AI Can Write Your Product Titles.
But Can It Curate Your Catalog?

01.A Polished Title Doesn't Mean a Correct Title

Consider a typical manufacturer product feed. An AI system can turn it into something much more useful:

That's where AI is genuinely valuable — taking fragmented manufacturer information and creating consistent, customer-friendly titles at scale. But technical ecommerce requires more than language generation.

02.One Wrong Attribute Changes Everything

A plumbing product may depend on:

• Connection size and thread type
• Voltage, flow rate and BTU capacity
• Material and finish
• Mounting configuration and dimensions
• Model compatibility and application

If an AI system misunderstands just one of these attributes, the result may be a product that sounds right but isn't.

03."Related" Doesn't Mean "Compatible"

The bigger problem can be product recommendations. On a faucet page, a recommendation engine may surface products with similar words or from the same broad category.

But a bathroom lavatory accessory isn't necessarily relevant to a kitchen faucet. A similar finish isn't necessarily the right match. And a semantically similar product isn't necessarily compatible.

Similarity ≠ Complementarity ≠ Compatibility

04.Understanding Product Relationships

A good recommendation engine needs to understand what relationship exists between two products. Is it:

• Compatible with?
• Frequently purchased together?
• Replacement part?
• Accessory?
• Alternative?
• Installation component?

Or should the products not be recommended together at all? That's merchandising — not just text generation.

05.Bad Recommendations Are More Expensive Than They Look

A recommendation carousel may seem like a small feature on an ecommerce website. It isn't. When a retailer displays "You may also like", the customer assumes the retailer has deliberately selected those products.

If the recommendations are obviously wrong, the customer doesn't necessarily think:

They may simply think:

For professional buyers, that's particularly damaging. A plumber, HVAC contractor or heating engineer isn't browsing for inspiration — they need the right product for a specific job. If the recommendations are unreliable, the retailer is potentially leaving revenue on the table and damaging the trust that is one of its biggest competitive advantages.

06.AI Should Scale Expertise, Not Replace It

This doesn't mean ecommerce businesses should abandon AI. Quite the opposite. AI is exceptionally useful for:

• Generating first-draft product titles
• Transforming manufacturer feeds
• Normalizing product descriptions
• Enriching catalog data and identifying missing attributes
• Creating SEO content and classifying products
• Processing thousands of SKUs

07.Let Humans Define "Correct". Let AI Scale It.

A merchandising expert can define the title structure for a category:

AI can then apply that structure across 50,000 products. Similarly, a product expert can define which products are compatible, complementary or alternative — and AI can use those relationships to automate recommendations across the catalog.

The result is not human versus AI. It is human expertise amplified by AI.

08.The Catalog Is Still the Source of Truth

The strongest technical ecommerce businesses will not necessarily be the ones generating the most AI content. They will be the ones with the best product data and product relationships underneath that content.

Because automation multiplies both quality and mistakes. If AI allows you to generate 100,000 product titles overnight, it can also generate 100,000 mistakes overnight.

09.The Human Advantage Isn't Disappearing

There is an interesting paradox in ecommerce AI: as generic content becomes cheaper to produce, product expertise becomes more valuable. Anyone can ask AI to write:

That's no longer a competitive advantage. Knowing exactly which faucet fits a particular installation, which accessories belong with it, which finish matches the selected variant, and which replacement parts are compatible — that is much harder. That's the expertise customers actually pay for.