AI and PIM integration: the why, the how & the benefits

Breaking down AI terms

Before diving deeper into AI and PIM integration, it’s helpful to understand the basic terms and concepts that will be discussed:

• AI: This is often described as the umbrella term. It relates to the overarching concept of making machines smarter. Aka artificial intelligence.
• Machine Learning (ML): As a subset of AI, refers to a machine’s ability to learn based on data and algorithms to train a model. Ultimately, the value of ML is its ability to enable machines to self-learn and in doing so create opportunities from data. It’s fair to say most AI leverages some form of ML. Why? Intelligence comes from learned, data-oriented behavior.
• Computer vision: This field of AI covers a machine’s ability to derive meaningful information from digital images, videos, etc. Using that visual input, the machine can act or make recommendations. An example of this is Custom Vision, which is part of the Microsoft Azure Cognitive Services.
• Natural language processing (NLP): Another branch of AI, NLP gives machines the ability to understand, interpret, and manipulate text and the spoken word, in much the same way as humans. Natural language understanding (NLU) and natural language generation (NLG) are both components of NLP. As with ML, NLP requires structured data for machines to process it efficiently and accurately.

Understanding these core AI concepts is critical as they drive how AI-powered solutions integrate with PIM systems and create smarter, more efficient workflows.

The why: Understanding the importance of AI and PIM integration

PIM ensures data consistency across all channels, which is crucial for AI to generate high-quality, reliable content. AI needs a solid foundation of product data, and PIM provides that foundation by centralizing and organizing all product-related information.

Example in Action: Global companies like New Balance and Carhartt rely on inriver’s PIM to provide complete and accurate product information across all platforms, including marketplaces, resellers, and social platforms. This would be a challenging task without PIM, as managing accurate product data across numerous channels and regions would become inefficient and error-prone.

What to look for in a PIM system for AI integration

For AI to work effectively, your PIM system must be capable of handling structured and accurate product data across all channels. Here’s some features to look for when choosing a PIM that will integrate seamlessly with AI:

1. Centralized Data Repository:
   • Your PIM system must act as a single source of truth, housing all product-related data. This ensures that AI models can pull accurate and consistent data, leading to better content generation and personalization.
   • Look for: A PIM solution that centralizes data in one place, providing a consistent, structured foundation for AI tools.
2. Real-Time Data Updates:
   • For AI to generate real-time content, your PIM should enable real-time data updates across all platforms. This helps ensure that the AI system always works with the latest product information.
   • Look for: A PIM system that offers real-time synchronization with AI applications, ensuring continuous, up-to-date data for accurate outputs.
3. Scalability:
   • As your business grows, so does the need for larger product catalogs and the complexity of AI applications. Your PIM must be able to scale with these changes, managing increased product information, languages, and markets.
   • Look for: A PIM solution that grows with your business needs, able to handle a high volume of product data, multiple languages, and market-specific content.
4. Integration Capabilities:
   • Your PIM should integrate smoothly with various AI-powered tools, including machine learning models, computer vision, and NLP. These integrations will help automate processes like content creation, translation, and customer recommendations.
   • Look for: A PIM with API capabilities for seamless integration with AI platforms and third-party tools like IBM Watson, OpenAI’s ChatGPT, or Google Cloud AI.
5. Flexibility and Customization:
   • AI models can be tailored to meet the specific needs of different markets or customer segments. Your PIM system should support customization for these different requirements, making it easier for AI to personalize content and experiences.
   • Look for: A PIM that allows for easy customization of product attributes, categories, and metadata to meet the specific needs of AI models.
6. User-Friendly Interface:
   • While AI and PIM can be powerful tools, they must remain accessible to your team. A user-friendly interface is essential for managing AI-driven product information and insights.
   • Look for: A PIM with an intuitive, easy-to-use interface that enables product managers and marketers to efficiently manage data and extract insights generated by AI.

The how: how AI and PIM work together to create seamless product experiences

Generative AI can automate the creation of product content—descriptions, specifications, and marketing copy—by pulling accurate data from a PIM system. This reduces manual effort and costs associated with maintaining product data. For example, AI can analyze product imagery using computer vision to automatically pre-populate key attributes such as color, size, or model specifics into the PIM system, ensuring consistency across all channels.

Additionally, PIM systems integrated with AI tools like IBM Watson can generate SEO-optimized content tailored to regional markets and search trends, improving discoverability and engagement.

Example in Action: inriver’s PIM integrates with AI tools like IBM Watson to streamline product content creation. Watson scans product descriptions and automatically populates keyword fields, while computer vision helps analyze product imagery, ensuring accurate and enriched data across multiple platforms.

1. Advancing Multimodal Content Generation: AI’s New Role in PIM

AI is evolving to support multimodal content creation, processing various forms of media such as text, images, and videos. With the right PIM system, businesses can:

• Automate Comprehensive Content Creation: AI creates detailed and engaging product descriptions using diverse media, significantly reducing manual content creation time.
• Enhance Localization: AI translates and tailors content across different media to meet the cultural needs of global markets.
• Improve Customer Engagement: AI-driven content provides a richer, more informative experience for customers, increasing conversion rates.

inriver’s AI-powered Inspire module integrates tools like OpenAI’s ChatGPT to automate content creation in multiple languages, ensuring hyper-localized and SEO-optimized product descriptions. The next iterations will allow users to input images, audio, and video, creating even more engaging product stories.

Example in Action: inriver’s Inspire module leverages OpenAI’s ChatGPT to generate hyper-localized, SEO-optimized content for customers like Prysmian Group, improving their global reach and engagement by tailoring product descriptions across different markets.

2. AI-Powered Personalization and Product Recommendations

AI is revolutionizing personalization in eCommerce. By analyzing customer behavior and preferences, AI recommends products tailored to individual needs. Brands can now leverage AI-driven recommendation engines through their PIM systems to create personalized experiences.

Example in Action: inriver partners with companies like Apptus to deliver AI-powered personalized recommendations that enhance the shopping experience for retail and e-commerce brands.

3. Conversational Commerce: AI for Real-Time, Personalized Customer Support

Conversational commerce is about providing convenience and personalization through digital assistants, chatbots, and live video chat. Using NLP, AI can engage customers in real-time, helping them discover products and answer questions. It opens up opportunities for upselling and cross-selling while fostering an ongoing relationship with customers.

Example in Action: inriver integrates with AI-powered chatbots to provide customers like Michelin with real-time support, offering immediate assistance based on accurate, up-to-date product data for their customer service needs.

4. AI-Driven Digital Shelf Analytics for Smarter Insights

AI-powered analytics help brands monitor their digital shelf performance by providing insights into product display, stock issues, and customer behavior. inriver’s Evaluate solution helps brands adjust pricing strategies and optimize their product presentation.

Example in Action: Inriver Evaluate provides brands like Carhartt with insights into how their products perform across multiple platforms, enabling better decision-making and optimized pricing strategies.

5. AI and PIM for Consistent, Accurate Translations

AI-powered translation tools rely heavily on consistent, structured product data to deliver accurate translations. PIM ensures that product information remains uniform across languages and regions, which is critical for accurate AI-driven translations.

Example in Action: Global e-commerce platforms, like Prysmian, use inriver PIM to standardize data and ensure accurate translations and culturally relevant content for international markets, improving their global sales reach.

6. Enhancing After-Sales Services with Generative AI and PIM

After-sales services are vital for customer satisfaction, and AI can significantly improve them by offering support through chatbots, virtual assistants, and personalized recommendations. With accurate, up-to-date data from PIM, AI can respond precisely to customer inquiries, suggest products, and connect them to human operatives when needed.

Example in Action: Michelin uses AI-powered chatbots integrated with inriver’s PIM system to provide instant after-sales support, ensuring that customers receive accurate, helpful information.

7. AI for Cross-Selling and Bundling

Effective product bundling and cross-selling can increase sales and enhance customer satisfaction. AI analyzes product data from the PIM system to generate personalized suggestions that increase order value and improve the shopping experience.

Example in Action: Pandora uses inriver’s PIM and AI to analyze product data and recommend personalized bundles, which boosts customer satisfaction and increases sales.

8. Generative AI for Visual Content Creation

Generative AI can automatically produce high-quality videos and images to showcase products. AI pulls detailed product information from the PIM system to create consistent, on-brand visuals that enhance customer engagement and drive sales.

Example in Action: A furniture retailer uses inriver’s PIM to generate dynamic product images and videos with AI, ensuring visual consistency across all digital channels and improving online shopping experiences.

9. Creating a Continuous Feedback Loop with AI and PIM

By integrating AI with PIM, businesses create a dynamic system that continually enhances product information. AI gathers and analyzes data, identifying discrepancies and automatically updating information to improve product descriptions and customer experience.

Example in Action: inriver’s screen scraping technology helps brands like New Balance continuously gather data across channels to improve product descriptions and other relevant details, ensuring consistent and up-to-date information.

Conclusion: the future of AI and PIM integration

As AI technologies continue to evolve, integrating them with a solid PIM system will be key to unlocking their full potential. A reliable PIM system ensures that AI has access to structured, accurate, and consistent product data, enabling businesses to automate tasks, personalize experiences, and scale operations efficiently.

inriver PIM is at the forefront of this integration, enabling businesses to stay ahead of the curve by harnessing the power of AI and creating better customer experiences across all touchpoints.

Leading brands like Michelin, Prysmian, and Pandora are leveraging AI and PIM to create personalized, data-driven customer experiences.

With the right PIM solution, businesses can ensure their AI applications are built on a foundation of accurate, consistent data, setting the stage for better customer engagement and satisfaction.