Artificial Intelligence is changing how customers discover, evaluate and purchase products. While much of the conversation has centred around ChatGPT, AI shopping assistants and automated customer service, many retailers are overlooking the factor that will determine who succeeds in this new era.
It is not the AI platform.
It is not the commerce platform.
It is not even your marketing.
It is your product data.
Retailers with complete, accurate and enriched product information will increasingly be recommended by AI search engines, shopping assistants and commerce platforms. Those with poor quality data risk becoming invisible.
For many businesses, AI product data will become one of the most valuable commercial assets they own.
Why Product Data Matters More Than Ever
Traditional search engines relied heavily on keywords, backlinks and page authority. While those factors remain important, AI systems operate differently.
Large language models attempt to understand products in context rather than simply matching keywords. Instead of asking:
“Cordless drill”
Customers now ask:
- Which cordless drill is best for building a timber deck?
- Which drill works with Makita batteries?
- What’s the best impact driver under $500?
- Which drill is suitable for commercial electricians?
To answer these questions confidently, AI requires structured, factual and comprehensive product information.
If your catalogue lacks detail, AI has very little information to work with.
Your Product Catalogue Has Become a Knowledge Base
Many retailers still think about product information as something required to populate a product page.
That mindset is rapidly becoming outdated.
Your catalogue is now a knowledge base that feeds:
- AI search
- ChatGPT and other large language models
- Google AI Overviews
- Google Shopping
- Merchant feeds
- Marketplace integrations
- Internal site search
- Customer service chatbots
- Recommendation engines
- Product comparison tools
The more knowledge your products contain, the more useful they become to both customers and AI.
What Does Good Product Data Look Like?
Many ERP systems were designed primarily for inventory management rather than digital commerce.
As a result, retailers often inherit product information that looks something like this:
Product Name
ABC123 Drill
Description
18V Cordless Drill
That’s enough for an internal warehouse.
It is nowhere near enough for AI.
A modern AI-ready product should include rich information such as:
- Detailed product descriptions
- Technical specifications
- Dimensions and weight
- Materials
- Colour information
- Installation instructions
- Compatibility information
- Warranty details
- Frequently asked questions
- Buying advice
- Usage scenarios
- Safety information
- Images from multiple angles
- Videos
- Technical documentation
- Certifications
- Replacement parts
- Related accessories
Every additional piece of structured information helps AI understand your products more accurately.
AI Understands Relationships
One of AI’s greatest strengths is understanding relationships between products.
Instead of simply recognising a drill, AI understands concepts such as:
This drill:
- uses 18V batteries
- suits timber framing
- is compatible with specific accessories
- is designed for trade professionals
- works alongside other tools in the same platform
Those relationships become incredibly valuable when customers ask complex purchasing questions.
Without structured data, AI cannot confidently make those recommendations.
Compatibility Data Has Become a Competitive Advantage
This is particularly important for industries such as:
- Automotive
- Industrial
- Electrical
- Plumbing
- Safety equipment
- Workwear
- Medical
- Building supplies
Consider automotive parts.
Instead of searching by SKU, customers increasingly ask:
Which brake pads fit my 2023 Ford Ranger Wildtrak?
The retailer with accurate compatibility data has a significant advantage.
The same applies to:
- printer cartridges
- batteries
- replacement filters
- hydraulic fittings
- industrial bearings
- PPE equipment
- replacement components
Compatibility data transforms a simple product catalogue into an intelligent recommendation engine.
AI Can Help Create Better Product Data
The good news is retailers no longer need to manually write thousands of product descriptions.
AI can assist with:
- expanding short ERP descriptions
- generating customer-friendly content
- creating technical summaries
- writing buying guides
- generating FAQs
- producing SEO-friendly copy
- extracting attributes from supplier documentation
- categorising products
- identifying missing information
- creating product comparisons
Rather than replacing your product team, AI dramatically increases their productivity.
Many retailers are now enriching tens of thousands of products in weeks instead of years.
Product Attributes Are Becoming More Valuable Than Categories
Historically, retailers focused heavily on category structures.
Today, attributes are becoming increasingly important.
Instead of asking customers to browse categories, AI filters products using attributes like:
- voltage
- pressure
- capacity
- material
- industry
- application
- brand
- certification
- compatibility
- dimensions
Rich attribute data enables smarter recommendations, more powerful filtering and significantly better AI understanding.
Why ERP Data Alone Isn’t Enough
Most ERP systems were never designed to power AI commerce.
They typically prioritise:
- inventory
- purchasing
- warehousing
- finance
- logistics
Customer-focused content is often limited.
This is why many retailers invest in Product Information Management (PIM) platforms or AI-driven enrichment processes.
These systems allow product information to evolve beyond operational requirements into a genuine sales and marketing asset.
Product Data Improves More Than AI
Investing in product data delivers benefits well beyond AI.
Retailers often see improvements in:
- search engine visibility
- conversion rates
- site search accuracy
- Google Shopping performance
- marketplace listings
- customer satisfaction
- reduced product returns
- fewer customer enquiries
- faster purchasing decisions
- higher average order value
Good product data improves every stage of the customer journey.
Preparing for AI Commerce
AI commerce is no longer a future concept.
Customers are already using ChatGPT, Gemini, Claude and other AI assistants to research products before visiting retailer websites.
The next phase is even more significant.
AI agents will compare products, evaluate specifications, assess availability and eventually complete purchases on behalf of customers.
When that happens, product data becomes your digital salesperson.
The richer your product knowledge, the greater the likelihood your products will be recommended.
Where Should Retailers Start?
Improving product data doesn’t require replacing your commerce platform.
A practical roadmap often includes:
- Audit your existing product catalogue.
- Identify missing attributes and specifications.
- Standardise product structures across categories.
- Introduce richer technical information.
- Improve compatibility data where relevant.
- Use AI to enrich descriptions and FAQs.
- Implement structured data and schema markup.
- Consider a Product Information Management (PIM) platform for large catalogues.
- Continuously improve product information as new products are introduced.
Retailers who treat product data as a strategic asset rather than an administrative task will be far better positioned for the future of commerce.
Final Thoughts
Every major shift in eCommerce has rewarded businesses that adapted early.
The rise of mobile commerce rewarded responsive websites.
The growth of search engines rewarded SEO.
The emergence of marketplaces rewarded strong product feeds.
AI commerce will reward businesses with exceptional product data.
Retailers that invest today in richer descriptions, structured attributes, compatibility information and AI-powered enrichment are building a competitive advantage that will continue to compound over the coming years.
At OSE, we help retailers transform product data into a strategic asset through ERP integrations, PIM solutions, AI-driven enrichment and modern eCommerce platforms. Whether you’re managing 5,000 products or 500,000, the quality of your product information will increasingly determine how easily customers, and AI, can find, understand and buy from you.
