Web: https://empremtabarcelona.com/

Three suppliers, thousands of products and a single ecommerce ready to compete

Empremta Barcelona needed a platform capable of bringing together a very extensive merchandising catalogue from different suppliers and with various product structures in a single environment.

The project faced a particularly ambitious challenge: integrating over 9,000 references from Mid Ocean, Makito, and PC Concept into a proprietary, organised, scalable ecommerce platform prepared to compete with some of the main players in the promotional merchandising market.

The volume of the catalogue necessitated planning the project differently from a conventional online shop. It was not just about importing products, but about transforming thousands of references from different sources into a coherent, navigable, optimised catalogue ready to grow.

To achieve this, we combined ecommerce development, automation, SEO, information architecture, and artificial intelligence to organise and categorise the catalogue at scale.

The result is a platform capable of converting thousands of products from different suppliers into a single digital ecosystem under the Empremta Barcelona brand.

Over 9,000 references in one platform

The size of the catalogue was one of the primary challenges of the project.

Working with over 9,000 references means managing thousands of products, variants, colours, materials, formats, characteristics, categories, subcategories, descriptions, images, internal references and data from different suppliers.

Moreover, each supplier organises their catalogue differently.

The same type of product can appear classified under different names, distinct structures, or incompatible attributes.

Thus, before constructing the user experience, it was necessary to establish a common catalogue logic.

Three suppliers, one structure

The platform integrates the catalogues of:

• Mid Ocean
• Makito
• PC Concept

Each has thousands of references but also their own way of organising products, families, attributes, and categories.

The challenge was to avoid Empremta Barcelona becoming merely a sum of three independent catalogues.

The user needed to perceive a single store, a single structure, a single navigation logic, and a single brand.

To achieve this, we developed an architecture capable of normalising the information from the different suppliers and turning it into a coherent commercial catalogue.

The challenge was not merely importing products

Importing products from different suppliers may seem like a relatively straightforward process from a technical standpoint.

The real problem arises afterward.

What happens if one supplier classifies a product as “Drinkware” and another as “Bottles and canisters”?

What occurs if an item appears as “Backpack”, “Rucksacks”, “Backpack” or “Back bag”?

How do we automatically classify thousands of new products?

How do we avoid duplicate categories?

How do we ensure a user finds similar products even if they come from different suppliers?

How do we organise the catalogue so that it also makes sense from an SEO perspective?

These issues make managing a catalogue of thousands of products largely an information architecture problem.

And it is precisely here that artificial intelligence can provide enormous processing capacity.

Artificial intelligence applied to the catalogue

One of the distinctive aspects of the project has been the incorporation of processes supported by artificial intelligence to facilitate the organisation, classification, and normalisation of the catalogue.

AI allows us to analyse large volumes of product information and automatically detect patterns that would manually require hundreds of hours of work.

Rather than relying exclusively on the original categories provided by each manufacturer, we can analyse elements such as:

• Product name
• Description
• Material
• Product type
• Use
• Features
• Potential audience
• Commercial family
• Associated keywords
• Available attributes

From that information, we can establish much more coherent categorisation rules.

A unique taxonomy for Empremta Barcelona

One of the main objectives was for the ecommerce architecture to respond to how customers search, not solely to how manufacturers organise the catalogue.

That is why we developed a unique taxonomy.

This structure allows products to be grouped around commercial categories that are understandable and relevant to the user.

For example:

• Bags
• Backpacks
• Bottles
• Mugs
• Textiles
• Office
• Technology
• Events
• Sport
• Sustainable products
• Corporate gifts
• Custom merchandising

From there, more specific subcategories can be built.

Artificial intelligence helps analyse each product and determine in which areas of the catalogue it makes the most sense to place it.

AI-assisted automatic categorisation

Manually classifying over 9,000 references would be an extremely slow process.

Moreover, the catalogue is not static.

Suppliers continuously introduce new products, modify references, remove items, and update their collections.

This is why we designed processes that allow part of this classification to be automated.

Artificial intelligence analyses the available information and proposes categories based on product characteristics.

For example, an item described as:

750 ml stainless steel thermal bottle with double wall

Can be automatically associated with concepts like:

• Bottles
• Thermal bottles
• Stainless steel
• Sustainable merchandising
• Corporate gifts
• Reusable products

This allows for the creation of a much richer organisation than the simple original category from the supplier.

AI does not replace strategy

Automation does not mean allowing a system to classify products uncontrolled.

Artificial intelligence operates within a previously defined structure.

First, we establish:

• The catalogue architecture
• The main categories
• The subcategories
• The relationships between products
• The SEO criteria
• The commercial priorities
• The exclusion rules

Afterward, we use AI to accelerate classification within that framework.

This allows us to combine the processing capacity of artificial intelligence with the strategic and commercial judgement of the team.

Normalisation of names and attributes

Another common problem in large catalogues is the inconsistency of information.

The same attribute may appear written in various ways.

For example:

Stainless steel

Acero inoxidable

Inox

Acero inox.

For a person, they may mean the same thing.

For a database, they could be four different values.

The normalisation processes identify these equivalences and convert them into a common structure.

This facilitates:

• The filters
• The internal searches
• The navigation
• The catalogue management
• The creation of categories
• The SEO

The user obtains a much more coherent experience even if the products come from different manufacturers.

Detection of similar products

Artificial intelligence can also be used to identify similar products.

When working with three large suppliers, it is common to find very similar products.

For instance, different manufacturers may offer:

• Thermal bottles
• Corporate backpacks
• Cotton bags
• Customisable mugs
• Notebooks
• Wireless chargers
• Sweatshirts
• Umbrellas

Detecting these similarities helps enhance the organisation of the ecommerce.

It also aids in creating alternatives when a product goes out of stock or is no longer available.

This turns the catalogue into a much more useful commercial tool.

A user-friendly architecture

All this technology has a very simple purpose:

To make finding a product among over 9,000 references easy.

A good architecture allows the user to start from a general need and progressively move towards specific products.

For example:

Merchandising

Bags

Customised bags

Cotton bags

Specific model

This journey reduces friction and helps the user reach the solution they need quickly.

An architecture also designed for Google

The organisation of the catalogue not only enhances the user experience.

It also has a huge impact on SEO.

Each category can become a page capable of responding to a specific search intent.

Instead of relying solely on product sheets, we build pages that can compete for searches such as:

• Customised bags
• Customised backpacks
• Customised bottles
• Merchandising for businesses
• Corporate gifts
• Promotional material
• Custom products for events

This significantly expands the search surface of the ecommerce.

Relevant positions against major competitors

One of the main objectives of the project was to enable Empremta Barcelona to compete on Google with some of the main references in the merchandising market.

This sector has large ecommerce businesses, massive catalogues, and companies with substantial digital investments.

To compete against them, it’s not enough to have many products.

It’s necessary to have:

• Architecture
• Content
• Technology
• SEO
• Speed
• User experience
• Constant updates

Empremta Barcelona has successfully built a relevant presence in multiple market categories.

The goal is not to rely on a single keyword but to be present in many searches related to different product families.

From supplier catalogue to a proprietary digital asset

The products come from external suppliers.

But the traffic, architecture, user relationships, and visibility belong to Empremta Barcelona.

This allows for transforming a catalogue distributed by third parties into a proprietary digital asset.

Instead of sending the customer to a manufacturer’s catalogue, Empremta can build its own experience.

It can decide:

• How to present the products
• How to organise them
• Which categories to prioritise
• What content to develop
• Which searches to target
• How to capture contacts
• How to build its brand

The online store thus becomes a tool for commercial independence.

Automation for a living catalogue

A catalogue of this nature changes constantly.

Each season new products appear.

Others disappear.

Colours change.

Materials change.

References are updated.

Images are modified.

New collections are incorporated.

This is why the system must be ready to manage a living catalogue.

Automation helps reduce the manual work associated with these changes.

When new references are introduced, classification processes can help automatically identify:

• The appropriate category
• The related subcategories
• The relevant attributes
• The possible tags
• The relationships with other products

This enables scaling the ecommerce without the growth of the catalogue necessarily multiplying the management work proportionately.

AI as a scalability tool

Classifying one hundred products manually may be feasible.

Classifying ten thousand products and keeping them updated is another issue.

AI allows us to apply similar criteria to thousands of references in much less time.

The goal is not to automate just for the sake of automation.

The goal is to be able to grow without losing control over the quality of the catalogue.

An infrastructure prepared for growth

Scalability was one of the fundamental principles of the project.

Empremta Barcelona needed a platform ready to:

• Add new suppliers
• Incorporate new references
• Create new categories
• Develop new integrations
• Automate new processes
• Expand functionalities
• Continue growing organically

This prevents the platform from becoming a limitation to business growth.

Continuous technical support

An ecommerce of this size requires constant maintenance.

It’s not solely about updating plugins or solving incidents.

Technical support is part of the project’s own growth.

At Genium, we continuously work on the platform to keep it stable, optimised, and prepared to evolve.

An ecommerce that never stops evolving

The catalogue changes.

The suppliers change.

Google changes.

Search habits change.

The customers’ needs also change.

This is why the ecommerce must continuously evolve.

Our work includes detecting opportunities and applying improvements related to:

• Performance
• SEO
• Usability
• Automation
• Integrations
• Architecture
• Conversion
• New functionalities

The platform becomes a living project.

The keys to the project

Integration

Three major suppliers connected within a single commercial platform.

Volume

Over 9,000 references organised within a coherent catalogue.

Artificial intelligence

Processes supported by AI to analyse, organise, classify, and normalise large amounts of product information.

Automation

Reduction of manual processes to facilitate the management and updating of the catalogue.

Categorisation

A unique architecture built around the real needs of users and not exclusively from supplier structures.

SEO

Categories and content prepared to compete in relevant searches within the promotional merchandising market.

Scalability

An infrastructure capable of incorporating new references, categories, functionalities, and suppliers.

Independence

A proprietary catalogue that allows for controlling the brand, experience, positioning, and customer relationships.

Support

A continuous technical support that keeps the platform stable and allows it to continue evolving.

Much more than integrating three catalogues

The Empremta Barcelona project shows that integrating thousands of references is not simply about importing data.

It’s about turning that data into a useful commercial structure.

Organising them.

Relating them.

Classifying them.

Making them findable.

Positioning them.

Keeping them updated.

And turning them into commercial opportunities.

The combination of integrations, automation, artificial intelligence, SEO, and continuous technical support allows for transforming the catalogues of Mid Ocean, Makito, and PC Concept into a single ecommerce capable of competing in a highly demanding market.

Over 9,000 references. Three major suppliers. A unique architecture. Artificial intelligence to organise the catalogue. And a platform prepared to keep growing.

Do you have thousands of products and need to turn them into an ecommerce?

We design platforms capable of integrating large catalogues, automating processes, using artificial intelligence to organise information, and building an architecture prepared to compete.