TL;DR
Fashion resale is growing rapidly and more and more brands are launching their own second-hand programmes. In a single quarter, 17 companies joined this trend to capture value beyond the first sale and adapt to new market demands.

Second-hand fashion is entering a new growth phase. During the third quarter of 2025, 17 fashion brands launched their own resale programmes, a clear sign that resale is becoming consolidated within the commercial strategy of many companies in the sector.

Source: The Fashion Resale Report – Q3 – December 2025

For years, resale was dominated by third-party platforms and specialised marketplaces. Today, brands are looking to participate directly in that market, regaining control over the life cycle of their products and creating new channels for customer relationships.

The context also favours this move. The global second-hand fashion market is growing at a significantly higher rate than traditional fashion and is attracting investment, technology and new operating models.

A combination of consumer demand, regulatory pressure and technological improvements is driving a structural change in the sector. This article analyses what is behind this explosion and what it means for brands, consumers and the planet.

What it Means When a Brand Launches a Resale Programme

When a fashion company launches its own resale programme, it is taking control of something that was already happening without it: its customers were selling and buying its used garments on external platforms such as Vinted, Wallapop or Depop.

The novelty is that the brand now decides to intervene in that circuit. It begins to participate directly in the purchase, collection or resale of used garments from its own catalogue. Instead of just selling new products, the company introduces mechanisms so that garments have several commercial lives.

Common resale models:

• “Take-back” programmes: The customer hands in used garments to the brand and receives a voucher or a discount to buy new products. Collected garments are refurbished and resold.
• Brand peer-to-peer (p2p) platforms: These are platforms where customers sell to each other within an environment controlled by the brand.
• Own second-hand marketplaces: The brand creates a specific section on its e-commerce site where it sells authenticated used products.
• Resale-as-a-Service: Some companies outsource the operation to specialised platforms that manage inventory, logistics and pricing.

Many brands use mixed systems that combine in-store collection, reverse logistics and online sales. Initiatives of this type already exist in companies such as Patagonia, Balenciaga or Valentino, which allow customers to return used garments in exchange for credit or sell pre-owned products through official programmes.

Source: ThredUp’s 13th Resale Report Shows Online Resale Saw Accelerated Growth in 2024, Expected to Reach $40 Billion by 2029 – March 2025

In all cases, the brand maintains control over the experience, product quality and the value narrative, which is key to protecting positioning and the perception of durability.

The Global Context of Resale

The growth of resale responds to a profound transformation in how consumers buy fashion. According to various industry reports, the global second-hand fashion market is growing 2 to 3 times faster than the new fashion market.

Forecasts suggest it could reach up to $367 billion by 2029, with a compound annual growth rate of 10%, consolidating itself as one of the most dynamic segments of fashion retail.

The growth is explained by several factors:

• Greater price sensitivity in the consumer.
• Digital access to global marketplaces.
• Cultural changes regarding sustainability.
• Greater trust in authenticated second-hand products.
  

Younger generations play a key role in this phenomenon. Gen Z and Millennials consider second-hand a standard option within their wardrobe, motivated by price, sustainability and the possibility of finding unique pieces. Almost 40% of consumers from these generations made a second-hand purchase on a social network in the last 12 months.

Furthermore, resale is already a relevant part of shopping habits. In some consumer communities, second-hand items represent nearly 28% of wardrobe content. The result is an increasingly professionalised and competitive market.

Why Are Brands Betting on Resale Now?

The growing interest of brands in resale responds to several strategic motivations:

1. Capturing value within the secondary market

For decades, brands sold a garment and lost control over its subsequent journey. Resale occurred in informal markets or independent platforms.

Resale programmes allow for reclaiming part of the value generated in the secondary market, which in many cases is considerable.

2. Acquiring new customers

Industry reports show that many consumers discover a brand for the first time by buying a second-hand product. A significant portion of them end up buying new products later on.

Resale thus functions as an acquisition channel with a lower barrier to entry.

3. Controlling brand perception

Brands also seek to maintain certain control over the authenticity and quality of products circulating in the second-hand market. An official programme allows for item verification, setting standards and reinforcing the perception of durability.

4. Technological improvements facilitating the operation

One of the main historical obstacles to resale was its operational complexity: unique inventory, manual authentication or costly logistics.

New solutions based on AI, automation and dynamic pricing systems are reducing those costs and allowing resale to operate at a larger scale. This makes integrating second-hand within the retail business model viable.

5. Tariff instability pushing towards resale

With the increase in tariffs on textile imports, 54% of retail executives consider resale as a more stable and predictable source of inventory against tariff fluctuations, according to the ThredUp Resale Report 2025. Among consumers, 59% state that if new trade policies make new clothes more expensive, they will opt for second-hand.

How this Translates in Spain and Europe

Europe has become one of the most active markets for fashion resale. Second-hand platforms have gained great popularity in countries such as France, Germany or Spain, where digital trade in used products has grown rapidly in recent years.

The most eloquent indicator of the European moment is Vinted. The Lithuanian platform closed 2025 reaching €1 billion in revenue, 40% more than in 2024. In the first half of 2025, according to the Institut Français de la Mode barometer, Vinted led the fashion sales ranking in France by volume, ahead of Amazon, Kiabi, Shein and Zara.

Vinted and Oxfam also partnered for the second consecutive year to organise a second-hand fashion show at London Fashion Week. The garments presented came from Vinted and Oxfam shops and were styled by thrifting pioneer Bay Garnett. The garments from the show could be purchased through Oxfam’s account on Vinted after the event.

Source: Oxfam x Vinted Runway Show LFW SS26

The big brands have also made moves. Spanish company Inditex launched Zara Pre-Owned on 12 December 2023 simultaneously in 14 European markets, including Spain, after having first tested it in the UK and then in France. The platform allows Zara garments to be sold, repaired and donated directly from its website and app.

Furthermore, the European Union is pushing a series of regulations related to the circular economy. Regulations such as future Ecodesign requirements and extended producer responsibility policies are pressuring brands to better manage their products’ life cycles.

The Impact on Sustainability (Beyond Marketing)

Sustainability is one of the most visible arguments associated with resale, but its impact depends on how these programmes are implemented.

From an environmental point of view, extending the useful life of a garment reduces the need to produce new units. In a sector characterised by fast production cycles and high levels of waste, this extension of the life cycle can significantly reduce the environmental footprint.

Circular models also promote:

• Repair and refurbishment of garments
• Re-use of materials
• Reduction of textile waste volume

At the same time, some experts point out that resale alone does not solve the structural problems of the sector if clothing production continues to increase. The real impact depends on how brands integrate circularity into their business model: durable design, reverse logistics and product recovery systems.

Resale Becomes Consolidated as a New Business Lever

The launch of 17 new resale programmes in a single quarter reflects a clear trend in the fashion industry: second-hand is becoming part of the sector’s operating model. The growth of the market, changes in consumer behaviour and new technologies are creating the conditions for resale to consolidate as a stable commercial channel.

Brands participating in this market seek to capture value throughout the full product life cycle, strengthen relationships with their customers and adapt to a regulatory environment increasingly oriented towards the circular economy. Every garment that returns to the commercial circuit opens a new opportunity for sales, data and customer relationships.

In the coming years, resale programmes are likely to become a standard part of the strategy for many fashion companies. The concept of product ownership is evolving and the second-hand market occupies an increasingly relevant place in that transformation.

In a sector obsessed with launching new collections, the next growth opportunity could be in the garments that already exist.

The post The Resale Explosion: 17 Fashion Brands Launch Second-Hand Programmes in a Single Quarter appeared first on Flipflow.

TL;DR
Private label leads the protein segment, while kefir establishes itself as a haven for premium and artisanal brands. Current innovation focuses on on-the-go formats and sophisticated flavours that manage to balance health benefits with an indulgent experience.

The yogurt aisle in Spain has become strategic territory for dairy manufacturers: per capita consumption is around 9 kg per year and yogurt accounts for around 13.5% of household spending on dairy, making it one of the key categories within the chilled shopping basket. 

In parallel, the total yogurt market maintains value growth supported by higher value-added segments (such as protein, kefir, and plant-based), the extension of flavour ranges, and formats designed for convenience, especially drinkable and single-serve options. Furthermore, plant-based yogurts are undergoing a phase of recovery and acceleration, with a 16.7% increase in volume between 2023 and 2024 and a value close to 93 million euros, driven by consumers seeking healthy and plant-based options. 

In this context of maturity, concentration, and the search for differentiation, Share of Shelf and innovation in formats become decisive levers for competing in the soya, protein, and kefir types.​

The Shelf Split: Who Dominates Visibility?

Presence on the shelf is the most direct indicator of a retailer’s commitment to a brand or category. In the Spanish market, the balance between manufacturer brands and private labels (MDD) varies drastically depending on the type of yogurt.

Kefir: The Haven for Premium Brands

The kefir segment stands out for a structure where leadership is set by manufacturers with an artisanal or premium profile. Pastoret and Kaiku concentrate the bulk of the range, defining the category’s quality standard. Pastoret leads with a 15.8% share of presence, followed very closely by Kaiku with 14%.

In this category, private labels play a less dominant role compared to other segments. Carrefour is the chain offering the deepest own-brand range (14%), competing directly in number of references with the leaders. Conversely, other chains like Mercadona (Hacendado) maintain a kefir offering more oriented towards the basics, with fewer variants and a clear focus on price. A relevant data point is that the kefir shelf still leaves room for organic and artisanal proposals, indicating that the consumer of this product values origin and production processes over savings.

Protein Yogurts: Private Label Territory

If kefir is the haven for premium brands, protein yogurts are the true battlefield for private labels. In this segment, the store brand captures 50% of the total shelf space. This figure represents a record level of concentration that puts traditional manufacturers under significant pressure.

Hacendado leads visibility with 16.7% of the shelf, followed by the Danone Group brand YoPRO with 14.8%. This direct competition between the retail leader and the manufacturer leader has generated what we can call a “visibility war”. Behind them, Carrefour and Dia also maintain a very strong presence with their own protein lines. In this scenario, it is extremely difficult for a new manufacturer to gain space without disruptive innovation or massive advertising investment.

Soya: A Specialists’ Market

The shelf for soya plant-based alternatives shows the highest concentration in the study. Two brands, Alpro and Sojasun, together exceed 53% of total visibility. Alpro is the absolute dominator with a 28.6% share, while Sojasun follows with 24.5%.

This structure indicates that the soya consumer is very loyal to specialist brands that have mastered flavour and texture. Private labels play a secondary but relevant role here as a follower; Hacendado and Carrefour act by covering basic price needs, but they do not lead in innovation or the volume of references.

Innovation in Formats: Convenience as a Purchase Driver

Packaging design and product quantity are factors that determine the moment of consumption. The analysed data shows that each category has found a “hero format” that responds to customer needs.

• In Kefir: The big winner is the 500g drinkable bottle. This format has allowed kefir to move beyond breakfast to be consumed in liquid form throughout the day. However, we are seeing a growing trend towards the “bucket” or wide pot, especially for creamier versions seeking a healthy dessert positioning.
• In Protein: The 120g individual pot remains the standard, but real growth is in on-the-go formats. Drinkable protein shakes have gained a lot of space because they allow for immediate consumption after exercise. Additionally, tactical formats like “mousse pots” are appearing, which attempt to bring protein into the realm of guilt-free sweet treats.
• In Soya: The family or multipack format is king. The 4x100g pack is the most popular, but large 400g or 500g formats (known as Big Pots) are gaining ground. These large containers suggest recurring consumption at home, where the product is used both on its own and as an ingredient in other recipes.

The Flavour Map: From Natural to Sophistication

Flavour is the final filter in the purchasing decision. Although natural flavour remains the foundation of the market, innovation is opening up very interesting new market niches.

In kefir, natural flavour is the absolute core. Nevertheless, brands are introducing what they call “healthy fruits” (blueberries, strawberries) to soften the product’s characteristic acidity. Exotic flavours are also appearing tactically to attract a younger, more curious audience.

In protein yogurts, chocolate and vanilla are the basic flavours that guarantee volume. But the true innovation retaining customers is flavours inspired by fine patisserie: salted caramel, cookies & cream, or stracciatella. The goal for brands is to offer a flavour perceived as an indulgence or a treat, while maintaining a healthy nutritional profile.

In the soya segment, we see a clear division. On one hand, natural and chocolate flavours cover basic demand. On the other, more sophisticated flavours oriented towards an adult palate are being introduced, such as coffee, hazelnut, or praline. This indicates that soya is looking to position itself as a plant-based pleasure for adults, beyond being a simple alternative to cow’s milk.

Innovation Insights by Type

The report synthesises well how innovation in formats and flavours is used to defend margins and build consumer loyalty.​

Kefir: Migration towards creamier and more premium proposals

In kefir, a clear margin protection strategy is evident:

• Migration from cheaper liquid proposals towards more solid and creamy products in premium-style packaging.​
• Leveraging territories such as organic, artisanal, or origin-based to justify higher price points.​

Innovation is concentrated on packaging (wide pots, differentiated formats on the shelf) and the consumption experience (denser textures, more elaborate recipes) without losing the functional anchor associated with digestive health.​

Protein: Indulgent flavours to retain the consumer

In protein, the price decrease observed in the period is accompanied by an effort to reinforce the appeal of the type through flavour.​

• Brands are working on flavours that evoke “pleasure” while maintaining a nutritional profile aligned with healthy consumption.​
• The on-the-go format becomes the axis of innovation to connect with consumption moments such as snacking, post-workout, or a quick afternoon snack.​​

In this way, protein is established as a satiating and healthy snack, with an offering that competes against other impulse and convenience categories.​​

Soya: Sophisticated flavours for an adult consumer

In soya, innovation is oriented towards a consumer seeking pleasure within a plant-based choice.​

• Compared to the “gym flavours” of protein or the purist profile of kefir, soya explores more sophisticated flavours such as coffee, hazelnut, praline, or red berries.​
• The combination of these flavours with big pot formats or multipacks positions the category as a recurring alternative in households seeking to reduce animal-based dairy consumption.​​

This strategy is supported by the global growth trend of plant-based products and the recovery of plant-based yogurt consumption observed in recent years.

Keys to Leading the Yogurt Shelf in the Coming Months

The Spanish yogurt market has proven capable of constantly reinventing itself. Shelf visibility is not a static state, but the result of a strategy that combines the right format with the flavour the consumer is expecting at any given time.

Companies that want to stand out must understand that innovation is no longer limited to launching a new flavour every season. The key to current success lies in the ability to adapt the product to new lifestyles. On-the-go formats and proposals that balance nutrition and pleasure are the ones winning the battle for space in the supermarket.

In conclusion, success on the Spanish shelf will depend on the agility to read these trends. Brands that manage to combine solid visibility with a differentiated flavour offering and convenient formats will be the ones that secure loyalty from a consumer who, although price-sensitive, continues to highly value innovation and quality in their daily diet. The yogurt aisle will remain one of the most interesting spaces to observe the evolution of consumption in Spain.

If you want to see the full details on visibility, formats, and innovation (including charts and tables), download the sector report by clicking here. 

The post Shelf Leaders: Analysis of Share of Shelf and Formats in Soya, Protein, and Kefir Yogurts in Spain appeared first on Flipflow.

TL;DR
Walmart is integrating Vizio into its advertising ecosystem to bring Retail Media to connected TV and close the loop between advertising impact and actual sales. By combining proprietary transactional data with CTV, it turns the living room into a new measurable and highly segmented point of sale.

Walmart has integrated its advertising network, Walmart Connect, with the capabilities of Vizio, a connected TV platform, to bring brand advertising directly into consumers’ homes.

This strategy leverages real purchase data to show relevant ads on smart TV screens, allowing concrete sales results to be measured. The move is part of a broader plan to expand the retail giant’s advertising business beyond physical stores and its website.

When Retail Media Sits on the Sofa

Retailers generate advertising revenue through their own channels, such as website searches or in-store screens. Walmart Connect represents this advertising network in the United States, where brands pay to appear at key moments of the purchasing decision. The acquisition of Vizio in 2025 adds a new layer: smart TVs in homes.

Vizio brings more than 18 million active accounts on its SmartCast platform, along with an operating system that facilitates ad insertion. Walmart is now combining this CTV (connected TV) inventory with its transaction data, creating opportunities for campaigns that influence actual purchases. The result shows in the numbers: Walmart’s global advertising business is growing strongly, and this integration accelerates the process.

An X-ray of Walmart’s Advertising Business

Walmart reported global advertising revenue of nearly $6.4 billion in its 2026 fiscal year (based on how large US corporations’ fiscal years operate), an increase of 46% compared to the previous year. In the fourth quarter of that fiscal year, Walmart Connect in the United States recorded year-on-year growth of 41%, driven by more advertisers and better targeting options.

These results position Walmart as a key player in the Retail Media market, a sector where retailers monetise their customer data and reach to attract brand budgets. Advertising represents one of the highest-margin segments for the group, as it leverages existing assets such as the customer base and digital platforms. The expansion into CTV via Vizio contributes directly to this momentum by opening up new video formats and audiences in the home.

The Vizio Purchase: Hardware, Software, and Data in the Walmart Ecosystem

Walmart acquired Vizio for $2.3 billion in early 2024, a deal that closed that same year. The company has a Smart TV platform called SmartCast, which reaches millions of homes, and a software division (Platform Plus) responsible for most of its gross profits.

This purchase gave Walmart control over TV hardware, the operating system that runs them, and advertising spaces within them. SmartCast allows for contextual or targeted ads, and Walmart integrates this data with its in-store and online purchase history. The effect is clear: more Vizio TVs sold generate more advertising opportunities, which fund improvements in hardware and content offerings.

The move is explained by the growing competition with Amazon, which uses Fire TV for similar purposes in streaming and e-commerce. Walmart thus manages to slip into the consumer’s living room, where it can influence purchase decisions before they reach the store or the website.

From the Shelf to the Living Room Screen: What Changes for Brands

Brands advertising on Walmart Connect now have more options within the ecosystem: CTV video, e-commerce searches, or in-store displays. Walmart segments audiences based on real purchasing behaviours, such as families buying products from a specific category.

A practical example: an appliance brand launches a spot on SmartCast aimed at recent Walmart customers who bought kitchen accessories. The advert can include calls to action that lead directly to the Walmart website or a nearby store. This integration makes the television function as an additional storefront, connected to the retailer’s actual inventory.

For brands, the benefit lies in precision: ads reach people with proven intent, and results are measured in concrete sales, not just impressions. Walmart Connect thus extends its offer to advertisers looking for impact in homes, beyond immediate online purchases.

Source: Walmart’s Acquisition of Vizio is Disruptive and Explosive Combined – February 2024

Real Closed Loop: Measurement and Attribution Across Store, Web, and TV

Walmart offers what is known as closed-loop advertising: a system that tracks the entire journey from ad exposure to purchase. In CTV, a spot seen on Vizio is linked with loyalty card data or online accounts to calculate the impact on sales in physical or digital stores.

This measurement crosses multiple screens: the TV at home, the Walmart website, the mobile app, and even screens at the point of sale. Advertisers receive detailed reports on sales uplifts, justifying investment in traditional television formats that previously relied on indirect metrics.

Walmart’s strength lies in its first-party data, collected directly from transactions, which avoids relying on third-party cookies. This closed attribution capability attracts brands seeking budget efficiency, especially in an environment where privacy limits other advertising options.

Implications for the Future of Retail Media

Walmart’s move is not tactical; it is structural. It integrates data, advertising inventory, and hardware under one umbrella, reducing friction and increasing control over the advertising value chain. The projected growth of Retail Media on CTV, which is set to double in size in the coming years according to eMarketer estimates, indicates that connected TV will stop being a complement and become a central channel within brand strategies.

For European or Spanish retailers, the signal is clear: the future involves not only optimising on-site or in-store presence, but expanding the ecosystem into content consumption moments. This implies investing in first-party data, unified measurement capabilities, and technological partnerships that allow closing the circle between advertising impact and actual sales.

Television as a New Strategic Shelf

What is at stake is the redefinition of the point of sale. Walmart is turning television into an additional shelf: one that lives in the living room, operates with transactional data, and is measured in incremental sales.

The retailer no longer waits for the consumer to enter the physical store or the website. It anticipates the moment of decision, influences it, and connects it directly to its inventory. In an environment where attention is the scarcest resource, controlling the home screen means gaining presence in the moment prior to purchase.

Whoever manages to connect entertainment, data, and transaction will have a competitive advantage that is difficult to replicate.

The post Walmart Wants to Turn your TV into its Store’s Best Shelf appeared first on Flipflow.

TL;DR
When data is scattered across multiple systems without integration or governance, the organisation loses efficiency, reliability, and decision-making speed. These 6 signs indicate that you have reached the limit of fragmentation and need a data unification strategy.

There comes a time in the life of many organisations when data stops being an asset and becomes a problem. It doesn’t happen all at once. It happens gradually, almost imperceptibly: one team creates its own spreadsheet to compensate for what the CRM doesn’t do well, another department exports reports in its own way, someone sets up an auxiliary database to cross-reference information that “is never where it needs to be”.

Over time, the result is always the same: data scattered across dozens of systems, with no connection between them, managed by different people using different criteria. This is called data fragmentation, and when an organisation reaches a certain level of operational maturity, it becomes one of the main obstacles to growth.

This article describes 6 specific symptoms indicating that your organisation has reached the limit of that fragmentation. If you recognise several of them, it is not a sign of poor management: it is a sign that you have grown and that the time has come to address the problem seriously.

What Do we Mean by Data Fragmentation? (And Why it’s Getting Worse)

Data fragmentation occurs when an organisation’s information is distributed across multiple systems, formats, and locations without any mechanism to unify it or guarantee its consistency. Each tool records what it can, in its own way, and no one has a complete view of anything.

The problem is not new, but it has worsened in recent years due to several factors. The first is the proliferation of SaaS tools over the last decade. Data sources have multiplied without most organisations developing a strategy to integrate them. Today, a medium-sized company may have customer data in the CRM, the email marketing platform, the support system, the online shop, in shared spreadsheets, and in reports exported manually every week. None of those systems communicates natively with the others.

Furthermore, fragmentation is self-sustaining: when teams do not trust centralised data because it is incomplete or outdated, they create their own alternative sources. And those alternative sources increase fragmentation. It is a cycle that is very difficult to break without deliberate intervention.

The second factor is the exponential growth in the volume of information. We generate more data than ever through mobile devices, sensors, and digital transactions. Without a clear integration strategy, this volume becomes unmanageable. Finally, the lack of a data governance culture causes companies to prioritise daily operations over the structure of their information. The result is a technological ecosystem full of patches, where data flows with difficulty and its quality degrades over time.

The 6 Signs that you Have Reached the Limit

Identifying the problem is the first step to solving it. These are the red flag signals indicating that fragmentation in your organisation is unsustainable.

1. There is no “single version of the truth” (metrics that do not add up)

Have you ever attended a meeting where two people presented contradictory data on the same metric? One says that 47 contracts were closed last month; another has 51 in their report. Neither is lying: they are simply drawing from different sources, with different filtering criteria, updated at different times.

When this occurs recurringly, the real problem is not the discrepancy itself: it is that the organisation has lost the ability to trust its own data. Meetings turn into debates about which number is correct instead of conversations about what to do with that information. Time is invested in reconciling figures, not in making decisions.

The absence of a reliable and shared data source —known in technical circles as a single source of truth— is one of the clearest indicators that fragmentation has reached a critical point.

2. “Excel Hell”: double or triple work and duplicates everywhere

If your employees spend a large part of their working day downloading CSV files from one platform to upload them to another, or manually cross-referencing pivot tables, your organisation has a serious fragmentation problem. The excessive use of spreadsheets as a bridge between systems is what we call “Excel hell”.

This working method entails four major problems:

• Firstly, it involves a very high operational cost. You are paying qualified professionals to perform “data cleaning and transport” tasks instead of analysing information. Some reports claim that employees lose, on average, 12 hours a week searching for information scattered in silos that they need to do their jobs.
• Secondly, the risk of human error is omnipresent. A poorly dragged formula or a row deleted by accident can invalidate an entire analysis.
• Furthermore, when critical processes depend on files managed by a single person, the organisation accumulates silent operational risk. What happens if that person is unavailable? Or if the file becomes corrupted? Or if someone works on an old version without knowing it?
• Lastly, this system generates a massive amount of duplicated and outdated data. The moment someone downloads data into an Excel sheet, that data is already dead, because it will not be updated if there are changes in the original system.

3. No one has a unified view of the customer or the product

In companies with very pronounced data silos, each team sees only a fragment of the customer relationship or the product life cycle. Customer service has an incident history, marketing sees campaigns and opens, sales records opportunities and orders, and finance focuses on billing and collections, but there is no point where all of that comes together coherently.

Imagine a customer calls support and the person assisting them has to consult 3 different systems to know who they are, what they have bought, if they have any open incidents, and when the last contact was. Or that the product team cannot cross-reference app usage behaviour with support data because both sources are incompatible.

Data fragmentation has a direct impact on the customer experience and on the product team’s ability to make good decisions. When information about an entity (whether a customer, a supplier, or a product) is spread across systems that do not communicate, the result is always a partial and, frequently, inconsistent view. This translates into avoidable errors, missed opportunities, and a customer experience below what the organisation would like to offer.

4. Integrating a new system or source is painful (and every integration is “handcrafted”)

Organisations with advanced fragmentation usually have a recognisable pattern when they need to connect two systems: someone spends weeks developing a bespoke integration, that development is not documented, and when something fails, no one knows exactly how it works inside.

Each integration is built from scratch, without reusing anything from before. The result is a data architecture that looks like a plate of spaghetti: many point-to-point connections, fragile, difficult to maintain, and almost impossible to scale.

When the question “Can we connect this system?” generates more fear than excitement, and incorporating a new tool into the digital ecosystem means weeks of technical work, coordination meetings, and a real risk of something breaking elsewhere in the system, it is a clear sign that fragmentation has reached its limit.

5. Slow reporting, slow decisions (the organisation is playing catch-up)

In a competitive environment, the ability to act with up-to-date information makes a real difference. When the process to generate a report takes days (because data must be collected from multiple sources, normalised, and the visualisation built manually), decisions arrive late.

The problem is not just one of speed. It is one of organisational culture. When teams know that obtaining reliable data requires a lot of effort, they stop asking for it. They make decisions with the information they have to hand, even if it is incomplete or old. Over time, the organisation loses the habit of deciding with data and starts to operate more on intuition than on evidence.

In this sense, fragmentation does not only slow down reporting: it erodes the analytical capacity of the organisation as a whole.

6. Growing risk in security, compliance, and auditing

Fragmentation is not just an efficiency problem; it is a top-level legal and security risk. With increasingly strict data protection regulations, such as the GDPR in Europe, companies have an obligation to know exactly where their customers’ personal information resides and who has access to it.

If data is spread across multiple platforms, personal cloud service accounts, or Excel files lost in shared folders, it is impossible to guarantee compliance. In the event of an audit or a request from a citizen to exercise their rights of access or erasure of data, the organisation will have serious difficulties responding completely and on time. Furthermore, each point of fragmentation is a potential security breach. It is much harder to protect information when you don’t have a clear inventory of where it is and how each fragment is protected.

First Steps to Building a Unified Data Architecture

Overcoming this limit requires a change of approach that goes beyond buying a new technological tool. There are several possible approaches depending on the level of maturity and resources available in each company. But the first step for all involves recognising that data is a strategic asset of the company, not a byproduct of applications.

To begin unifying information, it is recommended to follow these steps:

• Establish data governance: Define who owns each piece of data, who can access it, and what quality standards it must meet. This creates a common language for the entire organisation.
• Commit to a modern integration architecture: Instead of handcrafted point-to-point connections, look for solutions that act as an intermediary layer. This could be a centralised data warehouse or platforms that allow applications to be connected in a standardised way.
• Prioritise quality over quantity: It is preferable to have less data that is accurate, up-to-date, and accessible, than to have an immense data lake where no one finds anything reliable.
• Automate information flows: Eliminate manual intervention in moving data between systems whenever possible. This drastically reduces human error and frees up time for higher-value tasks.
• Foster a data culture: Educate all levels of the organisation on the importance of maintaining information integrity. Technology alone does not solve fragmentation if human processes continue to create silos.

Breaking Fragmentation: From Operational Brake to Strategic Advantage

Data fragmentation is not the exclusive preserve of large corporations or particularly sophisticated sectors. It appears naturally when business growth outpaces the capacity of systems and processes to sustain it coherently. The six signs we have analysed are manifestations of an information architecture that has become misaligned with current market demands.

Reaching this limit should not be interpreted as a failure, but as a strategic turning point. It is the opportunity to redefine data management as a structural pillar of the business, establishing true governance, a solid integration architecture, and a single reliable version of the truth. Resolving fragmentation not only improves operational efficiency and reduces risk; it enables advanced capabilities such as predictive analytics, intelligent automation, and real-time decision-making.

In this context, having a platform that allows for unifying sources, standardising metrics, and governing information centrally makes all the difference. With flipflow, organisations can build that layer of integration and control that transforms scattered data into a governed, accessible, and actionable strategic asset. Because a company that masters its data decides with confidence, executes with agility, and scales without its own internal complexity becoming an obstacle.

The post 6 Signs that your Organisation Has Reached the Limit of Data Fragmentation appeared first on Flipflow.

TL;DR
Analysis data: trends in average price and average discount in Spain for kefir, protein yogurts and soy yogurts during September–December 2025, based on information from our SaaS (full details in the downloadable report).

The yogurt market is undergoing a period of readjustment in Spain: household consumption has been falling for two years, but the market value continues to grow due to the effect of inflation and the rise of higher value-added segments such as protein, kefir or plant-based alternatives. Yogurt accounts for around 13‑14% of spending on dairy products in the home, with nearly 9 kg per capita per year, and is impacted by cost pressure and the normalisation of farm-gate milk prices following the peaks of 2022. 

In parallel, plant-based yogurts are accelerating: retail sales for this category reached approximately 93 million euros in 2024 in Spain, with cumulative growth exceeding 30% since 2022, driven by consumers looking for healthier and plant-based options. In this context of more selective consumption, greater price sensitivity and a search for functionality, understanding price trends and the role of promotions in soy, protein and kefir yogurts becomes key for dairy brands.

Price Trends by Type: Three Very Different Curves

Between September and December 2025, the three types analysed —kefir, protein and soy— sent mixed signals. There is no single trend in prices; instead, each segment responds to its own supply and demand dynamics.

This divergence forces manufacturers and retailers to make fine-tuned decisions: where they can defend margins, where adjustments are needed to sustain volume, and what role manufacturer brands and private brands play in each segment.​

Kefir: upward trend with a final adjustment

The average price of kefir during the period moved upwards, with very pronounced behaviour in autumn.​

• September: €2.30.
• October: €2.41 (+4.8% vs September).
• November: €2.55 (+5.8% vs October, +10.9% vs September).
• December: €2.48 (‑2.7% vs November, but still +7.8% vs September).​

The dynamic is clear: kefir became progressively more expensive until November, when it peaked, and corrected slightly in December without losing the price level gained. This fits with a category where positioning revolves around added value, origin and “eco/artisan” attributes, providing room to pass on part of the cost pressures while maintaining willingness to pay.​

Protein yogurts: downward adjustment and a new benchmark level

In protein yogurts, the movement was the opposite, with a price adjustment concentrated in the final stretch of the year.​

• September: €2.33.
• October: €2.35 (+0.9% vs September, practically flat).
• November: €2.06 (‑12.3% vs October).
• December: €2.02 (‑1.9% vs November, ‑13.3% vs September).​

The result is a downward “step”: the type entered December with an average price 13% lower than in September, suggesting a combination of higher promotional intensity, tactical repositioning by some brands and pressure from Private Brands as a lower-priced alternative.​

Soy yogurts: one-off price increase and return to equilibrium

Soy exhibited a pattern of increases followed by a quick correction, with clear signs that the market does not support a structural price jump.​

• September: €2.50.
• October: €2.69 (+7.6% vs September).
• November: €2.52 (‑6.3% vs October).
• December: €2.51 (‑0.4% vs November, +0.4% vs September).​

The October price hike acted more as a “peak” than as a new stable level, and the category closed the year at practically the same price as the start. This suggests a delicate balance between the perceived value of plant-based yogurts and the price sensitivity of a consumer who, while willing to pay more for nutritional or sustainability attributes, continues to compare them with traditional dairy yogurts and Private Brands.​

Brand Pricing Strategies: Private Brand Stability vs High-End Volatility

Behind these category averages are very different logics depending on the brand and the retailer. The report distinguishes clearly between the behaviour of Manufacturer Brands (MDF) compared to Private Brands (PB) in each type.​

Kefir: volatility in the ultra‑premium segment

In Manufacturer Brand kefir, two blocks are observed: relatively stable brands and a very volatile ultra‑premium segment.​

Among the stable brands, we find Activia (-1% between September and December) and Pastoret (-0.9% in the same period).

Volatility is concentrated in brands with ecological or artisan positioning (El Cantero de Letur and Granja Noé) and higher starting prices, pointing to active price management to avoid losing turnover in an environment of greater sensitivity to the final receipt.​ Both brands show very sharp drops from their peaks to December (‑15.3% and ‑30.4% respectively).​

In Private Brands, the pattern is very different: restrained and practically flat prices.​ Hacendado sets the market floor, with almost entirely stable prices (‑1.8% September‑December).​ Dia is the exception, with a clear rise during the period (+8.2%). Carrefour plays the role of the “higher” Private Brands, with prices above €2.​

Here, competition is defined more by positioning between retailers (Hacendado as the low-price reference, Carrefour as a premium Private Brand) than by inflation dynamics.​

Protein: stable premium, one-off adjustments and “price-fighter” Private Brand

In protein yogurts, the segmentation between manufacturer and retailer is also highly visible.​

In Manufacturer Brands, there is significant dispersion and movement, with a clear axis between stable premium brands and one-off adjustments. Pastoret maintains the highest price tier. YoPRO stands as a stable reference around €2.43 (‑1.2% in the period).​ Kaiku represents a distinct case: it rose sharply until November and fell notably in December (‑10.5% vs September), a pattern consistent with intense promotional actions.​

In Private Brands, the picture is one of stability and a focus on price. Dia and Carrefour operate in the lowest band, with minimal price changes during the period.​ Alipende acts as a completely flat anchor.​ Hacendado is positioned as the highest Private Brand in the block, but with a gentle and controlled increase (+1.8%).​

This confirms that, in protein, Private Brands function as “price fighters” and set the price floor, while Manufacturer Brands work more with brand value, innovation and highly tactical price management.​

Soy: manufacturers at the top end and Private Brands as a stable lower step

In soy yogurts, the manufacturer price level is clearly above Private Brands and with very consistent positions.​

Activia is the most premium brand and closed the period as the price ceiling.​ Alpro remains a stable “core”, with very contained variations.​ Sojasun provided the greatest variation: rising in October and correcting until December, with a fall of 3.9% compared to September.​

In Private Brands, Hacendado set the minimum at €1.35, staying completely flat throughout the period.​ Consum cut slightly (‑1.9%) and Carrefour was the only one with a moderate increase (+3.1%).​

Here, Private Brands do not seem to be the driver of average price fluctuations in the category, but rather a stable price base above which manufacturer brand adjustments move.​

Discount Landscape: Moderate on Average, Uneven in Practice

If the average price explains “where the market is”, the discount explains “how it competes” week by week. The report shows a discount landscape where the average is restrained, but behaviour is very uneven across brands.​

• Average discount for the set: ‑2.5% if non-promoted brands are included.​
• Average discount only among discounting brands: ‑3.7%.​
• Private Brands apply more aggressive discounts (average ‑5.1%) than Manufacturer Brands (average ‑1.3%).​

This means that most brands use shallow tactical reductions, while a few push with strong promotions that end up moving the average and contributing to the perception of a “price war” on the shelves.​

Price “agitator” brands: very aggressive promotions

A small group of retailers concentrated the deepest discounts (>5%).​ Carrefour (‑12.65%) was the most aggressive brand, with a strategy based not just on low base prices, but on intensive use of promotion.​

MARGUI (‑9.95%) and Alipende (-7.92%) are niche brands that need to “shout offer” to capture attention compared to major manufacturers, or retailers that use promotion as a primary tool to reinforce their price positioning.​

Brands with tactical discounts: defending volume without eroding too much margin

At a second level are the mainstream brands that combine shelf visibility with recurring promotions, but not as deep (discounts between 1% and 5%). At this level, we find brands such as Nestlé (-5.32%) or Danone (-4.42%). ​

These are traditional brands that are suffering pressure from Private Brands and are forced to sustain a high level of promotional activity to maintain volume, especially in types like protein, where Private Brands are gaining shelf space.​

This group also includes cases like YoPRO, with a much more moderate average discount (‑1.60%), relying on brand value and a wide range without entering an aggressive promotional spiral.​

“Untouchable” brands: stable prices and no promotions

At the opposite end are the brands that applied no discounts during the analysed period.​

• Private Brands with an “everyday low price” strategy like Hacendado and Consum.​
• Eco-artisan and premium brands like Pastoret, El Cantero de Letur or Casa Grande de Xanceda.​
• Sojasun, which maintains its positioning without resorting to promotion.​

In Private Brands , the logic is clear: prices already act as the category “floor” and temporary offers would lose meaning. In premium brands, foregoing discounts protects the perception of quality, origin and exclusivity, avoiding the dilution of positioning by entering the price conversation.​

Key Points for Decision-Making: How to Use this Data in Pricing and Promotions

With these patterns, there are several lines of action that typically work well in categories like yogurt:

1) Separate strategy by type (do not apply a single recipe): Kefir tolerates high prices better when the value is clear; it is advisable to care for the premium architecture and avoid a constant promotional war. Protein yogurts require closer monitoring of price and promotions, because the market is more sensitive and Private Brands are pushing hard. Soy yogurts allow for working on a differential if there is a solid proposal; the gap relative to Private Brands is established, but it must be justified.

2) Review the role of promotion (frequency vs depth): The average discount is low, but the brands that “move” the market do so with depth. This forces a decision: Do you need to compete with one-off strikes? Or is it better to build stability and defend margins?

3) Control consistency between base price and promotion: Especially in protein, part of the drop in average price can be explained by adjustments and promotional dynamics. If your base price is high, the promotion can become a “crutch” and end up educating the consumer to expect a discount.

Roadmap for Commercial Management in the Yogurt Category

The analysis of the final months of 2025 reveals a yogurt market in Spain moving at two speeds. Value-added segments, such as kefir and protein, lead innovation and growth in value, but they do so under radically opposite pricing strategies: kefir bets on premiumisation and rising margins, while protein is immersed in a price war led by distribution.

Private Brands have ceased to be simply a cheap option and have become the market regulator. Their ability to maintain stable prices while simultaneously applying aggressive promotions at key moments forces manufacturer brands to be more creative in their commercial policy.

For companies in the dairy sector, the key to success in the coming months will not lie only in product quality, but in the ability to monitor competitor movements in real time. Understanding when an own-label brand lowers its price floor or when a direct competitor activates an aggressive discount campaign is fundamental to reacting in time and protecting both market share and profit margins.

The Spanish yogurt market is mature and highly competitive. In this scenario, data management and the precise analysis of price trends become the best tools for navigating a consumption environment that continues to evolve. And flipflow is here to help you achieve it. 

If you want to see the full details by type and brand (including charts and tables), download the sector report by clicking here. 

The post Prices and discounts in soy, protein and kefir yogurts: an analysis of the Spanish market (2025) appeared first on Flipflow.

TL;DR
The Digital Shelf allows for the identification of weak signals that anticipate market changes before they impact sales. Analysing searches, assortment, prices and competitive movements helps in making decisions with an advantage and reducing strategic surprises.

The Digital Shelf as the Brand’s “Periscope”

A submarine navigates blindly until it raises its periscope. Only then can it see what is happening on the surface: if there is a storm, if a ship is approaching, or if the horizon is clear. Brands selling through digital channels have a similar instrument at their disposal: the Digital Shelf.

The Digital Shelf is the set of touchpoints where a product appears — or ceases to appear — in an online sales environment: product pages, search positions, consumer ratings, competitor prices, stock availability. All of this is there, updated in real time, accessible to those who know how to look.

The problem is that most brands only use the Digital Shelf for reactive tasks: correcting an incorrect price, claiming an outdated image, or responding to a bad review. They treat it as a breakdown control panel, not as a source of strategic intelligence.

This article proposes doing exactly the opposite: using the Digital Shelf as an early detection system for market changes, through what is known in strategic analysis as weak signals.

What Do we Mean by “Weak Signals” on the Digital Shelf?

The concept of a weak signal comes from the field of strategic foresight. A weak signal is an incipient, barely visible and apparently minor indication that anticipates a significant change before that change becomes evident to the entire market.

On the Digital Shelf, a weak signal could be:

• A secondary category that begins to gain search volume consistently.
• An unknown competitor that systematically appears in the top search results.
• A specific attribute (“no added sugar”, “concentrated”, “refillable”) that suddenly proliferates across product pages in the entire category.
• A gradual drop in reviews in a price segment that was previously stable.

At an analytical level, these signals have three characteristics:

1. Low magnitude: They affect few products or a reduced volume of users.
2. High recurrence: They are repeated across different retailers or categories.
3. Low immediate interpretation: They do not explain the present, but they suggest the future.

None of these signals, on its own, justifies a strategic pivot. But when they are identified systematically, cross-referenced with other sources and their evolution is interpreted over time, they can anticipate changes in demand, assortment or competition weeks or months ahead of the rest of the market.

The difference between a weak signal and background noise is, precisely, the ability to observe methodically.

Why the Digital Shelf Is the Best Detector of Weak Signals

Each source of market information observes a different phase of customer behaviour:

Behaviour always changes before volume does. The consumer explores first, adopts later and normalises at the end. Physical retail captures the final phase. The Digital Shelf captures the initial phase.

There are 4 specific reasons why the Digital Shelf offers advantages that other information sources do not:

• The first is speed. Digital Shelf data is updated continuously. A price change, a new entry in a retailer’s catalogue or a spike in negative reviews are visible within hours, not weeks. No traditional market study can compete with that cadence.
• The second is granularity. The Digital Shelf allows you to see what is happening at the reference, retailer, category and geographical market level simultaneously. This combination of levels is very difficult to obtain through other means.
• The third is that it reflects real behaviour. The searches consumers make, the products they buy, the attributes they mention in their reviews: all of this is observed behaviour, not declared. It is what people do, not what they say they would do in a survey.
• The fourth, and perhaps the most relevant in this context, is that the Digital Shelf captures competitors’ movements before those movements become public. A launch, a change in positioning or an aggressive pricing strategy manifests on the digital shelf before appearing in any press release or industry report.

That is why many market changes do not start with the consumer, but in the interaction between the consumer, the algorithm and the digital assortment.

Four Types of Weak Signals that Anticipate Market Changes

The weak signals that can be observed on the Digital Shelf are grouped into four large blocks: demand, assortment, pricing and competition.

1. Demand Signals

These are the first to appear because they reflect exploration. Demand signals indicate changes in what consumers search for, buy or value. On the Digital Shelf, they manifest in several ways:

• Search terms that gain position consistently.
• Changes in click-through and conversion rates per SKU.
• Attributes that begin to repeat in reviews.
• Adjacent categories that grow while the main category stagnates.

A common example: a snack brand detects that searches related to “protein” are growing in its category while those for “low calorie” are stabilising. Before that change reaches consumer panels, it is already visible in the channel’s search behaviour. Demand always starts in language, not in sales.

2. Assortment Signals

The assortment that retailers decide to include, maintain or withdraw from their platforms is another market thermometer. Retailers use the digital channel to test. Assortment signals are detected in:

• Appearance of new subcategories and expansion of niche formats.
• New SKUs gaining speed.
• Products with presence but no traction.
• Assortment gaps compared to the competition.

When several retailers begin to incorporate similar references simultaneously, or when a subcategory that didn’t exist before starts appearing in navigation menus, it is rarely accidental. Each of these movements tells a story. And it helps to adjust the portfolio by channel, prioritise references and detect opportunities for innovation or assortment rationalisation.

3. Pricing Signals

Price is the fastest strategic experiment in the market. Pricing signals relate to relative price position and its evolution. The following relevant changes can become signals of what is happening in the market through price:

• Deviations from the market average.
• Sequence of discounts and promotions.
• Price conflicts between channels.
• Concentration of products in new price ranges.
• Premiumisation of specific attributes.

When a category changes its price architecture, it is redefining its future positioning. Observing these signals helps to decide where to adjust prices, when to activate campaigns and how to protect margin without losing relevance.

4. Competitive Signals

The market first tolerates, then copies and finally integrates. Competitive signals show how other players in your category are moving. The movement of competitors on the Digital Shelf leaves very clear traces for those looking for them:

• New references launched.
• Changes in content on product pages.
• Variations in selling points.
• Appearance of new players in consolidated categories.
• Changes in digital share (share of search, share of shelf, share of voice).

These signals allow for the anticipation of competitor movements and the preparation of responses in assortment, communication, retail media investment or negotiation with retailers.

How to Build a System to Detect and Exploit these Signals

Detecting weak signals occasionally has little value. What generates a competitive advantage is having a systematic process that collects, interprets and turns them into decisions regularly.

Step 1 – Define Digital Shelf Metrics and KPIs

The first step is to decide what is going to be measured. Not everything that can be measured is relevant, and an excess of data is as paralysing as a lack of it. Fundamental Digital Shelf metrics are usually grouped into four blocks:

• Visibility: search position, share of search.
• Content: quality of listings, attribute compliance.
• Availability: stock, coverage by retailer.
• Reputation: review volume and score, temporal evolution.

To these metrics, you must add specific tracking of the competition: what references they have, where they appear, at what price and with what arguments.

Step 2 – Automate Data Capture and Monitoring

Without automated data capture, the cost of maintaining an updated view becomes unsustainable. Digital Shelf analytics solutions like Flipflow allow for the continuous collection of information from multiple retailers and marketplaces, standardising it and presenting it in dashboards.

Automation not only reduces manual effort but also improves coverage of categories, products and channels. The greater this coverage, the lower the risk of “blind spots” where weak signals occur unnoticed. Furthermore, Digital Shelf data can be cross-referenced with internal sales information to evaluate the real impact of each signal.

Step 3 – Turn Signals into Actionable Alerts

The next step consists of transforming variations in metrics into clear and prioritised alerts. Not all deviations require immediate action, so it is advisable to define business rules that take into account the weight of each SKU, the channel and the category.

Examples of useful alerts:

• Warnings when the availability of a key SKU falls below a threshold at a strategic retailer.
• Alerts for loss of position on priority keywords for several consecutive days.
• Notifications when a competitor reduces its price in a certain range across a set of comparable products.
• Signals of a rapid increase in negative reviews in a product family.

These alerts must reach the responsible teams (sales, marketing, revenue, supply chain) accompanied by sufficient context (what has happened, since when, and what response is expected from the responsible team) to decide what action to take.

Step 4 – Integrate these Signals into Business Decisions

The final step, and the most difficult one, is cultural: ensuring that Digital Shelf signals reach the meetings where decisions are made. This implies that data is presented clearly and actionably, that there are individuals responsible for them, and that established processes exist to turn a signal into a specific action: a price adjustment, a change in product page content, a conversation with a retailer or an assortment review.

Case Studies: Stories from the Digital Shelf

To understand the value of these weak signals, it is useful to see how they can change the course of specific decisions:

The competitor nobody saw coming

A consolidated baby food brand began to lose search positions to a new brand with almost no sales history. Initially, the team attributed it to a technical problem. When they reviewed the data in more detail, they found that the new brand had systematically optimised its product pages with very specific attributes that parents were searching for but that the leading brand was not including in its content. The adjustment took months to make. Months that the competition took advantage of to consolidate their position.

The new model with 5-star reviews

A third case can be found in consumer electronics. A manufacturer detects, thanks to Digital Shelf analytics, that a new model from an emerging brand is starting to accumulate very positive reviews on a specific marketplace and gaining search ranking positions for terms associated with “value for money”. Although the absolute volume is still small, the pattern holds for several weeks. The company interprets this signal as a risk of disruption and decides to accelerate the launch of an intermediate range, reinforce comparative content and bet on bundles with added services. The early response allows them to defend their position before that new player reaches critical mass.

A brand that saw the format change coming

A household cleaning products company detected, over several months, that searches for concentrated formats were growing steadily across several retailers while their references in that segment had barely any visibility. The data reached the category team before any market study picked it up. This gave them time to negotiate space with retailers and prepare the launch of their own reference before the category was flooded with competitors.

In all these stories, the common element is that the signal appears first on the Digital Shelf, in the form of subtle changes in searches, reviews, prices, rankings or launches, and only later in business indicators.

The Digital Shelf as an Early Warning System

The brands that win in digital channels are not necessarily those with the best products or the highest budgets. Frequently, they are the ones that best read what is happening in the market before that market changes.

The Digital Shelf, well observed and well analysed, offers that capability. Weak signals are there: in the search terms that grow, in the competitors that move, in the attributes that proliferate, in the reviews that change tone. The challenge is not accessing that information — today it is more accessible than ever — but building the discipline and processes to interpret it regularly and act on it in time.

Because on the Digital Shelf, by the time a weak signal becomes an obvious trend, the window to act with an advantage has already closed.

The post Stories from the Digital Shelf: How to Detect Weak Signals that Anticipate Market Changes appeared first on Flipflow.

TL;DR
Bad Bunny’s performance at Super Bowl LX captured much of the event’s attention, benefiting various brands. Limited releases and merchandising linked to the show caused searches and sales to skyrocket. The key for retail lies in planning collections and campaigns aligned with high-impact cultural moments.

Bad Bunny’s show at Super Bowl LX captured the attention of 124.9 million live viewers and generated 4 billion views on social media during the 24 hours following the event. This explosion of interest did not stop at entertainment: it quickly moved into the world of retail, where brands like Zara and Adidas saw their products become unexpected protagonists.

In this article, we explore how a performance lasting barely 13 minutes transformed the retail landscape, from fashion to merchandising, and what practical lessons retail professionals can apply to replicate these results in future events.

The “Benito Bowl” as a Value Machine for Brands and Retailers

When Bad Bunny took to the halftime stage at Super Bowl LX, he didn’t just offer a musical performance lasting 13 minutes and 41 seconds: he ignited a machine. It was an economic phenomenon measurable in conversation, searches, and sales.

According to media impact analytics estimates, the artist accounted for 38.81% of the total Media Impact Value (MIV – Launchmetrics) of the event, generating around 170 million dollars in media value. In practical terms, this means that almost 4 out of every 10 digital interactions related to the Super Bowl revolved around his performance.

This data has a clear interpretation for any retailer: consumer attention behaves like a scarce resource that is radically redistributed during major cultural events. When that focus is concentrated on a specific figure, everything surrounding them receives a “knock-on effect”.

Brands that appeared on stage, even indirectly, obtained exposure comparable to a traditional 30-second advert… without paying the cost of the advertising space. In today’s retail ecosystem, where advertising saturation makes acquisition more expensive, associating with cultural moments becomes a high-performance strategic alternative.

The Super Bowl has always been a global showcase. But this year’s halftime show served as a practical demonstration of something more relevant to commerce: pop culture is capable of activating demand faster than any campaign planned in isolation.

Fashion in Prime Time: Zara and Adidas at the Centre of the Game

Zara: When Fast Fashion Takes Up Luxury Space

Bad Bunny’s decision to wear a full Zara outfit during his performance (collared shirt, tie, sports-inspired jumper, and cream-toned chinos, with the “Ocasio 64” detail embroidered in tribute to his uncle) did not go unnoticed. Zara did not only outfit the lead artist but also the 50 dancers, the 12 band musicians, and the 40 members of the orchestra, marking its historic debut in a Super Bowl halftime show.

This fact is particularly significant because the Super Bowl has historically been the territory of premium labels or exclusive collaborations. On this occasion, a mass-market retailer occupied the aspirational space.

The result demonstrates a structural shift in fashion consumption:

• Cultural legitimacy no longer depends solely on price.
• Context can elevate the perception of value.
• The consumer interprets the product through the moment.

An extreme example illustrates this well: staff t-shirts given by Inditex to its employees as corporate gifts appeared in online resale reaching prices close to 35,000 dollars.

This case illustrates the power of rapid production in fast fashion. Zara, with its model of proximity and immediate response, integrated cultural elements in record time, elevating accessible garments to collectible status. For other retailers, the lesson lies in preparing limited editions that capture the essence of global events: it is not just about selling clothes, but about associating the brand with a cultural moment that generates immediate desire and controlled resale.

Adidas and the Choreographed Drop of the BadBo 1.0

Adidas took its collaboration with Bad Bunny, which began in 2021 with reworks of classic models like the Gazelle and Forum Low, to a new level with the launch of the BadBo 1.0, his first signature trainer. The brown colourway, limited to 1,994 pairs in reference to the artist’s birth year, sold out on 2nd February at a retail price of 160 dollars, but its resale reached an average of 795 dollars — a markup of 397% — on secondary platforms.

During the show, Bad Bunny presented the white “Resilience” colourway, which also sold out in minutes with resales at 271 dollars (+69% markup), while the dancers reinforced the brand’s presence with Sambas, Ballerinas, and Superstars in every televised shot.

Searches for Adidas experienced a 20% jump immediately after the performance, according to consumer trend data. This commercial choreography — pre-show drop to generate hype, live debut to accelerate desire, and post-event launch to capture demand — resulted in impeccable turnover in both physical stores and e-commerce.

The relevant element was not the product itself (the market is saturated with collaborative trainers) but the exact synchronisation with the moment of maximum televised attention of the year. Here lies one of the most important lessons for retail: a launch out of context competes against thousands of stimuli; within a cultural event, it competes against none.

Merchandising, Searches, and Sales: Retail as a “Reflection” of the Show

A Merchandising Market that Lives off Peaks

The merchandising associated with Latin music moves around 6.8 billion dollars globally, but its behaviour does not respond to stable demand. It works in waves of attention, and Bad Bunny’s performance at Super Bowl LX proved this clearly once again.

In the first 24 hours after the show, searches related to merchandising grew by 53%. During the following 72 hours, conversion skyrocketed: sales of products linked to the artist and the NFL universe increased by between 340% and 580%.

This pattern reveals something important: the consumer does not buy solely to own a product, but to preserve the experience. The t-shirt, flag, or accessory acts as a tangible extension of a collectively shared moment. The event happens in the stadium or on the screen, but its continuity materialises in retail.

That is why the channel (physical or digital) ceases to be a transaction point and becomes a space for cultural prolongation. The peak of conversation transforms into traffic, and traffic into sales, provided the product is available at the right time.

Source: Bad Bunny’s Super Bowl stage illustrates “surreal journey” through Puerto Rico – February 2026

Synchronising Physical and Digital Catalogues

The official collections linked to the show did not appear by chance. They were activated weeks before through pre-sales, staggered launches, and coordinated availability between e-commerce and physical stores. Data from streams and searches served as precise predictors: peaks in Spotify playlists indicated real-time stock adjustments, integrating accessible tools like Google Trends to optimise hybrid assortments.

The retailers who prepared their assortment in advance, integrating references aligned with the aesthetic of the show or the cultural context, captured the primary demand. Furthermore, they did so with better margins, because they sold based on relevance and not through discounts. In contrast, those who reacted after the event only accessed the final phase of the cycle: residual demand.

The difference between both behaviours was not in the product or the price, but in the timing. In massive cultural events, the right stock at the wrong time has practically the same value as having no stock.

Commercial Opportunities and Retail Tactics Left by the “Benito Bowl”

The impact of the show leaves several operational lessons for retail. Below is a practical summary applicable to retailers of any size:

1. Planning with Cultural Calendar Logic

Commercial planning cannot depend solely on traditional seasons. It must integrate relevant events from the cultural calendar into purchasing and campaigns. Events like the Super Bowl concentrate global attention for a few days but generate purchase intent even before they occur. Integrating them into the buying cycle allows for the anticipation of very specific demand peaks, usually between 3 and 5 days around the event.

2. Designing Capsule Collections and Exclusive Collaborations

Another implication is the real utility of capsule collections. It is not just about launching themed products, but about creating limited units linked to a recognisable narrative. When the consumer perceives legitimate scarcity and narrative coherence, the perceived value increases and collectibility appears, even in mass categories.

3. Coordinating Online and Physical Store Drops

It is also key to synchronise availability with moments of attention. The pre-show, the halftime break, and the subsequent hours do not show the same purchasing behaviour, but they are all part of the same cycle. Mechanics such as pre-orders, waiting lists, or priority access for recurring customers help convert interest into sales without depending on aggressive promotions.

4. Adjusting Advertising Spend to Specific Windows

Advertising spend should follow the same temporal logic. Concentrating activation in the days leading up and in the 24–72 hours following takes advantage of the maximum level of organic attention, which reduces the acquisition cost compared to campaigns without a cultural context.

5. Measuring Beyond ROAS

Finally, performance cannot be evaluated only with direct attribution metrics. Indicators such as share of voice or the increase in store traffic allow for a better understanding of the full effect of associating with major media moments. Without this broader vision, part of the return remains outside the analysis and the real profitability of the strategy is underestimated.

Source: Bad Bunny’s Halftime Show Was a Love Letter to Latin Memory – February 2026

When Culture Sets the Pace of Retail

Bad Bunny’s performance at Super Bowl LX exceeded the usual impact of a major televised show. It served to observe, in real-time, how a cultural moment can activate conversations, searches, and purchases immediately and in a coordinated manner.

The brands present around the show accumulated exposure and became integrated into the meaning of the event. It is this nuance that transforms an ordinary product into an object of desire or even a collectible, because the consumer does not perceive only what they buy, but the context to which it belongs.

For retail, the implication is direct. Assortment, price, or promotion remain relevant, but their effectiveness increasingly depends on the fit with the right cultural moment. Ultimately, understanding when the consumer is emotionally involved is as important as knowing what they want to buy. When both factors coincide, demand appears with an intensity that is difficult to replicate through purely promotional means.

The post From the “Benito Bowl” to the Shelf: Merchandising, Fashion, and Retail Opportunities after the Super Bowl appeared first on Flipflow.

TL;DR
Real-time store checks are transforming trade marketing in retail. They enable instant monitoring of prices, stock and promotions, improving in-store execution, prioritising actions and maximising ROI, with decisions based on up-to-date and reliable data.

In retail, the difference between good planning and a good result usually lies in store execution. Real on-shelf availability, the price applied, shelf visibility, well-set promotions and installed point-of-sale material drive daily conversion. This is why store checks remain a central piece of Trade Marketing.

The problem arises when information arrives late, incomplete or difficult to verify. In high-turnover categories or those with aggressive competition, waiting days or weeks to understand what happened at the point of sale reduces the room for manoeuvre. According to a study conducted by KX and the Centre for Economics and Business Research (CEBR), 80% of companies using real-time data report increases in their revenue, contributing to a collective growth estimated at $2.6 trillion globally. Conversely, retailers that depend on delayed reports make decisions based on obsolete information and miss opportunities to capitalise on trends in the moment.

In this context, geolocated and real-time store checks are becoming a standard for sales, trade and operations teams. Below, we will explore what changes with this approach, what benefits it brings and how to make the leap from an analogue model to a data-native one, without unnecessary friction.

What Is a Store Check? (and Why the Classic Model Falls Short)

A store check is a structured in-store verification to measure how a brand, category or promotion is being executed. It serves to answer very specific operational questions such as: is there stock? Is the price as agreed? Is the planogram being respected? Has the competition gained space?

In Trade Marketing, the store check is the basis for detecting deviations, prioritising actions and justifying investments in visibility or promotion.

Traditional store checks

The traditional model usually relies on face-to-face visits carried out by sales reps, merchandisers, promoters or agencies. Data capture is done with:

• Paper forms or spreadsheets.
• Photos without a clear standard, sent via instant messaging.
• Manual reports at the end of the day or week.
• Subsequent consolidation in spreadsheets or internal tools.

This approach may work in small operations or with few stores, but it becomes cumbersome as the number of points of sale, references (SKUs) and the need to react quickly grow.

For decades, the model has worked because it was the only thing available. But today we know it has significant cracks.

Typical limitations

The problem with the traditional store check is not that it is useless, but that it is slow, unreliable and difficult to scale. The most common limitations include:

• Low effective frequency: not all stores are reached with the desired regularity.
• Data that arrives late: the “what has happened” is known when the “what to do” has already lost its impact.
• Difficulty validating data: photos without context, without confirmed location or without an exact time.
• Inconsistencies in measurement: each person interprets what “well executed” means differently.
• Biases and manual errors: incomplete loading, estimated values, duplicates.
• Poor traceability: it is difficult to reconstruct what was surveyed, where, when and under what conditions.
• Unactionable reports: too much description and too little prioritisation by impact.

These limitations are not trivial. They represent decisions made with incomplete information, missed opportunities and Trade Marketing budgets that do not generate the expected return.

The “New Way” of Doing Store Checks: Geolocated, Digital-First and Evidence-Based

The new generation of store checks in retail is based on real-time market analytics platforms that integrate data from thousands of points of sale and convert them into insights that are actionable almost instantly. Solutions like flipflow connect prices, assortment, promotions, visibility in search engines and marketplaces, along with competitor metrics, to offer a dynamic view of the market, beyond the physical store visit.

Instead of depending on manual observations, brands continuously monitor what is happening in each channel. Trade Marketing teams can detect price changes at a key retailer, poorly configured promotions on the digital shelf or aggressive launches from competitors. Information is presented in comparative dashboards with filters by retailer, category, location or period, facilitating the quick identification of risks and opportunities.

This digital-first approach reinforces decision-making with structured data updated with high frequency. It allows for the validation of hypotheses on commercial execution: for example, determining if a drop in sales is due to lower digital visibility, a price mismatch against the competition or the absence of an agreed promotion.

Furthermore, these platforms align teams under a single source of truth, which is exportable and integrable with other internal tools. With this common base, it is possible to prioritise points of sale, optimise promotional investment and systematically verify correct execution in the market.

Finally, they act as a permanent competitive radar: they detect variations in price and assortment, changes in the category or the entry of new brands. This visibility allows for quick reactions and strategy adjustments before the impact on sales consolidates.

Why the Future of Trade Marketing is Data-Native and in Real-Time

Trade Marketing no longer competes only on execution, but on reaction capacity. In an environment where prices, assortment and promotions change daily between retailers and digital channels, making decisions with delayed reports is equivalent to operating blind.

Real-time store check platforms transform the internal conversation: they replace perceptions with continuous market evidence. The result is not just better reporting, but faster execution, which is defensible before management and directly connected to commercial impact.

1. Faster decisions and better ROI

The trade spend (investment in promotions, discounts, displays and commercial agreements) requires constant operational control. With real-time store checks, you can:

• Detect poorly implemented promotions within the first few hours.
• Redirect resources to stores with the highest losses due to stockouts.
• Adjust materials and mechanics based on real response.
• Avoid paying for executions that did not take place.

ROI improves because investment stops being retrospective and starts being managed during the campaign, not after.

2. Greater visibility of in-store execution

Commercial directors have spent decades wondering what is really happening at their thousands of points of sale. Aggregated reports show averages but hide real variability.

Modern store check platforms offer dashboards that answer critical questions in seconds:

• What percentage of my stores currently has stock of the star product?
• In how many points of sale is my Christmas campaign visible?
• Which retail chains execute our promotions best?

This visibility extends to all levels. The national manager sees trends by region, the regional manager drills down into their areas, and the supervisor reviews store by store. Everyone has the information they need for their level of decision-making.

3. Field team productivity and control

The field team stops being a data collector and becomes an executor guided by data.

With planning based on real incidents:

• Routes are prioritised based on potential economic impact
• Visits focus on solving previously detected problems
• Redundant audits are eliminated in stable stores
• Each intervention remains traced and verifiable.

The supervisor not only knows what the team visited, but what problem they solved and what effect it had. This reduces low-value visits, increases effective coverage and improves coordination with sales and head office.

4. Foundation for AI and automation

The structured and consistent data generated by digital store checks are the perfect fuel for artificial intelligence and machine learning.

With enough history, algorithms can:

• Predict stockouts: Identify patterns that precede stockouts and alert before they occur
• Detect anomalies: Automatically flag stores with atypical behaviours that require attention
• Optimise visit frequencies: Determine which stores need weekly visits and which can be audited monthly
• Suggest corrective actions: Recommend the best strategy according to the type of problem detected

This layer of artificial intelligence does not replace the human team, but it does multiply their effectiveness by prioritising where to focus attention.

The KPIs that Improve with Real-Time Store Checks

The implementation of modern store checks directly impacts key business metrics:

• Product availability (OSA – On Shelf Availability): This is perhaps the most critical KPI in retail. According to IHL Group, a 1% increase in OSA can increase sales by 2-4%. The global impact of shelf availability issues represents losses of approximately $634 billion annually for the retail sector. Real-time store checks allow for the detection of stockouts on the same day and the activation of urgent replenishment.

• Perfect display compliance: Many brands have agreements with retailers on how their shelf space should look. Stanford studies show that manual audits can have error rates of up to 20%, directly affecting compliance reliability. Stores that maintain more than 95% execution compliance outperform the rest by 8-10%, demonstrating the value of continuous verification and automatic alerts.

• Issue resolution time: This used to be measured in days or weeks. Now, the full detection-assignment-resolution-verification cycle can be completed in hours. This is especially critical during product launches or seasonal peaks.

• Promotional effectiveness: Being able to correlate visit data (was the promotion executed?) with sell-out data (did it generate incremental sales?) allows for the calculation of the real ROI of each promotional mechanic and the optimisation of the following year’s calendar.

• Competitive advantage in space: Real-time dashboards allow for share of shelf analysis and relative location versus the competition. Many brands have discovered that competitors systematically displace them in certain chains, information they can use in commercial negotiations with the retailer.

How to Transition from Analogue to Data-Native Trade Marketing

Adopting store checks based on real-time market analytics does not imply replacing field operational processes, but rather changing the source of truth on which the organisation works. The transition is primarily analytical and organisational: moving from occasional reports to continuous market monitoring. It works best when structured in stages and prioritising the effective use of data.

Phase 1 — Pilot in a key category or retailer

Start by monitoring a limited perimeter (for example, a strategic category or a priority retailer). This allows you to validate metrics, define relevant alerts and demonstrate internal value before scaling. The goal is not coverage, but generating the first actionable decisions.

Phase 2 — Definition of KPIs and operational alerts

Before expanding coverage, translate the commercial strategy into clear indicators: price deviations, absence of promotion, loss of visibility, stockouts or assortment changes. The platform must be configured to point out exceptions, not to produce more reporting.

Phase 3 — Incorporation into decision processes

Data only adds value when it enters the workflow. Integrate the dashboards into commercial routines: weekly meetings, campaign tracking and promotional planning. The team stops analysing “what has happened” and starts deciding “what to do now”.

Phase 4 — Integration with internal systems

Connect the platform with CRM, commercial planning tools or revenue management. In this way, incident detection can trigger actions: renegotiations, promotional adjustments or account prioritisation.

Phase 5 — Management culture based on continuous evidence

The key change is cultural: decisions are justified with current market data, not with historical data or isolated perceptions. Management, sales and trade marketing operate on the same source of truth.

Companies that follow this approach reduce internal friction because value appears from the first few weeks: better commercial conversations, faster decisions and less dependence on retrospective analysis.

The ROI of Total Visibility

The return does not come from “measuring for the sake of measuring”. It arrives when visibility is converted into decisions and actions. In real-time store checks, ROI usually appears on four fronts:

1. Recovered sales due to fewer stockouts: detect earlier, replenish earlier, lose less.
2. Better promotional effectiveness: the campaign is executed as planned and corrected while it is live.
3. Investment optimisation: trade spend is reassigned from stores with low execution to those that can capture demand.
4. Operational efficiency: fewer reporting hours, fewer unproductive visits, better team focus.

To estimate it credibly, it is advisable to compare before and after in a pilot: stockouts, promo compliance, sales in treated versus control stores, and field operational costs.

Furthermore, there is another intangible but very valuable benefit: the peace of mind of knowing what is happening in your points of sale right now, not last week.

Conclusion: From Reactive Control to Live Management

For years, Trade Marketing has operated with a retrospective logic: measure, consolidate, analyse and, finally, act. The problem was not a lack of effort, but a lack of immediacy. In a retail environment where competitive dynamics change daily, that sequence is insufficient.

The new generation of store checks introduces a change of focus: the store —both physical and digital— moves from being audited occasionally to being monitored continuously. With information available in real-time, management evolves from corrective to adaptive.

This context modifies the role of Trade Marketing within the organisation. It becomes a constant source of operational intelligence for sales, revenue management and senior management, supporting decisions with current market signals instead of hypotheses or late reviews.

Adopting a data-native model implies working with greater precision: identifying where to intervene, when to do so and with what priority, reducing the distance between what was planned and what was executed at the point of sale.

Ultimately, the value lies in managing retail as a living and changing system. Brands that operate under this logic will execute with greater consistency and compete with an advantage thanks to their visibility and capacity to react.

The post Real-time Trade Marketing: The New Era of Geolocated Store Checks in Retail appeared first on Flipflow.

TL;DR
For companies in the chocolate sector in Mexico, Chile and Spain, innovation is not an abstract concept, but a direct response to the demands of a fast-changing consumer. After analysing the UK market in our latest category report, it is clear that this country acts as a mirror of what we will soon see on FMCG shelves across the Spanish-speaking world.

The Context of the International Chocolate Market

The chocolate market in the United Kingdom reached $6.85 billion in 2025 and is projected to grow to $10 billion by 2035, with a compound annual growth rate of 3.8%, driven by the demand for premium products and online channels. Within this context, chocolate sharing pouches (pouches) stand out as a key format in confectionery, with a surge in flexible packaging such as resealable bags that respond to the search for convenience, sustainability and the at-home consumption experience.​

Although 95% of Britons consume chocolate and 4 out of 5 do so at least once a week, HFSS regulations have reduced visibility at key in-store points and curtailed impulsive consumption, accelerating innovation in reformulation, recyclable materials and value propositions such as complex textures and premium flavours. 

In this second article based on data from our SaaS, we delve into how packaging formats and new ingredients are redefining commercial success. While in Mexico chocolate has deep cultural roots linked to tradition, and in Chile per capita consumption is one of the highest in the region, the United Kingdom leads the adoption of premium formatspremium and sustainability solutions that lead the way for any exporter or local manufacturer.

The Hegemony of Formats: From “Sharing” to “Portioning”

The sharing pouch format dominates the British shelf, but its use has evolved. According to data from our report, the zip-lock Doypack (Stand-up Pouch) is the most popular format in the category. Its ability to stand upright facilitates shelf visibility and improves the user experience at home.

Airtight closure as a purchase requirement

One of the most relevant findings is the change in perception regarding the zip closure. 54% of British consumers consume the contents of a sharing bag alone over several days. This has transformed the airtight or resealable closure. This element was previously perceived as an optional added value, but currently consumers consider it a basic purchase requirement. In practical terms, the closure fulfills three functions that influence repeat purchases:

• Preservation: maintains texture and freshness.
• Convenience: allows opening, serving and storing without complications.
• Consumption control: facilitates portioning without the product deteriorating.

This phenomenon marks a shift away from the traditional concept of “sharing” towards “portioning”. Companies in Spain and Latin America can draw a clear lesson: the consumer seeks to self-manage their indulgence. Making it easier for the product to be opened and closed several times allows the manufacturer to offer larger formats (100g-200g) without the customer feeling they must finish it in one go for fear of it going stale.

Other formats on the shelf

Although the stand-up pouch leads, the report identifies other formats with a relevant presence, which are used to play with price, occasion or differentiation:

• Pillow Bag: Still a cost-effective option for entry-level or private-label products.
• Mini-Sharing / Grab Bags (80g-90g): These function as an intermediate step between the individual bar and the large bag, ideal for on-the-go consumption.
• Flat Bottom Gusset Bag: Commonly used for irregularly shaped chocolates or larger truffles that require a stable base and a more rigid presentation.

For innovation and marketing teams, the lesson is clear: format is no longer chosen solely for efficiency. It is chosen for its ability to sustain a real and repeated consumption experience.

Innovation Insights: Flavours and Textures that Justify the Price

In a market where the average price has risen by 17% in the last quarter of 2025, innovation is the primary tool for maintaining perceived value. Brands that manage to sustain prices between £3 and £5 do so through propositions that offer a complex sensory experience.

The “Fully Loaded” trend

The report highlights the success of “Fully Loaded” propositions. Brands like Marks & Spencer, with their Choc Marks range, are redefining what the consumer expects from a chocolate bite. These propositions combine multiple inclusions and textures in a single piece: pistachio, wafer, toasted corn or sea salt.

This technical complexity allows the price to be perceived as fairer. When the product offers crunch, creaminess and salty nuances simultaneously, it stops competing solely on volume to compete on the intensity of the experience. Mexican companies, with their access to unique local ingredients, have a huge field of exploration here for the export market.

The pistachio phenomenon and the viral effect

Flavour is the engine of the sector, and in 2026 pistachio is positioned as the star ingredient. Driven by the viral effect of “Dubai Chocolate” on social media, pistachio has moved from being a niche flavour to a clear path for launching modern variants. These versions are perceived as accessible luxury and allow traditional brands to refresh their catalogue without leaving the FMCG price range.

On the other hand, “blonde” chocolate (caramelised white chocolate) has ceased to be a limited edition to become a stable flavour on the British shelf. Supermarkets like Waitrose and Sainsbury’s have normalised its presence, opening the door to new permanent combinations that were previously considered too risky.

Regulatory Impact and Healthy Reformulation

The HFSS (high in fat, sugar and salt) legislation in the United Kingdom has forced an acceleration in the reformulation of bagged chocolate. This regulation, which came fully into force in January 2026, restricts the placement of less healthy products at checkouts or supermarket entrances.

The use of functional fibres

To compensate for sugar reduction without sacrificing the creaminess that the consumer demands, brands are turning to technical ingredients. Inulin, a plant-based fibre, is increasingly being used to maintain the structure and sensory profile of chocolate with fewer calories.

In countries like Chile, where the culture of nutritional warning labels is well established, these British technological solutions represent a learning opportunity. The challenge is not simply to remove sugar; it is to reformulate so that the consumer does not notice the difference in the mouth. Innovation in functional ingredients is the key to maintaining competitiveness in markets with strict health legislation.

Sustainability: From Plastic to Paper

Sustainability has moved from being a marketing message to an operational necessity. The flipflow report shows an accelerated transition towards more environmentally responsible packaging.

Recyclable paper bags and mono-materials

Leading brands are migrating their multi-layer plastic formats towards Paper-Based Pouches (recyclable paper bags) or easy-to-recycle mono-materials. Although this change presents technical challenges, especially in maintaining the seal and moisture barrier, manufacturers who have led the way are already winning the preference of younger consumers.

This trend is especially relevant for Spanish companies, which operate under increasingly demanding European circular economy directives. Innovation in materials that maintain zip-lock functionality but are 100% recyclable is one of the fields with the greatest growth potential.

Brand Values and New Consumption Habits

The report reveals that success in the chocolate pouches segment also depends on the emotional and ethical connection with the consumer.

The ethical message as a purchase determinant

Tony’s Chocolonely’s case is paradigmatic. Its communication focused on eradicating slavery in cocoa cultivation demonstrates that company values can be just as determinant as the product format.

Source: Jon Richards – LinkedIn – 2025

This approach connects especially with Gen Z and Millennials, who are willing to pay extra for products with clear fair trade certifications. In Mexico, where the origin of cocoa is a mark of national identity, there is immense potential to communicate these stories of social impact and sustainability.

E-commerce growth and the “Big Night In”

The consumption occasion is also changing. E-commerce growth and quick commerce platforms has shifted the peak demand for chocolate towards the night. The highest number of impulsive purchases via apps is recorded between 20:00 and 22:00.

This habit favours the use of digital Retail Media. With a paid share of 4.6%, still relatively low, brands that invest in advertising specifically targeted at these times will be able to compensate for the loss of physical visibility at checkouts due to HFSS regulations.

The “Big Night In” (movie or games night at home) is the perfect scenario for sharing pouches, and brands that best adapt their communication to this specific moment will lead the category.

Conclusion: Useful Innovation, Clear Formats and Packaging that Solves Everyday Needs

The detailed analysis of the chocolate pouches category in the United Kingdom offers us a clear roadmap for innovation. It is not enough to manufacture quality chocolate; current success depends on a precise combination of a functional format (Doypack with zip closure), a complex sensory experience (trending textures and flavours like pistachio) and a firm commitment to sustainability and health.

For chocolate companies, these data represent an opportunity to stay ahead of the competition. The trends towards portioning, reformulation using functional fibres and the adoption of recyclable materials are already here. The general direction is clear: brands that innovate with utility, choose easy-to-understand formats and design packaging that accompanies the real use of the consumer will win.

If you want to delve deeper into insights on innovation, formats, flavours and sustainability in the UK chocolate market, you can download the full report by clicking here.

The post What Makes Chocolate Successful Today? Key Innovation Drivers in Formats, Flavours and Sustainability appeared first on Flipflow.

TL;DR
In AI product and brand recommendations, every response varies significantly in content and order. Chasing the top spot is of little use; the key is appearing frequently, as a repeated presence in these lists indicates relevance and authority.

In recent months, many brands have started asking themselves the same thing: if more and more users are asking ChatGPT, Gemini, or Perplexity to recommend products, does it make sense to “position” oneself in those answers as was previously done on Google? 

A new study by SparkToro and Gumshoe.ai points to an uncomfortable answer: AI-generated recommendation lists are so volatile that chasing fixed rankings is, quite simply, a bad investment.

A Massive Experiment to Put AI to the Test

The work by SparkToro and Gumshoe starts from a very specific question: are AIs consistent enough to accurately measure a brand’s visibility in their recommendations? To answer it, they conducted 12 types of brand and product recommendation queries across the 3 most popular AI models in the United States (ChatGPT, Claude, and Google Search’s “AI-created view”). They then analysed the nearly 3,000 different responses received. 

The questions spanned very broad requests, such as “science fiction novels”. They also included much more specific cases, such as “Volvo dealerships in Los Angeles” or “cloud computing providers for SaaS”. Each prompt was repeated dozens of times in each tool. Afterwards, the results were normalised into ordered lists of brands or products. This allowed them to measure which elements were repeated and which ones changed from one response to another.

The following image shows a visualisation of the huge variety of product/brand combinations generated by the 12 different prompts, executed between 60 and 100 times each:

The statistical conclusion is definitive: less than 1% of responses repeat the exact same list of brands when the same request is made to the same model. And the probability of the list being ordered in the same way falls below 0.1–0.3%, even in categories with few possible options.

Three Types of Variation in Each Response

Volatility is not limited to the “top 3”. AIs modify three variables at once almost every time:

• The list of brands or products.
• The order in which those recommendations appear also changes.
• And the total number of items included in the list changes, ranging from 2–3 items to more than 10.

The breadth of the “universe of options” also influences this. In queries with thousands of possible answers, such as science fiction novels, the diversity of lists is enormous, while in cases like Volvo dealerships in a specific city, the variation is reduced because there are simply fewer possible candidates.

But even in these narrower scenarios, the data shows that the models do not behave like a classic search engine ranking: the order shifts from response to response and the composition of the list never fully settles.

In the words of Rand Fishkin, co-founder and CEO of SparkToro:

“These tools are probability engines: they’re designed to generate unique answers every time. Thinking of them as sources of truth or consistency is probably nonsensical.”

Probabilistic Engines, Not Search Rankings

The study forces us to abandon a widespread assumption: thinking of AI as a Google SERP with a different design. Generative models function as probabilistic text engines that, based on a context, choose from many possible answers; they do not consult a static table of positions.

SparkToro summarises it clearly. If you ask an AI to recommend brands or products a hundred times, almost all the responses will be unique in those three dimensions (list, order, and length). This happens while users formulate prompts that are very different from each other, even when they share the same purchase intent, which further multiplies the diversity of the result. The SparkToro and Gumshoe.ai study goes much deeper into this semantic part. It explores the different ways people express the same request to the AI. If you are interested, you can read more about this part of the article by clicking on this link.

The consequence is that concepts like “always being first” in AI responses have little empirical support. At most, a brand can aspire to be part of the set of candidates that appear frequently when the model tries to solve a specific need: choosing a digital bank, e-commerce software, headphones, or an online supermarket.

When Presence Carries More Weight than Position

Amidst such volatility, SparkToro’s own study identifies a much more stable data point: the frequency with which a brand appears in responses. This is what several analysts are already starting to call “AI visibility”. It is not so much about what position you appear in, but in how many responses you are present when a family of related queries is formulated.

This phenomenon can be illustrated with a specific example from the report. In one of the analysed queries, related to “e-commerce consultants”, the agency Smartsites appeared in 85 of the 95 responses returned by Google’s AI, although it did not always occupy the same position. In other words, its position fluctuated, but its presence was almost constant—a clear sign of leadership in that category.

The message is direct for the retail sector and brands. In recommendation lists created by AIs, appearing repeatedly matters more than topping the ranking occasionally. The metric is starting to look more like an AI “Share of Voice” than a traditional top 10.

What Brands and Retailers Can Do From Now On

The first practical implication involves expectations. No retailer or manufacturer can guarantee “always being first” in an AI response for a specific category, no matter how much budget they dedicate to content or campaigns. The reasonable goal is to aim to be part of the set of brands that the AI considers relevant and mentions frequently for a given intent.

Beyond that, experts point to three lines of work:

• Build authority in the sources that feed the models: authoritative media, own documentation, in-depth content, and verified reviews, both on marketplaces and specialised sites.
• Clarify the brand’s category and value proposition, so the AI can easily associate it with specific needs (“local online supermarket”, “mid-range electronics store”, “eco-friendly household brand”, etc.).
• Continuously monitor how AIs describe the company and which products they choose as examples. This will help detect both positioning opportunities and potential reputation crises.

For retail, there is also a specific nuance: many AI queries mix product, service, and logistics information. The models value everything from availability and price to return policies, shopping experience, or perceptions of sustainability, according to recent analysis on how AI constructs its recommendations in e-commerce. This requires thinking of “AI visibility” as a global reflection of the brand, not just an extension of product page SEO.

A Shift in Mindset for the Sector

The SparkToro research arrives at a moment marked by economic pressure, consumer volatility, and the rise of AI. These factors are reshaping the path to purchase. For retail, this involves accepting that visibility is no longer played out only in physical shop windows or Google search results. It is also contested in synthetic, personalised, and largely unpredictable conversations.

In this new scenario, the temptation to search for “the new magic metric” is understandable. But the data reminds us that there is no direct equivalent of Google’s “top spot” in AI responses, and basing investment decisions on unstable rankings can prove expensive.

What does seem clear is that repeated presence in AI recommendations will increasingly be an indicator of relevance and authority for brands. Achieving this requires combining a good product, a good experience, and a good reputation, translated into signals that models can read and reuse. And measuring it correctly will require less obsession with exact position and more of a culture of probabilistic data, experimentation, and methodological transparency.

The post In AI Recommendations, What Matters Is Appearing Often, Not in Which Position appeared first on Flipflow.