For a long time, product registration was treated as an operational task. Name, code, brand, dimensions, color, material, category, subcategory, price, inventory, image, and a technical description good enough to feed the ERP, publish the product on the ecommerce platform, and make the item available online.

It worked for years.

But it worked for an internet that no longer exists.

Consumers have changed the way they search. They are no longer just looking for a product name. They describe a need. They share a situation. They bring a question. They ask for advice. They compare possibilities. They have a conversation.

And this is where many ecommerce platforms begin to reveal a major weakness: they are still prepared to respond to keywords, while consumers are already asking questions in natural language.

I have been showing this in talks and recent projects. We urgently need to rethink the way products are registered in ERPs, ecommerce platforms, and digital catalogs. The ERP may need a technical description, because its role is to organize the operation. But a brand’s own ecommerce platform cannot bring that same cold, limited, internal logic into the consumer experience.

The ERP sees the product as an inventory item.

The consumer sees the product as a solution within a context.

This difference may seem simple, but it changes everything.

During a talk at ABRIN, I used an example that clearly illustrates this new moment. I ran a conversational search for a toy for a level 3 autistic child, something that requires attention to very specific characteristics, such as appropriate sensory stimulation, safety, simplicity, predictability, resistance, texture, noise level, usage format, and level of complexity.

This is not an ordinary search. It is a search filled with context.

It is not about looking for a “children’s toy.” It is not even about looking for an “educational toy.” The intent is much deeper. The consumer wants help to choose better. They want to reduce the risk of buying the wrong product. They want to understand what makes sense for a child with specific needs.

When I brought that same logic to one of the largest toy ecommerce sites in the world, Toys R Us, the results showed the size of the problem. The search led to products such as a three level parking garage, because of the association with “level 3,” and a level 3 difficulty puzzle, exactly the opposite of what that search intent required.

This example is powerful because it does not show only a search failure. It shows an interpretation failure.

The website found words. But it did not understand the person.

That is the real rupture.

For years, we believed that improving internal search meant better organizing keywords, tags, categories, and filters. This still matters, but it is no longer enough. The new search is no longer born only from isolated terms. It is born from context, intent, usage occasion, restrictions, needs, consumer profile, and purchase purpose.

The customer does not want to type “black cotton T shirt size M.”

They may ask: “Which black T shirt can I wear to a casual event, that does not get too warm and does not wrinkle easily?”

They are not only searching for “ergonomic office chair.”

They may ask: “Which chair makes sense for someone who works eight hours a day from home, has lower back pain, and has little space in the bedroom?”

They are not simply looking for “sensory toy.”

They may say: “I need a safe gift for a level 3 autistic child who is bothered by noise and likes soft textures.”

The difference between these searches is not in the product. It is in the intelligence required to connect the product to the real problem.

And most owned ecommerce sites are still not ready for this.

I have had the opportunity to conduct analysis projects for companies in different segments, and the scenario repeats itself with worrying frequency. Catalogs rich in SKUs, but poor in meaning. Products that are well registered for the operation, but poorly explained for the journey. Descriptions that serve the system, but do not support the decision. Important attributes hidden. Benefits poorly translated. Possible uses ignored. Restrictions not declared. Consumption occasions absent.

Digital retail still carries the legacy of the internet of the 2000s. An internet based on entries, rigid fields, keywords, and category based navigation.

But consumers have already been trained by another logic.

They talk to AI to choose a trip, compare a smartphone, plan a diet, understand a health issue, summarize a contract, organize a party, choose a gift, and decide what to buy. They do not want only a digital shelf. They want guidance.

And when guidance does not come from the website, it comes from somewhere else.

This may be the most important point for any company with its own ecommerce platform: the fight for the sale begins before the visit to the website. In many cases, it starts in a conversation with artificial intelligence. The consumer asks AI what to buy, why to buy it, which criteria to consider, which brands to compare, and which risks to avoid.

If AI does not understand your products, it will not recommend your products.

And it only understands what is well structured, well described, well contextualized, and connected to a real search intent.

The keyword is dead as the center of search.

This does not mean it has disappeared. It means it has lost the throne.

In times of AI, it is not enough to register “blue school backpack.” You need to explain who it is for, in which occasion it works, which age group it serves, how much weight it supports, which routine it fits into, which pain points it solves, which doubts it removes, and which choice criteria it can answer.

It is not enough to register “facial moisturizer.” You need to explain skin type, texture, usage moment, restrictions, sensitivity, expected result, composition, comparison with other products, and common questions from buyers.

It is not enough to register “educational toy.” You need to explain the skill it stimulates, the real age range, level of complexity, need for supervision, sensory stimulation, safety, inclusion, durability, and usage context.

Product registration must stop being only technical and become semantic.

It must stop answering only “what is it?” and start answering “who is it for?”, “when does it make sense?”, “why choose it?”, “when should it be avoided?”, and “which problem does it solve?”

This movement is not just an SEO improvement. It is a structural change in sales.

Because ecommerce platforms that do not understand context lose relevance on three fronts.

They lose inside their own websites, when they deliver poor results for more complex searches.

They lose outside their websites, when artificial intelligences cannot correctly interpret their products.

And they lose at the decision stage, when the consumer finds clearer, more useful, and more trustworthy information somewhere else.

The irony is that many companies invest millions in media, traffic, performance, and technology, but still treat product registration as a secondary, almost bureaucratic step. In the new search environment, however, product registration becomes a strategic asset. It is the raw material for discovery, recommendation, and conversion.

A poorly described product may even appear.

But it will hardly be chosen.

The next leap for owned ecommerce will not be only about adding AI to customer service, creating a chatbot, or personalizing the storefront. Before that, companies will need to put their house in order. Review product registration. Enrich attributes. Rewrite descriptions. Create smarter taxonomies. Map search intents. Understand real consumer questions. Translate technical characteristics into clear benefits. Prepare the catalog to be understood by both people and machines.

Consumers are already searching in a different way.

They no longer want only to find products. They want to find answers.

The big question is whether your ecommerce is prepared to answer.

Because while many websites are still trying to match words, consumers are already expecting someone to understand their context.

And when one brand does not understand, another one will.

Or AI will understand on its behalf.

And if it make you think, make it happen!

Caio Camargo