The new DéporTienda, the same as Deportivo de la Coruña, is not a simple store merchandising with a facelift. It is a case study of how spatial analytics, computer vision and predictive models can impact the retail sports. And a club from, for now, the Second Division has done it.
RC Deportivo celebrates its 120th anniversary immersed in a modernization operation that goes beyond what happens on the pitch: museum, hospitalitysports city… But there is a project that says more about the direction the club wants to take than any signing or renovation of the stands. It’s your store.
La DéporTienda has just reopened in its historic location next to the Abanca-Riazor stadium after two months of works. And more than just the furniture or decoration has changed. The nervous system of space has changed: it is now monitored, analyzed and, according to those responsible, it is capable of anticipating decisions before they are made.
The cameras watch
The project started with an observation phase of at least four months in the old store. The company responsible for the technological layer is Noumena Group, a Barcelona company founded in 2011 and specialized in spatial analytics with computer vision and Machine Learning.
Its CEO, Aldo Sollazzoexplains that the system they have implemented in Riazor has the same DNA as the one they developed for Barcelona City Council in the analysis of Superapples and the green axles: cameras that process images to understand how people move through a space.
Material for sale, and in the background, the wave made of PETG. Image provided.
“It works through cameras connected to a brain based on edge computing“explains Sollazzo. “Each camera converts the input visual in a string text that guarantees anonymity and complies with the GDPR and the European AI law. We do not store images: we store spatial data,” he explains to Xataka by phone call.
The system maps movement flows within the store, segments visitors by estimated age ranges and gender, generates heat maps and cross-references all this with product distribution and sales data. So far, descriptive analytics. What Noumena proposes as differential is the predictive layer.
Predict before moving a shelf
“The difference with other systems is that our data are not numbers disconnected from space,” says Sollazzo. “They are linked to the built environment. And that allows us to train models to predict what would happen if we redistribute the product, move the furniture or relocate the payment points.”
In practice, this translates into decisions such as estimating whether an alternative display arrangement maximizes product exposure. Or whether relocating cash registers based on traffic reduces queues on busy days. Or calculate how many staff the store will need for a specific event. All this without the need for trial and error in the field.
Heat maps on the store floor (top-down view). They represent the distribution of visitor flows in three different scenarios or moments, probably different furniture configurations or different temporal moments (normal day, match day, special event…). The most intense areas indicate a greater concentration of people, the dark areas are cold areas where few people pass through. It is clearly seen how the traffic distribution changes depending on the scenario: in some configurations there are obvious bottlenecks at the entrance and next to certain exhibitors, while in others the flow is distributed more homogeneously. The numbered white elements are the furniture and display modules. Image provided.
Three-dimensional visualization of the same flow data as in the previous image. Instead of a flat heat map, occupancy data is represented as volumetric columns that “grow” from the floor: the higher the column height, the higher the traffic density at that point. The isometric perspective allows you to see the store as a built space (you can sense the walls, the modules) with superimposed spatial data. It is the representation that connects analytics with architecture, which is the point that Sollazzo emphasizes as differential: the data is not abstract, it is anchored to the physical environment. Image provided.
Panel with a comparison of key indicators: net sales, visitors, items sold, conversion rate, average ticket… All within the framework of an event day, with a specific anniversary that drives attendance and purchase. Image provided.
This tab crosses spatial data with sales data by product. The graphs show the ranking of suppliers, where Kappa logically dominates as it is the technical brand of the club; the interactions by exhibitor or the comparison of interest versus sales by supplier, where it is seen that Kappa generates a lot of interest and many sales, while Soricastel and Texprint (merchandising, not technical clothing) generate interest but convert less. This type of data is what allows us to decide if a supplier needs a better location, better price or less space. Image provided.
Thanks to this research, the club has increased its working square meters by 10% and enhanced product exposure by 15%. For a football club store next to a stadium, where on match days the footfall can multiply by twenty (a figure declared by the club), those margins matter a lot.
The system, furthermore, cross internal data with external variables: weather forecast, events in the city or at the stadium, mobility data in the surrounding area… “In celebration of the 25th anniversary of the League We had 250% more occupancy compared to a normal day,” recalls Sollazzo. “Without this technology it would be impossible to anticipate how much stocks “Do you need, how much workforce, how to redistribute the points of sale so that the queue does not block the flow of the store.”
What is measured and what must be demonstrated
The KPIs that the club will monitor are those expected in any serious operation of retail: average ticket, conversion rate, average stay time, number of visits, distribution of flows by module and visitor profile. The return on investment, according to Sollazzo, is expected in one year. The idea, in theory, is to sell more, of course, but also to make better, more informed decisions about stocking and distribution.
The declared ambition, in any case, goes further: that the data from this store serve as a model for future openings or commercial spaces of the club. “It becomes a working method,” summarizes Sollazzo. “It’s not a tool for a store, it’s a replicable system.”
Noumena platform, the interface to which the club has access to consult data in real time. In the image, density of visitors segmented by estimated age during the celebration of the 25th anniversary of the League (May 17, 2025). Image provided.
It is advisable to qualify the promise. The concept of retail smart is not new. Fashion chains, department stores and sports brands have been experimenting with sensors, heat maps and behavioral analytics for years. In fact, Noumena has previously worked with chains of sneakers in similar projects in cities such as Riyadh, Dubai or Paris.
What makes this case special is the context: a Second Division football club, with the resources and scale that this implies, betting on a technological infrastructure that is not usually associated with its category. Of course, Dépor, although it is in the Second Division, is not a Second Division club.
A wave of recycled plastic and a paint that absorbs CO2
Technology is not just in the software. The architectural design, by the Barcelona studio External Reference, has introduced a five-meter wave-shaped sculptural structure made in PETG recycled through robotic 3D printing by La Maquina, the digital manufacturing division of Noumena Group. The piece runs through the entire store and works as a visual thread that connects the club’s maritime identity (the blue and white colors, the Atlantic culture of A Coruña) with the commercial space.
The furniture is modular, designed together with HMY Group to adapt to both daily operations and the peaks of match days. And the walls are coated with Pure Tech, a paint whose composition, according to the manufacturer, is capable of capturing CO₂ and nitrogen oxides from the environment. Pure Tech is also part of the Noumena Group ecosystem.
Image provided.
Image provided.
Image provided.
Here it is worth pointing out something that does not appear in the club’s official statement: Noumena is not only the provider of spatial analytics. It is the group that also includes La Maquina (3D printing) and Pure Tech (painting). Aldo Sollazzo is CEO of all three. This means that a good part of the project value chain falls on the same business group.. It does not invalidate the results, of course, but it does contextualize the scope of the operation and the nature of the discourse.
Why this matters beyond A Coruña
The most interesting question is not whether the DéporTienda is pretty or whether the PETG wave looks good in photos. The question is whether a club with the resources of a Second Division team can convert the data into a real competitive advantage off the pitch.
Deportivo, as we said, is not just any club in its category: it was League champion in 2000, it was a regular in the Champions League at the beginning of the century, it defeated giants like Milan, Juventus, Arsenal and Bayern, and it has spent years on a journey through the lower divisions of which now, in the midst of the fight for direct promotion, could be coming out: is third after matchday 37 at the time of publishing this article.
Its social mass continues to be disproportionate for the category. That fan base is precisely what makes the store more than just a point of sale: It is a channel of relationship with a community that He has maintained his link with the club even in the worst years. A pride possibly greater than that of the 2000 League.
If the system works (and this remains to be demonstrated with real performance data, not with percentages of improvement prior to the opening), Dépor will have built something that most clubs in its environment do not have: a data-driven decision infrastructure for your commercial business. This is no small feat in an industry where merchandising It continues to be, in many cases, more of an eye than science.
Ultimately, it remains to be seen if the future proves them right or if, as happens with so many ambitious technological projects, the promise exceeds the execution. For now, what there is is a store in Riazor that knows how many people visit it, how they move around inside it, what they look at and for how long. And that he believes he can anticipate what will happen if something changes. For a football club, that is already a lot.
Featured image | Loaned
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