Availability, Price, and Consumer Insights: The Three Data Points that Reveal Actual Demand in Digital Retail

The post Availability, Price, and Consumer Insights: The Three Data Points that Reveal Actual Demand in Digital Retail appeared first on Flipflow.

TL;DR
Flipflow repeats as the only Spanish company in the 2026 Gartner Market Guide for Digital Shelf Analytics. Discover what this recognition means and how sector trends—agentic AI, AEO, and Retail Media—define the future of the digital shelf.

We have done it again. For the second year in a row, Flipflow is featured in the Gartner Market Guide for Digital Shelf Analytics, published in May 2026, as the only Spanish provider among those representative worldwide. 2025 was the first time; 2026 is a confirmation.

This repeated recognition is no coincidence: it is the result of continuing to build a platform that evolves at the pace the market demands, with proprietary technology, real coverage, and a team that puts its customers at the heart of every decision.

What is the Gartner Market Guide for Digital Shelf Analytics?

Gartner is the world’s most influential technology research and intelligence consultancy. Its reports and market guides are an essential reference for technology, marketing, and digital commerce leaders at major global companies. Being included as a representative vendor in a Gartner Market Guide is equivalent to passing one of the most demanding quality filters in the sector.

The Market Guide for Digital Shelf Analytics analyses solutions that provide data and intelligence to brands and manufacturers about their products on third-party digital channels: marketplaces, retailer sites, social networks with selling capabilities, or emerging AI platforms. The report covers market trends, vendor selection criteria, and recommendations for buyers.

In its 2026 edition, analysts Jason Daigler and Greg Carlucci have selected 27 representative vendors worldwide. Flipflow is the only one headquartered in Spain.

Why Being Included Two Years in a Row Matters

Entering a Gartner Market Guide for the first time is a notable achievement. Repeating the following year is something else: it means the team of analysts has re-evaluated the market, reviewed the candidates, and concluded that Flipflow continues to meet—and exceed—the benchmark standards.

This consecutive recognition confirms three things:

1. Technical consistency. It was not just a one-off moment. Our Digital Shelf Analytics platform continues to evolve, with improvements in channel coverage, data quality, and automation capabilities.
2. Relevance in the global market. In an ecosystem dominated by US and Asian companies, Flipflow demonstrates that Spanish technology can compete and stand out on the international stage.
3. Customer trust. Gartner also considers the enquiries their analysts receive from companies evaluating DSA solutions. Flipflow appearing recurringly on that radar reflects that there are real organisations asking about us as a reference option.

What does Gartner Say about the DSA Market in 2026?

This year’s edition of the Market Guide reflects a significant acceleration in trends that were already emerging in 2025. These are the most relevant:

AI Agents: from insight to automatic action

Gartner identifies agentic artificial intelligence as the most promising evolution in the DSA market. Until now, these tools detected a problem (for example, that a competitor had lowered their price on Amazon while sales of a specific SKU were falling) and presented the information to the user for them to make a decision. The next step is for an AI agent to act directly: adjust the price, update the product listing, and re-syndicate it to the corresponding channel, all with a single click or even completely autonomously.

This ability to close the loop between data and action, which the report calls a closed-loop process, is the most important differentiator Gartner recommends evaluating when choosing a DSA provider. At Flipflow, we have been working in this direction for some time with Tyrell AI, our AI agent.

Retail Media: connecting shelf data with advertising investment

Retailers have turned their digital spaces into genuine advertising networks. Platforms such as Amazon Ads, Carrefour Links, or El Corte Inglés Ads allow brands to buy sponsored visibility right where the purchase decision occurs. Gartner highlights that the most advanced DSA solutions already integrate Digital Shelf data with Retail Media management, allowing, for example, a sponsored products campaign to be activated automatically when a competitor reduces their stock or modifies their price.

AEO: the new frontier of visibility

One of the most relevant updates in the 2026 edition is the attention Gartner pays to Answer Engine Optimisation (AEO): the visibility of products on AI platforms such as ChatGPT, Gemini, or Perplexity. These environments are rapidly changing product search and discovery patterns, and the report notes that current DSA providers still have a significant gap in this area. It is an emerging space where monitoring capability will become critical in the coming years.

Geographical expansion and B2B

The report also highlights the growth of Digital Shelf Analytics usage in markets outside the US and in B2B segments, where the proliferation of industrial marketplaces and digital distributors opens up new opportunities to apply digital shelf analytics.

Selection Criteria: Why Flipflow Is on The List Again

Gartner applies a rigorous selection process. To be included in the Market Guide, a provider must simultaneously meet the following criteria:

• Real multi-channel coverage: monitor multiple marketplaces, retailers, and social platforms, not just one dominant channel.
• Proprietary SaaS product: offer a platform that the client can manage autonomously, with dynamic dashboards and actionable data.
• Full functional capabilities: search positioning, prices, content, stock availability, ratings and reviews, competitive intelligence.
• Integration with the PXM ecosystem: connection with PIM, BI tools, and Retail Media networks.
• AI roadmap: evidence that the provider is developing or already offering automation and artificial intelligence capabilities.

Additionally, Gartner takes into account active enquiries from its clients regarding DSA solutions. Flipflow appearing recurringly in those conversations speaks to a real market presence and not just meeting technical requirements on paper.

Flipflow in 2026: More Powerful, More Connected, More Global

This second recognition comes at a time when the Flipflow platform has reached a notable level of maturity. Today we offer:

• Comprehensive digital shelf monitoring: prices, content, stock, organic and sponsored positioning, ratings and reviews, new competitor products, and unauthorised sellers.
• Coverage of hundreds of retailers and marketplaces in Spain, Europe, and international markets.
• Integration with Retail Media tools to connect shelf data with advertising investment and maximise return.
• Configurable alerts and workflow automation, with AI capabilities to close the loop between insight and action.
• Connectors with PIM, ERP, and BI platforms so that DSA data feeds decisions across the entire organisation.
• Customisable dashboards adapted to different teams: marketing, trade marketing, sales, e-commerce, and analytics.

All of this is supported by a Customer Success team that accompanies each client through the implementation and continuous evolution of their Digital Shelf strategy.

Gartner Recommendations: What to Consider if you are Evaluating a DSA Solution

The report includes a series of questions and criteria that Gartner recommends using in any DSA tool selection process. The most relevant are:

• On channel coverage: Does it monitor all channels where your products are sold? Is it easy to add new retailers or marketplaces? Does it have coverage in the geographical markets where you operate?
• On data quality: How often is the information updated? What happens when it is not possible to collect data from a channel? How long is historical data kept?
• On AI and automation capabilities: Does the tool suggest actions or execute them directly? Does it have AI agents or are they on its roadmap? Can it integrate shelf data with purchases on Retail Media networks?
• On integration and workflow: Does it connect with the existing PIM or ERP? Are the integrations bi-directional? Can it trigger alerts or workflows in other systems?
• On AI visibility: Does it offer or plan to offer visibility tracking for products on platforms like ChatGPT, Gemini, or Perplexity?

Flipflow provides an answer to all these points. If you are in the evaluation process, we would be delighted to show you how in a demo.

Conclusion: Two Years Selected by Gartner, a Long-Term Commitment

Being recognised two years in a row by Gartner as the only representative Spanish company in the Digital Shelf Analytics market is not a finishing line. It is a validation of the path taken and, above all, an impetus to keep moving forward.

The DSA market is undergoing a full transformation: agentic AI, Retail Media integration, and the emergence of AI channels as a new product visibility landscape will redefine how brands manage their digital presence in the coming years. At Flipflow, we are prepared to lead that transformation from Spain.

Thanks to our customers for their trust, and to Gartner for once again recognising the value of what we build every day.

Want to see Flipflow in action? Request a demo and discover in a strategic session how you can dominate the Digital Shelf with real data and smarter decisions.

The post Flipflow, the only Spanish company in the Gartner Market Guide for Digital Shelf Analytics for the second consecutive year appeared first on Flipflow.

TL;DR
Marketplace success depends on the synergy between price, stock, and Buy Box control. Only structural governance based on data and retail intelligence allows for the recovery of real channel control and the protection of brand value.

The digital commerce ecosystem has reached a level of complexity that exceeds traditional management tools. For any brand operating on marketplaces like Amazon, Miravia, or Walmart, visibility has become the most valuable and, at the same time, the most fragile asset. Many companies focus their efforts exclusively on adjusting their profit margins, assuming that success depends solely on a competitive figure. However, the reality of the data shows a different picture.

Real control of digital presence does not reside in a single variable. It is based on a three-pillar structure that interacts constantly: the awarding of the purchase button (Buy Box), immediate product availability, and price stability. Ignoring the relationship between these factors leads to a loss of brand authority and a drain on revenue that is difficult to recover. In this article, we will analyse why digital channel governance requires a cross-sectional view that goes beyond simple price monitoring.

The Illusion of Control in the Marketplace Environment

Many mass-market brands operate under a false sense of security provided by having a listed catalogue and a defined pricing strategy. This phenomenon is known as the illusion of control. A brand may set a Recommended Retail Price (RRP) and believe its authorised distributors respect it. But the marketplace environment is dynamic and often opaque.

The moment a product is published on an open platform, it is exposed to third-party intervention. Unauthorised sellers, parallel imports, or even errors in competitors’ repricing algorithms can alter the brand’s presentation to the end consumer in a matter of seconds. Manual control is insufficient given this speed of change.

The lack of structural governance causes companies to act reactively. They only detect the problem when sales drop or when a key distributor complains about unfair competition on the platform. By then, damage to organic positioning and consumer perception has already occurred. Real control involves anticipating these deviations by using retail intelligence that unifies data from all actors involved in the channel.

Buy Box: What it Is and Why it Matters More than it Seems

The Buy Box is the prominent box that appears on the Amazon product page with the direct purchase buttons. In practice, it is the point where conversion is concentrated: whoever controls that space for a product at any given time captures the vast majority of that listing’s sales. According to data from SnapSoft, approximately 82% of Amazon sales are made through this button.

The problem for brands is that this space is assigned dynamically by Amazon’s algorithm. And this means it can change hands at any time. To determine which seller gets the featured position, Amazon takes a wide variety of factors into account: price, product availability, shipping policies, and the seller’s rating in terms of customer service.

But there is a very common error in channel management: assuming the Buy Box is won or lost primarily on price. In the past, the algorithm could be fooled with a very low final price. Nowadays, many different aspects are considered in Buy Box allocation, so while price is an important factor, it is not the only criterion.

Losing this visibility space has immediate consequences. If an unauthorised seller (often referred to as a “hijacker“) takes the Buy Box, the brand loses the direct relationship with the customer and control over the shopping experience. Furthermore, the advertising budget is usually invalidated if the brand does not own the purchase button. This means marketing investment ends up benefiting a third party’s sales.

Availability: The Silent Factor that No One Monitors Well

If price is the most monitored variable, availability is probably the most neglected. And yet, it acts as a prerequisite for everything else: without real availability, neither the best price nor the best product page is of any use.

Availability is not simply equivalent to “having stock”. Availability ensures the product is listed, in stock, and accessible at the retailers where the consumer expects to find it. When any of these three elements fail, the impact is not limited to the digital channel. An online retailer’s stockout can drive demand towards a physical channel where the brand has less margin, or worse, towards a competitor who does have the product available.

To compete for the Buy Box, sellers need sufficient stock to fulfil orders quickly, and the listing must show ‘in stock’ status. This means a brand with the best price and seller history can still lose the Buy Box if its inventory falls below a critical threshold at a specific time.

There is another less obvious effect: availability gaps open windows of opportunity for competitors and unauthorised sellers. When a brand’s product temporarily disappears from its main channel, competitors and resellers exploit that void to gain visibility and accumulate performance metrics. When the brand recovers stock, it finds that regaining the Buy Box takes time, because the algorithm has already given preference to whoever met the demand during the stockout.

Price: The Easiest Variable to Measure and the Most Difficult to Stabilise

Price is the most visible piece of data in the digital ecosystem, making it the primary focus of attention. However, its management is extremely complex due to total market transparency. Any price change at a major retailer can trigger a chain reaction across other sellers within minutes due to the use of dynamic pricing tools.

Price erosion occurs when sellers enter a downward spiral to win the Buy Box. This not only affects the immediate profit margin but also degrades the brand’s perceived value. If a high-end product is constantly sold below its market value, the consumer starts to doubt its exclusivity or quality.

Furthermore, for brands operating with Minimum Advertised Price (MAP) agreements, the breach of these limits by unauthorised sellers creates serious conflicts with official distributors. A distributor who respects the rules feels penalised if the brand allows other resellers to cannibalise the market with unsustainable prices.

The problem is amplified in multi-country environments. Small price differences between markets create arbitrage opportunities. For example, a distributor who buys product in a cheaper market and resells it in another where the price is higher creates inconsistencies that distort the international distribution architecture.

The Triad in Action: How the Three Factors Interact

Buy Box, availability, and price are not three independent indicators managed separately. They are an interdependent system: the state of each conditions the behaviour of the other two.

Let’s see how this works in practice with three specific scenarios:

Scenario 1: competitive price, insufficient availability

A brand maintains the correct price within its MAP policy, but its inventory falls below the optimal threshold on a marketplace. The algorithm penalises availability, the brand loses the Buy Box to a third party that does have stock, and that seller —without needing to respect the MAP— starts to gain ground with a lower price.

Scenario 2: perfect availability, price above MAP

An authorised distributor has plenty of stock but decides to raise the price to capture a higher margin during a period of high demand. The consumer perceives the product as expensive compared to other references, migrates to alternatives, and the listing loses organic positions within the marketplace.

Scenario 3: Buy Box controlled by an unauthorised seller

An external reseller wins the Buy Box thanks to aggressive pricing and accumulated performance metrics. The brand loses the primary conversion point, but more worryingly, marketplaces allow any seller to compete for the sale, meaning that seller can operate for weeks before being identified if there is no continuous mapping system.

In all three cases, the underlying problem is the same: the absence of an integrated view of the three factors. A brand that only monitors price may detect Scenario 2, but not 1 or 3. One that only reviews the Buy Box can identify who has control, but without connecting it to why they won it or what correction is necessary.

In operational terms, this involves looking at the triad collectively. The brand needs to know which SKU is being offered by whom, at what price, with what availability, and under what purchase condition it appears on the platform. Without that integrated reading, decisions arrive late or are made based on an incomplete part of the problem.

From Reactive Price Monitoring to Structural Channel Governance

The traditional model of price control in the digital channel has a recognisable pattern. Someone manually detects an anomaly, escalates it internally, a verification process opens, and by the time action is taken, the damage has been accumulating for days. Teams check prices by hand, conflicts explode when there is already noise, and the pricing strategy becomes disconnected from actual execution. This model has direct and indirect costs. In large structures, a margin erosion of just 1% can represent millions in losses.

Structural channel governance starts from a different logic. Instead of reacting to deviations that have already occurred, it builds a continuous visibility system that allows action before problems escalate.

Tools like flipflow’s Pricing & Seller Control module transform data chaos into actionable information.

This methodology allows brands to:

• Identify unauthorised sellers: Precisely locate actors eroding brand value in any marketplace worldwide.

• Monitor price policy compliance: Verify in real-time whether official distributors respect established agreements and detect deviations before they become a trend.

• Analyse Buy Box health: Understand what percentage of the time the brand owns the buy button and what factors (price, stock, or logistics) are causing the loss of this space.

• Optimise distribution: Decide which channels and sellers deserve more support based on their behaviour and respect for the brand’s strategy.

• Prevent international channel conflicts: A governance system detects early signals of parallel resale, cross-border inconsistencies, and hotspots of conflict, generating evidence ready for negotiation and enforcement.

This is the difference between reactive price monitoring and structural governance. Monitoring serves to know what is happening; governing serves to intervene with context, prioritise risks, and protect margin and brand positioning.

The Pricing & Seller Control module from flipflow is designed specifically to meet this need: to turn the price and seller ecosystem into a continuous governance system, by country and by channel. The results are concrete. In the case of Havaianas, implementing this model allowed for a 50% reduction in unauthorised sales, a 25% decrease in channel conflicts, and a 31% increase in DTC sales to marketplaces.

Conclusion — Real Control vs. The Illusion of Control

Every organisation selling on marketplaces and online retailers should ask themselves a key question: Do we have real visibility over who sells our products, under what conditions, and at what price in each channel and country?

If the answer depends on multiple sources, manual reviews, or delayed reports, control is more apparent than real.

Having an active price dashboard is useful. But if that dashboard only captures what has already happened, if it does not connect price with availability and the Buy Box, and if it does not distinguish between a one-off deviation and a structural channel dynamic, the visibility it offers is partial.

In 2026, digital governance requires answering four questions continuously and automatically: Who controls the Buy Box of strategic SKUs, whether active sellers are authorised, whether price policies are met, and whether there is stock consistency across channels and markets.

When those answers are available in real-time, management stops being reactive and becomes a channel control strategy. And that difference, in organisations with international scale, translates directly into protected margin, stabilised positioning, and a coherent distribution architecture.

Buy Box loss is rarely due to price alone. Usually, it is the visible symptom of a lack of governance. This is where platforms like Flipflow act as an intelligence layer capable of connecting price, stock, and visibility to transform scattered data into real digital channel control.

Want to see how the digital channel governance model works applied to your organisation? Discover flipflow’s Pricing & Seller Control module and request a personalised demo.

The post Beyond Price: Why you do not control your digital channel if you ignore the Buy Box and Stock appeared first on Flipflow.

TL;DR
Based on data from the first quarter of 2026 across 4 European markets (Spain, France, Italy, and the UK), we explore which anti-ageing cosmetics brands are investing most heavily in Retail Media, the extent to which they rely on this strategy to remain visible, and which are managing to build a solid presence without the need to pay.

In just a few years, Retail Media has evolved from an emerging bet into one of the pillars of the digital strategy for FMCG brands. Forecasts from WARC Media suggest that investment in this channel could reach €200 billion by 2027, consolidating a growth trend that is already transforming how brands compete for consumer attention.

Among the categories driving this investment most strongly are health and beauty, and especially facial skincare. Growing concern regarding skin ageing, prevention, sun protection, and the use of active ingredients has fuelled the rise of anti-ageing categories. At the same time, today’s consumer is much better informed: they compare prices, check reviews, analyse ingredients, and switch between perfumeries, supermarkets, marketplaces, and specialist shops before making a purchase decision.

In this scenario, gaining online visibility has become an increasingly competitive battle. For a cosmetics brand, appearing in the top search positions within Amazon, Primor, Boots, or an online pharmacy can be decisive in making it into the consumer’s basket… or falling off their radar entirely.

In the first article of this series, we analysed how organic visibility is distributed across the digital shelf in the anti-ageing category across 4 European countries. In this second analysis, we focus on the other side of that visibility: the side that is paid for.

What our Retail Media Analysis in Cosmetics Measures

The report analyses anti-ageing cosmetics brands in four European markets: Spain, France, Italy, and the United Kingdom.Our sample includes retailers such as Amazon, Primor, Douglas, Boots, and Easypara, alongside the following brands: Nivea, Eucerin, Neutrogena, Vichy, Olay, Garnier, L’Oréal Paris, Bella Aurora, Nuxe, Weleda, Cantabria Labs, and Sesderma.

It focuses on two main dimensions:

• Paid share: presence obtained through advertisements within the retailer or marketplace.
• Organic share: visibility achieved without direct investment in ads, linked to the natural positioning of the brand and its products.

The comparison between the two allows for the detection of three distinct situations:

• Brands that buy a significant portion of their visibility.
• Others that achieve good results with a solid organic base.
• Brands with an absence of paid investment in markets where their competitors are bidding.

This reading is particularly important in cosmetics, where consumers often search by need, benefit, or category rather than always for a specific brand.

The Weight of Investment

The first major conclusion of the report is that paid investment is not distributed equally across countries. Spain and the UK are the markets most concentrated in paid investment, while France and Italy present a more fragmented and accessible environment for medium-sized brands.

This means that entering and competing in Retail Media does not cost the same in every market. In the UK, advertising pressure is much more intense and the barrier to entry is higher. Conversely, in France and Italy, the competitive space is more evenly distributed, leaving more room to build a presence without the need for very high investment volumes.

In strategic terms, this necessitates segmenting investment by country. The same brand may need a strong presence in one market and a more tactical activation in another. The most common mistake would be applying the same level of advertising pressure across all countries without taking local competitor behaviour into account.

Nivea, the big spender

Nivea stands out clearly as the brand with the greatest weight in Retail Media, with a 39.86 global paid share. Its role is especially relevant because it combines scale, coverage, and sustained presence across different markets, something that allows it to defend positions in highly competitive environments.

The report also shows that Nivea adopts a flexible approach by country. In the UK, for example, it concentrates a very significant portion of its investment and reaches a strong dependency on paid visibility; in Italy, however, its profile is much more organic. This difference confirms that the strategy works based on local priorities, not a one-size-fits-all recipe for the whole of Europe.

For a cosmetics brand, this case illustrates an important idea: investing a lot is not enough on its own. Investment must respond to a specific need for defence, expansion, or demand capture. When done well, paid activity accelerates results; when done without local criteria, it only increases the cost of visibility.

Brands with a flexible mix

Eucerin, Neutrogena, Olay, and Garnier show more nuanced profiles, with different combinations of paid and organic depending on the country:

• Eucerin has a particularly high paid share in Spain and a relevant one in the UK, but is entirely organic in France. This suggests a selective strategy: the brand pushes where it needs to reinforce coverage and relies more on its natural strength where it can already stand alone.
• Neutrogena, for its part, has high levels of investment in Spain, France, and Italy, although it does not activate paid investment in the UK. Its case is interesting because it combines markets where it buys visibility intensely with others where it leaves all the weight to organic traction.
• Olay and Garnier operate with a more balanced logic between paid advertising and organic presence.

100% organic brands

At the other extreme are the brands that do not activate paid investment in any of the analysed markets. Cantabria Labs, L’Oréal Paris, and Sesderma appear with a paid share of zero across all four countries.

This does not automatically imply inefficiency. In some cases, it may reflect brand strength, good organic positioning, or a deliberate strategy not to compete in auctions. L’Oréal Paris in France is the clearest example: it achieves 100 per cent organic visibility without the need to bid.

That said, the absence of paid activity also carries a risk. In highly competitive markets, not participating in the auction can leave space for the competition to capture incremental demand, better defend certain terms, or intercept searches more easily.

Which Advertising Formats are Most Commonly Used?

By type of advertising, sponsored products clearly dominate: representing 58.76% of all investment. This is the format most oriented towards direct conversion, appearing when a consumer is already looking for a product in a retailer’s search engine. Behind this are sponsored display (23.08%) and sponsored brands (14.20%), while sponsored video barely reaches 3.96%.

This distribution confirms that the anti-ageing category prioritises strategies for capturing existing demand over brand building or discovery. Brands invest primarily where the consumer already has purchase intent, rather than in formats that generate that intent from scratch.

Amazon, Douglas and Primor Account for Almost All of the Activation

The breakdown by retailer also offers an interesting reading. Investment is distributed primarily among three platforms: Amazon, with 35.07%; Douglas, with 33.08%; and Primor, with 30.50%.

The distance between these three channels is small. Amazon maintains a central role due to its scale and international coverage, but it does not monopolise investment. Douglas and Primor appear as highly relevant spaces for activation in cosmetics, especially in markets where they carry more weight as a shopping destination.

Boots and Easypara have a marginal weight, below 1% each in the global breakdown analysed. This suggests that, during the period studied, brands prioritised environments with higher volume, greater coverage, or higher conversion capacity.

For marketing and sales teams, this data reinforces an important idea: paid visibility in European cosmetics requires a multi-retailer strategy. Concentrating all investment in a single channel can limit reach and leave gaps available for the competition.

Paid versus Organic Visibility: The Efficiency Analysis

Beyond how much each brand invests, the relevant question is how much visibility it gets in return for that investment. This relationship between paid spend share and total visibility is what reveals whether a brand is buying its presence or earning it.

Brands with a high dependency on advertising spend

These brands are those that present the greatest strategic risk. The most extreme case is Vichy in the UK: its visibility in that market is 100% paid. In other words, without advertising investment, Vichy would practically disappear from the British digital shelf. It has 40.15% visibility in that market, but no organic base to sustain it if the budget is cut.

Nivea in the UK combines leadership and vulnerability: it concentrates 68.42% of advertising spend in that market and 32.50% of its visibility depends on payment. Its position is solid, but it is clearly sustained by budget. Neutrogena in Italy presents a similar profile of questionable efficiency: with 20% of advertising spend, 60% of its traffic depends on investment.

Brands with high organic efficiency

Brands that show the opposite pattern. L’Oréal Paris in France records a 0% paid spend share and 100% organic visibility: it is the clearest case of natural authority in the analysed set. The brand achieves presence without investing in advertising, relying on brand recognition, the quality of its catalogue, and its positioning in retailer search engines.

Olay in the UK is another standout example: with only a 5.26% paid share, it maintains an organic visibility of 95.65%. Garnier in France also presents a very efficient mix, with 84.21% organic visibility and barely 8.33% advertising spend.

Blind spots: markets where room is left for competition

The analysis also identifies a series of situations where brands with an organic presence are not activating advertising in markets where the competition is doing so. This can be interpreted as efficiency in some cases, but in others, it represents a failure to defend positions or accelerate share.

The most striking case is L’Oréal Paris in the UK: despite its brand strength, it operates with 0% advertising spend in the most competitive market in the analysis, where other brands are investing intensely.

Nuxe and Sesderma in the UK have an organic presence but no advertising investment, which limits their ability to capture additional demand or protect their search terms against competitors who are bidding.

In Spain, both Sesderma and Cantabria Labs operate entirely organically. In the case of Cantabria Labs, which leads organic visibility in that market, the absence of advertising investment could be a coherent strategic choice. However, regarding Sesderma, with low organic visibility (2.34%), the lack of paid support makes it difficult to improve its position.

Conclusion: Visibility that is Bought and Visibility that is Built

The analysis of Retail Media in the anti-ageing category leaves two clear conclusions. One is that advertising investment is highly concentrated among a small number of brands, which creates a strong asymmetry between those who can buy visibility and those who rely mainly on their organic positioning. The second is that investing more does not always mean competing better: some of the brands with the highest spend show such a high dependency on payment that any budget adjustment can directly affect their digital presence.

In this context, efficiency is not solely about increasing investment, but about building a balanced strategy between organic visibility and paid activation. The brands that achieve the best results are those that work from a solid base—with an optimised catalogue, quality content, and good positioning within retailers—and use Retail Media selectively to reinforce, defend, or accelerate that presence. When advertising acts as a complement rather than the sole driver of visibility, growth is more sustainable and dependency on spend is reduced.

In a market where Retail Media investment will continue to grow strongly in Europe, understanding which part of visibility is earned and which is bought will be key to optimising budgets, prioritising markets, and competing profitably on the digital shelf.

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This article is part of a series based on the Flipflow Q1 2026 Cross-Market Benchmark, which analyses digital shelf positioning and Retail Media investment for 12 anti-ageing cosmetics brands in Spain, France, Italy, and the UK. Click here to download the full report.

The post Retail Media in European Cosmetics: Who Buys Visibility, and Who Earns It appeared first on Flipflow.

TL;DR
Data inconsistency in product listings across different retailers reduces conversion rates and causes returns to skyrocket. Standardising information through a single source of truth and Digital Shelf Intelligence tools like flipflow is essential for protecting profitability and brand consistency.

Introduction: When Every Retailer Tells a Different Version of your Product

In today’s e-commerce ecosystem, a brand’s presence is fragmented across dozens of platforms. The same product might be on sale on the brand’s official website, on Amazon, on digital department store sites like El Corte Inglés, or on specialised marketplaces. This ubiquity is a sales opportunity, but it also represents a logistical and communicative challenge of great proportions.

Imagine a consumer looking for a specific coffee machine. First, they check the price on a comparison site, then they visit the product listing on a major retailer’s site and, finally, they go to the manufacturer’s official website to confirm the exact measurements because they have limited space in their kitchen. If they read on the retailer’s site that the coffee machine is 30 cm high, but the official website states it is 35 cm, immediate doubt is created.

Doubt is the primary enemy of conversion in the digital environment. Faced with uncertainty, users often choose not to buy or to look for another brand that offers them consistent information. The problem lies in the fact that brands often send different data files to each seller, or the retailers themselves edit the information to fit their internal templates, losing the original accuracy along the way.

Inconsistent product content has measurable consequences. It affects conversion, organic positioning, return rates, and team efficiency. However, few organisations treat it as what it truly is: a structural problem that requires a proactive solution.

What Do we Mean by Inconsistent Product Content?

Product content is all the information that accompanies an item in its digital presentation: title, short and long descriptions, images, videos, technical specifications, categories, keywords, barcodes (EAN/GTIN), weight, dimensions, instructions for use, legal warnings, and any other attribute that the retailer or platform requires to list the product.

Inconsistent product content occurs when the attributes of the same item vary across different digital points of sale. This is not simply a typo in a description, but a structural discrepancy in the information that defines the product.

According to the standards of Google Merchant Center and the guides from Amazon Product Listings, high-quality content must be accurate, complete, and uniform. Inconsistency manifests in several ways:

• Contradictory technical attributes: Differences in dimensions, weight, manufacturing materials, or technical compatibilities.
• Disparate visual content: Using old photographs on some channels and modern renders on others. The absence of videos or 360º images on certain retailers while others have them also creates a sense of neglect.
• Misaligned titles and keywords: A product called “A1 Running Shoes” on one site and “Professional A1 Sports Footwear” on another makes rapid identification difficult for the user.
• Outdated stock and price information: Although pricing is often dynamic, a listing showing features that no longer exist in the current model generates false expectations.

In essence, inconsistency is the result of not having a “Single Source of Truth” for product data.

Why does this Problem Usually Go Unnoticed?

Many companies operate under a siloed structure. The marketing department creates the content, the sales team distributes it to retailers, and the IT department manages the databases. In this chain of command, the supervision of how the final product appears on each Digital Shelf often falls into a no-man’s-land.

There is also a scale factor. Manually reviewing 20 products across 3 retailers might seem manageable. Controlling 2,000 references across 15 channels, with variants, promotions, packaging changes, and frequent updates, is far more complex. The problem goes unnoticed because it requires constant monitoring that few teams can afford. Without Digital Shelf Intelligence tools, a brand would have to individually check every SKU on every retailer’s site to verify if the information is correct.

Furthermore, there is a false belief that, once the data feed has been sent to the retailer, the job is done. The reality is that marketplace algorithms and the internal processes of distributors can alter the display of data, truncate descriptions, or prioritise obsolete information that already resided in their previous databases.

Finally, content errors do not always trigger an immediate alert. An incomplete listing can remain active. One outdated image can stay published for months. And any incorrect attribute can reduce conversion without anyone directly linking it to the data problem.

This is why the cost accumulates bit by bit. There is a problem that exists and generates losses, but no one has a complete view of its magnitude.

The Hidden Cost of Not Standardising Product Listings Across Retailers

The lack of standardisation in product listings has commercial, operational, and reputational consequences. Some are visible in the short term; others affect brand performance progressively.

1. Lower conversion on the product page

The product listing is the moment of truth in e-commerce. It is where the buyer decides whether to add to the basket or leave the page. When a customer finds a listing with confusing descriptions, low-quality images, or information that does not allow them to understand if the product is right for them, they lose trust in the brand and abandon the purchase.

A technical specification sheet must be specific and contain relevant keywords, explain what the product is and what it is for without salesy phrases or exaggerations, and detail measurements, materials, and other concrete features.

An optimised and consistent product listing acts as a silent salesperson 24/7. If the information provided is fragmented, the salesperson is “mute” or, worse still, giving erroneous information. The loss of sales due to a lack of trust is the most direct and hardest cost to recover.

2. Poorer positioning in search engines and within the retailer

SEO is not limited to Google. Within Amazon or any marketplace, the algorithm rewards listings that are complete and follow their data standards. If a brand sends non-standardised data, it is likely that its products will not appear in search filters (for example, filters for colour, material, or size).

Google Merchant Center is very strict with data specifications. If listings are inconsistent or do not meet technical requirements, products can be rejected for Google Shopping campaigns, drastically reducing the brand’s visibility at the moment of highest purchase intent.

Something similar happens within marketplaces. Amazon, for example, uses listing information to understand product relevance. A poor title, uninformative bullet points, or incomplete attributes limit the algorithm’s ability to connect the product with relevant searches.

The consequence is clear: if content is not well normalised and optimised, the product can lose organic traffic both inside and outside the retailer.

3. Loss of brand consistency

Every touchpoint with the buyer is an opportunity to reinforce, or erode, brand perception. When a product is presented differently across each retailer, the brand message loses coherence. A buyer who has seen the product on one channel with a clear value proposition and arrives at another channel where the presentation is generic experiences dissonance, which affects trust and brand recognition.

Brands working on premium positioning are especially vulnerable: inconsistency in content communicates a lack of care, regardless of the actual quality of the product.

Standardisation helps protect the brand narrative. It allows you to define which information must remain stable across all channels and which elements can be adapted to the context of each retailer.

4. More returns, complaints, and customer frustration

A deficient product listing does not only affect conversion: it also drives up after-sales costs. When customers buy based on incorrect, incomplete, or unclear information, returns and complaints become inevitable. A description indicating a material different from the actual one, incorrect dimensions, a lack of assembly information, or images that do not faithfully reflect the colour of the product generate wrong expectations that end in frustration.

The economic impact is direct. Reverse logistics involves the cost of return transport, reconditioning the item and, in many cases, the loss of the profit margin. Furthermore, both retailers and brands must dedicate more time and resources to managing incidents and correcting errors manually. Added to this is a less immediate but equally relevant damage: negative reviews and low ratings, which affect product positioning and deteriorate consumer trust for months.

5. Operational inefficiency and increased burden on teams

Keeping content updated across multiple retailers without a centralised system is a task that consumes resources disproportionately. Every product update involves working retailer by retailer, format by format, often manually.

When information is incomplete or distributed across different systems, the result is always the same: slower processes and a higher operational burden. E-commerce or trade marketing teams end up spending hours on repetitive data maintenance tasks that could be invested in growth strategies and higher-value activities.

Product data standardisation allows for the reduction of this double work. It also facilitates the incorporation of new references, expansion into other marketplaces, and the management of bulk changes.

6. Regulatory or reputational risk in sensitive categories

In certain product categories—food, cosmetics, health, children’s products, electronics with specific technical requirements—listing information has legal implications. An outdated ingredient list, the absence of safety warnings, or failure to meet labelling requirements on a specific channel can lead to serious regulatory issues.

Google Merchant Center product data specifications state that published content must comply with Shopping Ads policies, landing page requirements, and currency and language requirements, among others. Each retailer adds its own demands. Without systematic control of published content, it is very difficult to guarantee compliance across all points of sale.

Standardisation ensures that critical and mandatory information is present on all channels, protecting the company from potential legal sanctions and reputational crises.

Standardising Does Not Mean Publishing Exactly the Same on All Retailers

One of the most common misunderstandings when talking about standardising product listings is thinking that it implies publishing identical content on all channels. In reality, standardising means something else: having a single, verified, and updated data source from which to adapt content to the specific requirements of each retailer.

Each platform has its own language and its own audience. For example:

• Amazon requires long titles loaded with keywords for its A9 algorithm.
• Instagram Shopping prioritises visual impact and short texts.
• Google Shopping needs very specific technical attributes in its feed (GTIN, brand, product category).
• Other retailers may require specific nomenclatures for sizes, colours, formats, or units of measurement.

Standardisation provides the foundation: correct, updated, and consistent data. The key lies in combining consistency and adaptation. Consistency to protect essential data and the brand. Adaptation to maximise visibility and conversion on each channel. Both are necessary and are not mutually exclusive.

Digital Shelf Intelligence as a Protective Shield

To combat inconsistency at scale, technology is the only viable solution. Knowing what content is actually being published on each retailer’s site is the first step to correcting any problem. And this is where Digital Shelf Intelligence platforms play a fundamental role.

These solutions allow for continuous monitoring of how products appear across different digital sales channels: what title the listing has, which images are being shown, if key attributes are present, if the content meets brand standards, or if it has undergone any unauthorised modification.

This real-time auditing capability transforms product content management from a reactive process—correcting when a problem arises via a complaint or a drop in sales—into a proactive one: detecting the deviation before it has a commercial impact.

Platforms like flipflow, specialised in Digital Shelf Intelligence, allow brands and manufacturers to have visibility over the actual state of their listings across multiple retailers simultaneously, identify where there are content gaps, and prioritise corrections based on potential impact on sales or brand compliance. Furthermore, these tools facilitate collaboration between e-commerce, trade marketing, sales, content, and customer service. Everyone works with a shared vision of the product’s actual status on the digital shelf.

The combination of a single source of data for well-managed products with a layer of continuous Digital Shelf monitoring closes the loop: you control both what is sent and what is actually published and how it evolves over time.

Conclusion: How to Start Correcting the Problem

Inconsistent product content across retailers rarely appears in any profit and loss report, but its economic impact is real and cumulative. It manifests in conversions that don’t happen, in positioning that degrades, in returns that increase, and in teams spending time on maintenance tasks instead of value creation.

Correcting it requires addressing the problem on two fronts. The first is internal: establishing a single source of truth for product data, with clear processes for updating and multi-channel distribution. The second is external: implementing verification mechanisms that allow you to know, at all times, what content is actually published at each digital point of sale.

For brands that want to start, the first practical steps are relatively concrete: audit the current state of content across the main retailers, identify the products with the highest turnover or margin where inconsistencies have the most impact, and define the minimum attributes that must be present and correct across all channels.

Because in e-commerce, every product listing is a direct touchpoint with the consumer. And when a brand loses control over how its catalogue is presented, it doesn’t just lose consistency: it loses sales, trust, and the ability to compete. In the end, the problem is often not with the product itself, but with everything that happens before the customer can correctly evaluate it.

The post Inconsistent Product Content: The Hidden Cost of Failing to Standardise Listings Across Retailers appeared first on Flipflow.

TL;DR
Amazon has taken a decisive step in its commitment to artificial intelligence applied to e-commerce. On 13 May 2026, the company unveiled Alexa for Shopping, an agentic assistant that replaces Rufus and, for the first time, can complete purchases on the user’s behalf even outside the Amazon marketplace.

From Rufus to Alexa for Shopping: What has Changed and Why

Rufus arrived in 2024 as Amazon’s AI shopping assistant. In two years, the tool was used by more than 300 million customers and helped generate nearly $12 billion in annualised incremental sales. Usage data was more than solid: Rufus users were 60% more likely to complete a purchase than those who did not use it.

However, the competitive landscape had changed. ChatGPT, Gemini and Perplexity had begun to position themselves as alternatives for searching and comparing products, threatening to become intermediaries between the consumer and shops. Faced with this pressure, Amazon has decided to take a qualitative leap. It has unified Rufus with Alexa+, its generative AI voice assistant, to create a shopping experience that is more integrated, more personalised and, above all, harder for the competition to replicate.

Rajiv Mehta, Amazon’s Vice President of Conversational Shopping, stated that the company realised that customers were starting shopping “missions” in one place and resuming them in another, as Rufus and Alexa did not share memory or context. The idea is that «the customer doesn’t have to think about where they started a conversation with Amazon», explained Mehta in an interview with GeekWire.

The result is Alexa for Shopping, available to US customers in the Amazon Shopping app, on the web and on Echo Show devices. Any user with an Amazon account can access it for free, without needing a Prime subscription or having any Alexa device.

Source: Meet Alexa for Shopping, your personalised, agentic AI assistant on Amazon – May 2026

How Alexa for Shopping Works: Key Capabilities

One of the first visible differences is the integration of the assistant directly into the Amazon search bar. Previously, users had to click on a chat bubble icon to open Rufus. Now, the icon with a cursive ‘A’ replaces Rufus across the entire app and website. And it allows questions to be asked in natural language without leaving the usual search flow.

These are the most relevant functionalities:

• Dynamic product comparisons: The assistant can select several items from search results and compare them side-by-side, analysing features, prices and ratings.
• Price history: Available for hundreds of millions of products, it allows users to check the price evolution over the last year directly from the product page.
• Alerts and automatic purchases: Users can ask the assistant to notify them when a product drops below a certain price or to buy it automatically at that moment, without needing to return to the app.
• Scheduled purchases: Through so-called Scheduled Actions, it is possible to set up recurring top-ups (detergent, pet food, vitamins) or ask the assistant to add items to the basket if certain conditions are met, such as the price falling below a threshold or at least two months having passed since the last order.
• Continuity between devices: What the user shares with Alexa on their Echo Show informs their shopping experience in the app, and vice versa. The assistant remembers previous conversations, preferences and habits, so there is no need to start from scratch in each session.
• Personalised shopping guides: For complex decisions such as buying a TV or preparing a gift, the assistant can generate a bespoke guide that compares options inside and outside Amazon.

Source: Meet Alexa for Shopping, your personalised, agentic AI assistant on Amazon – May 2026

Buy for Me: When the Assistant Completes the Purchase for You

The feature that has attracted the most attention, and also generated the most controversy, is Buy for Me. Thanks to this, Alexa for Shopping can locate a product on another retailer’s website and complete the purchase on the user’s behalf. To do this, it uses the payment and shipping details stored in the Amazon account.

Alongside Buy for Me, Amazon has enhanced Shop Direct, which allows products from third-party shops to be discovered from within the Amazon interface itself. This combination turns Alexa for Shopping into a shopping agent that operates beyond Amazon’s own catalogue, something unprecedented in the history of the platform.

The practical implication is significant. Users can ask the assistant to find a specific item, compare options from various retailers and authorise the purchase, all within the same conversation. For those who manage their regular shopping through Amazon, the time saving is evident.

The Competitive Context: Amazon vs the AI Giants

The launch of Alexa for Shopping responds to a clear dynamic: general AI assistants are entering the e-commerce field. OpenAI, Google and Perplexity have launched tools that allow products to be researched and, in some cases, purchases initiated through conversational interfaces.

Amazon has opted for a strategy different from that of its rivals. While OpenAI and Google work with open protocols that allow multiple brands to integrate with their agents, Amazon is building its own closed ecosystem, with its own data, catalogue and direct integration with its logistics infrastructure. CEO Andy Jassy summed it up clearly a few weeks ago in Amazon’s Q1 2026 Earnings Call:

“External agents lack personalisation, purchase history and reliable access to stock data and delivery times. That combination is, for now, difficult to match.”

At the same time, Amazon has actively blocked external agents from accessing its platform. In March 2026, a federal judge prevented Perplexity’s Comet browser from making purchases on Amazon on behalf of users, although the order was stayed pending appeal.

Source: Meet Alexa for Shopping, your personalised, agentic AI assistant on Amazon – May 2026

What this Means for Brands and Sellers

The impact of Alexa for Shopping on the Amazon seller ecosystem deserves attention. Amazon has integrated the assistant directly into the search bar. Furthermore, it shows AI-generated summaries at the top of results. All this alters the dynamics of one of the most valuable advertising spaces in digital commerce.

The sellers who invest in sponsored product advertising to appear in top positions may see those positions now competing with answers generated by the assistant. In parallel, the Buy for Me feature has generated tension with some external retailers. They point out they have not authorised Amazon to complete purchases on their websites on behalf of their customers. This raises certain questions about the ownership of the customer relationship.

E-commerce analyst Juozas Kaziukėnas has described the launch as “a graduation party for Rufus“: the beta label disappears and the assistant begins operating under the Alexa brand, with all the recognition that implies. According to the analyst himself, consumer familiarity with the Alexa name is far superior to that of Rufus. This should accelerate the assistant’s adoption.

Privacy and Control: What the User Needs to Know

Alexa for Shopping works because it accumulates context: purchase history, previous conversations with Alexa, stated preferences and browsing habits. This accumulation of data is what allows the assistant to be genuinely useful, but it also raises legitimate questions about privacy.

Amazon has enabled an Alexa privacy panel where users can review and manage what information the assistant holds. This includes stored voice recordings and preferences. Any user can check what the assistant knows about them with a simple question, and update or delete that information from the same panel.

Conclusion: E-commerce Enters the Era of the Agent

Alexa for Shopping represents a shift in model for how Amazon conceives the relationship between consumer and shop. For decades, the online shopping process has followed the same pattern: the user searches, filters, compares and decides. With an agentic assistant capable of tracking prices, remembering preferences and executing purchases autonomously, a growing part of that process passes into the hands of AI.

The challenge for Amazon lies in winning consumer trust for this level of delegation. For sellers and brands, it lies in understanding how to optimise their presence in an environment where the first point of contact could be a response generated by an assistant, rather than a traditional product page. E-commerce has been evolving for years. With shopping agents, that evolution has just entered a new phase.

The post Goodbye Rufus: Amazon Launches Alexa for Shopping, its New AI Shopping Assistant appeared first on Flipflow.

TL;DR
Our analysis shows that leadership in the anti-ageing cosmetics Digital Shelf in Europe is local and fragmented: no single brand consistently dominates Spain, France, Italy, and the United Kingdom. This study also reveals that small improvements in digital execution can lead to major differences in visibility and competitiveness across retailers and marketplaces.

The European cosmetics market has been growing steadily for years. The sector reached €104 billion in retail sales in Europe in 2024, according to the Market Performance 2024 report by Cosmetics Europe, surpassing the symbolic €100 billion barrier for the first time and consolidating Europe as the world’s second-largest market, behind only the United States.

Source: Economic value of the cosmetics and personal care industry – Cosmetics Europe

Within this industry, the anti-ageing category is one of the most dynamic: it combines a growing structural demand, consumers with a high willingness to spend, and increasingly intense competition in both physical and digital channels.

The rise of e-commerce has profoundly transformed how cosmetic brands compete for consumer attention. Today, much of the battle for visibility is fought in the search results of platforms like Amazon, on the digital shelves of major specialist chains, and in retailers’ internal search engines. This space is known as the Digital Shelf, and monitoring it has become a strategic priority for any brand wanting to grow in Europe.

At flipflow, we have analysed the behaviour of 12 anti-ageing cosmetic brands across four markets—Spain, France, Italy, and the United Kingdom—during the first quarter of 2026, with data extracted from Amazon, Boots, Easypara, Douglas, and Primor. These are the main findings from the digital shelf visibility analysis.

What is the Visibility Index on the Digital Shelf and Why it Matters

The visibility index measures the presence and competitiveness of a brand’s products on e-commerce platforms and other digital channels. In practical terms, it reflects how often and in what position a brand’s products appear when a consumer searches for a term relevant to the category.

In the anti-ageing analysis, market-specific search terms were used: antiedad in Spain, anti-âge in France, antiage in Italy, and anti aging in the United Kingdom. The average **visibility index** stands **at around 8.3% across the four countries**, but what really stands out is the enormous dispersion between brands: some exceed 40% visibility in a specific market while others are close to 0%.

Leadership in Europe is lLocal: There is no Pan-European Champion

One of the most striking findings of the analysis is that no brand is capable of consistently dominating the four European markets analysed. Leadership is markedly local and changes from country to country.

Spain: local leadership and brands with room to grow

In Spain, the average visibility index in the anti-ageing category is 8.33%. The market shows clear leadership from Cantabria Labs, which reaches 22.17% visibility and is the best-positioned brand for the search “antiedad”. Behind it is Neutrogena, with 15.79%, followed by Bella Aurora, with 12.76%. These three brands are clearly above the national average and capture a large part of the available visibility.

At the bottom are Vichy, Weleda, and Sesderma, with lower levels, which leaves room to improve presence in strategic categories and strengthen the defence of key terms.

The most interesting fact is that the Spanish market combines a very strong local leader with a solid international competitor, something that opens the door to more aggressive strategies for optimising content, assortment, and presence with retailers. For a cosmetics brand, this means that just being present isn’t enough. You have to work on the product page, keyword relevance, catalogue consistency, and availability to gain sustained positions in high-intent searches.

France: a more balanced and open market

France presents a more balanced picture. The average index is also 8.33, but leadership is more distributed: Bella Aurora leads the ranking with 17.20, followed by Weleda with 13.70 and Nuxe with 10.74.

Unlike other markets, here there is no absolute dominance by a single brand. This greater dispersion means that small operational improvements can more easily move the needle on visibility. At the bottom, Cantabria Labs and Sesderma record no visibility, while Garnier and Olay are in more modest positions.

France is, therefore, a market where digital execution carries a lot of weight. The strategic takeaway is clear: if a brand improves its positioning, optimises its content, and better manages its priority terms, it can gain presence quickly. It is one of the markets with the most room for redistributing positions. There is no absolute dominance, and that favours brands capable of optimising their presence at each retailer.

Italy: high concentration and very marked leadership

Italy is the country where concentration is most evident. The average visibility index is 8.38, but Bella Aurora reaches 37.28, a figure far superior to the rest of the competitors. Neutrogena, with 9.47, and Eucerin, with 8.01, form the chasing pack, far behind the leading brand.

This data shows a market with strong asymmetry. When a brand dominates by such a margin, others are not just competing for visibility, but for the very possibility of getting on the consumer’s radar. At the opposite extreme, Sesderma and Cantabria Labs record no visibility, showing clear space to build presence from scratch or to recover lost positions.

This scenario is particularly useful for understanding how the Digital Shelf works in highly competitive categories: if the leading brand has very fine-tuned execution, the rest need a much more consistent strategy to get close. Here, the challenge is not just to grow, but to break the barrier separating the leaders from the chasing group. Italy also proves that the Digital Shelf must be analysed market by market, because the global average can hide wide competitive differences.

United Kingdom: the most concentrated market

The United Kingdom is the most concentrated market of the four analysed. The average index remains at 8.33, but Vichy leads with 40.15, followed far behind by Nivea at 10.25 and Eucerin at 9.94.

Our reading is very clear: Vichy holds an almost hegemonic position in this market, while other brands trail far behind. The concentration around Vichy is so high that the real competitive space seems to be on the second tier, where several brands are grouped between 5% and 10% visibility. Additionally, Cantabria Labs and Bella Aurora record no visibility, and Weleda remains at a low level, confirming that the UK requires very fine-tuned execution to compete.

This environment is particularly relevant for any cosmetic brand working on digital internationalisation. The UK concentrates a lot of competitive pressure and penalises a lack of consistency in content, assortment, or positioning more than other markets. When a brand dominates here, it’s usually because its digital presence is very well built and sustained.

European Ranking: Bella Aurora and Vichy Lead, but with Geographical Dependence

By consolidating the results from the four countries, Bella Aurora ranks as the brand with the highest global average visibility, at 16.81%. Its position is mainly supported by Italy, where it reaches 37.28%, and France, where it leads with 17.20%. It also maintains a solid presence in Spain, at 12.76%.

However, its absence in the United Kingdom limits its consolidation as a pan-European leader. The case reflects a brand that is very strong in Southern Europe but has little to no presence in the British market within the sample analysed.

The second global position goes to Vichy, with an average visibility of 14.90%. Its result is heavily influenced by the United Kingdom, where it reaches 40.15%. In Spain, however, it drops to 4.36%. This difference shows a very marked geographical dependency.

Third place is occupied by Neutrogena, with a global average of 10.22%. The brand stands out especially in Spain, at 15.79%, and maintains a presence in all markets, although it loses strength in the UK.

Eucerin appears as one of the most consistent brands, with a global average of 8.81%. Its visibility ranges between 7.66% in Spain and 9.94% in the UK, with a volatility of just 2.28 points. This stability indicates a homogeneous execution, albeit without clear leadership in any country.

Behind them are L’Oréal Paris at 7.49%, Nivea at 7.41%, Nuxe at 7.00%, Weleda at 6.91%, Olay at 6.76%, Garnier at 5.78%, Cantabria Labs at 5.54%, and Sesderma at 2.40%.

Volatility: The Data that Reveals each Brand’s True Consistency

Average visibility helps rank the market, but volatility allows for an understanding of each brand’s consistency across countries. A brand may have a high average thanks to a single very strong market, while another may maintain a more stable presence without major peaks.

Bella Aurora shows a volatility of 37.28 points, moving from 37.28% in Italy to 0.00% in the United Kingdom. Vichy shows a similar pattern, with a difference of 35.79 points between the UK and Spain.

Cantabria Labs also reflects a strong local dependency: it reaches 22.17% in Spain but records no visibility in France, Italy, or the UK. Its volatility is 22.17 points.

At the opposite end are brands with a much more uniform presence. Olay is the most stable, with only a 1.06-point difference between its best and worst markets. Garnier also shows low dispersion, with 1.21 points, and Eucerin maintains low volatility of 2.28 points.

This reading is key for marketing, sales, and e-commerce teams. A high average visibility might seem positive, but if it depends on a single country, the competitive risk is higher. A stable, albeit more modest, presence can provide a more solid base for sustained growth.

What Cosmetic Brands can Learn from this Analysis

The anti-ageing cosmetics Digital Shelf analysis offers several useful ideas for brands selling on European digital retailers and marketplaces.

• First, leadership is local. No brand consistently dominates the four markets analysed. Spain, France, Italy, and the UK have their own dynamics, with different leaders and varying levels of concentration.
• Second, visibility can change significantly with small adjustments. In more balanced markets, like France, an improvement in content, availability, prices, reviews, or assortment can help climb rankings quickly.
• Third, consistency matters. Brands like Eucerin, Olay, or Garnier don’t always lead, but they maintain a more stable presence across countries. This regularity can be valuable for building a European strategy that is less dependent on a single market.
• Fourth, absences also speak volumes. Brands with a good position in one country may not appear in other relevant markets. Detecting these gaps allows for the prioritisation of commercial actions, review of retailer agreements, and adaptation of the catalogue strategy.

Conclusion: The European Digital Shelf is a Fragmented Territory with Real Opportunities

The anti-ageing market on the European digital shelf presents fragmented leadership, with no clear winner dominating all four markets. Each country has its own competitive dynamics, and visibility tends to concentrate on a few players per market, even though the national average is stable at around 8.3%.

For brands, this has direct implications: a good position in one country does not automatically transfer to the rest. Small differences in digital execution—catalogue quality, product page optimisation, assortment management by retailer—can translate into very wide visibility gaps on the shelf.

In such an environment, monitorising the Digital Shelf is not just a benchmarking exercise: it is a competitive lever. Brands that know their position and those of their competitors in real-time at each retailer and in each market are better placed to make quick and efficient decisions.

In the second article of this series, we will analyse the role of Retail Media (paid advertising within the retailers themselves) and which brands are buying visibility, which are winning it organically, and which are leaving spaces open to the competition.

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This article is part of a series based on Flipflow’s Q1 2026 Cross-Market Benchmark, which analyses digital shelf positioning and Retail Media investment for 12 anti-ageing cosmetic brands in Spain, France, Italy, and the United Kingdom. Click here to download the full report.

The post Who Leads the Digital Shelf in Anti-Ageing Cosmetics in Europe appeared first on Flipflow.

TL;DR
Carrefour has sealed a partnership with Vusion to deploy large-scale smart store solutions in France until 2030. The agreement reinforces its commitment to more efficient, connected, and data-driven operations.

Carrefour has taken a decisive step in the transformation of its physical stores with a strategic alliance with Vusion to deploy large-scale smart store solutions across its hypermarkets and supermarkets in France until 2030. The agreement places Carrefour among the major European retailers most clearly accelerating point-of-sale digitalisation.

The initiative addresses an increasingly visible need in retail: to gain operational efficiency without losing agility or service quality. In this context, Vusion’s technology serves as a support for updating prices, monitoring shelves, and improving in-store execution through data and automation.

Carrefour and Vusion, a Strategic Alliance

What have both companies announced?

Carrefour and Vusion have announced a collaboration to deploy smart store solutions across the group’s store network in France. The project includes digital shelf labels, connected rails, and AI vision-based systems, with the aim of making daily store operations smarter.

The idea is simple: to provide stores with tools that allow for faster and more precise action. This affects key processes such as price updates, stock control, replenishment, and shelf monitoring.

Why is it relevant for Carrefour?

This move is part of a broader transformation within the group. Carrefour seeks to adapt its commercial network to an environment where the physical store must be more agile, connected, and efficient.

The partnership is not limited to a one-off trial. Its value lies in the deployment at scale, which is particularly relevant in an environment where operational consistency and reaction speed make the difference. For Carrefour, this means moving towards a store model better prepared to meet consumer and business demands.

Alexandre Bompard, Chairman and CEO of Carrefour, stated:

“The digitalisation of our shelves forms the essential foundation for deploying our vision of modern commerce, serving competitiveness, the quality of working life for our employees, and customer satisfaction.”

What Vusion’s Technology Provides

Digital shelf labels and the connected store

One of the pillars of the solution is Digital Shelf Labels, which allow prices and content to be updated centrally and in real-time. This reduces errors, improves information consistency, and streamlines the management of campaigns or promotional changes.

Furthermore, these tools help better integrate the physical store with digital commerce logic. In an environment where information must be immediate and accurate, point-of-sale connectivity gains weight as a competitive advantage.

Automation and operational improvement

Vusion’s proposal also incorporates computer vision and artificial intelligence to monitor shelf status and detect incidents. This can help locate out-of-stocks, placement errors, or commercial execution issues more quickly.

The impact is not just technological. It is also operational. Automation frees up staff time for higher-value tasks and improves the store’s responsiveness. Thierry Gadou, Chairman and CEO of Vusion, commented:

“With Carrefour, we share the same vision of a modern store at the heart of tomorrow’s omnichannel commerce. We are going to make this vision a reality in the coming years. Following Walmart’s decision to deploy EdgeSense in all its US stores, Carrefour becomes the first major European retailer to deploy Vusion’s latest-generation platform at scale. The goal is threefold: to improve the banner’s performance and the satisfaction of both customers and employees.”

Source: Carrefour and Vusion join forces to deploy the smart store at scale – February 2026

Vusion, Awarded for its Innovation at Retail Technology Show 2026

The partnership with Carrefour comes at a particularly favourable time for Vusion. The company was recognised as the winner at the Retail Technology Show’s 2026 Innovation Awards for its Connected Store solution.

This award reinforces the credibility of its proposal and confirms that its technology is not only innovative but also applicable at scale. In a sector where scalability and interoperability are key, this recognition carries significant weight.

For Carrefour, this award serves as external validation of the chosen path. It is not just investing in an advanced solution, but in a technological partner already distinguished for its ability to connect the physical store with smarter data and processes.

The combination of a major retail banner and award-winning technology reinforces the strategic scope of the project. The message is clear: the modernisation of the physical store is a reality in full deployment.

What does this Move Mean for the Future of Retail?

1. The physical store as a smart space

The partnership between Carrefour and Vusion reflects a profound evolution in the role of the physical store. Establishments are no longer merely places of sale, but are becoming connected spaces capable of generating data and improving decision-making in real time.

This change fits with a broader trend in European retail, where artificial intelligence, automation, and data analysis are gaining prominence in point-of-sale management. Chains that move in this direction will be better positioned to optimise resources and respond quickly to consumer needs.

2. Impact on efficiency and shopping experience

In practical terms, a smarter store allows for improved price updates, product availability, and the quality of commercial execution. This affects both internal efficiency and the customer experience, which finds a more precise and orderly environment.

It also opens the door to future applications related to retail media, in-store behaviour analysis, and greater integration between physical and digital channels. In this sense, Carrefour is moving towards a more data-driven distribution model better prepared for the future.

3. A move with vision

Carrefour thus establishes itself as one of the major European retailers most firmly committing to large-scale physical store digitalisation. Vusion’s backing gives solidity to a proposal that combines innovation, scalability, and real-world application in daily store operations.

The direction is set: technology is no longer valued just for its novelty, but for its ability to solve specific problems and improve key business processes. In this field, the partnership between Carrefour and Vusion marks a significant step for European retail.

The post Carrefour Scales Smart Store Rollout with Vusion appeared first on Flipflow.

TL;DR
An opportunity map by postcode allows for identifying where untapped commercial potential exists. It is used to prioritise territories, adjust assortments, guide sales visits, and distribute budgets using objective criteria. The result is more precise decision-making and a better return on commercial effort.

In modern retail, making commercial decisions based on national averages is a path to inefficiency. Two postcodes can share similar demographics on paper and behave radically differently in terms of sales, brand penetration, or response to promotions. The relevant question for any sales manager, trade marketing, or category manager is not what is happening at a national level, but exactly where it is happening and why.

Territorial intelligence answers that question. And its central tool is the opportunity map by postcode: an analytical visualisation that represents the commercial potential of each area and allows it to be compared with current business performance. The utility of this type of analysis lies in answering very specific questions: Where is there the most 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?

Geomarketing has been answering these types of questions for decades. Thanks to advances in geocoding, most large organisations in the sector have begun combining location data with demographic and behavioural analysis to create more precise and profitable strategies. What has changed in recent years is the accessibility of these tools and the ability to keep the analysis continuously updated, not as a snapshot, but as an always-on system.

This guide describes the complete process for building an opportunity map by postcode, with each step detailed and action-oriented, followed by the most relevant use cases in the retail environment.

How to Build an Opportunity Map by Postcode Step by Step

Step 1. Define the business objective

Before touching any data, you must clearly establish which decision the map is intended to support. An opportunity map can have many uses, but its design changes according to the objective.

Some common objectives are:

• Increase sales in territories with low penetration.
• Detect postcodes with potential for opening new points of sale.
• Prioritise sales team visits.
• Adapt the assortment by area.
• Improve the efficiency of local campaigns.
• Identify areas where the competition has a greater presence.
• Reduce risks of delisting in certain territories.
• Adjust prices according to local market conditions.

Defining the objective from the start determines which data is essential, which variables enter the opportunity score, and how the results are interpreted.

If the objective is not clear, the map ends up being just a pretty visualisation. Conversely, when the goal is well-defined, every piece of data you add to the map will have a specific function and the analysis will be much more actionable.

Step 2. Choose the appropriate territorial unit

The postcode is the most common unit because it combines sufficient granularity with data availability. However, depending on the type of business and the specific objective, it may be more useful to work with municipalities, census tracts, provinces, or even catchment areas defined by travel time.

For FMCG retail and physical store distribution analysis, the postcode offers the right balance: it is small enough to detect relevant differences between urban areas or between neighbourhoods in the same city, and large enough for external statistical data (income, demographics, population density) to be reliable and comparable.

The choice of territorial unit also affects the scale of the analysis. A postcode-level map in a large city may have hundreds of units; a provincial-level one may have fifty. The territorial unit should help you make an actionable decision. The key is to use a unit that is stable, comparable, and easy for teams to activate.

Step 3. Cross-reference internal and external data

This is the step where the map acquires real analytical depth. In this step, you must cross-reference your own sales data with external information that contextualises current performance.

Common internal data:

• Sales by point of sale or territory, normalised by postcode.
• Numeric distribution (number of active points over the total available).
• Assortment by store and by area.
• History of sales visits and results.

Relevant external data:

• Socio-demographic data by postcode: average income, household size, age pyramid, education level.
• Density and typology of points of sale in the area.
• Presence and assortment of competitors by territory.
• Category consumption data or panel data aggregated by region.

You can also incorporate assortment and pricing intelligence data. This allows you to analyse whether the available assortment in an area matches local demand, whether prices are aligned with the competitive environment, or if there are relevant differences between territories.

Retailers that collect the postcode at the point of purchase or through loyalty programmes have a significant advantage: they can directly map the geographic concentration of their clientele and cross-reference it with census demographic data to understand what type of consumer buys from them, where they live, and where the brand is not reaching.

Territorial intelligence platforms automate this cross-referencing, normalising variables to the postcode level and generating visualisations that are updated periodically. This allows the opportunity map to stop being a one-off analysis and become a recurring operational tool.

Step 4. Create an opportunity score

With the data cross-referenced, the next step is to build a composite metric that summarises the potential of each territory into a single comparable value: the opportunity score.

This score usually combines several dimensions with different weights according to the objective:

• Market potential: estimated category size in that area, based on consumption data, demographics, and density of points of sale.
• Current performance: own sales, active distribution, or estimated share relative to potential.
• Gap: difference between estimated potential and current performance. The larger the gap, the greater the theoretical opportunity.
• Competitor presence: level of competitor saturation in the area, which modulates the ease of capturing the opportunity.

The essential part is to normalise the variables to be able to compare them. If one variable is in pounds, another in percentage, and another in number of inhabitants, it is advisable to transform them to a common scale, for example from 0 to 100. The resulting score converts multi-variable complexity into a simple number that allows territories to be ranked from highest to lowest opportunity.

Heat maps by postcode are the most intuitive visual representation of this score: more intense colours indicate the areas where attention should be concentrated.

Step 5. Segment the territories

A continuous opportunity score is useful for ranking, but segmenting territories into groups facilitates rapid, consistent operational decision-making. Common segments combine two axes: opportunity level (high/medium/low) and current performance (high/medium/low).

A typical segmentation can generate four action groups:

• Priority growth territories: high opportunity, low current performance. These are the ones that justify a greater investment of commercial resources.
• Consolidation territories: high opportunity, performance already good. The goal is to maintain and defend the position.
• Monitoring territories: moderate opportunity with a tendency to improve or worsen. They require tracking but no immediate action.
• Low priority territories: little opportunity and low performance. They only deserve attention if there are changes in the competitive or demographic context.

This segmentation should be reviewed periodically, as territories can migrate from one group to another due to changes in distribution, competitive activity, or the demographic composition of the area.

This approach avoids applying a uniform strategy to all territories. In retail, local differences influence demand, competition, and profitability. Segmenting allows actions to be adapted according to the real behavior of each zone.

Step 6. Prioritise by impact and feasibility

The final layer of the map must answer a very practical question: which areas deserve to be acted upon first. This turns the map into an action plan. Not all high-opportunity territories are equally feasible to activate with available resources. Final prioritisation combines the opportunity score with operational criteria:

• Estimated impact: how much incremental volume or margin the activation of that territory can generate.
• Feasibility of activation: geographic distance from sales teams, available logistical coverage, existing relationships with key operators in that area.
• Cost of activation: necessary investment in visits, trade actions, point-of-sale materials, or assortment adjustments.

The combination of impact and feasibility allows for the construction of a prioritisation matrix that guides the team toward territories where the return on effort is highest. High-impact, high-feasibility territories are the first on the agenda; high-impact but low-feasibility ones move to a medium-term plan.

The map must be updated periodically. Opportunities change due to new openings, price variations, competitor actions, population changes, seasonality, campaigns, and evolving shopping habits. A monthly or quarterly review is usually useful for retail teams with high commercial activity.

Use Cases in Retail

The utility of an opportunity map is measured by the decisions it allows you to make, not by the sophistication of the analysis. Below are the five most common use cases in retail and FMCG organisations. Each one starts from the same principle: converting territorial data into concrete actions with a measurable impact on the business.

Detecting zones with assortment gaps

One of the most direct uses of the territorial opportunity map is the identification of areas where the active assortment in store does not reflect the category’s sales potential. A brand may have 27 references available at points of sale in one postcode and only 15 in another with a similar socio-demographic profile. That difference has a measurable cost in lost sales.

Territorial intelligence allows you to visualise the real assortment by store and by postcode, detect inconsistencies relative to the area average or to what is distributed in comparable territories, and build a structured argument to negotiate with operators for assortment expansion where demand is backed by data. Instead of arriving at the shelf with perceptions, the sales team arrives with geolocated evidence.

Organising sales visits by impact

Sales teams always have more territories to cover than resources allow. Without data-based prioritisation criteria, route planning and visits tend to replicate previous habits or respond to specific emergencies, rather than maximising business impact.

The opportunity map allows for assigning each territory, and by extension each point of sale, a priority value based on the gap between potential and actual performance. Sales teams stop acting by inertia and start concentrating time where the return is highest. This improves commercial productivity and also helps justify route decisions with objective data.

Prioritising local campaigns

Local activation campaigns have a higher return when designed for territories where untapped demand exists. The opportunity map allows you to identify those postcodes and inform decisions on where to concentrate investment in local advertising, point-of-sale promotions, events, or sampling actions. It also allows for detecting areas similar to those already performing well. This “territorial lookalike” logic helps expand campaigns with less risk and better budget use.

By cross-referencing the opportunity score with income and demographic profile data by postcode, it is also possible to adapt the message and offer to the characteristics of each area, increasing the relevance of the action and improving conversion. Many marketing apps and platforms already allow for showing differentiated content based on user location, making territorial segmentation directly impactful on digital channels as well.

Reallocating trade marketing resources

Trade marketing budgets are rarely distributed optimally from a territorial point of view. They are often assigned following historical sales volume (reinforcing where sales are already good) instead of being oriented toward where the greatest potential for incremental growth exists.

The opportunity map reverses that logic. High-potential, low-performance territories are, by definition, those with the greatest capacity to respond to a trade investment. Reallocating resources such as point-of-sale materials, promoter staff, or activation budgets toward those territories improves the overall trade marketing ROI and accelerates share capture in under-penetrated zones.

Identifying territories with risk of delisting or cannibalisation

The opportunity map is not only for finding where to grow: it also helps detect where there is a risk of losing position. A territory where sales drop below estimated potential in a sustained manner may be a signal that a competitor is gaining shelf space, that a silent delisting is occurring, or that there is an availability problem that aggregate reports are not capturing.

By monitoring the real assortment by postcode and cross-referencing it with sales signals, it is possible to detect delistings the moment they happen and act before they become permanent. Similarly, it allows for identifying cannibalisation situations between own references in the same territory, where the introduction of a new SKU is reducing sales of another without generating net incremental volume. Cannibalisation can also occur between physical and online channels. If certain postcodes show strong digital growth and a store decline, territorial analysis can help understand if it’s replacement, complementarity, or a change in customer behavior.

From Postcode to Commercial Action

A well-constructed opportunity map by postcode transforms the way commercial and trade marketing teams make decisions about the territory. It stops being an isolated analytical exercise and becomes the starting point for data-driven planning: which areas to activate first, where to adjust assortment, how to distribute trade budget, or when to anticipate a distribution problem before it affects results.

Building the map requires combining internal data with external information, normalised at the postcode level, and translating it into an actionable opportunity score. Territorial intelligence tools like flipflow automate much of that process, making map maintenance continuous rather than dependent on one-off analytical projects.

The remaining question for any retail organisation is not whether territorial analysis is relevant—it is—but whether the level of granularity and updating used today is sufficient for precise decision-making. In markets where competition operates at the postcode level and consumers expect an offer adapted to their environment, working with national or regional data no longer provides the same advantage as working with data from each territory.

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TL;DR
MediaMarktSaturn has taken a new step in its retail media strategy with the expansion of its In-Store offering to eight European markets. The company is thus strengthening a business line that is gaining weight within the retail sector. This line is increasingly interesting to brands and advertisers due to its ability to make an impact at the point of purchase.

The latest development comes via a technological infrastructure designed to operate campaigns programmatically and centrally, with the support of One Tech Group. In practice, this allows for the scaling of in-store advertising activations. It also allows for better coordination of local and multinational campaigns within a commercial network that already has a highly significant presence in Europe.

An Expansion with European Reach

The expansion incorporates new markets into a network that was already operating in Germany and Spain, and which now adds Austria, Switzerland, Turkey, Belgium, Luxembourg and Hungary. Overall, coverage stands at around 738 stores and more than 53,000 screens, with a potential audience of some 68 million weekly contacts, according to the sources consulted.

This move places MediaMarktSaturn in a stronger position within the European Retail Media ecosystem. The company gains geographical scale and also reinforces the consistency of its commercial proposal. This is key in a market where advertisers seek measurable, segmentable and easy-to-activate solutions across several countries.

How its In-Store Model Works

MediaMarktSaturn’s proposal is based on advertising at the point of sale, an especially valuable environment because it connects brand communication with the moment when the consumer is closest to making a decision. In-store screens, digital inventory and programmatic management are all part of the same offering designed to turn the physical space into a more effective advertising channel.

In this context, the value lies not just in the presence of adverts, but in the possibility of activating relevant messages in an environment with high purchase intent, as explained by Boris Prondzinski, Managing Director at MediaMarktSaturn Retail Media & Partner Marketing:

“By expanding our in-store retail media offering across Europe, we are making reach at the Point of Sale predictable and actionable for advertisers across national borders.”

For categories such as consumer electronics, technology, accessories or small domestic appliances, in-store retail media allows for accompanying the shopper at a very advanced stage of the decision-making process.

Furthermore, centralised technological management makes it easier for advertisers to work with greater speed and efficiency. These types of solutions typically attract both brands that already invest in Retail Media and manufacturers looking for a more precise way to connect with specific audiences within a major European distributor.

Source: Consumer electronics retailer MediaMarktSaturn taps One Tech Group retail media platform – October 2025

The Role of One Tech Group

The alliance with One Tech Group is an important part of the announcement. Thanks to this collaboration, MediaMarktSaturn can offer a more homogeneous infrastructure for booking, managing and measuring campaigns across different markets, something essential when the goal is to operate with a pan-European logic. Boris Prondzinski notes:

“Together with the One Tech Group, we are thereby strengthening a channel that reaches consumers directly in the shopping environment and can increasingly be integrated into data-driven omnichannel campaigns. In this way, we are creating a unique platform for brands that want to reach their target audiences in physical stores across Europe.”

This type of technological integration often makes the difference between an isolated advertising network and a platform with real capacity for growth. In MediaMarktSaturn’s case, programmatic advertising provides flexibility, better operational control and more possibilities for adaptation to different formats and campaign objectives.

Daniel Siegmund, founder and CEO of One Tech Group, states:

«This expansion gives advertisers access to one of the networks with the widest reach in Europe. The combination of high frequency, targeted audience engagement and international reach makes this inventory an exceptionally attractive component for both local and pan-European campaigns.».

What it Means for Brands and Advertisers

MediaMarktSaturn’s expansion comes at a time when European retail media continues to accelerate. Brands are increasingly looking for channels with their own data, clearer measurement and a direct link to sales. In this scenario, the physical store is once again taking a central role within commercial activation strategies.

The interest of this news also lies in the combination of reach, context and precision. An advert placed at the point of sale does not compete on equal terms with a generic awareness campaign. It is inserted into an environment where the customer is already exploring, comparing or deciding what to buy. This increases the potential for conversion and makes advertising investment more interesting.

MediaMarktSaturn also benefits from its specialisation in electronics, a category with high promotional frequency and great sensitivity to price, availability and contextual recommendation. For many brands, this network can become an especially useful environment for driving launches, seasonal promotions or campaigns linked to moments of high demand.

The Evolution of its Strategy

The current expansion does not appear in isolation. MediaMarktSaturn has been building a more complete Retail Media offering for some time, with launches such as Sponsored Product Ads and Sponsored Brand Ads, in addition to its progress in in-store solutions. This evolution confirms that the company is working on a phased strategy, with different formats to cover various stages of the funnel.

It is also worth remembering that the company had already strengthened its commitment to the channel through previous technological agreements, such as its collaboration with Criteo, which helped lay the foundations for part of its advertising infrastructure. This base makes it easier for it to now take a more ambitious step with a wider and better-connected network across markets.

In 2026, interest in Retail Media is not limited to online campaigns or sponsored spaces in e-commerce. The physical point of sale is gaining prominence because it combines proximity, context and conversion capacity. MediaMarktSaturn is taking advantage of precisely this trend to consolidate a more robust and commercially attractive proposal.

A Market that Continues to Mature

MediaMarktSaturn’s expansion also helps us understand where the sector is heading. Retail Media in Europe is ceasing to be a tactical initiative and is becoming a strategic line within major retailers. The ability to offer integrated, measurable and scalable solutions that work both inside and outside the store is becoming increasingly important.

For the market, this means greater competition, more technological standardisation and sustained growth in advertising investment in retail environments. For advertisers, it opens the door to formats closer to the purchasing decision and a more direct relationship between investment and results.

With this expansion, MediaMarktSaturn reinforces its position as one of the key players in point-of-sale monetisation in Europe. The company demonstrates that the physical store remains a strategic space for commercial communication when combined with data, technology and a well-structured advertising proposal.

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