without the product category structure that guides online shoppers, customers could easily get lost on an ecommerce site. However, proper categorization makes it easier for customers to find the products they want while maximizing their shopping experience.
Product categorization is an important process that benefits both companies and customers. It enables brands to manage large amounts of product data more efficiently. For example, an ecommerce store can deal in a wide variety of products, such as clothing, electronics, and furniture. To easily retrieve, edit and update product data, such a store should establish a reliable product taxonomy and then proceed to categorize products based on their characteristics. Failure to do so will result in inaccurate data and inconsistent product representation across all sales channels. On the contrary, efficient categorization leads to a better customer experience, more product visibility and improved product data accuracy.
HOW CAN AI IMPROVE PRODUCT CATEGORISATION IN PIM?
Now that the importance of product categorization is clearly established, let's look at the role of AI in this crucial PIM function. Without the input of AI and its subsets, PIM can efficiently categorize products. But of course AI makes everything better, faster and more accurate. Therefore, companies with large product data should consider implementing AI-driven PIM in their long-term product strategy. AI improves the process of categorizing products in several ways. Here are five such ways:
AUTOMATED DATA ENRICHMENT
AI can improve product categorization in PIM software through automated data enrichment. AI has robust algorithms and techniques that allow it to automatically enrich product data. For example, using Natural Language Processing, AI can automatically extract product features from data sources, such as product descriptions and images, and add them to product data fields. This ensures that all relevant product features are captured and included in the categorization process.
In addition, AI can normalize attribute values to ensure consistency across different product categories. For example, AI can recognize that “gray” and “gray” are the same color and normalize them to a single attribute value. In addition, AI can automatically update product data based on product attributes or taxonomy changes. This ensures that product data is always up-to-date and accurate. If
as a result, the need for human input is reduced, enabling the process of product data management.
MORE ACCURATE PRODUCT DATA
Incomplete, inaccurate, and duplicate information are forms of dirty data that can harm product taxonomy and categorization. When using manual methods, dirty data is likely to corrupt the categorization process. However, AI negates that by ensuring higher data accuracy. An important way AI ensures accurate data is through automated data entry. After extracting product attributes from various sources, Ai can automatically populate the data fields in the PIM software. This eliminates the need for manual data entry, which is prone to errors.
Also, AI can scan tons of product data, detect missing or duplicate attributes and immediately prompt end users to update the information. In addition, AI features such as automatic categorization and attribute normalization can significantly improve the accuracy of product data, making AI-powered PIM a huge asset for ecommerce brands.
FASTER CLASSIFICATION
A Unilever case study showed that using AI to automate product categorization reduced the time it takes to classify with 97%. AI-powered PIM helps businesses save time otherwise spent on repetitive and manual tasks, enabling brands to process more product data at a time and improving productivity in other areas. This is possible thanks to the robust functionality of AI, which allows it to process and perform multiple tasks simultaneously. Also, machine learning algorithms can learn from past classification decisions and improve the accuracy and speed of future classifications. Therefore, with a significant amount of data, brands can benefit from speed while maintaining efficiency that allows them to categorize products in the best possible way.
DYNAMIC TAXONOMY
Many brands use a static taxonomy system where the predefined structure and categories remain unchanged. While such a taxonomy is easier to maintain, it creates problems when the company tries to introduce new ones that don't easily fit into existing categories. For example, an electronics store might have a taxonomy based on categories such as laptops, smartphones, and smartwatches. If such a brand adds smart speakers to its range, categorizing the new acquisition becomes problematic.
Therefore, there is a need for dynamic taxonomy where new categories are created upon detection of new attributes. AI can help implement a dynamic taxonomy system using machine learning algorithms that can automatically create new attributes that are consistent with the existing structure. This enables companies to better manage their product information, improving product findability in the process.
RICHER CUSTOMER EXPERIENCE
By improving the product categorization process in PIM software, AI ultimately improves the customer experience. With better product categorization, customers will easily find the products they need, increasing customer satisfaction and improving sales. AI can also suggest other products that the customer might be interested in based on their browsing history and behaviour. This creates a much-needed sense of personalization that will always delight customers.
In conclusion, product categorization is a crucial process PIMsoftware that helps companies manage their product data more efficiently. AI can significantly improve this process by improving data accuracy, increasing efficiency and providing a better customer experience. AI-powered PIM software enables companies to gain a competitive advantage by providing their customers with accurate and relevant product information at all times.
