An online buyer’s response to visual images is multifaceted and deeply intertwined with cognitive, emotional, and cultural processes. I have previously addressed how understanding these responses is crucial for product information management’s (PIM) role in effectively leveraging visual communication to capture customer attention and interest.

Hence, media assets play a crucial role in shaping the ecommerce experience. In fact, 80% of customers say the experience is just as important as the products themselves. High-value assets enhance visual appeal, facilitate product understanding, build trust, reduce uncertainty, increase engagement, differentiate, optimize for mobile, and promote social sharing and virality. Investing in high-quality media assets is essential for ecommerce business looking to succeed in a competitive online marketplace.

With the exponential growth in generative AI (GenAI), it was only a matter of time before the two crossed paths. Combining PIM systems with GenAI techniques for media classification offers several benefits in organizing and enriching product data.

Automated Tagging and Classification

Generative AI models, like convolutional neural networks (CNNs) or recurrent neural networks (RNNs), can be trained to analyze media assets and automatically tag them with relevant metadata. For example, a GenAI model classifies images based on product categories, colors, patterns, or other visual attributes. These tags then seamlessly integrate into the PIM system, generating product data and improving searchability.

Semantic Image Understanding

Advanced generative AI models, like generative adversarial networks (GANs) or variational autoencoders (VAEs), can learn the semantic meaning of images and videos. This understanding allows the system to categorize media assets not just based on pixel-level features but on higher-level concepts such as product type, style, or context. The enriched metadata enhances organization and retrieval of media assets within the PIM system.

Content Moderation and Quality Control

GenAI models can moderate content and control quality by identifying inappropriate or low-quality media assets. Think: AI algorithms detect offensive content, watermarks, or blurry images, ensuring only high-quality and appropriate media assets are included in the PIM system.

Personalization and Recommendation

Analyzing media assets and associated metadata personalizes product recommendations for customers. The AI learns from past interactions and preferences to suggest visually similar products or recommend complementary items based on visual characteristics.

Visual Search

Integrating generative AI capabilities enables advanced visual search functionality. Customers upload images of products they’re interested in, and the system uses GenAI to find visually similar items from the product catalog. This enhances user experience and simplifies product discovery.

Dynamic Content Generation

GenAI models dynamically generate media assets tailored to specific contexts or customer segments. The system generates customized product images for different marketing campaigns, seasonal promotions, or target demographics, optimizing the visual content based on PIM-driven insights.

Cross-Channel Consistency

By leveraging generative AI for media classification, organizations ensure consistency in visual content across various channels and touchpoints. This consistency reinforces brand identity and improves overall coherence of the customer experience.

Combining generative AI techniques with product information management systems further enhances the impact visual media assets have across customer ecommerce experiences. Additionally, this integration enhances the efficiency, effectiveness, and intelligence of media asset management. Even more now than ever, organizations can give customers an experience that matches and enriches product quality.

Malik Azeez, Director of Product Information Management & Offshore Delivery