TL;DR
Spain leads the discount channel growth in Europe with an 8.4% increase in sales, driven by a pragmatic consumer and a private label share that already reaches 59%. This trend consolidates the Spanish market as a benchmark for efficiency and savings in Europe.

Spain has placed itself at the centre of the European FMCG discount map. The growth of the channel in 2025 confirms a clear trend: Spanish consumers are increasingly buying in formats that combine competitive prices, a streamlined assortment, and a strong private label presence. This progress, moreover, occurs in a context where the European market is evolving at more moderate rates and with very different dynamics between countries.

A Change that Goes Beyond the Data

Spain’s leadership in the discount channel

The latest industry data places Spain as the fastest-growing market for discount in Europe, with an 8.4% increase in value sales during 2025 and a 7.5% advance in retail space. This evolution reinforces the position of this format within Spanish grocery retail and shows that its growth responds to a sustained trend, rather than a temporary peak.

The interest in the data lies not only in the growth figure but in what it represents for the sector. Discount is gaining ground in a highly competitive market, where consumers increasingly value the balance between price, convenience, and trust in their purchase.

Source: The State of Grocery Retail Europe 2026 – McKinsey & Company – April 2026

Why is this growth attracting attention?

Spain’s relevance in this phenomenon is better understood when compared with Europe as a whole. According to the report The State of Grocery Retail Europe 2026 by McKinsey and EuroCommerce, FMCG behaviour in Europe remains marked by pressure on margins, the search for efficiency, and the transformation of the business model. In this context, Spain stands out for the speed with which discount and private labels are consolidating.

Furthermore, other sector coverage confirms that the advance of the discounter channel in Spain is not isolated, but part of a broader evolution of the FMCG market. Journalistic analysis agrees that Spanish consumers are favouring formats more oriented towards savings and functional shopping.

Key Market Data

Sales, space, and the weight of private labels

One of the great drivers of this change is private label. In Spain, private label sales reach 59%, according to recent data published by Circana. This figure is significantly higher than the European average and helps explain why discount finds particularly favourable ground here.

The combination of own-brand, concentrated assortment, and a tight pricing policy allows these banners to gain share in an inflationary environment or one of cautious consumption. Added to this is the physical expansion of the channel, which continues to open up space in the market and reinforce its presence in urban and peripheral areas.

Source: The State of Grocery Retail Europe 2026 – McKinsey & Company – April 2026

Comparison with the European average

Compared to Spain, the European average shows more contained growth and a commercial structure less inclined towards discount. In many markets on the continent, promotions still carry greater weight and private label penetration does not reach such high levels as in Spain.

This difference helps explain why the country has become a benchmark for analysing the evolution of the channel. Spain meets several favourable conditions: greater acceptance of own-brands, price sensitivity, and a rapid adaptation of operators to more efficient shopping models.

What Explains the Rise of Discount?

Price, savings, and private label

The most evident factor is price. In an environment of monitored household spending, consumers look for ways to maintain control over their shopping bills without giving up an adequate basket. Discount responds precisely to this need through low prices, more contained promotions, and a simpler offering.

Private labels also play a decisive role. Spanish consumers have lost part of the historical prejudice towards own-brands and increasingly perceive them as a reliable, practical option with good value for money. This change in perception has boosted both discount and the FMCG sector as a whole regarding private label.

A more pragmatic consumer

The shopping profile has also changed. Today, the logic of smart saving carries more weight than the search for excessive variety. Consumers compare, prioritise, and select with greater attention, and this favours formats that simplify the decision-making process.

This behaviour fits with a more rational basket and a growing interest in completing the shop quickly and efficiently. In this scenario, discount offers a proposal very much aligned with what a significant part of the Spanish market is looking for today.

Impact on the Sector

For manufacturers and retailers, this evolution has several implications. The first is pressure on margins, as competing in a channel with tight prices forces a refinement of costs, assortment, and logistics. As Daniel Läubli, global head of Grocery Retail at McKinsey, summarises:

“Retailers’ cost ratios are at historically high levels. The good news is that there is a wide range of opportunities for retailers to build competitive advantages, for example, through truly differentiated own-brand products or through the use of artificial intelligence”.

The second is the need to differentiate clearly, whether through brand, innovation, service, or operational efficiency.
Also, commercial strategy is changing. The growth of discount forces a review of the relationship between manufacturer brands and private labels, as well as the role of promotions in customer acquisition and loyalty. In parallel, the sector must read this trend as a long-term signal: discount does not only compete on price, but also on format, convenience, and trust.

Spain as a Benchmark for the New European FMCG Market

Spain is establishing itself as one of the most interesting markets in Europe for understanding where FMCG is heading. The leadership of discount and the progress of private labels show that Spanish consumers are adopting shopping patterns that are very demanding on price and very open to efficient models.

This position makes the country a benchmark for the European food sector. What happens here in the coming months will be key to interpreting the evolution of the discount channel, private labels, and the response of manufacturers and retailers to an increasingly pragmatic consumer.

In short, discount growth in Spain reflects a profound market transformation. The data serves as a starting point, but the real story lies in the change in shopping habits, the consolidation of private labels, and the new competitive logic of European FMCG.

The post Spain Leads Discount Growth in Europe: What is Happening and Why it Matters appeared first on Flipflow.

TL;DR
Marketplaces have shifted price control from brands to third-party sellers competing for visibility and the Buy Box. This price dispersion erodes margins, creates channel conflict, and weakens brand positioning. The solution lies in monitoring sellers, detecting deviations, and managing pricing with real-time data and alerts.

Imagine you have been working on your brand strategy for months. You have defined the positioning, calibrated the recommended price to fit the perception of value you are looking for, and built a consistent narrative across all your channels. Then you go onto Amazon or any other marketplace and see your product listed at three different prices, by three different sellers, none of whom you have directly chosen.

That is exactly what happens to thousands of brands every day.

The rise of marketplaces has democratised access to the final consumer. But it has also decentralised control over something fundamental: the price at which your product appears to that consumer. And price, in the digital environment, communicates much more than a number. It communicates who you are as a brand. According to Wiser, price positioning directly influences consumer behaviour because it determines how the buyer perceives a brand’s value compared to its alternatives. If that perception changes because of sellers competing with each other without coordination, the positioning built by the brand begins to weaken.

This article analyses why pricing has stopped being an internal lever for brands and has become a disputed territory, what consequences this loss of control over positioning has, and what brands can do to regain the initiative without falling into the most common channel management errors.

What Has Changed: From Brand Control to a Multi-Seller Ecosystem

For decades, price control was an almost exclusive prerogative of the brand or the authorised retailer. The structure was relatively simple: brand → distributor → point of sale → consumer. Each link had clear rules, agreed margins and, in many cases, minimum price agreements that protected commercial consistency.

Marketplaces broke that logic.

Platforms like Amazon, Miravia, or large retailers with an open marketplace allow any seller —authorised or not— to list a product and compete for the sale. The result is a multi-seller ecosystem in which the brand coexists with authorised distributors, parallel resellers, stock liquidators, and arbitrage operators, all under the same listing.

This model has obvious advantages: a wide catalogue, greater availability, and price competition that can benefit the consumer. But for brands that have invested in building value positioning, this ecosystem represents a structural threat. The price is no longer set by those who know the brand strategy. It is set by whoever wins the Buy Box.

Why the Price Is No Longer “Yours”

There are several reasons why the price has stopped being “yours” and has come to depend on others. We explain the main ones:

1. Because the final price is shown by a seller, not your brand book

Your brand book may define a premium, aspirational, or volume positioning. But the consumer does not buy an internal document: they buy what they see on the screen. In marketplaces, that visible price usually comes from a specific seller, and can also include shipping, availability, or conditions that modify the final perception of value.

BigCommerce highlights that on Amazon, the Buy Box is decided based on criteria such as total price, fulfilment, shipping speed, and account health, not just the listed price. The brand, in many cases, does not control any of those factors when the seller is a third party. The practical result is that your price identity is left in the hands of an external actor whose sole priority is winning the sale, not protecting your positioning.

2. Because visibility also depends on the seller

The problem goes beyond the price itself. On platforms like Amazon, the Buy Box can account for more than 80% of sales. Therefore, losing that position directly alters the distribution of demand. If the dominant seller is not the one that best fits your strategy, the customer’s perception of your offer is built from a context that you do not fully control.

There is an additional consequence. If your brand also sells directly and an external seller has the Buy Box with a lower price, your own visibility on the listing is relegated. In practice, your direct channel loses effectiveness against a third party that is using your own products to compete against you.

3. Because pricing is no longer static, it is dynamic

Marketplaces operate with dynamic logic. Prices change frequently due to human decisions, repricing tools, overstock or lack of stock, tactical campaigns, or competitor moves.

Furthermore, external sellers —especially the more sophisticated ones— use automatic repricing tools that adjust their prices in real-time based on the competition. This means that the price of your product can change several times a day, in response to the moves of other sellers, stock changes, or variations in demand.

For a brand with a positioning strategy based on price-value, this dynamism is especially problematic. Price positioning is not just a number: it is a consistent signal that builds perception over time. When that signal fluctuates unpredictably, the perception of value is eroded. The consumer who saw your product at €49.99 yesterday and finds it at €34.99 today does not interpret that as a one-off offer; they may interpret it as the “real” price always having been €34.99.

How Sellers are Redefining your Positioning

A brand’s price positioning is not a static asset. It is the cumulative result of the price signals that the market receives over time. When those signals are emitted by external actors without strategic coordination, the positioning becomes distorted.

A seller with a price that is too low can “reposition” your brand downwards

A seller liquidating stock at prices far below the recommended RRP does not just lose margin on that transaction. They redefine, in the eyes of the buyer, the real value of the product. If an item that usually costs €80 repeatedly appears at €45 through a seller with a poor reputation, the buyer updates their price reference. When the brand tries to return to the €80 price, it has to overcome resistance that it did not generate itself but must now manage.

This phenomenon is especially destructive in categories where price is an indicator of quality or exclusivity. In these categories, a low price does not necessarily generate more sales; it can generate distrust.

A seller with a price that is too high can make you appear uncompetitive

The problem also exists at the opposite extreme. If a seller publishes excessive prices, the product may seem expensive compared to equivalent alternatives and lose conversion, even when the brand has solid value arguments.

The risk is not just losing a one-off sale. An inflated price can reinforce the idea that the brand is not aligned with the market or that its channel is disorganised. This is especially sensitive in categories where consumers compare quickly.

Price dispersion destroys consistency

When the same product appears at very different prices depending on the seller, which can happen even within the same platform, the buyer enters a state of uncertainty about what the “correct” price is. This uncertainty can lead to a purchase stall, a search for alternatives, or the conclusion that the product has an inherently volatile and unpredictable price.

Price dispersion does not only affect immediate conversion. It affects long-term trust in the brand. A consumer who has bought at €60 and later discovers that another person bought the same thing for €40 through another seller on the same platform experiences a sense of grievance that is difficult to resolve with a discount on the next purchase.

Price consistency matters because it sustains trust. If that consistency disappears, the purchase decision becomes more uncertain and the perceived value is eroded.

The seller who gains visibility conditions market perception

In marketplaces, the visible seller is not always the one most aligned with the brand’s strategy, but the one who best combines price, stock, and service. That makes that seller the real spokesperson for the offer to the user.

When that role is occupied by a reseller, a parallel distributor, or a seller with an opportunistic strategy, the brand is represented by a logic that may not reflect its desired proposal. In terms of positioning, whoever dominates visibility ultimately dominates the price narrative as well. And your own sales teams, your physical retailers, and your strategic partners see that price as a reference. The effect is systemic.

Risks of Losing Control of the Channel

The consequences of not actively managing the ecosystem of sellers accumulate silently until they become difficult to reverse. Among the most relevant risks are:

• Structural margin erosion: When external sellers compete with each other downwards, the market reference price falls progressively. The brand is pressured to adjust its own price to avoid being priced out of the market, with the consequent impact on profitability.
• Channel conflict: Physical retailers working with a brand under minimum price agreements have well-founded reasons for complaint when they see the same product at lower prices in marketplaces managed by third parties. This tension can lead to a loss of distribution in strategic channels.
• Brand damage difficult to quantify: The impact on perception is not immediately reflected in the company’s profitability, but it materialises in lower conversion rates, greater price sensitivity on the part of the buyer, and a loss of differentiation from competitors.
• Entry of unauthorised sellers: The lack of visibility over who is selling your products can hide the presence of resellers operating outside distribution agreements, with stock of dubious origin or failing to comply with warranty conditions, generating claims that directly impact the brand’s reputation.

What can a Brand Do to Regain Control without Making Channel-Related Mistakes?

Regaining control does not mean imposing the final price on all sellers. The useful path involves commercial intelligence, monitoring, and active management of the seller ecosystem. These are some recommended actions:

• Establish and communicate a clear pricing policy: Defining a recommended RRP and, where legally viable, a minimum advertised price (MAP) is the starting point. Without that documented reference, it is impossible to identify deviations or start conversations with distributors about compliance.
• Regularly audit the seller ecosystem: Knowing who is selling your products, on which platforms, at what price, and under what conditions is basic information that many brands do not have systematically. Manual auditing is possible for small catalogues but becomes unfeasible beyond a certain volume of SKUs and markets.
• Prioritise direct sales in the Buy Box: On platforms like Amazon, a brand’s best defence against the proliferation of sellers is to have a competitive presence in the Buy Box itself or through a trusted distributor. This requires continuous attention to prices, stock, and seller metrics.
• Review agreements with distributors: Distribution contracts should include explicit clauses on the channels in which distributors can operate and under what price conditions. Without this contractual framework, brands have few tools to act against disruptive behaviour.
• Establish alerts and protocols: When a seller drops the price significantly or a new seller appears on a sensitive listing, the team needs a quick signal and a clear protocol to act as quickly as possible.
• Act with data, not assumptions: The most common mistake brands make when addressing this problem is doing so reactively, when the damage is already visible. Proactive management requires continuous and structured data on the behaviour of the seller ecosystem.

What a Retail Intelligence Solution like Flipflow Provides

For brands with a presence in multiple marketplaces, multiple countries, and catalogues of a certain breadth, manual management of the seller ecosystem is unfeasible. Growing in marketplaces, online retailers, and D2C without control is not scaling. It is opening the door to margin erosion, parallel resale, and inter-channel conflicts. It is in this context where our Pricing & Seller Control module provides differential value.

Flipflow’s proposal is based on a clear premise: the problem of losing price control in the digital channel is not a one-off problem of a “misplaced price”. It is a structural loss of control over the distribution architecture. And the larger the international scale, the greater the risk the brand faces.

On that basis, we articulate our solution around several axes:

• Complete mapping of sellers and distribution
• Structural control of pricing and deviations.
• Actionable alerts in real-time.
• Integrated vision by market and channel.

In short, we turn what has historically been a problem of late reaction —”we find out when there is already tension with the retailer“— into a system of continuous governance of the digital channel. This ability to anticipate is, in an environment as dynamic as today’s, the difference between protecting brand positioning and yielding it to whoever has the lowest price at that moment.

The post Price Is No Longer in Your Hands: How Third-Party Sellers are Undermining your Brand Positioning appeared first on Flipflow.

TL;DR
Google has taken a new step in agentic commerce with an update to its Universal Commerce Protocol (UCP) that incorporates a multi-item cart, real-time catalogue and integration with loyalty benefits. The move aims for a smoother shopping experience within AI environments and opens new opportunities for retailers, brands and e-commerce managers.

Google Takes a New Step in Agentic Commerce

Google’s latest update confirms a clear direction: bringing AI-assisted shopping to a more complete and operational environment. Instead of just showing products or helping with searches, UCP is starting to cover stages closer to conversion, such as selecting multiple items, checking availability and applying registered user benefits.

This advancement matters because it reduces part of the distance between purchase intent and the final checkout. For brands, the change is not limited to a technical improvement: it also affects how the catalogue is presented, how promotions are triggered and how customer data is managed in an AI-mediated context.

Furthermore, Google is aligning these capabilities with its Merchant Center ecosystem and experiences like AI Mode in Search and the Gemini app, suggesting a broader adoption strategy. The goal seems clear: to make agentic commerce more useful for users and more accessible for retailers.

What Exactly has Google Announced?

Before going into detail, it is worth understanding that this is not an isolated change, but an evolution in how Google is integrating the shopping experience within AI-assisted environments. The UCP update aims to reduce friction across the entire process, from discovery to conversion, relying on more accurate data, smoother interactions and greater continuity between the user’s relationship with the brand and the shopping environment itself. The UCP update introduces three main improvements:

1. Multi-item cart from the same shop

This function addresses a very specific need: allowing the user to buy more than one product without starting from scratch every time. For categories such as fashion, home, electronics or beauty, this improvement can streamline purchases involving product combinations, replenishments or recurring orders.

From a commercial standpoint, the multi-item cart also favours the average basket size. The less effort the user has to make to add related items, the more options there are for them to complete a larger basket. In an AI-mediated shopping environment, this simplicity can make the difference between a useful interaction and a lost conversion.

2. Catalogue with real-time information

Access to live data is one of the most important points of this update. A real-time connected catalogue reduces price errors, improves user trust and prevents the shopping experience from becoming outdated relative to actual stock or active promotions.

For retailers, this implies a higher demand for feed quality and data governance. If information is not well-structured, the agentic experience quickly loses value. In contrast, when the catalogue is well-maintained, AI can become a very effective discovery and conversion layer.

3. Identity linking to activate loyalty benefits

The connection with loyalty programmes adds a strategic layer to AI-assisted shopping. The user doesn’t just find a product and move towards checkout, they can also retain the benefits associated with their customer account.

This is especially valuable for brands with mature loyalty programmes, because it protects the value of the direct relationship with the customer. If membership incentives survive the interface change, the experience is more coherent and the commercial proposition gains weight.

What Impact does this Announcement Have on E-commerce and Retail?

Beyond specific features, this announcement introduces a relevant change in the logic of the digital funnel: purchasing no longer depends exclusively on owned environments and is instead integrated into AI-mediated experiences. In this context, what is at stake is not just conversion, but also who controls critical points of the customer relationship (data, personalisation and access to the moment of purchase) within the Google ecosystem.

Less friction in the purchasing process

In practice, friction occurs when the user has to repeat searches, re-enter preferences or check too many times if a product is still available. The new UCP attempts to solve part of that problem by centralising the cart, catalogue and user context in a single experience.

This does not eliminate the role of traditional e-commerce, but it does introduce a new touchpoint in the purchase path. For some brands, the value will be in capturing orders earlier; for others, in improving the performance of campaigns, feeds and loyalty programmes within this new environment.

More personalisation in the user experience

Personalisation gains weight when AI can recognise not only what the user is looking for, but also who they are and what associated benefits they have. The identity linking makes the experience more relevant and less generic, especially in purchases where price, shipping or member benefits influence the decision.

This level of personalisation can improve brand perception and increase the probability of closing a sale. For the retailer, it also opens the door to adapting promotions and messages to identified users without losing consistency across channels.

More value for loyalty programmes

Loyalty programmes usually depend on the user seeing a clear and easy-to-activate benefit. If the agentic experience respects that value, these programmes gain presence at the moment of purchase and are not relegated to the brand’s own website or app.

This can be especially useful in sectors where recurrence is high and repeat purchases carry significant weight. Beauty, specialised food, consumer electronics or premium fashion are examples where the connection between loyalty and conversion has significant potential.

How Merchant Center Fits into this Strategy

Merchant Center appears as the integration piece that facilitates the adoption of UCP by businesses. Google has been simplifying access to these capabilities so that more retailers can participate in the ecosystem without depending on complex developments from the start.

From an operational point of view, this means that catalogue quality, data structure and attribute updates become even more important. If Google wants to offer more precise shopping experiences within AI environments, the merchant’s database must be prepared for it.

What Brands should Keep in Mind

The first priority is reviewing product feed quality. Price, stock, variants, descriptions and promotions must be well-maintained for the UCP experience to be reliable and competitive. Without this prior work, the tool’s potential is greatly reduced.

The second is aligning loyalty, CRM and e-commerce so that customer identity can be activated without friction. If the system does not correctly recognise the user or does not apply their benefits consistently, part of the update’s value is lost.

The third is thinking about the impact on attribution and commercial control. When part of discovery and checkout moves to AI environments, brands must review how they measure conversion, how they attribute results and to what extent they depend on an external platform to drive sales.

What this Move Means for the Future of Checkout

Google is outlining a scenario in which the checkout does not only depend on a website or an app, but also on AI assistants capable of managing part of the purchasing process. This can change how users discover products, compare options and finalise orders.

For the sector, the conclusion is twofold. On one hand, there is a real opportunity to improve conversion, personalisation and loyalty value. On the other, there is a growing need for solid data, well-structured catalogues and a clear strategy for operating in environments where AI acts as an intermediary between brand and consumer.

The evolution of UCP suggests that agentic commerce will not be a marginal trend, but a channel that will gain weight as Google expands its integration with Search, Gemini and its shopping ecosystem. For retailers and brands, the question is no longer whether it is worth preparing, but how much room they want to leave for others to occupy that space first.

The post Google Expands UCP with Multi-Item Cart, Live Catalogue and Loyalty Benefits appeared first on Flipflow.

TL;DR
The Digital Shelf is no longer just about e-commerce; it is also the infrastructure that defines sales in physical stores. Managing visibility, content, and stock through Digital Shelf Intelligence is the only way to avoid shopper friction and guarantee revenue across all channels.

Introduction: The End of the Border between “Clicks” and “Bricks”

When a consumer enters a supermarket with a shopping list on their mobile, they carry with them weeks of accumulated digital influence. They have seen product pages, read reviews, compared prices across platforms and, in many cases, decided which brand they will buy before setting foot in the store. The physical aisle only confirms, or frustrates, that decision.

This phenomenon has profound implications for brands and retailers. According to data from Scandit and Nielsen, 83% of consumers use some type of shopping app on their smartphone while inside a physical store, and 88% compare prices in-store to find the best deal. Added to this is what Pricer highlights: the smartphone accompanies the consumer inside the establishment and turns the store into a connected space, where price, information, and promotions are contrasted in real time. The modern shopper arrives informed, with expectations created in the digital environment, and any inconsistency between what they found online and what they see on the physical shelf generates friction, distrust, and lost sales.

The logical consequence is that managing the digital channel well has stopped being an exclusively e-commerce matter. The Digital Shelf (the set of presences, content, and positioning of a brand in digital sales environments) now determines commercial performance across all channels, including the physical store. Treating both worlds as separate silos is one of the most costly strategic mistakes that retail and FMCG organisations can make in 2026.

The Digital Shelf as Commercial Infrastructure

Treating the Digital Shelf as commercial infrastructure means understanding it as an operational foundation that sustains visibility, consistency, and performance across all digital touchpoints. Its function is not limited to “being present,” but to ensuring that the product appears, is understandable, is credible, and is available when the consumer needs it. This foundation affects both the online channel and behaviour in the physical store.

This vision is especially useful for brand, e-commerce, trade marketing, and retail intelligence teams. If the Digital Shelf is fragmented, the brand loses control over its narrative, over the comparison against competitors, and over the connection between traffic, conversion, and sales. If it is well governed, it becomes a structural asset that drives revenue on several fronts simultaneously.

Visibility, content, and availability

The three operational pillars of the Digital Shelf are visibility, content, and availability. Visibility determines whether the product appears in the top results when the consumer searches for a category. Content — images, descriptions, technical attributes, ratings — defines the quality of the product page and its ability to convert. Availability guarantees that the product is listed, in stock, and accessible at the retailers where the consumer expects to find it.

When any of these three elements fails, the impact is not limited to the digital channel. A product listing with low-quality images or incomplete attributes erodes the brand perception that the shopper will take with them to the store. A product with online availability issues generates uncertainty about whether they will find that item on the physical shelf. Consistency across these three axes is a necessary condition for effective commercial execution at all touchpoints.

Brand governance and digital shelf control

One of the most frequent challenges in organisations with wide distribution is the lack of consistency in brand presentation across different digital retailers. The same product can have listings with different content, prices, and attributes depending on the platform, which generates confusion for the consumer and dilutes the brand identity.

Digital shelf governance is the ability to ensure that the brand is presented with the same quality standards across all retailers where it operates. This includes continuously auditing the content of listings, detecting inconsistencies, correcting errors, and ensuring that product, price, or promotional updates are transferred synchronously to all channels. Without this structural control, the Digital Shelf becomes a fragmented environment where the brand loses control of its commercial narrative.

The approach we promote at flipflow with our Digital Shelf Intelligence module goes in that direction: continuously monitoring what happens with each product, at each retailer, and against each competitor. This vision allows for a move from manual and sporadic reviews to a more consistent and actionable management style.

The relationship between Digital Shelf and Retail Media

The Digital Shelf and Retail Media already operate as connected disciplines. Retail Media investment drives traffic, but that traffic lands on a product listing, a category, and a specific proposition. If the product is not well-prepared, the investment loses efficiency. Therefore, content, stock, and visibility must go hand in hand with ad spend.

Furthermore, Retail Media amplifies the importance of the Digital Shelf because it increases competition for attention. When several brands bid for the same space, the difference is not just made by the budget, but also by the quality of the digital shelf execution. The brand that appears better, responds better, and is available wins the commercial advantage.

At this point, the Digital Shelf stops being an isolated operational task and becomes part of the growth system. Investment pays for traffic; digital infrastructure converts that traffic into a decision.

5 Mechanisms by which the Digital Shelf Dictates Offline Sales

The influence of the digital environment on physical sales operates through specific and measurable mechanisms. Identifying them allows organisations to design Digital Shelf strategies that directly impact the bottom line of the physical channel.

1. Discovery

The first mechanism is discovery. Before going to the store, many consumers use search engines, marketplaces, or the retailer’s site to identify which product fits their need. If a brand does not appear, it is not part of the shortlist.

In practice, this means that digital visibility can determine which products are taken into consideration and which are left out. Good online positioning creates latent demand that later transfers to the physical shelf. The store receives a preference that is already formed.

2. Trust

Trust is built with information and social signals. Reviews, ratings, images, descriptions, and technical attributes help the shopper reduce their uncertainty.

This trust travels with the consumer to the store. If they have already validated a brand online, they are more likely to look for it on the physical shelf and be willing to pay for it. If they find poor or inconsistent information, that predisposition weakens.

3. Availability expectation

Online availability works as a promise. When the shopper checks the retailer’s website and sees a product available, they interpret that there is a high probability of finding it. If they see an out-of-stock or an uncertain delivery, they modify their expectation.

This mechanism is decisive because many decisions are made before travelling to the store. The consumer may choose another store or substitute the brand even if the product was physically available. Prior perception carries a lot of weight. That is why digital availability acts as a leading indicator of offline purchasing behaviour.

4. Price and promotion perception

The fourth mechanism is the perception of price and promotion. The consumer compares online before buying offline and carries a mental reference of value with them. If they find an attractive offer, a clear discount, or a well-explained promotion, that information influences their decision at the point of sale.

This necessitates the alignment of pricing, promotions, and communication across channels. When online and physical prices generate different messages, confusion arises. The brand may lose credibility or cause rejection if the consumer perceives inconsistency between what they have seen on screen and what they see on the shelf.

5. Consistency of commercial execution

The omnichannel experience perceived by the consumer is only as strong as its weakest link. If brand communication is impeccable in the digital channel but execution in-store (signage, product location, information at the point of sale) is not aligned, the purchase journey breaks down.

Consistency of commercial execution between the Digital Shelf and the physical shelf is the mechanism that closes the cycle and converts digital presence into a real sale.

The Mistake of Treating the Digital Shelf as a Project rather than as Infrastructure

Many organisations have approached the Digital Shelf as a project: an initiative with a beginning, development, and end, usually led by the e-commerce or digital marketing team, with limited scope and temporary resources. This approach generates partial and unsustainable results.

A project ends. An infrastructure is maintained, updated, and scaled. The difference is not semantic: it defines how resources are allocated, who is responsible for results, and how often the strategy is reviewed.

When the Digital Shelf is managed as a project, recurring symptoms usually appear:

• Product content updated occasionally, not continuously
• Absence of systematic monitoring of visibility against competitors
• Disconnection between marketing, sales, e-commerce, and supply chain teams
• Digital Shelf metrics that are not connected to global business objectives.

Most organisations believe they have control over their digital presence because they accumulate data, but data without structure hides what is really happening in the market. The difference between accumulating data and having digital governance is the same as the difference between monitoring and controlling.

Treating the Digital Shelf as infrastructure involves creating organisational structures and continuous processes: periodic content audits, alert systems for visibility losses, cross-functional teams with clear responsibilities, and metrics integrated into business dashboards.

How to Operationalise this Vision with Digital Shelf Intelligence

The issue is not just collecting data, but converting scattered signals into specific commercial decisions. To achieve this, a layer of intelligence is needed that observes the market continuously and translates complexity into clear priorities.

A Digital Shelf Intelligence solution allows for the monitoring of critical variables such as:

• Availability
• Price
• Promotions
• Content
• Ratings and reviews
• Search positioning
• Assortment
• Competitor activity

The value appears when this information is organised to answer business questions: Where am I losing visibility? Which retailers concentrate the most execution issues? Which SKUs have stock or content problems? Which competitors are gaining presence?

A platform of this type helps to unite teams that often work with separate data. Marketing can understand which content needs improvement. Trade marketing can review promotions and execution. Sales can anticipate risks by retailer. E-commerce can detect gaps in visibility and availability. Management obtains a clearer view of which factors are affecting performance.

Furthermore, this approach facilitates the connection between the Digital Shelf and results. If a brand observes a drop in sales in a specific category, it can check if the problem stems from a loss of visibility, an out-of-stock, a poorly activated promotion, or superior competitive pressure. This traceability greatly improves the ability to respond.

Operationalisation also involves defining a stable framework.

A useful scheme includes:

1. Prioritise key retailers and categories: Not all channels carry the same weight. It is advisable to start with the retailers that have the greatest impact on sales or the highest strategic relevance.
2. Define critical KPIs: Availability, share of search, content, price, promotions, ratings, and assortment are usually the most relevant.
3. Establish alert thresholds: For example, quickly detecting a drop in visibility or an out-of-stock in core products.
4. Assign owners: Every incident must have a clear owner to prevent problems from remaining unresolved.
5. Review business impact: Monitoring makes sense when it is connected to sales, share, margin, or investment efficiency.

Finally, it is advisable to integrate the Digital Shelf into an omnichannel reading. It is not enough to know what is happening online. One must also understand how that execution translates into physical traffic, brand preference, and store turnover. This connection turns data into commercial intelligence. Organisations that adopt this structured digital governance approach manage to reduce the time spent on manual reporting tasks by between 50% and 80%, freeing up analytical capacity for strategic decision-making.

Conclusion: The Retailer of the Future will be Data-Driven

Retail has entered a phase in which the competitive advantage does not belong to the one with the most products on the shelf, but to the one who best understands what happens at every touchpoint with the consumer, digital and physical, and acts accordingly with speed and precision.

The Digital Shelf is now the infrastructure on which that advantage is built. It determines how consumers discover products, what trust they develop toward brands, what expectations they bring to the store, and what experience they have when they reach the point of sale. Ignoring this dynamic or managing it reactively carries a direct cost in sales, market share, and customer loyalty.

The retailer and brand of the future will be data-driven in the most operational sense of the term: they will make decisions about visibility, content, availability, and price based on up-to-date and comparable data, with continuous review processes and teams aligned around shared metrics.

In this scenario, having Digital Shelf Intelligence tools like those developed by flipflow helps to move from intuition to action, from a snapshot to continuous control, and from a basic digital presence to a more robust commercial execution across all channels.

The post Online Presence as Commercial Infrastructure: From the Digital Shelf to the Physical Aisle appeared first on Flipflow.

TL;DR
Walmart will roll out digital price tags across all its US stores by the end of 2026 to streamline pricing, reduce manual labour and improve operational efficiency. The technology enhances the omnichannel experience and in-store accuracy, but it also sparks debate about dynamic pricing and regulation.

Walmart will bring digital price tags to all its United States stores before the end of 2026. This move confirms the extent to which physical stores are incorporating technology to gain efficiency and precision in daily management. The company has been testing this system for some time, but is now expanding the rollout nationwide with a much greater scope.

In this article, we update the analysis we previously published on flipflow regarding digital shelf labels, because the news from Walmart goes a step further and makes this technology a benchmark for the entire retail sector.

What Walmart has Announced

Walmart will replace paper labels with digital labels across its entire network of US stores before the end of 2026. The company had previously announced that the technology would reach about 2,300 stores, but the new announcement expands the scope to cover all its establishments in the country.

According to official information, the goal is to improve the speed at which prices are updated, reduce manual labour and strengthen coordination between the store, inventory and online orders. In practical terms, this means less time spent replacing labels one by one. It also means more capacity to focus on higher-value tasks for the customer.

How Digital Shelf Labels Work

A system connected to pricing

Digital shelf labels, also known as electronic shelf labels or digital shelf labels, are small electronic devices that replace traditional paper labels. They work by being connected to a central system, so that the price and other data can be updated remotely from an internal application.

Changes in minutes, not days

In Walmart’s case, the company explained that a price change that previously could take up to two days can now be done in just minutes. Additionally, these labels include extra features such as LED signals to make it easier to locate products or speed up the preparation of online orders.

What Changes in Operations

The main impact of the system is on store operations. Walmart manages more than 120,000 products on its shelves, and every week it carries out thousands of price updates for launches, sales or promotions. With digital labels, this work is centralised and becomes much more agile.

Amanda Bailey, an electronics team leader at a Walmart store in Ohio, estimates that digital labels have cut the time she previously spent on pricing tasks by 75%. This has allowed her to focus more on helping customers. She also noted that these labels are a revolutionary change for Walmart Spark delivery drivers. Thanks to them, they can see a flashing light and easily locate the product.

The technology also helps to reduce errors between the price shown on the shelf and the one that appears at the till or on digital channels. For the store team, this translates into fewer repetitive tasks and more time for restocking, customer service and order preparation.

Impact on the Shopping Experience

For the customer, the change may seem small at first glance, but it has clear effects on the shopping experience. Digital labels allow for more consistent prices and facilitate alignment between the physical store and online commerce, something that is increasingly important in omnichannel environments.

They can also help to improve clarity on the shelf, especially in large stores where product turnover and frequent promotions make it more complex to keep everything updated. In this sense, the technology not only modernises the point of sale but also reduces friction at key moments of the purchase.

Debate Over Dynamic Pricing

The advancement of these labels has raised concerns among consumers, media and regulators due to their potential link to dynamic pricing. The concern is understandable. If a label can be updated in real-time, it could also be used to modify prices very quickly based on demand or the time of day.

Some lawmakers view DSLs with caution, calling them a gateway to dynamic price hikes. Senator Ben Ray Luján (Democrat for New Mexico) has taken a leading legislative role not only for this type of labelling:

“With food costs rising each month, it’s more important than ever that any new technologies implemented in grocery stores are helping to lower costs, not raise them. That is why I’ve introduced the Stop Price Gouging in Grocery Stores Act, legislation that is intended as a preventative measure to put common-sense guardrails in place at large retail stores and protect consumers.” 

Another congresswoman, the Democratic Representative for Oregon, Val Hoyle, is promoting a bill in the House of Representatives. This would prohibit the use of digital labels on shelves. There have been no reported cases linking them to price increases yet. However, in her opinion, it is only a matter of time.

«Without proper regulations, it is not so hard to see corporations using the loopholes to raise prices on consumers. The idea exists. It is only a matter of time before a billionaire in a boardroom implements the idea», Hoyle stated.

Walmart has insisted that this is not the purpose of its rollout. The company states that the system works in a closed environment, does not collect customer data and maintains the same price for all shoppers within the same store. Even so, the debate remains open and will continue to accompany the expansion of this technology in US retail.

What it Means for Retail

Walmart’s expansion confirms a broader trend. The digitisation of the shelf is no longer a pilot test, but an increasingly serious part of store modernisation. Other chains are also adopting electronic labels, albeit at different rates and with different objectives.

For the sector, the move has a clear strategic reading. Digital labels allow price, inventory and commercial execution to be connected more quickly, and open the door to more flexible operations in an environment where physical and digital experiences must function coherently. In this context, the Walmart case acts as an indicator of where large-scale retail may be headed in the coming years.

Why it Matters Now

Walmart is not just changing how it labels its products. It is accelerating a transformation that affects internal efficiency, the customer experience and the debate about the future of pricing in retail. In the coming months, the expansion of these labels will also serve to measure the extent to which technology improves operations without creating friction for the consumer.

The underlying message is clear: the physical store continues to play a central role, but it increasingly depends on digital systems to function with agility, consistency and scalability.

The post Walmart Accelerates its Digital Shelf Labels: This is How the In-Store Experience will Change in 2026 appeared first on Flipflow.

TL;DR
Territorial intelligence allows for identifying where the true commercial opportunity lies by crossing potential, performance, coverage and competition at the postcode level. The opportunity map turns data into decisions, helping to prioritise resources and maximise commercial impact.

Introduction: The End of the “One-Size-Fits-All” Strategy

For years, many retail organisations have made commercial decisions by applying uniform criteria to radically different territories. The same planogram for Madrid as for Murcia. A single product mix in a high-income neighbourhood and in a peripheral area. The same commercial effort in a saturated market as in one with untapped potential.

This logic has an understandable explanation: it simplifies operations, reduces analysis effort and facilitates standardisation. But it has a silent and cumulative cost. Resources are distributed without discrimination, opportunities are diluted and problems are camouflaged in averages that lie.

Modern retail demands another way of thinking about territory. A way that starts from granular data, identifies where real potential exists and guides commercial decisions with surgical precision. That way has a name: territorial intelligence. And its central tool is the postcode opportunity map.

What is a Postcode Opportunity Map?

A postcode opportunity map is an analytical visualisation that represents the commercial potential of each area and allows it to be compared with current performance. Its utility is based on answering very specific questions:

• Where is there more potential demand for my category?
• In which areas am I below what I could be selling?
• Which territories have room for improvement in distribution, assortment or price?
• Where should commercial resources be concentrated?

The key is not to limit oneself to simply plotting sales on a map. A good territorial analysis crosses several layers of information: market size, sociodemographic profile, current performance, presence of competitors, point-of-sale coverage, and assortment and pricing variables.

This logic connects with decades of geographical analysis applied to retail. Reilly already proposed in 1931 that commercial attraction depends on mass and distance, and Huff developed a model in 1964 to estimate commercial areas of influence. Today, with more data and better tools, that foundation can be applied to daily sales, trade marketing and expansion decisions.

Unlike conventional sales analyses, which look inwards, the opportunity map looks outwards. It compares what the business is capturing with what the market could offer. That gap, when it exists, defines the opportunity.

Why is the Postcode a Useful Unit in Retail?

A municipality is too large. An individual point of sale, too small. The postcode fits well in that middle ground where commercial decisions actually materialise. It has a sufficient level of detail to locate opportunities without falling into unmanageable fragmentation. Furthermore, it connects well with field decisions: commercial routes, resource allocation, local campaigns, focus by fascia and point-of-sale network analysis.

Its utility is supported by several advantages:

• Allows for moving from regional aggregates to micro-territories.
• Facilitates comparing similar areas with each other.
• Detects pockets of underserved demand.
• Improves the allocation of commercial and promotional efforts.

Public sources also reinforce this approach. The INE (National Statistics Institute) offers data on population, income and demographic characteristics that can be approximated or related to specific territories. Eurostat provides comparable indicators on population density, urbanisation and disposable income. These layers help estimate the potential demand by area.

For example, within the same city, two postcodes can differ substantially in average disposable income, household density, age profile or presence of competitors. Treating them the same is ignoring information that already exists and which, when incorporated into the analysis, completely changes priorities.

From an operational point of view, the postcode also has practical advantages. CRM systems and sales receipts frequently collect this variable. Statistical institutes publish demographic data at this level. Commercial data platforms segment the market by postcode. This means that building an opportunity map with this granularity is technically feasible for most organisations with a minimum of analytical maturity.

What Variables should a Territorial Opportunity Map Include?

A territorial opportunity map is valuable when it brings together variables capable of explaining the potential and performance of each area. Its richness will depend on the quality and diversity of the variables that feed it.

A robust model integrates at least 5 dimensions.

1. Demand potential

This dimension estimates how much the business could sell in each territory if it captured its natural market share. To build it, variables such as disposable income per household, average family size, working-age population density, the expenditure index in the category and sector consumption data published by statistical sources or specialised providers are combined.

In retail, demand potential does not always coincide with current sales volume. There are territories with high purchasing capacity where the brand has not yet penetrated well, and others where demand is more mature but growth is already limited. Therefore, the map must allow for a distinction between market size and actual capture.

Demand potential answers the question: How much opportunity is there in this area? Without this estimation, any performance analysis lacks context.

2. Current performance

The second layer analyses the performance of the territory at the present moment. It includes indicators such as sales, average transaction value, purchase frequency, year-on-year evolution, margin or share per area. With these data, postcodes that are already offering good results and those that have not yet reached their potential are identified.

This block allows for putting actual performance into context against estimated potential. A territory may record a high volume of sales in absolute terms and yet be below what would be expected based on its size and profile. Similarly, there are areas with more modest figures that stand out for their high efficiency relative to their demand base.

By crossing both dimensions, the capture rate is obtained, i.e., the percentage of the available market that is already being captured. A low rate in high-potential territories points to growth opportunities, while a high rate in lower-potential areas usually indicates a scenario of maturity or saturation.

3. Coverage and distribution

Commercial opportunity does not depend solely on consumer interest, but also on effective access to the offer. This dimension evaluates the physical presence of the business: point-of-sale network, distance to the nearest establishment, travel times, overlaps between areas of influence and areas with insufficient coverage.

In many cases, low capture in high-potential territories is not due to a lack of demand, but to a limited or poorly distributed presence. Detecting this is key to not erroneously attributing the problem to factors such as competition or market interest.

Furthermore, it is advisable to analyse the quality of that coverage. Presence may exist in a postcode, but with poor execution: low visibility, limited assortment or irregular replenishment. In these cases, improvement does not necessarily involve expanding the network, but rather optimising how those areas are being operated.

4. Competition

Competition provides context and helps to understand if an area is underexploited or highly contested. It is worth analysing how many competitors operate in the territory, what type of format they have, what coverage they achieve and what share of presence they seem to have.

Competitive analysis allows for detecting areas where the brand can gain space with a differentiated proposal, but also territories where the pressure is so high that investment requires a more solid justification. In an opportunity map, competition does not only indicate risk; it also signals where active demand exists and, therefore, where it is worth fighting for share.

The underlying logic is similar to that proposed by Huff: the attraction of a commercial area depends on the relative attractiveness of the offer and the cost of accessing it. In modern retail, that attractiveness includes assortment, price, convenience, brand awareness and competitive pressure.

5. Assortment and price variables

Some organisations add a fifth layer to the map: the suitability of the assortment and price positioning to the socioeconomic profile of each territory. An assortment that is misaligned with local purchasing power, or prices perceived as inappropriate for the context, can limit capture even when potential and coverage are favourable.

Incorporating this variable requires crossing internal category and price data with the economic profile of each area. When done well, it allows for designing assortment localisation strategies with a direct impact on conversion.

This approach is highly relevant for Retail Intelligence platforms that work at the intersection of territory, pricing and assortment. The commercial opportunity of a postcode does not depend solely on opening more points or selling more units; offering the right mix for that competitive and socioeconomic environment also plays a part.

How to Interpret the Map to Make Commercial Decisions

The opportunity map is only useful if it is turned into action. The key lies in interpreting it as a prioritisation tool, not just as a pretty visualisation. To do this, territories should be organised based on a combination of opportunity, performance and ease of activation.

• High-priority growth territories: high potential, low capture, adequate coverage and moderate competition. These are the natural candidates to receive more commercial investment, acquisition campaigns and assortment reinforcement.
• Consolidation territories: high potential, medium or high capture, well-established presence. Here, the priority is to retain customers and extract more value from the transaction without cannibalising already achieved positions.
• Strategic review territories: low potential, high capture, oversized coverage. These may be candidates for resource reallocation or, in extreme cases, a review of physical presence.
• Territories with identified barriers: high potential, low capture, but with clear causes such as insufficient coverage or high competitive pressure. They require specific decisions before increasing commercial investment.

The value of the map appears when it helps answer the question “what do I do first and where”. This categorisation of territories turns the map into a prioritisation tool, not just a descriptive one. It allows the management team and the commercial area to speak the same language and make decisions based on shared objective criteria. At this point, territorial intelligence ceases to be an analytical exercise and becomes an operational guide.

Common Errors when Using Territorial Maps

The use of commercial maps provides a lot of value, although it also presents risks if the analysis is oversimplified. Here are some of the most frequent errors:

• Building the map and not updating it: The market changes: competitors open and close, neighbourhood demographics shift, buying behaviour changes. A static map loses relevance within a few months.
• Working only with internal data: If the analysis is built solely on own sales data, the map describes the business’s past, not the market’s potential. The external data layer is essential.
• Ignoring granularity: Aggregating data at a provincial or regional level eliminates the differences that the map should highlight. The value of the analysis lies precisely in the ability to distinguish between adjacent areas.
• Analysing only volume and forgetting context: A territory may seem attractive based on absolute sales, but hide high commercial costs, strong competitive pressure or low profitability. Prioritising without looking at margin, coverage and real potential can lead to inefficient decisions.
• Treating the map as an end in itself: The utility of the map is measured by the decisions it generates, not by its technical sophistication. Without a clear process to translate the analysis into concrete actions, the exercise loses value.

Avoiding these errors improves the quality of the diagnosis and increases the impact of commercial prioritisation.

How to Scale this Approach with Retail Intelligence

Building a territorial opportunity map manually, crossing diverse data sources and keeping it updated, involves a high cost in time and resources. In organisations with extensive networks or especially fragmented markets, this complexity grows exponentially.

Scaling this approach requires a technological foundation capable of integrating several layers of information in a single environment:

• Internal sales and distribution data
• Assortment and pricing variables
• Geographical information
• Competitive signals
• Dynamic visualisation of the territory

Retail Intelligence platforms solve this problem by automating the integration of internal and external data, normalising variables at the postcode level and generating territorial visualisations that are updated periodically. This allows the opportunity map to stop being a one-off analysis and become a recurring operational tool.

Solutions such as flipflow, focused on Assortment, Pricing and Territorial Intelligence, allow for this approach to be maintained over time. It is not just about visualising the map, but about identifying opportunities by postcode, understanding which levers generate the greatest impact in each area and prioritising actions with consistent criteria. The result is more coherent decision-making, better allocation of commercial effort and a greater concentration of resources where the potential return justifies it.

From Intuition to Territorial Precision

Territorial intelligence by postcode is not a tool reserved for large corporations with advanced data teams. With the right sources and a clear methodology, any retail organisation can build a model that transforms its way of prioritising markets and distributing resources.

The starting point is deciding to stop treating all territories in the same way. The next step is building the map. And the result, when done well, is a commercial team that stops operating by intuition and starts operating with data that reflects where the real opportunity lies.

In an environment where every point of sale, every SKU and every territory competes for resources, making better decisions on where to act makes the difference. The postcode offers a practical level of reading to do so with greater precision. And when that analysis is integrated into a Retail Intelligence strategy, territory takes its rightful place within commercial decision-making.

The post Territorial Intelligence in Retail: Opportunity Mapping by Postcode and Commercial Prioritisation appeared first on Flipflow.

TL;DR
Analysis data: evolution of Share of Shelf and innovation in formats and flavours for different tiers and brands of gin and vodka in the Spanish market, between December 2025 and February 2026, based on information from our SaaS (full details in the downloadable report).

The spirits market in Spain continues to go through a phase of adjustment and changing habits. In 2024, sales in the sector fell by 2.4% to €2,075 million, while volume consumption declined by 3.7%. Data for 2025 has not yet been published, but forecasts at the end of the year pointed to a further 2% decrease in market value.

Even so, Spain remains one of the main European markets for spirits, with a vibrant hospitality culture (on-trade) and a grocery channel (off-trade) that has gained strategic weight in purchasing decisions for home consumption.

In this context, understanding which brands are winning shelf space and how they are innovating in their assortment is key to anticipating competitive moves. It is not enough to look at price or promotions: the breadth of the range, the choice of formats, and the focus on specific flavours are increasingly conditioning brand visibility and the ability to capture the consumer in a digital and omnichannel environment. Below, we analyse how the major gin and vodka brands are managing their presence and which product trends are setting the tone in this 2026.

The Battle for Share of Shelf: Quantity or Exclusivity?

The Share of Shelf measures a brand’s participation on the shelf—that is, how many references (SKUs) it occupies within a category and its weight compared to its competitors. In a market like spirits, this metric is particularly useful because it shows who dominates through assortment breadth, who bets on variety, and who prefers to concentrate on a few highly recognisable references.

According to the data analysed between December 2025 and February 2026, the gin and vodka categories present very different visibility structures.

Gin: Leadership through variety

In the gin category, there is no single brand that dominates absolutely. Instead, we find leadership shared by three giants: Beefeater, Larios, and Tanqueray. Each of these brands holds a 10.7% share of shelf, with 6 different references or products in the analysed market.

This equality suggests a clear strategy: brand “depth” is built through variety. By launching multiple versions—especially focused on flavours—these brands manage to saturate the shelf. This saturation phenomenon forces retailers to maintain their presence, often displacing smaller brands that cannot offer such a wide range of options.

Just behind, brands like Gordon’s and Bombay maintain a solid block with an 8.9% share each (5 products). It is interesting to observe how in this upper segment, brands classified as “standard” and “premium” are mixed, demonstrating that the Spanish consumer seeks a balance between trust and quality.

At the top end of the market, the picture changes. Brands with a more exclusive profile appear in a more fragmented way. Martin Miller’s, Nordés, or Bull Dog have a shelf share of between 3.6% and 1.8%. A different logic is seen here. More premium or botanical gins seek to maintain a curated presence without the need to over-expand their assortment. This decision protects positioning but limits the ability to gain visibility against those who do work with a more extensive offering.

Vodka: Portfolio breadth dominance

Unlike gin, the vodka market in Spain is much more concentrated. Here, a single brand dictates the pace of the shelf: Absolut. With an impressive 20.8% Share of Shelf and 10 active references, it is the exception in the spirits market.

Its strategy is based on using a historical heritage of flavour innovation to take over entire shelves. By offering variants such as Citron, Raspberri, or Vanilia, the brand ensures that, regardless of consumer preference, there is always one of its bottles available.

Other brands like Ciroc and Au Vodka (both with a 12.5% share and 6 products) complete the leading group. Collectively, these three brands control almost half of the available assortment, leaving the rest of the market to ultra-premium proposals operating under a logic of fragmentation and exclusivity.

The conclusion is clear: in vodka, the shelf rewards the player who manages to combine a strong brand with a wide assortment. Basic references remain relevant, but the ability to attract attention and cover different consumption occasions increasingly depends on variants, flavours, and designs with greater visual impact.

Innovation in Formats: Packaging as a Storyteller

The report reveals that while the classic 70cl bottle remains the market standard, brands are using packaging design to build value and justify premium price positioning.

Design as “Storytelling” and status

In gin, packaging has become a tool for storytelling. The design and the narrative regarding the origin of the botanicals help build a perception of value that goes far beyond the liquid. The consumer is no longer just buying a spirit; they are buying a narrative of craftsmanship or geographical origin.

In the case of vodka, the dominant trend is “Bling-Bling”, whose main premise is to “shine like stars”. Brands like Au Vodka and Ciroc opt for striking visual codes that convey status. These containers are designed to be recognisable from a distance, especially in nightlife settings or for sharing on social media. The goal is to capture the purchase through aesthetics and the consumption occasion associated with social success.

Tactical formats and limited editions

Innovation also responds to specific market needs:

• 0.0% Gin: The alcohol-free format has gained weight as a tactical lever to expand consumption occasions. It allows brands to be present in moments where alcohol is not an option, without replacing their main product.
• Limited editions in vodka: These are used as novelty accelerators. By creating a sense of urgency and exclusivity, vodka brands manage to revitalise their presence on the shelf without needing to permanently change their base recipe.

The Revolution of Colour and Flavour: “Instagrammable” Profiles

If the format builds the first impression, flavour is defining the shelf’s renewal. The trend towards “premiumisation”, defined by the maxim of “drinking less, but drinking better”, has driven a radical shift in the flavours we find in shops.

Our report shows that the classic remains relevant, but innovation is moving towards more striking, more recognisable profiles that are easier to communicate digitally.

The rise of visual flavours

Flavour must now be visually attractive to be shared on digital platforms. In gin, this translates into an expansion towards southern citrus and floral botanical profiles. Grape-based proposals are also gaining ground, offering a clear sensory and visual differentiation compared to traditional dry-cut gin.

In vodka, the trend is even more extreme. Ultra-sweet variants and those with striking colours are growing. The main appeal here is “sweetness, colour, and visual status”. These brands act as “visual blockers” on the shelf. They need several references of different colours so as not to go unnoticed by a consumer who chooses based on the visual impact of the bottle or the colour of the mixer.

The role of “core defenders”

Faced with this explosion of colours and flavours, traditional brands like Gordon’s, Bombay, Smirnoff, or Eristoff maintain efficient volume by focusing on their core product. Their strategy is defensive: they maintain a couple of innovations in sweet flavours to prevent the competition from stealing younger consumers, but they protect their original recipe as the main sales driver.

The case of Seagram’s stands out; despite being a high-volume premium brand, it maintains a strategy of containment. It relies on its original recipe and only introduces very measured innovations to preserve its identity.

What Does this Tell us About the Market?

The first major takeaway is that visibility no longer depends solely on price. In a more rational consumption scenario, with lower purchase frequency and more sensitivity to value, brands need additional reasons to enter the basket. The shelf, packaging, and flavour variety become tools as important as promotion.

The second takeaway is that premiumisation is still very much present. Consumers accept drinking less, but seek better, more curated experiences that are more aligned with a specific occasion. This explains why products with a better brand story, differentiated design, and a richer flavour proposal are thriving.

The third takeaway is that innovation is increasingly linked to digital visibility. In an environment where purchases are consulted, compared, and discovered online as well, having a broad and coherent range helps protect share, gain space, and reinforce brand perception.

Implications for Manufacturers and Distributors

For manufacturers, the message is quite clear: winning visibility requires making good decisions about where to expand the assortment and where to concentrate efforts. In gin, leadership is built with range depth and extensions that bring novelty without breaking brand territory. In vodka, however, a broad assortment seems almost a prerequisite for competing with guarantees.

For distributors and retail, the challenge lies in balancing variety and efficiency. An assortment that is too narrow limits innovation and leaves out proposals with potential; one that is too broad can dilute turnover and complicate stock management. The key is to build an assortment that combines defensive brands, high-turnover references, and differential bets.

For brands, there is also a clear opportunity in designing more coherent portfolios. The references that work best are not necessarily those that compete only on price, but those that provide a clear signal of occasion, flavour, or visual style. In categories so exposed to impulse and image, that clarity is worth a lot.

Conclusions: Visibility as a Competitive Advantage

The report data underlines that success in the Spanish spirits market does not depend on a single variable. Gin requires constant management of flavour variety to avoid losing space to competitors, while vodka rewards those players capable of building a broad and visually impactful portfolio.

Innovation has shifted from the content to the container. Packaging design, the ability to generate social media content through the colour of the liquid, and adaptation to new trends like alcohol-free consumption are the levers moving the shelf.

For companies in the sector, the current challenge is to find the balance between protecting the main product—the one that generates volume—and experimenting with flavours and formats that capture the attention of the consumer looking for novelty and status. In a market where visibility is bought with variety, understanding your own Share of Shelf and that of the competition is the first step towards a winning commercial strategy.

If you want to see the full details of Share of Shelf and innovation in formats and flavours, by tier and brand, download the free industry report by clicking here.

The post Mastering the Shelf: Visibility and Innovation Strategies in the Spanish Spirits Sector appeared first on Flipflow.

TL;DR
Carrefour becomes the first major European retailer to integrate part of the shopping experience into ChatGPT. The initiative opens a new era in conversational commerce, although it still presents operational limits.

The Future of the Supermarket is Already Here

Artificial intelligence has already entered retail in many ways: customer service, demand prediction, logistics optimisation, or offer personalisation. Now it takes a visible step for the end consumer. Carrefour has announced an integration with ChatGPT in France that allows the preparation of the shopping basket through natural conversation.

The news positions Carrefour as the first major European retailer to bring online shopping to this conversational environment. The move has a clear reading: the supermarket’s digital channel is beginning to open up to new interfaces, where the user asks, clarifies, and decides without relying so much on the traditional search engine or a website’s menus.

For the European sector, the announcement has strategic value. Conversational shopping is no longer a laboratory test and is entering real commercial ground. From here, many companies will ask the same question: Can ChatGPT become a new gateway to grocery e-commerce?

What has Carrefour Announced?

The proposal presented by Carrefour in France allows users to interact with the brand within ChatGPT to explore products, get recipe ideas, check availability, and build a basket with selected items. According to information published by various media outlets, this integration is part of a broader strategy by the company to strengthen its digital presence and experiment with new customer relationship channels.

The company is not starting from scratch. Carrefour had already developed previous initiatives linked to artificial intelligence, such as Hopla and Hopla+, aimed at improving the online shopping experience and exploring new forms of consumer assistance. The launch on ChatGPT can, therefore, be seen as a logical evolution within that roadmap.

What can the user do within ChatGPT?

Within ChatGPT, the customer can make requests as if they were talking to a personal assistant. For example:

• Prepare a weekly shop with a specific budget.
• Look for products for a specific recipe.
• Ask for gluten-free or lactose-free options.
• Find items for a quick dinner.
• Select items according to household preferences or needs.

The big advantage lies in natural language interaction. The user does not need to navigate through multiple categories to start. They can describe what they are looking for in their own words and receive a tailored proposal.

This dynamic fits grocery shopping very well, where many decisions stem from a specific need: “I want to organise menus for five days” or “I need an economical shop”. ChatGPT helps to order that intent and translate it into a selection of items.

Furthermore, the focus is especially interesting in FMCG categories, where many purchases are repeated and where speed is as important as price or variety. A well-guided conversation can shorten several steps of the purchasing funnel and make product choice more fluid.

How the service is accessed

The functionality is available in France, which is the market chosen by Carrefour for this initial roll-out. According to coverage published by specialist and generalist media, access is through ChatGPT, where the user interacts with the experience enabled by Carrefour to start their shopping.

From that conversation, the system suggests products and organises the selection. Closing the order remains connected to the distributor’s digital ecosystem. That is, the AI helps in the discovery, recommendation, and basket preparation phase, while the purchase is validated within the commercial environment of carrefour.fr.

This detail is important because it clarifies the real scope of the launch. It is not a purchase completely resolved within the chat, but a hybrid process between conversation, recommendation, and transfer to the supermarket’s online channel.

Current Limits: Innovation is Still in the Early Stages

The technological novelty brings visibility and opens an interesting business path, but the experience must still evolve to become more solid and fluid. Several aspects stand out among the current limits:

1. Recommendation accuracy: Grocery shopping requires a lot of detail. It is not enough to suggest “milk” or “pasta”. The consumer wants brand, size, price, promotions, and availability.
2. Connection with real stock and offers: If an AI recommends a product that is later unavailable or changes price when moving to the shopping environment, the experience loses value.
3. Friction in the process: Although the conversation simplifies the start, the purchase still needs subsequent steps in the retailer’s environment to be completed. This can take away some of the immediacy that the user expects.
4. Consumer trust: In food, many decisions are sensitive: allergies, diets, brand preferences, freshness, or substitutions. The customer needs to feel that the recommendation is useful and reliable.
5. The learning curve: Not all consumers are ready to do their shopping by talking to an AI. There will be profiles that find it practical and others who continue to prefer traditional navigation.

The proposal is promising but requires technical and operational maturation to reach a truly end-to-end purchase within the conversational environment. It also remains to be seen how the available catalogue, the depth of recommendations, and the system’s personalisation capacity evolve.

The launch should be read as a test for the future rather than a definitive solution. Carrefour is testing a new gateway to online commerce, but the experience still depends on other elements of the brand’s digital ecosystem.

Why Is it a Milestone for European Retail?

Carrefour’s announcement is significant for one simple reason: it sets a precedent in Europe. Until now, the conversation about generative AI in retail had focused on productivity, automation, or customer service. With this step, AI enters the commercial moment more visibly. This has several implications:

The first is competitive positioning. Being a pioneer gives visibility and places Carrefour at the centre of the debate on innovation in supermarkets, e-commerce, and artificial intelligence.

The second is a change of interface. For years, online shopping has been based on search engines, filters, and category navigation. ChatGPT introduces a different logic: the user expresses a need and the system organises a response.

The third is market learning. Whoever moves first can better understand how the customer buys in conversational environments, what questions they ask, what categories work best, and what obstacles appear in the experience.

Furthermore, there is a relevant European element. Grocery retail in Europe operates in a demanding context, with strong competition, price sensitivity, and increasing regulation around data and technology. A group like Carrefour activating this model in that environment sends a clear signal to the market.

What the Sector Can Learn from this Move

Carrefour’s decision leaves several useful lessons for any retail, FMCG, or e-commerce company:

1. Data quality rules

For an AI to recommend well, the catalogue must be well-structured. Poor descriptions, incomplete attributes, or outdated commercial information generate unhelpful responses.

2. Conversational experience requires real integration

Success does not depend only on the assistant. Stock, prices, promotions, logistics, and the checkout process also influence it. If the elements are not connected, the result will be inconsistent.

3. Natural language can reduce friction

Many consumers know what they need but do not always want to go through a website step by step. Conversation can save time and help discover products with less effort.

4. It pays to launch, measure, and correct

Carrefour has started in a specific market. This approach allows testing real use, detecting failures, and adjusting the experience before considering a larger expansion.

5. AI must provide practical utility

Technological enthusiasm alone does not guarantee adoption. The consumer will repeat if they perceive time savings, relevant suggestions, and a simple purchase.

For the sector, the message is direct: conversational AI has commercial potential, but it requires technical, operational, and strategic preparation.

Conclusion: Towards Clickless Commerce

Carrefour’s initiative does not yet inaugurate a completely autonomous supermarket within ChatGPT, but it does point to a very clear direction for the future of retail. AI-assisted shopping is beginning to consolidate as a new territory for innovation, with the potential to change how we discover products, how we compare options, and how we complete an online purchase.

For the sector, the signal is clear: clickless commerce has already begun to take shape, albeit in an early stage. And Carrefour not only confirms this but has been the first in Europe to show it in a tangible way, demonstrating that the shopping of the future will increasingly begin with a simple conversation.

The post Carrefour Revolutionises Retail: First European Giant to Integrate the Shopping Basket into ChatGPT appeared first on Flipflow.

TL;DR
LLMs allow for the conversion of data and text into actionable insights within Retail Intelligence. Their real value emerges when integrated with reliable data and decision-oriented processes.

Retail Intelligence Today

Retail Intelligence has matured as a discipline. Today, retail data teams handle increasing volumes of structured information (sales, stock turnover, penetration, prices) but also considerable amounts of unstructured information: customer reviews, field reports, supplier communications, social media data, and competitive signals scattered across multiple sources.

The challenge is no longer data availability. Currently, the challenge is to turn that data into concrete decisions, on time, and with sufficient context for business teams to act with confidence.

In this context, LLMs (Large Language Models) have shifted from being a technological curiosity to an operational tool with clear applications. Their ability to process text, reason about context, and generate structured responses makes them a natural complement to Retail Intelligence platforms that already possess a solid data infrastructure.

This article describes the most promising use cases, the nuances to consider when implementing them, and practical recommendations for teams looking to move from proof of concept to generating real value.

Specific LLM Use Cases in Retail Intelligence

1. Automated analysis of customer feedback

One of the clearest uses of LLMs in retail is the analysis of the voice of the customer. Product reviews, satisfaction survey responses, point-of-sale comments, and social media mentions represent a source of qualitative information that retail teams rarely exploit systematically. The volume is too high for manual analysis, and traditional sentiment analysis solutions offer insufficient granularity.

LLMs allow for the extraction of specific attributes from feedback: which product aspects generate the most satisfaction, which complaints repeat most frequently, and how the perception of a category evolves after a range change or promotional action. Beyond generic sentiment analysis, a well-configured model can classify comments by product attribute (price, quality, availability, shopping experience) and link them to specific commercial moments.

For example, a retailer can ask the system to summarise the main causes for returns in a category, identify recurring complaints about sizing or quality, or group negative reviews by theme. It is also very useful for prioritising actions. If the system detects that a group of products is accumulating comments about damaged packaging, delivery times, or lack of consistency in the description, the team can intervene sooner and coordinate with operations, logistics, or catalogue teams.

From a Retail Intelligence perspective, this use case holds special value because it adds context to commercial data. A drop in sales or an increase in returns is no longer seen as an isolated number but becomes connected to the actual customer experience.

2. Richer competitive monitoring

Competitive intelligence in retail has historically depended on monitoring prices and shelf presence. LLMs expand the scope of this monitoring by allowing the processing of textual sources that previously fell under the radar: e-commerce product sheets, analyst notes, changes in competitors’ sales pitches, or social media movements.

Some practical examples:

• Identify which competitors have expanded their range in a specific category
• Summarise price changes and promotions by brand or format
• Detect new value propositions in product sheets
• Compare commercial messages in campaigns or landing pages
• Highlight movements that coincide with changes in own demand

This use is particularly valuable for pricing, category management, and trade marketing. In markets with high promotional turnover, the speed of competitive reading makes clear differences.

The advantage lies not in the raw speed of data capture, but in the ability to provide context and relevance to information that would otherwise be lost in the noise.

3. Explaining commercial anomalies

Detecting an anomaly in sales data is relatively simple with standard statistical tools. Explaining it is much harder. When a category drops by 12% in a specific week, the analyst needs to cross-reference multiple sources (checkout data, delivery information, logistical incidents, promotional activity) to build a coherent hypothesis. This process can take hours.

LLMs, integrated into the data flow, can automate an initial diagnostic layer: which variables seem most related to the anomaly, which stores concentrate the problem, or what changes occurred just before the deviation. From there, they can generate an explanatory hypothesis that the analyst can validate or discard in minutes instead of hours.

The goal is not to replace the analyst’s judgement, but to reduce the time needed to reach a reasonable hypothesis. This frees up capacity for second-order analysis: understanding why something is happening, not just what has happened.

4. Support for category managers and trade marketing teams

Category managers and trade marketing teams handle a particularly demanding mix of information. They need to understand turnover, margin, promotional elasticity, store execution, channel performance, competitor actions, and consumer response. Doing all this with agility is not always easy.

An LLM-based system can serve as a support layer for very specific tasks, for example:

• Generate weekly summaries by category
• Compare performance between regions or store clusters
• Detect SKUs at risk of stockouts or margin erosion
• Synthesise promotional execution and its results
• Explain relevant deviations with a clear narrative
• Prepare executive reports for commercial meetings

This type of support has two practical effects. On one hand, it reduces the time spent on repetitive data collection and summarisation tasks. On the other, it improves the ability to arrive at meetings with a more structured reading of the business.

McKinsey highlights that generative AI has clear potential in synthesis, documentation, and knowledge support tasks. In retail, this promise fits very well with the needs of category management and trade marketing, where information is spread across many sources and the demand for a response is constant.

5. Internal assistants for retail teams

Perhaps the use case with the highest short-term adoption is that of internal conversational assistants geared towards data queries. Instead of depending on an analyst or knowing how to write a SQL query, a store manager, sales technician, or area manager can ask questions in natural language about the performance of their area and receive an immediate response with the relevant data and necessary context.

“What is the evolution of the snacks category in the impulse channel this quarter compared to the same period last year?” is the type of question that currently requires technical mediation. With a well-built assistant on reliable data, the answer should be available in seconds for anyone on the team.

The effect on the organisation is significant: democratisation of data access, reduction of bottlenecks in analysis teams, and greater speed in operational decision-making.

Recommendations for Retail Teams

Adopting LLMs within Retail Intelligence can provide a lot of value, but it should be done with focus and method. Here are some practical recommendations for getting off to a good start:

Prioritise use cases with visible impact

The temptation in AI projects is to start with what is technically interesting. The recommendation is to start with what hurts. Identify the most frequent frictions in the workflow of analysis, category management, or trade teams: processes that consume disproportionate time, decisions delayed by a lack of information synthesis, reports that no one reads because they arrive late. That is where LLMs generate quickly visible value.

Review data quality before scaling

LLMs cannot recognise if data is poorly structured, incomplete, or inconsistent. A model working on outdated product information or on sales data with gaps will produce responses that seem coherent but lead to erroneous conclusions. Before deploying any application in production, it is worth auditing the quality of the data sources that will feed the system.

Combine structured and unstructured data

An important part of the differential value of LLMs lies in joining both worlds. If the system only queries sales and stock, the jump compared to a traditional tool may be limited. If it also incorporates reviews, receipts, store reports, or operational documentation, the quality of the insight improves significantly.

Design experiences intended for end users

A technically correct application that business users do not adopt generates no value. The interface design, the level of detail in responses, the type of questions the system can and cannot answer: everything must be calibrated for the end-user profile, not for the technical team building it. The more natural the interaction, the higher the adoption by non-technical profiles.

Maintain human supervision and clear controls

LLM responses can contain errors, especially when working with data they do not know well or when asked to infer beyond what the context allows. In Retail Intelligence applications, where decisions have direct commercial consequences, it is essential to maintain validation controls: indicate data sources, make uncertainty explicit when it exists, and establish human review processes for outputs that feed high-impact decisions.

Measure productivity and decision speed

To evaluate success, it is not enough to measure the use of the tool. It is also advisable to track indicators such as:

• Time saved in report preparation
• Speed in answering business questions
• Number of queries resolved without manual intervention
• Adoption by commercial teams
• Improvement in analysis and reaction times

Establish a baseline before implementing and measure the results once you start using your Retail Intelligence tool connected to LLMs. AI initiatives work best when linked to specific operational results.

Start small, scale with discretion

A well-defined pilot (for a specific category, team, or use case) generates learnings that a broad rollout blurs. It allows for detecting failures before they have an organisational impact, validating the value proposition with real users, and building the internal case for scaling with credibility.

Conclusion: From Experimentation to Real Value

Ultimately, the real leap is not in adding LLMs as an additional layer, but in integrating them into a Retail Intelligence architecture capable of connecting data, context, and decisions within the same operational flow. When this integration is solid, technology stops being perceived as an isolated tool and becomes part of the teams’ daily routine, directly influencing how they prioritise, analyse, and act.

This is where an approach like that of flipflow makes sense. Beyond centralising information, the differential value lies in structuring the data so that it can be activated: combining internal and external sources, offering a unified view of the market, and facilitating the translation of insights into actionable decisions without friction.

In this scenario, LLMs do not replace Retail Intelligence platforms; they amplify their impact. They allow for more natural interaction with information, reduce the distance between question and response, and accelerate the critical step between detecting an opportunity and executing an action. But this capacity only fully materialises when supported by a robust, well-modelled, and business-oriented database.

The key is to build a system where data, analytics, and generative capabilities work in a coordinated manner, aligned with business needs. When this fit is real, teams not only understand better what is happening but can also act accordingly with much more fluidity and judgement. This is where intelligence stops being analysis and becomes action.

The post LLM Use Cases in Retail Intelligence: Practical Applications and Recommendations for Retail Teams appeared first on Flipflow.

TL;DR
Analysis data: evolution of average price and average discount in Spain for different gin and vodka tiers and brands, between December 2025 and February 2026, based on information from our SaaS (full details in the downloadable report).

The spirits market in Spain is undergoing a period of sustained change. The category remains closely linked to hospitality, tourism, nightlife, and home consumption—four drivers that influence both pricing and promotional activity. Added to this is a more selective consumer who compares more, seeks perceived quality, and pays attention to format, brand, and occasion.

In this context, gin and vodka continue to be two key references within the FMCG range and the digital channel. Gin maintains a solid base through tradition, versatility, and its presence in classic mixed drinks. Vodka, for its part, retains its ability to adapt to very different consumption profiles, from entry-level options to high-end propositions with strong visual and aspirational appeal.

Seasonality also plays a role. Winter, and especially December, sees a concentration of celebrations, social gatherings, and impulse buys. January and February tend to be more restrained, with lower promotional intensity and greater sensitivity to price or perceived value. Therefore, analysing what happens between December and February provides a clear understanding of how brands move once the major Christmas commercial peak ends.

For companies operating in this sector, understanding price evolution and the effectiveness of promotional campaigns is vital. It is not enough to look at general figures; it is necessary to drill down into the details by segment and region to identify growth opportunities. Below, we break down the most relevant findings obtained through our Retail Intelligence platform, focusing on the period from the end of 2025 through the first quarter of 2026.

Context: Declining Consumption and Rising Premiumisation

In 2024, spirits consumption in Spain stood at around 180 million litres, representing a fall of nearly 3.7% compared to the previous year and the second consecutive year of decline. Despite this contraction in volume, turnover remained at around 7.2 billion euros, indicating a greater contribution from the price mix and the high-end range.

This dynamic is supported by a clear trend towards premiumisation: more and more consumers are willing to pay more for higher quality cocktails and spirits, especially younger segments, who state an intention to increase their consumption of premium references. In parallel, inflationary pressure and spending restraint are driving a “drink less, but better” approach, with a growing preference for brands with perceived value, distinctive design, and higher average price points.

Price Evolution in Gin: General Stability with Growth in Trendy

The evolution of gin prices between December 2025 and February 2026 shows a relatively stable market. There is no sharp break between months, but there are clear signals regarding where growth is concentrated and where corrections appear.

If we look at price segments, the Standard range goes from €16.37 in December to €15.65 in February, representing a 4.4% drop. The Premium range barely moves, remaining practically flat (+0.1%). Ultra-Premium also remains stable, with a slight rise of 0.7%. The standout note comes from the Trendy segment, which rises from €17.69 to €18.48, an advance of 4.5%.

This breakdown says a lot about market behaviour. Gin is not experiencing a generalised price war. What is seen is a combination of restraint in the middle of the market, some pressure in the entry-level bracket, and progressive improvement in those propositions with greater brand appeal, design, or positioning.

What is happening within Standard and Premium gin

In Standard gin, the adjustment is explained by different trajectories according to the brand. Gordon’s leads the most visible fall, with a 6.9% decrease. Rives also retreats, albeit more gradually, with a 4.1% drop. In contrast, Ampersand rises by 6.5%, while Larios remains practically stable, with a variation of -0.8%.

In Premium, although the segment average barely changes, there are significant movements internally. Seagram’s rises by 16.2%, and Beefeater advances by 10.5%. Against this, Bombay barely varies and Tanqueray falls slightly by 3.2%. The result is a balance between brands pushing prices up and others acting as a brake.

Ultra-Premium and Trendy: where gin gains value

At the top end of the market, stability does not mean immobility. Brockmans concentrated the most volatility, with a peak in January of €41.88 after starting at €38.58 in December, and a subsequent correction to €38.74 in February. Other brands show more sustained evolution: Nordés rises by 5.2%, Bull Dog by 6.0% and Hendrick’s by 2.4%.

In the Trendy segment, Puerto de Indias goes from €17.90 to €18.75, with a rise of 4.7%. This is sustained growth, without large fluctuations, reinforcing the idea of consolidation. In other words, there are brands that are managing to sustain a higher price thanks to a clear product and image proposition.

Price Evolution in Vodka: Between Weakness at Entry Level and Strength in the High-End Range

If gin conveys stability, vodka presents a more fragmented picture. Here, an evident polarisation appears between segments losing value and segments strengthening.

The Standard range goes from €13.34 in December to €12.65 in February, a 5.46% fall. The largest contraction occurs in Premium, with a 13.8% decrease. At the high end, the opposite occurs: Ultra-Premium rises by 5.9%, while Trendy remains practically flat, with a slight improvement of 1.1%.

The reading is clear: the vodka consumer is behaving very differently depending on the price bracket. The middle of the market is losing strength, while the high end manages to sustain and even raise its average price.

Standard and Premium: clear adjustment at the base and in the middle

Within Standard, opposing trajectories coexist. Smirnoff rises from €12.65 to €14.30, 13.0% more. Moskovskaya advances by 14.1% and Beveland also grows by 13.0%. However, Eristoff falls by 10.8%. This mix helps explain why the segment falls in aggregate even though several brands are rising.

In Premium, downward pressure is much more evident. Absolut goes from €17.20 to €14.57, a 15.3% drop. Skyy retreats by 15.6%. Stolichnaya, on the other hand, remains completely stable at €14.84 throughout the period. The problem for the segment is that the declines of the leading brands weigh more than the specific stability of a single reference.

Ultra-Premium and Trendy: strength at the top, calm in the visual segment

In Ultra-Premium, growth is mainly explained by Grey Goose, which rises from €55.58 to €60.01 between December and February, an 8.0% increase. Beluga remains fixed at €45.80 and Belvedere barely yields 0.7%. The result is a segment with the ability to defend price and improve its position.

In Trendy, movement is gentle. Au rises by 1.9% and Cîroc by 2.5%. These are moderate rises, closer to fine-tuning than a strong change in positioning.

Regional Differences: Where is it Most Expensive to Drink Spirits?

Regional analysis reveals that the price of a bottle can vary significantly depending on the autonomous community. These differences respond not only to logistics but also to the density of competition and the local consumer profile.

In the standard gin category, Navarra and Madrid rank as the regions with the highest prices, exceeding €15.60 on average. Conversely, La Rioja presents the most competitive prices, with an average of €12.79. If we move to the Ultra-Premium segment, the Balearic Islands lead the maximum price ranking (€35.02), likely due to strong demand from the luxury sector and international tourism throughout the year.

In the case of vodka, Madrid stands out as the most expensive region for the Premium segment, reaching an average of €26.55, which represents a considerable difference compared to the €17.73 in La Rioja. However, in Ultra-Premium vodka, La Rioja rises to occupy the top spot on the table (€56.26) followed closely by Navarra (€55.83 average), while Galicia remains the most affordable area to purchase these high-end references.

Discount Landscape: Seasonality Rules

Promotional analysis is key to understanding how brands activate sales during off-peak periods. The data reflects a clear pattern: the Spanish market concentrates much of its promotional effort in December, leveraging the Christmas campaign (driven by gatherings, gifts, celebrations, and home restocking) as the main driver for customer acquisition. Following this, the spirits market enters a maintenance phase characterised by a notable reduction in promotional pressure.

Promotional intensity in gin

During December 2025, 68% of the analysed gin brands featured some type of discount, with an average reduction of 3.91%. However, by January and February, coverage dropped drastically to only 4 active brands.

In this scenario, Brockmans positions itself as the “agitator” brand. Its strategy does not appear to be a one-off discount, but rather constant pressure that reached -11% in December and remained at -7% in February. This suggests a tactic aimed at aggressively gaining product turnover.

Other brands use discounts more tactically. Larios and Bombay limited their promotions exclusively to the month of December to compete during the Christmas consumption peak, disappearing from promotional activity for the rest of the quarter. For their part, brands like Beefeater or Tanqueray apply what we call a “soft nudge”: small, surgical discounts, closer to a brand reminder than a true lever for price change.

The vodka promotional “blackout”

The vodka market is much more restrictive with discounts. In January and February, the category “shuts down” almost completely, with only one brand active in promotions.

Skyy leads the most extreme move in the entire report, applying a 19% discount in February. Such aggressive action usually responds to stock clearance needs or a determined attempt to displace the competition on the shelf.

It is very relevant to highlight the existence of a block of “disciplined” brands that did not apply a single cent of discount in the three months analysed. Brands like Absolut, Beluga, Belvedere, Smirnoff and Stolichnaya protect their value positioning by avoiding the promotion war, indicating a clear focus on brand consistency over specific volume.

What These Moves Mean for Spirits Brands

The combination of relative price stability, selective corrections by tier and a very seasonal use of discounts paints a scenario where the value strategy revolves around three main axes:

• Looking after mid-range positioning: declines in Standard and Premium require a clear definition of which brands will compete on price and which will be protected with lower promotional investment.
• Focusing on high-end and trendy ranges: traction in Ultra-Premium and Trendy, especially in vodka, indicates that growth is concentrated in consumers willing to pay more for distinctive attributes of quality, design and experience.
• Managing December as a “key month”: the concentration of promotions in this month reinforces the importance of properly planning offers, discounts and visibility to maximise the campaign without damaging the average price for the rest of the year.

In parallel, the rise of 70cl formats with packaging storytelling, alcohol-free variants as a tactical lever and more visual and “Instagrammable” flavours reinforce the ability of some brands to sustain and even raise prices, relying on perceived value rather than just promotions.

Beyond the Discount: How Value is Built in 2026

The spirits market in Spain is leaving behind purely transactional logic to enter territory where price is only part of the equation. The data points to something more structural: the brands that resist best—and even grow—are not necessarily the cheapest or the most promoted, but those that build a coherent proposition between product, positioning and consumption context.

This has a direct implication: competing by lowering prices outside key moments like December is not only inefficient but can erode value without generating a sustainable advantage. Instead, brands that understand when to activate the promotional lever and when to withdraw it, and that are able to justify their price through brand, design or experience, are playing in another league.The opportunity, therefore, is not in offering more discounts, but in offering them better… or in not needing them at all.

If you want to see the full details of prices and discounts by tier and brand (including charts and tables), download the industry report for free by clicking here.

The post Pricing and Discount Strategies in the Spirits Sector: Analysis of the Spanish Gin and Vodka Market appeared first on Flipflow.