Retail media has become one of the most powerful growth levers in European beauty e-commerce. As shoppers move their skincare routines online and search for solutions across Amazon, specialist pharmacies and beauty retailers, cosmetics brands are locked in an increasingly competitive battle for digital visibility. Sponsored Products, Sponsored Brands and display formats now shape what consumers see, what they click and ultimately what they buy. In a sector worth close to €120 billion, how brands appear on these digital shelves is no longer a tactical concern. It is a core driver of growth, profitability and market share.

Against this backdrop, a fundamental strategic question has emerged for marketing and e-commerce teams: how much should be invested in paid media to sustain visibility, and at what point does that investment become inefficient.

Analysts expect retail media to account for just over one‑fifth of global digital ad spend in 2025, while many CPG brands already allocate around a quarter to a third of their digital budgets to retail media channels—health and beauty brands often sit at the upper end of that range, reflecting the category’s performance focus and intense competition. As retail media networks scale on the back of retailers’ first-party data and brands’ demand for measurable, conversion-focused performance, the line between necessary investment and diminishing returns is becoming harder to define. In cosmetics, where competition for physical shelf space has fully translated into competition for digital placement, the tension between paid and organic visibility is especially pronounced.

How the Benchmark Looks at Retail Media in Beauty

The Retail Media section of the benchmark analyses the paid advertising activity that brands deploy within retailer sites and marketplaces. It considers both how often a brand appears thanks to paid placements (Paid Share) and how often it appears organically (Organic Share).

The Paid Dependency Ratio, compares the level of paid investment with total visibility. A high ratio highlights brands that must spend heavily to secure modest presence. A low ratio indicates that organic equity and content are doing much of the work, with paid media acting as an accelerator rather than the main engine.

Data comes from Q3 2025, covers 12 leading beauty brands and the results are broken down by country and by retailer, with a particular focus on Amazon and selected specialists: Primor (Spain), Douglas (Italy), Boots (UK) and Easypara (France).

While the first post of this series focused on organic Digital Shelf visibility, this second instalment dives into paid versus organic share, investment strategies, efficiency dynamics and the strategic gaps that are shaping the next phase of competition in European beauty retail media.

National Investment Patterns: From UK “Pay‑to‑Compete” to France’s Organic Bias

One of the most striking findings from the report is the dramatic variation in how brands allocate resources between paid media and organic visibility across the four European markets studied. The data reveals a clear gradient of paid-media intensity, where the United Kingdom stands out as the most paid‑dependent country, with an average Paid Share of 15.74% across brands. Italy follows with 12.73%, then Spain with 8.72%, while France remains the most organic‑driven market at 7.05%.

This gradient mirrors the competitive dynamics observed on the Digital Shelf. In the UK, high levels of paid activity create a “pay‑to‑compete” environment where sponsored placements act as an entry ticket rather than a differentiator. Even brands that are usually organic‑leaning, such as Vichy or Nivea, increase their paid mix sharply when operating in British retail media.

Italy shows similar but slightly lower dependency, with many brands using paid media to secure visibility within a fragmented retailer ecosystem. Spain, by contrast, demonstrates a more balanced approach. Some brands, such as Olay and Nivea, invest aggressively, whereas others maintain almost entirely organic presence. France goes further in that direction; limited retail media expenditure aligns with the dominance of long‑established pharmacy brands and a strong organic base built over decades of offline credibility.

For international beauty teams, these differences mean the same paid strategy cannot be rolled out uniformly. Budget allocations and expectations of return must be calibrated per country.

Brand Archetypes: Distinct Paid vs. Organic Strategies

The benchmark reveals a clear segmentation of brand strategy aligned with product positioning and category characteristics. Understanding these archetypes provides actionable intelligence for brands contemplating their paid media investment levels.

Dermocosmetic and Pharmacy Brands: Paid-Media Dependent

Brands positioned in the dermocosmetic and pharmacy segment—including Neutrogena (14.72% global average paid share), Olay (14.02%), and Vichy (13.89%)—show consistently higher reliance on paid media across markets. This pattern reflects category dynamics where paid visibility often functions as a table-stakes requirement: consumers accustomed to searching for functional, efficacy-driven skincare products in competitive retail environments expect sponsored results to occupy prominent positions.​

Additionally, these brands often compete against a deep bench of dermocosmetic options, necessitating paid investment to defend and expand shelf presence. The investment profile suggests that in the dermocosmetic category, organic presence alone—no matter how well-optimised—carries insufficient weight to compete effectively against brands willing to bid aggressively for high-intent keywords.

Mass-Market and Equity-Led Brands: Organic Foundations

In contrast, globally recognised brands with established equity and heritage demonstrate lower paid dependencies. L’Oréal Paris records a global average paid share of just 5.31%, and Garnier reaches 8.46%. These lower ratios reflect the outsized weight of organic factors for mass-market brands: content depth, review velocity, social proof, and consumer awareness drive discoverability independent of paid support.​

Niche and Regional Brands: Highly Polarized Profiles

Smaller or more regionally focused brands exhibit the widest range of paid strategies. Cantabria Labs invests minimal paid resources globally (1.30% average) yet achieves 11.80% visibility in its home market of Spain through organic strength, demonstrating the power of local equity. Sesderma records virtually zero paid investment (0.09% average) and shows weak performance across all markets, reflecting either a strategic choice to compete exclusively on organic factors or, more likely, insufficient resources for paid media investment in highly competitive environments.​

Where Beauty Brands Spend: Amazon, Specialists and Ad Formats

Across the four markets, Amazon is the central engine of retail media in beauty. Around half of all spend flows to Amazon placements, underlining its importance for both scale and conversion. Primor in Spain, Douglas in Italy and Boots in the UK form a second tier of investment, capturing meaningful but much smaller portions of spend. Easypara in France receives minimal budget, which is consistent with that country’s broader organic tendency.

This distribution reveals a dual reality. Amazon concentrates performance media, where brands chase lower‑funnel conversions at scale. Specialist retailers, on the other hand, play a crucial role in shaping brand and category perception within their home markets, even if paid spend there is lower. For example, Primor remains fundamental for beauty in Spain, Douglas for Italian prestige and Boots for skincare credibility in the UK.

A similar skew appears in ad formats. Sponsored Products account for roughly 59% of investment, far outweighing Sponsored Brands (around 18%), Sponsored Display (about 14%) and Sponsored Video (just over 8%). Beauty advertisers favour placements that have direct impact on ranking and conversion, often on product listing pages where shoppers are making final choices.

The downside of this configuration is an underinvestment in upper‑funnel and mid‑funnel tactics—especially video—that could drive awareness, education and long‑term preference for more complex or premium lines. Many brands are concentrating their budget on immediate performance at the expense of building future demand.

Efficiency Analysis: The Paid Dependency Ratio

One of the most illuminating insights from the benchmark is the Paid Dependency Ratio—a metric that compares the share of visibility paid through advertising against the total visibility achieved. When this ratio is high, brands are paying disproportionately for visibility; when it is low, organic fundamentals are doing the heavy lifting and paid media acts as an accelerator.​

High Dependency: The Efficiency Warning Signal

Certain brand-market combinations show alarming inefficiency. Vichy in the UK stands out as the most glaring example: investing 33.33% of budget into retail media yet achieving only 5.52% total visibility creates a 6.04x dependency ratio, indicating severe misalignment between spend and results.​

Common drivers of high dependency ratios include:

• Weak product detail pages: Insufficient content, missing attributes, or poor images that fail to convert paid traffic into sustained visibility
• Thin reviews and ratings: Limited or recent review velocity that reduces algorithmic weight and shopper confidence
• Misaligned targeting: Broad keywords or placements that generate impressions but not conversions, inflating spend while diluting efficiency
• Competitive overbidding: Excessive competition for branded or category keywords that drives CPCs beyond rational ROI thresholds

High Efficiency: Organic Leverage

In contrast, several brand-market combinations demonstrate exceptional efficiency. Cantabria Labs achieves 11.80% visibility in Spain with only 0.45% paid investment (0.03x ratio), indicating that organic equity is driving the vast majority of visibility. Garnier in Spain shows similar efficiency: 18.54% total visibility with just 3.88% paid share (0.21x ratio). Weleda in the UK, despite a substantial 20.59% paid share, converts this into remarkable 27.71% total visibility (0.74x ratio) due to strong organic fundamentals that amplify paid investment.​

These efficiency leaders share common characteristics:

• Rich product content: Detailed descriptions, multiple attributes, and comprehensive information aligned to retailer taxonomies
• Strong review profiles: Abundant, recent, and authentic reviews that generate algorithmic weight and consumer confidence
• Precise keyword coverage: Targeting of high-intent, lower-competition terms where paid investment delivers outsized impact
• Solid baseline equity: Established brand recognition and consumer familiarity that reduce the burden on paid media to drive discovery

The Blind Spot Problem: Zero Paid, Zero Visibility

A critical finding from the analysis concerns brands with zero paid investment in specific markets. Sesderma, Cantabria Labs, and Bella Aurora record 0% paid share in several countries (notably France and the UK for all three brands), resulting in 0% total visibility in those markets.​

This pattern reveals a fundamental market dynamic: in high-friction, competitive environments, organic visibility alone cannot lift a brand from a standing start. Without initial paid investment to generate impressions and traffic, even high-quality organic fundamentals remain invisible. The remedy requires a staged approach: minimal initial investment focused on hero SKUs and localised high-intent keywords with manageable competition, paired with immediate investment in organic strengthening—content enrichment, reviews and ratings seeding, and structured data optimisation—so that early paid investment converts into sustainable organic visibility.

Key Conclusions and Strategic Takeaways for Beauty Brands

Flipflow’s benchmark points to several structural truths shaping competition for beauty brands in Europe. Market leadership, first of all, is neither uniform nor purely budget-driven. The brands that dominate Digital Shelf visibility in a given country are not always the biggest investors in paid media. Some outperform through strong organic equity and content execution; others rely heavily on tactical spend. Defining the right balance between these levers at both brand and market level is now a prerequisite for setting realistic objectives and budgets.

Efficiency, meanwhile, varies sharply by geography. The UK stands out for its high Paid Share combined with some of the weakest Paid Dependency Ratios, signalling intense competition and a growing risk of overpaying for marginal visibility gains. Spain shows the opposite dynamic. In a more organic-driven environment, brands such as Garnier and Cantabria Labs convert limited paid pressure into strong and resilient presence.

Investment patterns remain heavily biased towards Amazon and lower-funnel formats. While this approach delivers conversion at scale, it often leaves strategic gaps in awareness, education and premium brand storytelling, all critical in higher-value skincare. Specialist retailers continue to shape brand perception in their core markets and deserve a more central role in retail media strategies aimed at authority building, not just short-term sales.

The key takeaway is clear. Sustainable Digital Shelf performance is built on the synergy between organic strength and targeted paid amplification. Buying visibility alone leads to rising costs and fragile rankings. Relying solely on organic equity risks disappearing in markets where competitors invest aggressively. For category managers and e-commerce leaders, Flipflow’s “Digital Shelf & Retail Media Performance in European Beauty – Q3 2025 Cross-Market Benchmark” provides the empirical foundation to design this balanced model with confidence. Download it to access brand-level visibility scores, paid versus organic splits and retailer-specific efficiency diagnostics.

The post Retail Media in European Cosmetics: Paid vs. Organic and the Efficiency Paradox appeared first on Flipflow.

Black Friday has become an event where every minute counts. During the days of maximum commercial intensity between Black Friday and Cyber Monday, brands face an unprecedented challenge: making strategic data-driven decisions while millions of consumers browse, compare and purchase simultaneously.

But when the party is over and it is time to take stock, the final question is always the same: What worked and what didn’t?

The difference between companies that triumph and those that simply survive Black Friday lies in their ability to monitor the right indicators at the precise moment. It is not enough to review the figures at the end of the day. The competition is fought minute by minute, and those with immediate visibility can react, adjust and optimise while the commercial battle unfolds.

This article analyses the 10 key indicators you should have watched during Black Friday 2025, explaining why they are vital and how to interpret them to turn data into concrete actions.

Why is “Real-Time” Non-Negotiable during Black Friday?

During Black Friday, the digital environment experiences extreme volatility. Prices fluctuate, inventories run out in minutes, competitors adjust their strategies and consumer behaviour changes depending on the time of day. Working with data that is even a few hours old equates to making decisions blindly.

Real-time monitoring allows critical problems to be detected before they turn into catastrophes. If your website starts loading slowly due to massive traffic, every additional second can translate into thousands of frustrated users abandoning your site. Detecting this problem six hours late involves losing a significant amount of sales. In real time, you can activate additional server resources or implement immediate technical solutions. The ability to react quickly also allows you to capitalise on unexpected opportunities. If one of your products performs exceptionally well due to a viral mention, you can increase advertising spend, secure additional stock or create complementary campaigns while interest is at its peak.

Furthermore, consumer behaviour in 2025 has been different from previous years. Nowadays, buyers visit multiple shops before deciding, compare prices online and offline simultaneously, and demand personalised experiences even during the shopping rush. An automated message arriving hours after they abandon the cart may be too late. A product recommendation that loads after the user’s attention span has lapsed will never be seen.

The retailers that have won Black Friday 2025 were not lucky. They had dashboards showing them exactly what was happening while it was happening, with alerts triggering immediate actions. While others analysed the data a day after Cyber Monday, they had already adjusted their strategies multiple times.

Critical Sales KPIs

1. Conversion rate

The conversion rate measures the percentage of visitors who completed a purchase. During Black Friday, this indicator reveals if your attraction strategy is really working or if you are burning through budget bringing in traffic that does not convert.

The global average for e-commerce conversion is around 1.9%. For specific sectors such as beauty and wellness, rates of up to 6.8% can be reached. Brands in the top 20% of performance exceed 3.2%, and those truly optimised are around 4%.

The value of monitoring conversion in real time is being able to segment it by multiple dimensions simultaneously. Breaking it down by acquisition channel, product category, device or time slot reveals much more actionable information. You could discover that your conversion from mobiles is significantly lower than that from desktops. This real-time information allows you to immediately investigate if there is a technical problem, a confusing step in the purchase process on small screens or if your offers are not presented attractively on mobiles.

2. Return on Ad Spend (ROAS)

Return on Ad Spend (ROAS) measures how much revenue each euro invested in advertising generates. During Black Friday, where the cost of ads skyrockets, maintaining a healthy ROAS becomes a complex and vital balancing act.

If you invest one thousand euros in ads and generate five thousand euros in attributable sales, your ROAS is 5:1. During Black Friday, a ROAS of 3:1 or higher is usually considered successful, although it varies by sector and margins.

Real-time monitoring of ROAS allows you to redistribute budget dynamically. If one campaign obtains a ROAS of 7:1 while another barely reaches 2:1, it makes sense to move budget towards the first. This flexibility can significantly multiply the total effectiveness of your investment.

3. Average Order Value (AOV)

Average Order Value (or AOV) indicates how much an average customer spends on each transaction. This KPI is especially revealing during Black Friday because it reflects the effectiveness of your cross-promotion, product bundling and volume offer strategies.

Monitoring AOV in real time allows you to evaluate if your tactics to increase basket size are working. If you have implemented offers like “free shipping on orders over 50 euros”, the AOV will immediately show you if customers are responding to these incentives. The AOV also reveals if your discounts are attracting high-value customers or bargain hunters. A customer buying with an AOV of 150 euros deserves different treatment to one buying for 35 euros.

On the other hand, a sudden drop in average order value may indicate that your discounts are so aggressive that customers are only buying individual products without exploring the rest of your catalogue. Detecting this trend in real time allows you to adjust the presentation of complementary offers or modify the thresholds of your promotions.

User Behaviour KPIs

4. Traffic sessions and traffic quality

The volume of sessions reflects how many users visit your site, but during Black Friday you need to go beyond simple counting. Receiving 100,000 visits during Black Friday means nothing if 80,000 are bots or accidental clicks.

Traffic quality matters as much as or more than quantity. Thousands of visitors leaving your page immediately represent a cost with no return, especially if you paid to attract them.

Quality is evaluated via metrics such as bounce rate, average time on site and pages viewed per session. High-quality traffic shows low bounce rates, prolonged times and multiple pages visited.

During Black Friday it is fundamental to segment traffic by acquisition source. Organic traffic usually shows higher purchase intent than generic paid traffic. Understanding which channels bring you higher quality visitors allows you to optimise budget allocation.

5. Web performance

Loading speed directly influences conversions. Studies show that every additional second can reduce conversions by between 7% and 20%. During Black Friday, when users actively compare multiple shops, a slow site equates to lost sales.

Monitoring must include technical metrics such as time to first byte, full load time and time to interactive. During massive traffic events, it is common for performance to degrade progressively. Your site may start loading in two seconds but slow down to five or six as traffic increases.

In addition to general performance, you need to watch the highest value pages: best-selling products, cart and checkout. A performance problem at any of these critical points disproportionately affects your results.

6. Cart abandonment rate

Cart abandonment measures the percentage of users who add products to the cart but do not complete the purchase. This indicator reflects friction in the final stages of the conversion funnel, where the customer has already shown clear intent.

In e-commerce, 70.22% of carts are abandoned on average. On mobile, that rate rises to 75.5%. During Black Friday, these numbers can vary significantly, especially in fashion (84.4%) and luxury/jewellery (81.4%). The most frequent reasons include unexpected shipping costs, complex checkout processes, lack of preferred payment options or that the customer is comparing options.

During Black Friday, monitoring abandonment in real time allows you to implement immediate countermeasures: activate retargeting campaigns, send automated reminders or offer additional incentives specifically aimed at users with abandoned carts.

Competitive Monitoring KPIs

7. Competitor price tracking

During Black Friday, prices fluctuate constantly. A product costing €199 at 10:00 in the morning may cost €169 at 11:15 because a competitor dropped the price first. Monitoring competitor prices in real time allows you to maintain your strategic positioning.

Monitoring does not necessarily imply matching every offer. It requires understanding your positioning strategy and acting accordingly. If your differentiation is based on service or quality, you can afford not to be the cheapest, but you must know the price difference to ensure your value proposition justifies it.

8. Buy Box and visibility in marketplaces

If you sell on marketplaces like Amazon, getting the Buy Box drastically determines your sales volume. Most buyers complete the purchase from the Buy Box without exploring alternative offers. Losing the Buy Box equates to losing visibility and sales.

Algorithms consider multiple factors: price, stock, shipping speed, seller rating and fulfilment history. During Black Friday, these factors fluctuate constantly.

Monitoring your position minute by minute allows you to react before losing too many sales. If you lose it, you can analyse which factor displaced you and decide if adjusting your offer makes strategic sense.

9. Stock and availability

Inventory is the most common bottleneck on Black Friday. Correctly predicting how much stock you need is almost impossible. Monitoring availability in real time prevents two disasters: running out of stock when there is still demand, or having excess stock that you do not sell later.

Having automated alerts when stock drops to 20% of what was planned, by category and by SKU, allows you to make decisions in real time. You can increase the discount to accelerate sales before a stockout, switch your ads to products with better availability, or simply order express restocking if there is still time.

It is equally important to monitor your competitors’ stock. If a rival runs out of stock of a popular product that you still have available, you can temporarily increase your advertising spend to capture the unsatisfied demand.

Digital Shelf Analytics

Digital Shelf analytics goes beyond sales: it measures your visibility, which predicts future sales.

10. Share of Voice and visibility

Share of Voice measures what percentage of the digital conversation in your category belongs to you. This indicator combines search engine positioning, presence in marketplaces, social media mentions and volume of advertising impressions compared to the competition.

During Black Friday, your visibility in search results, marketplaces and digital media determines what portion of the total demand you can capture.

Real-time monitoring of Share of Voice allows you to identify specific opportunities. If your presence in searches for a category is low compared to your general positioning, you can adjust your content strategy or increase the bid on those keywords.

Architecture of a Real-Time Dashboard

Building an effective monitoring system requires careful technical planning. All the real-time monitoring demanded by an event like Black Friday can now be centralised in a single platform: flipflow. Instead of building complex integrations between multiple tools, flipflow unifies data from e-commerce, Retail Media, marketplaces, stock and competition in a single environment, allowing for an instant reading of the business.

In flipflow you can create the dashboards you want and organise the information your way, by priority levels. Thanks to its integration capacity, flipflow connects in real time with your proprietary data sources. This eliminates delays, information silos and technical dependencies, ensuring that all decisions are always based on updated data.

Furthermore, flipflow’s automated smart alerts turn the dashboard into an active surveillance system. You can define thresholds to detect stockouts, loss of Buy Box or aggressive price movements by the competition. Instead of constantly checking the panel, the system notifies you when something requires immediate action. Thus, the team moves from analysing data to acting at the exact moment when sales can still be saved.

Conclusion: See First, React Faster, Win Later

Black Friday has transformed into an event where analytical capacity and reaction speed determine who leads the biggest consumption event of the year. The ten KPIs analysed represent the indispensable minimum to compete effectively.

The fundamental difference between companies that fully take advantage of Black Friday and those that let opportunities slip away lies not in the size of their budget or the aggressiveness of their discounts, but in their ability to see what is happening while it is happening and act accordingly.

Preparing adequately for future commercial events requires investing in the technical infrastructure that makes this real-time visibility possible. Integrated dashboards , automated alerts and trained teams represent competitive advantages as important as the product you sell itself.

Because the next Black Friday will not start at the beginning of November 2026. It starts today, in how you build your monitoring system, how you define your critical indicators and how you train your team to interpret data when every minute counts. And when the next Black Friday of 2026 arrives, you won’t improvise: you will act with full knowledge of the facts.

The post Black Friday 2025 Post-mortem: 10 Critical KPIs you Should Have Monitored in Real Time appeared first on Flipflow.

In a world where every opinion counts, product reviews have become a strategic asset. Every comment, every star, every sentence a customer leaves about your product is a signal, a direct message from the market. However, reading them one by one is not enough. To transform those words into decisions, you need tools that translate emotions into clear and actionable data. 

This is where our new review sentiment analysis comes in, a solution that takes the voice of the customer to a whole new level.

From Intuition to Data

For years, brands have made decisions based on intuition or superficial indicators: a drop in sales, an increase in returns, or a spike in negative comments. What was missing was context: understanding whether dissatisfaction stems from product quality, after-sales service, shipping, or packaging.

Our sentiment analysis allows you to analyse opinions across multiple dimensions: quality, shipping, service, packaging, value for money, ease of use, durability, and consistency between what was promised and what was received. Each of these metrics offers a different angle on the customer experience, allowing you to detect real issues before they impact your sales and find opportunities for improvement with surgical precision.

Sentiment that Speaks for Itself

Flipflow classifies every review not only as positive, negative, or neutral, but delves into the drivers of satisfaction and frustration. For example, a product may receive a high score for quality but negative comments about shipping. With this information, logistics teams can act while the product continues to be appreciated by customers.

Every comment becomes a map of insights, where you can identify which aspects of your offering need attention and which are working perfectly. This allows every decision to be backed by real, specific data rather than assumptions.

Reading Between the Lines: Full Textual Analysis

The power of this solution is not limited to sentiment metrics. You can explore the full text of every review, filtering by keywords and detecting language patterns. This means you can identify recurring issues, validate hypotheses, and better understand how customers describe your product.

An increase in the word “fragile” in packaging reviews points to a potential problem with the materials used, while frequent mentions of “hard to use” in the usability category guide the redesign of instructions or interfaces. This granular view transforms every opinion into a strategic resource.

A Unified View for All Teams

One of the biggest challenges for companies is that different areas work with different customer data. Marketing, product, e-commerce, or customer service interpret information separately, generating silos and disconnected decisions.

With our sentiment analysis, all teams access a single source of truth. From the global brand view to product detail, each area can act with aligned information, make faster decisions, and coordinate effective actions that directly impact the customer experience.

Strategic Actions Based on Insights

The true advantage of knowing your customers’ sentiment is not just measuring it, but acting on it. By crossing sentiment metrics by product, category, or brand, strategic patterns can be detected:

• Which products exceed expectations and can serve as benchmarks for marketing campaigns.
• Which service areas need reinforcement to reduce negative comments.
• How to adjust pricing or the communication of product value according to customer perception.
  

This information allows you to prioritise actions and resources, ensuring that every decision has a direct impact on customer satisfaction and loyalty.

Furthermore, review sentiment analysis does not only benefit the company internally. It also provides a competitive advantage. By comparing your brand with the competition and evaluating how your products are perceived against others in the market, you can identify opportunities for differentiation, adjust your strategy, and make smarter decisions.

The Voice of the Customer as a Strategic Advantage

Your customers’ opinions are much more than stars and comments; they are strategic signals that, when well analysed, become an asset for your business. With our sentiment analysis in reviews, it is no longer necessary to read thousands of reviews to detect patterns: the tool does it for you and allows you to act with speed and precision. Every insight can improve the product experience, align all teams, and anticipate competitors’ moves, transforming every opinion into an opportunity for growth.

Very soon, with the integration of our AI agent, Tyrell, this capability will reach a superior level, anticipating trends and needs with unprecedented precision. Listening to your customers has never been so easy, clear, and powerful.

Turn every review into an opportunity for improvement and growth.

👉 Request a demo and discover sentiment analysis in action.

The post Discover what your customers really feel: sentiment analysis in product reviews with flipflow appeared first on Flipflow.

For years, the conversation about Retail Media has revolved around the same names: Amazon, Walmart or Mercado Libre. By late 2025, however, growth is shifting elsewhere: Retail Media networks of specialised retailers by category. These networks are offering better efficiency metrics and higher ROAS than many generalists.​

In Europe, it is estimated that the Retail Media market will double in four years. With annual growth four times higher than that of digital advertising as a whole, it will exceed €31 billion by 2028.

Source: European Retail Media set to double in four years – WARC, October 2024

In this context, vertical platforms focused on specific sectors, such as household cleaning, pet products or sporting goods, stand out for their advertising effectiveness. They demonstrate return on investment (ROAS) capabilities that systematically outperform traditional categories. The main reason lies in the precision of their first-party data and the high purchase intent of their audiences.

In this article, we will explore how niche markets are redefining expectations in Retail Media and which categories are leading this revolution. Furthermore, we will analyse the concrete strategies that brands can implement to maximise their performance in these specialised environments.

The Current Landscape: Retail Media Beyond the Giants

Retail Media will cease to be an “emerging channel” to consolidate itself as the third great advertising pillar alongside search and social, with a projected global volume close to $180 billion in 2025. In Europe, recent reports from IAB Europe show strong optimism: the majority of advertisers and agencies state they are increasing investment and particularly value access to first-hand retailer data and proximity to the point of sale.​

Although large marketplaces continue to concentrate a good part of the advertising budget, the ecosystem is expanding rapidly. More and more medium-sized and specialised retailers are launching their own Retail Media networks to monetise their audiences and consumer knowledge. This phenomenon is especially visible in categories where the purchase decision is more complex, more recurrent or strongly linked to trust.

This expansion has a clear effect: advertising inventory is fragmenting, but far from being a problem, it opens up new opportunities for brands. Less saturated environments are emerging, with high-intent audiences and, above all, a much greater capacity to measure the real impact on incremental sales, and not just on clicks or impressions.

Compared to generalist platforms, where a dog food brand competes for attention with electronics, fashion or entertainment, vertical retailers offer a context completely aligned with user intent. When a consumer browses a shop specialised in pet products, each advertising impact occurs within an environment where the predisposition to buy is already activated. This multiplies relevance, efficiency and, ultimately, return on investment.

Niche Categories Leading the Revolution

Household Cleaning

Home and DIY retailers have become key players in Retail Media because they concentrate high-value purchases and long decision processes, which require more impact than the typical last-minute banner. Networks such as The Home Depot’s (Orange Apron Media) combine millions of e-commerce visits with in-store purchase data and advanced geographic and contextual segmentation solutions.​

Furthermore, their measurement approach no longer focuses only on ROAS. They use frameworks such as ROMO (Return on Marketing Objective), which contemplate brand objectives, average order value, cross‑sell or recurrence. For cleaning and home maintenance categories, this allows campaigns to be linked to behaviours such as scheduled replenishment, renovation projects or seasonal changes. In this way, every euro invested is more likely to generate real value.

Moreover, these platforms capture valuable data on very specific preferences. For example, consumers concerned about eco-friendly products, those who prioritise efficacy over price or buyers sensitive to fragrances. This granular segmentation allows for extraordinarily relevant advertising campaigns.

Pet Products

Pet care is considered a recession-resistant market with strong migration to the online channel, where some estimates place it close to 40% of sales, with prospects of exceeding 50% in the medium term. Digital marketing benchmark studies show that this category records above-average click-through rates and lower acquisition costs than many other consumer verticals.​

Retailers and specialised platforms, such as Chewy or large grocery chains with a strong pet care assortment, use subscription and loyalty programmes to enrich their first-party data and segment by pet type, size, sensitivity, average order value or purchase frequency. This context favours highly profitable Retail Media: clear audiences, recurrent buying cycles and scope to test creatives oriented towards “new‑to‑brand” and increasing basket value with treats, toys or accessories.​

Luxury Beauty and Health

The premium beauty and skincare segment has seen a proliferation of specialised platforms offering sophisticated advertising experiences. Retailers such as Sephora, Ulta Beauty and others have developed robust advertising capabilities.

The beauty category benefits especially from enriched advertising formats: application tutorials, user-generated content, detailed reviews and personalised recommendations based on skin type, specific concerns and ingredient preferences. Recent reports point out that niche and independent brands are growing faster than large consolidated groups, which reinforces the role of specialised Retail Media as a lever for visibility and discovery.​

In parallel, health and wellness categories (supplements, advanced personal care, health devices) leverage user sensitivity to expert recommendation and social proof. Retail Media networks in online pharmacies and parapharmacies allow combining transactional information with contextual signals, such as seasonal changes or wellness-linked campaigns. Thus, they can launch highly relevant messages via native formats, educational content and personalised recommendations.

Sports and Fitness

Sport and fitness constitute another fertile field for vertical Retail Media. Sports retailers , from large chains to cycling or running specialists, know not only what is bought, but how often, in which discipline and at what level. This depth allows for segmentation by practice profile (beginner vs. advanced), average order value or interest in premium brands.​

In this context, campaigns can focus both on direct conversion of high-value equipment (bicycles, technical gear) and on cross-selling accessories, apparel, sports nutrition or services (workshop, repairs, experiences). The possibilities multiply when the retailer combines its e-commerce data with loyalty programmes, training apps or in-store experiences.​

Why Do Niche Markets Achieve Better ROAS?

There are several reasons why these verticalised markets achieve a better return on advertising investment. Below, we review them:

Ultra-specific first-party data

The first decisive factor is the quality of first-party data. Consultancies like BCG point out that the advanced use of this data can generate revenue increases of between 3% and 5% and similar improvements in margin, especially when integrated into Retail Media strategies. Specialised retailers have a detailed view of purchasing behaviour in their category that generalists cannot match.​

Knowing the type of pet, the level of sports practice or the skincare routine allows for the creation of audiences and messages that fit precisely. This level of granularity increases the probability of clicks and conversion, and reduces impression wastage, which directly improves ROAS.​

High-intent audiences

Purchase intent represents perhaps the most determining factor in advertising effectiveness. When a user browses a platform specialised in baby products, their categorical intent is already declared. Each visit represents an extremely high-value advertising opportunity.

Contrast this with generalist platforms where a user might be exploring electronics, clothing and food products in the same session. The dispersion of intent dilutes advertising effectiveness. In vertical environments, thematic concentration ensures that each advertising contact occurs at a mentally receptive moment.

Vertical benchmark studies show that, in categories such as pets or beauty, click-through and conversion ratios for well-segmented campaigns can be clearly above generalist e-commerce averages. The result is a superior ROAS without the need to multiply investment.​

Unique buying cycles requiring sophisticated measurement

Another decisive factor is the way in which measurement is adapting to the long or recurrent buying cycles specific to each category. Each vertical has very different consumption dynamics, and specialised platforms know them in depth. Whilst cleaning products are repurchased every three to six weeks, sports equipment can have decision cycles that span months or even years, albeit with more frequent complementary purchases over time.

This reality is leading advertisers and Retail Media networks to go beyond traditional ROAS. It is becoming increasingly common to incorporate metrics such as incrementality (iROAS), “new-to-brand” sales, contribution to brand objectives or advanced attribution models. In niche markets, where a single conversion can imply high value or a long-term subscription, this approach is especially relevant. A higher initial advertising cost can be amply compensated in the medium and long term.

Thanks to a much more sophisticated understanding of the customer journey, it is possible to apply optimisations that could not be implemented on generalist platforms. In the latter, homogeneous attribution models are used for categories with radically different purchasing behaviours.

Lower advertising saturation

Vertical platforms usually present environments less saturated with advertising than the generalist giants. Whilst on Amazon a product may compete with dozens of ads on the same page, smaller specialised retailers maintain more moderate advertising densities.

This lower saturation benefits both users and advertisers. Consumers experience less advertising fatigue, maintaining receptiveness towards well-targeted messages. Brands, for their part, obtain greater relative visibility for each impression purchased.

Furthermore, competition for advertising inventory is usually less fierce on emerging vertical platforms, resulting in significantly lower costs per click. A brand can obtain premium placements at a fraction of the cost it would pay on massive platforms.

Strategies to Maximise ROAS in Specialised Markets

Selection of specialised RMN

The strategic choice of vertical Retail Media networks constitutes the first critical step. Not all specialised platforms offer the same capabilities or reach the right audiences. For a sports supplement brand, for example, it may make more sense to prioritise a sports retailer with a strong digital presence than a generalist marketplace.​

Brands must evaluate various factors, such as audience size and composition, and the quality of data available for segmentation. They must also consider the sophistication of advertising tools, the formats offered and measurement capabilities. It is preferable to concentrate investment on two or three leading vertical platforms than to scatter it across dozens of smaller specialised sites without critical mass. Alignment between the platform’s customer profile and the brand’s target audience is also fundamental. 

Leverage emerging formats

The formats working best in niches combine relevance and storytelling capacity: sponsored video, native ads in product carousels, recommendations in internal search results or in‑store activations synchronised with digital campaigns.

In niche categories, showing product usage, the expected result or testimonials from other customers has a direct impact on the purchasing decision. Combining these formats with high-impact placements (category pages, search results, baskets) ahelps to increase incremental sales and ROAS.​

The key is to view these specialised formats as strategic investments rather than additional costs. The incremental return amply justifies the extra creative effort.

Personalisation based on behavioural data

The great asset of niche retailers lies in the depth of their user behaviour data: purchase history, frequency, price sensitivity, preference for certain brands or ranges. Activating this data in dynamic campaigns allows the message, recommended product and impact frequency to be adapted to each segment.​ Personalisation is not limited to the initial advertising message. It extends to the entire post-click experience, including adapted landing pages and purchase journeys optimised for each profile.

Recent cases on Retail Media platforms show significant increases in “new‑to‑brand” and average order value when strategies based on consumption moments (for example, monthly pet food purchase or sports season preparation) are used and creatives are adjusted to those contexts. At this point, brands benefit especially if they can cross-reference information from various networks and understand which segments respond best at each retailer.​

Continuous testing and optimisation

Vertical markets, although smaller than massive platforms, still offer sufficient volume for rigorous testing programmes. This includes A/B testing of creatives, experimentation with different audience segments, variation of promotional offers, campaign timing aligned with specific buying cycles, and optimisation of bidding strategies.

The advantage of vertical platforms is that learning cycles are faster. With highly relevant audiences, performance signals emerge more quickly, allowing for agile iterations. A campaign can be significantly optimised in days or weeks, compared to months in less focused environments.

For the advertiser, the challenge is to coordinate this information centrally and convert it into a clear budget distribution strategy by channel and category.​

Conclusion: The Future of Retail Media in Niche Markets

Everything points to Retail Media continuing to grow at double-digit rates in the coming years. But what is truly relevant is not just its size, but how its structure is transforming. In Europe, the development of local and regional networks, together with the strength of specialised retailers in categories such as food, beauty, sport or home, is shaping an ecosystem that is much more diverse, fragmented and, at the same time, more sophisticated than that of other markets. In this new scenario, niche markets cease to be a residual space to become one of the most promising terrains of the channel.

Trends consolidating the prominence of niches

The very trends defining Retail Media in 2025 reinforce this competitive advantage of vertical environments. The growth of off-site Retail Media —where retailer data is activated on third-party media such as social networks, online video or display— clearly favours those with well-defined audiences, clear interests and high purchase intent. Added to this is the take-off of in-store media, which allows the loop between digital impact and physical purchase to be closed through screens, dynamic signage and omnichannel experiences. In categories where the product is tested, touched or experienced, this bridge between the digital and physical worlds multiplies the value of the advertising impact.

Furthermore, the consolidation of measurement standards and best practices in incrementality and attribution are reducing entry barriers for many advertisers. As analysis tools mature, it becomes increasingly simple to demonstrate that a campaign at a niche retailer does not just generate visibility or clicks. It also allows real sales, incremental growth and long-term value to be measured.

In this context, niche categories start with structural advantages that are difficult to replicate in generalist environments. Brands that know how to combine these strengths with an orderly strategy of network selection, formats and measurement models will be in a privileged position to protect their margin, gain relevance and grow sustainably in the coming years.

The post The rise of vertical Retail Media: Why niche markets outperform traditional categories in ROAS appeared first on Flipflow.

The European cosmetics market represents one of the most dynamic and competitive landscapes in global beauty retail. With a valuation approaching €119 billion in 2025 and projected steady growth through the decade, cosmetics brands are facing increasingly sophisticated consumers who research, compare, and purchase products across multiple digital channels. 

Skin care, and especially anti‑ageing treatments, sits at the heart of this transformation. These products attract highly informed, high‑intent consumers who scrutinise ingredient lists, reviews and promises of efficacy. The result is an extremely competitive environment where dermocosmetic pharmacy brands and mass beauty giants fight for the same search results and product listing pages.

Within this context, the concept of the Digital Shelf—the online space where products are displayed, discovered, and evaluated—has emerged as a decisive battleground for brand visibility and commercial success.​

This article presents key findings from flipflow’s cross-market benchmark study on Digital Shelf performance in the anti-aging skincare segment across Spain, France, Italy, and the United Kingdom during Q3 2025. The analysis covers 12 leading cosmetics brands, including Garnier, L’Oréal Paris, Vichy, Neutrogena, Weleda, Olay, Nivea, Eucerin, Nuxe, Sesderma, Cantabria Labs, and Bella Aurora, monitored across five major retailers: Amazon, Primor, Douglas, Boots, and Easypara.​

Why Digital Shelf Visibility Matters for Cosmetics Brands

The Digital Shelf determines whether consumers will find a brand’s products when searching online. As e-commerce continues to capture a larger share of beauty sales (43% of European beauty purchases are expected to occur online by 2025) brands that fail to optimise their online presence risk losing relevance in a market where discovery increasingly begins with a search query rather than a store visit.​

In the anti-aging category specifically, the Europe anti-aging skincare ingredients market was valued at USD 415.80 million in 2024 and is expected to reach USD 589.05 million by 2032, growing at a CAGR of 4.45%. This growth is driven by rising consumer awareness, demand for preventive solutions, and technological innovations in active ingredients. For brands competing in this segment, strong Digital Shelf positioning translates directly into commercial opportunity.​

A Fragmented Landscape with Tight Country Averages

One of the most striking findings of our benchmark is how similar the overall Digital Shelf intensity is across the four markets. Spain records an average visibility of 8.37%, France 8.39%, Italy 8.33% and the UK 8.46%. On the surface, these numbers suggest comparable levels of competition.

The detail underneath tells a different story. Leadership positions change sharply from one country to another and no single brand dominates everywhere. Garnier, Vichy and Weleda each hold strong positions, but always in different combinations by market. Domestic champions like Cantabria Labs and Nuxe shine on their home turf, while some global brands exhibit surprising weaknesses in specific countries.

The European digital shelf for beauty therefore behaves as a patchwork of local battles rather than a single unified market.  Understanding where individual brands excel, and where they underperform, provides actionable intelligence for marketing and e-commerce teams seeking to optimise their digital strategies.

Spain: Twin Leadership in a Crowded Field

The Spanish market for anti‑ageing products is dynamic and highly contested. When consumers search for “antiedad”, overall visibility averages 8.37%, yet two brands clearly distance themselves from the rest. Garnier stands out with an impressive 18.54% visibility index, more than double the national average. Cantabria Labs follows with 11.80%, while Weleda secures a solid 10.46%.

This combination creates a pattern of “twin leadership”: Garnier as a powerful international mass‑market reference and Cantabria Labs as a strong local dermocosmetic anchor. The presence of Weleda in third position shows that natural and plant‑based propositions also resonate strongly with Spanish shoppers.

At the other end of the ranking, Eucerin, Nuxe and Sesderma remain well below the country average with scores between three and four percent. For these brands, Spain represents a clear opportunity: the market is large, and the category is vibrant, yet their products are not surfacing as often as their reputation might justify. A review of assortment depth, keyword coverage and retailer partnerships would be the natural next step.

France: A Distinctly Local Market

France is traditionally associated with dermocosmetic excellence, and the digital shelf confirms this reputation. For the keyword “anti‑âge”, the national average visibility sits at 8.39%, similar to Spain, but the pattern by brand looks very different.

Vichy leads the French online anti‑ageing category by a clear margin with 15.68% visibility. Eucerin and Neutrogena follow closely at 10.90% and 10.88%, forming a trio of brands that benefit from strong pharmacy heritage, trusted expertise and long‑standing distribution networks.

Spanish brands find French e‑commerce harder to penetrate. Sesderma posts only 1.37% visibility and Cantabria Labs 1.42%. Even a heavyweight such as Olay—strong in the UK and Italy—achieves only 7.73%, lagging behind its performance elsewhere. The French digital shelf appears highly France‑centric, privileging brands with deep roots in the local pharmacy ecosystem and content tuned precisely to French consumer language and regulatory nuances.

For international brands, this suggests that entering France successfully cannot rely on simply replicating strategies from other European markets. It requires tailored claims, specialised retailer partnerships and a close understanding of how French shoppers search and filter within the anti‑ageing category.

Italy: Garnier in Front, Dermocosmetics Close Behind

Italy‘s “antiage” searches confirm Garnier’s pan-European strength, with the brand capturing 17.12% visibility, again roughly double the 8.33% national average. This performance positions it comfortably ahead of Eucerin at 10.18% and Olay at 10.14%, which together form a competitive chasing pair just above the 10% mark. These results underline that Italian shoppers combine interest in accessible mass brands with openness to more specialist skin‑care offers.

Further down the table, Sesderma struggles with only 2.10% visibility. Vichy and Bella Aurora remain below the national mean with 6.14% and 6.54% respectively. The contrast with Vichy’s dominance in France is particularly telling: its French strengths do not automatically translate to the Italian digital shelf. The issue does not appear cyclical; rather, it suggests structural gaps in localisation, range architecture or review generation that need targeted correction.

United Kingdom: Weleda’s Breakout Moment

In the United Kingdom, the “anti aging” keyword yields the highest country average at 8.46%, though the real story lies in the extraordinary performance of a single brand. Weleda achieves a visibility index of 27.71%, vastly outperforming every competitor and every other market in the study. This result places Weleda as a leading reference for natural and ethical skin care within UK digital channels.

Garnier and Olay form a strong second tier with 11.83% and 10.79% visibility. Both maintain comfortable positions above the country average and confirm that British shoppers remain receptive to both heritage mass brands and more clinical derma propositions.

Spanish brands, in contrast, register very low visibility. Cantabria Labs and Bella Aurora each record 1.63%, while Sesderma reaches 5.06% (notably higher than in other markets). These figures highlight the difficulty of gaining traction in anglophone online retail without a clear localisation strategy, strong retailer relationships and communication that matches UK consumer expectations.

The UK’s elevated paid-media intensity (that we will explore in a separate analysis) means that organic fundamentals—content quality, local keyword semantics, and retailer mix—are especially critical for brands seeking cost-efficient visibility.​

Consolidated Brand Performance: Consistency vs. Market Dependence

When aggregating results across all four markets, Garnier emerges as the most consistent leader with a 14.24% global average visibility, performing above the national average in all four countries studied. Weleda ranks second with 13.94%, although this figure is heavily influenced by its exceptional UK performance.​

The mid-tier includes Olay (8.95%), Vichy (8.79%), Nivea (8.23%), Neutrogena (8.23%), and Eucerin (8.19%), all competing within a narrow range. These brands demonstrate varying degrees of market-by-market consistency.

Sesderma’s position at the bottom, failing to exceed the national average in any market, signals a need for comprehensive strategic review across content quality, keyword localisation, and retailer breadth.​

Two insights matter for European strategy. Garnier appears as the most consistent cross‑market performer, surpassing the national average in every country. This reliability suggests strong baseline equity, extensive distribution and disciplined optimisation of product pages and keyword coverage.

Weleda, in contrast, owes much of its high position to its extraordinary UK result. The brand performs respectably in Spain, France and Italy but does not reach the same heights as in the UK. Its profile illustrates how a focused local play, when well executed, can dramatically influence pan‑European averages.

Volatility Analysis: Where Strengths and Weaknesses Are Exposed

Looking at each brand’s best and worst markets highlights how stable or exposed its online presence really is. L’Oréal Paris and Nivea stand out for their relatively low volatility. L’Oréal’s visibility ranges only from 6.92% in Spain to 8.5% in Italy, while Nivea fluctuates between 7.36% in the UK and 9.37% in Spain. These mild spreads imply that their digital shelf fundamentals (distribution, content and SEO within retailers) remain consistently solid.

Other brands experience far wider swings. Weleda jumps from 8.31% visibility in France to 27.71% in the UK, a spread of 19.4 points. Vichy moves from 5.52% in the UK to 15.68% in France; Cantabria Labs from 1.42% in France to 11.80% in Spain; and Nuxe from 3.68% in Spain to 9.49% in France. Such volatility reflects a strong home‑market bias where domestic equity and distribution create peaks, but international execution remains uneven.

Sesderma occupies another category altogether, underperforming broadly rather than oscillating between strength and weakness. Its highest visibility, 5.06% in the UK, still falls behind the leaders, while its lowest, 1.37% in France, reveals minimal presence. For a brand with international ambitions, this profile indicates the need for a comprehensive digital shelf rethink covering content depth, imagery, attributes, reviews and retailer coverage.

Strategic Lessons for Beauty Brands Competing Online

Several clear lessons emerge from the Digital Shelf analysis. The first is that each European market behaves as its own digital ecosystem. The similar averages mask very different rank orders and competitive dynamics. Strategies that work in Spain or Italy often falter when transplanted directly to France or the UK. Brands need genuinely local playbooks that reflect how shoppers search, which retailers they trust and what claims resonate.

A second lesson concerns the balance between consistency and specialisation. Brands such as Garnier, Nivea and L’Oréal Paris show the advantages of maintaining a stable mid‑to‑high level of visibility across all markets. Their presence may not always be spectacular in any single country, but the overall portfolio is resilient. At the same time, examples like Weleda in the UK or Vichy in France illustrate the power of focused local excellence. The strongest digital shelf strategies blend both: a solid baseline everywhere, complemented by selected “hero markets” where the brand invests in deeper range, stronger partnerships and more intensive optimisation.

The third insight relates to hidden gaps. Our data reveals several brands that perform well in some markets yet clearly under‑deliver in others. Eucerin, strong in France, lags in Spain. Neutrogena’s success in France does not fully translate to the UK. Olay shines in the UK and Italy but remains middling in Spain and France. These discrepancies usually point to tactical issues (limited SKUs, missing hero formats, insufficient review volume, or weak alignment with local keyword patterns) rather than to structural brand problems. Systematic auditing of these factors provides some of the fastest gains in digital shelf performance.

In all these areas, reliable, granular analytics such as the ones provided by Flipflow’s Digital Shelf Analytics solution help teams benchmark against competitors, set realistic targets and track progress over time.

Conclusion: Winning the Digital Shelf in European Beauty

The European cosmetics market in 2025 presents both opportunity and complexity for brands seeking Digital Shelf visibility. With e-commerce capturing an ever-larger share of beauty purchases and consumers increasingly relying on search-driven discovery, online visibility has become a strategic imperative rather than a tactical consideration. Our benchmark reveals a competitive landscape where market leadership is fragmented, with no single brand dominating across all countries. 

Garnier emerges as the most consistent cross‑European leader in Digital Shelf visibility. Vichy and Weleda show how local strength can propel a brand to standout positions when combined with the right retailer mix and content strategy. Domestic champions like Cantabria Labs and Nuxe demonstrate the weight of home‑market heritage, while several global players reveal underexploited opportunities in specific countries.

The overarching message is clear: success on the digital shelf in European beauty depends on precise localisation, meticulous optimisation of product pages and a constant, data‑driven assessment of how visibility evolves across retailers and markets. Brands that monitor their Digital Shelf performance with the level of detail offered by Flipflow’s analytics platform can identify gaps early, prioritise investment and convert shopper intent into sustainable growth. 

The full “Digital Shelf & Retail Media Performance in European Beauty – Q3 2025 Cross‑Market Benchmark” (download it on the link) provides deeper charts and brand‑by‑brand breakdowns for teams that want to translate these findings into concrete action plans, master the Digital Shelf, and sharpen their competitive edge in a market valued at nearly €120 billion. In a category where every search result is a micro‑battle for attention, the brands that professionalise their Digital Shelf today will own the European beauty consumer tomorrow.

The post Digital Shelf Performance in European Beauty: Who Wins the Anti‑Ageing Race? appeared first on Flipflow.

Black Friday is once again confirmed as the fundamental pillar of the digital commercial calendar in Spain. In 2025, this event will concentrate almost 25% of all annual online sales. Marketplaces such as Amazon, El Corte Inglés, AliExpress and TikTok Shop will lead in user acquisition and digital traffic. 

The Spanish preference for the online channel is becoming increasingly noticeable: in the first quarter of 2025 alone, national e-commerce grew by 18.2% year-on-year, reaching a turnover of 25,752 million euros according to the CNMC.​

Consumption Patterns and Black Friday Growth

During the 2024 campaign alone, the average spend per shopper during Black Friday amounted to €230. Furthermore, the online average purchase ticket is forecast to exceed €485 in 2025, representing a 6.5% increase compared to the previous year. 

Spanish e-commerce will close 2025 with an estimated volume of 45,062 million euros, 4.8% more than last year. This signals stability and maturity in the Spanish digital market.

Generation X leads spending and purchase frequency, with an average of 11.8 transactions per user in the last twelve months and an annual spend exceeding €345.6. The sectors recording the greatest dynamism in online sales are beauty, personal care, home and pets. On the other hand, automotive accessories and food show growth exceeding 4%.​

Strategies and Challenges for Brands and Marketplaces

Omnichannel integration and dynamic forecasting allow retailers to maintain sustained growth. The use of artificial intelligence and predictive models helps reduce stockouts and optimise price campaigns, which is especially crucial for maximising results during Black Friday.​

As pointed out by Jordi Vilardaga, Head of Supply Chain at NTT DATA, in the “Black Friday 2025 Report”:

“The preceding weeks are key. The consumer no longer buys on impulse: they plan, compare and decide with criteria.”

Click & collect, vertical marketplaces and live shopping continue to gain traction and drive the national market.​ Luis Simoes, Managing Director Iberia at NIQ, highlights that:

“Retailers and manufacturers must treat Black Friday as a peak season, not just as a one-week promotion. Omnichannel coordination and dynamic forecasting are fundamental to capturing online demand while avoiding stockouts during this massive sales period preceding major Christmas shopping.”

Cyber Monday and the “Cyber Week” Revolution

Cyber Monday is gaining weight in Spain. In 2025, the average ticket is expected to reach €300 per online shopper according to Webloyalty forecasts. In some categories, the average spend of Black Friday will be exceeded for the first time. 77% of users already plan to take advantage of offers on Cyber Monday. This consolidates an extended window of discounts and digital opportunities, favouring a combined growth of 10% in online sales between both campaigns.​

The fastest growth is seen in technology, fashion and food products, which lead transaction volumes in both events. Furthermore, Spain will reach an 11.2% online retail share this year, a reflection of digital maturity and the rise of digital commerce among traditional operators too.​

A Common Trend, Multiple Ways to Shop

The rise of Spanish e-commerce translates into an international projection: currently, the country is the fifth largest market worldwide (behind the USA, Germany, Brazil and the UK) in sales volume during Black Friday, with a 6.3% global share.

More than 90% of consumers in developed countries consider the 5 days between Black Friday and Cyber Monday as key dates in the commercial calendar. However, the way this phenomenon is experienced varies significantly according to the culture and expectations of each country. While in the United States the event is associated with the start of Christmas shopping and massive offers both in physical stores and online, in Europe Black Friday reflects differentiated consumption strategies, where value, quality and digitalisation coexist in different proportions.​

Source: Black Friday 2025: The impact of intelligent retail – NTT Data, November 2025

United Kingdom

The British market is highly price-oriented, with consumers seeking convenience and aggressive promotions, especially in fashion, toys and electronics. Comparison between shops and early purchasing set the tone for British digital consumption.

France

The French public prioritises quality and the after-sales experience, maintaining great loyalty towards brands. The dominant categories are beauty, fashion and home, in a demanding commercial environment marked by excellence.

Spain

Spain figures among the most active countries in Europe, with digitally mature and highly participatory consumers. The main categories during BFCM are fashion, footwear and beauty, supported by the strong growth of online sales and purchase planning to anticipate the Christmas campaign. 

Germany

The German market is distinguished by its organisation and advanced digitalisation, with high use of artificial intelligence in the purchasing process. Electronics, home and fashion are the star categories, showing a rational, planned and efficient customer profile.

Italy

The Italian consumer stands out for their rationality and taste for design, guided by technology and a preference for stylish items. Online shopping plays a leading role, especially in electronics and fashion.

United States

In the USA, the “Cyber Five” sets records in sales and participation, aligning the nation’s omnicanal experience—the most consolidated in digital consumption—with the rise of social commerce and constant innovation from giants like Amazon and Walmart. 

A Campaign that Redefines the Digital Commercial Calendar

Black Friday and Cyber Monday are no longer simple promotional milestones, but authentic engines of digital consumption on a global scale. In Spain, their role is particularly decisive. They concentrate a substantial part of the annual online sales volume, accelerate the adoption of new technologies and consolidate consumers as informed, demanding and fully digital actors.

The maturity of e-commerce, together with the growing sophistication of brands, retailers and marketplaces, draws a scenario in which precision, anticipation and the omnichannel experience will be key to competing in 2025 and beyond. In a context marked by constant comparisons, the search for value and increasingly rational decisions, those who know how to interpret data and adapt with agility will capture an essential part of the demand.

Ultimately, Black Friday and “Cyber Week” will continue to redefine the commercial calendar, consolidating themselves as a peak season for global commerce and a decisive showcase where digital consumer loyalty is measured and won.

The post Black Friday 2025: One in Four Online Purchases in Spain is Made in a Single Week appeared first on Flipflow.

Introduction: The Death of ‘One Size Fits All’

Here’s a statistic that should worry any e-commerce director: according to a survey by McKinsey, 71% of consumers expect personalised interactions and 76% get frustrated when they don’t. In other words, when the experience doesn’t meet their expectations, switching brands is now easier and more common than ever.

The key to winning back their attention is to understand how they search. Today’s consumer no longer browses generic categories: they filter, compare, and select based on very specific needs. They don’t search for “face cream,” but for “paraben-free cream for sensitive skin with SPF 50”.

For decades, brands operated with a single, static content model. They would create one standard description and replicate it across all channels: Amazon, Zalando, their own online shop, or specialised marketplaces. With the same text, the same specifications, and the same images. Creating distinct product detail pages (PDPs) for 10,000 different SKUs was simply unfeasible. Content marketing teams couldn’t keep up, budgets soared, and the available technology couldn’t handle that volume of personalised information. The result was predictable: generic content that tried to speak to everyone but truly connected with no one.

Source: The value of getting personalization right—or wrong—is multiplying – McKinsey, November 2021

Looking ahead to 2026, continuing with that strategy is a direct path to failure. Winning on the Digital Shelf requires adapting the content of each SKU to the channel’s context and, above all, to the specific profile of the user searching for it.The data speaks for itself: companies that adopt advanced, AI-based personalisation strategies can generate up to 40% more revenue from these initiatives. Moreover, the most mature companies in this area grow about 10 percentage points faster than their direct competitors. The better a company uses its data to know and understand its customers, the greater the impact on the business.

In this context, mass personalisation is no longer a luxury reserved for large tech corporations but has become a basic competitive necessity.

What Is SKU-Level Personalisation?

Often, when we talk about personalisation in e-commerce, our minds automatically turn to CRM strategies: emails that include the customer’s name or product recommendations based on browsing history. However, SKU-level personalisation operates on a different and much deeper layer of the shopping experience.

We’re talking about the ability to modify the structural elements of the product detail page —title, description, benefits, and image gallery—to match the expectations of the audience segment viewing that item or the nature of the channel where it is displayed.

Let’s think about a pair of high-end running trainers. The physical product is exactly the same: same sole, same upper, same cushioning technology. However, the way it is presented can and should vary radically.

When a professional marathon runner is looking for these trainers, the product detail page must prioritise specific technical data: energy return, the drop that favours a midfoot strike, the weight, or the midsole composition. The images will highlight cross-sections of the technology, close-ups of the sole, and performance graphics.

In contrast, when a user focused on street fashion is looking for the same model, the presentation changes completely. The page highlights the exclusive design, limited colour palette, collaboration with a renowned designer, and the story behind the model. Images show complete outfits, pairings with different garments, and the product in attractive urban settings.

But the product remains identical. What changes is the narrative, focus, and hierarchy of information that each type of user receives.

The Engine of Change: Attributes and Structured Data

Carrying out this personalisation manually for ten products is feasible. Doing it for thousands of SKUs is impossible without a solid data foundation. This is where product information management comes into play. Personalisation is a data game, not a creative magic trick.

The fundamental element of this strategy is the “attribute”. An attribute is any discrete piece of data that defines a product characteristic: colour, material, size, weight, country of origin, type of fastening, etc. Each of these attributes acts as a smart tag that allows the system to identify which products match each specific search.

When a user enters an online shop and selects “Jackets”, then “Waterproof”, and finally “Colour: Black”, they are interacting directly with the attributes the brand has previously defined. If a brand has an excellent jacket, with a complete and persuasive description, but has forgotten to tag the “waterproof” attribute in the database, that product will be invisible to the user applying that filter. The quality of the text becomes irrelevant if the product doesn’t appear in the search results.

A critical example can be found in the food and cosmetics sector. Imagine a consumer searching for vegan products. If the product page doesn’t have the “vegan” attribute explicitly marked and structured (not just mentioned in a paragraph of text, but tagged in the corresponding system field), the marketplace’s algorithm won’t be able to index it correctly for that specific search.

Therefore, before thinking about generating creative copy automatically, companies must audit and clean their structured data. The granularity of the attributes determines the capacity for personalisation. The more specific details a product has broken down into data, the greater the potential for creating precise and relevant shopping experiences.

How to Scale: The Role of Generative AI

The main historical obstacle to mass personalisation was simply impossible to solve with traditional methods: how do you create and maintain personalised content for tens or hundreds of thousands of SKUs, multiplied by different channels, languages, and audience segments? A quick calculation: 10,000 products × 5 channels × 3 audience variants × 4 languages = 600,000 different content versions. Impossible to manage with human copywriters.

This is where Generative Artificial Intelligence becomes the indispensable operational tool. It allows a shift from a manual copywriting model to an editorial supervision model, multiplying content production capacity.

Let’s see how it’s applied in four key areas:

1. Advanced translation and localisation

AI platforms can translate product descriptions into multiple languages, but they go far beyond literal translation. Generative AI enables “transcreation” processes at scale.

They adapt idiomatic expressions, adjust cultural references, and respect market-specific regulatory standards. A description for a food supplement must comply with very different regulations in Spain, Germany, or the United States, and these platforms can automate those adjustments.

2. Attribute enrichment

One of the most powerful applications of current technology is the ability to extract information from images. Suppose a fashion brand receives 1,000 photographs of its new collection, but the textual information is scarce. AI tools can analyse the pixels in each image and automatically detect features: “long sleeve”, “V-neck”, “floral print”, “coral red”. This data is automatically converted into structured attributes in the management system (PIM), saving thousands of hours of manual data entry and reducing human error.

3. Adapting the tone of voice

Each sales channel has its own language. Amazon rewards brevity, feature lists, and keyword density. In contrast, a luxury brand’s own online shop or a social network like Instagram requires an aspirational, evocative, and emotional tone.

Generative AI makes it possible to take a product’s technical attributes (e.g., “organic cotton”, “made in Portugal”) and generate multiple versions of the description. One version will be technical and optimised for SEO on marketplaces; another will be narrative and enticing for the corporate website. The system can rewrite thousands of product pages in minutes to adapt them to each channel’s style guide, maintaining brand consistency while adjusting the linguistic register.

4. Available technological solutions

The market already offers mature solutions for implementing mass personalisation. Product Information Management (PIM) platforms like Akeneo, Salsify, or inRiver integrate AI capabilities to enrich, translate, and adapt content. Other specialised tools focus specifically on generating optimised product descriptions.

Many of these platforms allow you to define templates with rules: “For products in category X, when the user comes from channel Y and belongs to segment Z, prioritise these attributes and use this tone”. The system applies these rules automatically to thousands of SKUs simultaneously.

The important thing to understand is that these tools do not replace human judgement. They require supervision, adjustments, and validation. But they drastically reduce the time and cost of creating personalised content on an industrial scale.

KPIs and Measuring Success

Implementing mass personalisation requires investment and a profound cultural shift. And, like any serious business initiative, it also needs clear metrics to evaluate its effectiveness. It’s not enough to deploy technology and assume it works: it is essential to measure, compare, and optimise continuously.

Attribute completeness

This is a catalogue health indicator. It measures the percentage of data fields that are filled in for each SKU. A product with 100% completeness is much more likely to appear in filtered searches than one with 60%.

Conversion rate per SKU

By personalising the content, we should see an increase in conversion. If we adapt the page for a technical product to an expert audience, the clarity of the information should reduce friction and increase sales.

Share of shelf

This indicates what percentage of relevant searches in your category your brand captures. If you sell coffee machines and there are 10,000 monthly searches for “automatic espresso machine”, how many of them do you appear on the first page for? This metric reveals your real visibility on the Digital Shelf.

Returns and quality signals

This metric is fundamental and often overlooked. A precise and detailed product description aligns customer expectations with the reality of the item. If AI helps us to better detail sizes or materials, we should see a reduction in returns for reasons like “the product was not as expected” or “inaccurate description“.

A/B testing

The ability to generate content quickly allows for hypothesis testing. We can launch two versions of a title or a main image for the same product over a controlled period and measure which one generates more clicks and sales, optimising the catalogue based on real behavioural data.

Personalised recommendations alone account for almost a third of e-commerce revenue, and sessions adapted to user behaviour can more than triple the average order value. This is possible because AI detects patterns and purchasing signals that a human analyst would take months to discover, making it possible to create highly relevant experiences instead of generic messages.

Challenges: Data Quality, Privacy, and Consistency

Despite the clear advantages, adopting this technology comes with significant challenges that organisations must manage prudently.

The first obstacle is the quality of the source data. AI algorithms work on the premise that they learn from and operate on the information they are given. If the product database contains errors, duplicates, or outdated information, the AI will scale those errors at breakneck speed. Cleaning and normalising master data is an unavoidable preliminary step.

Another significant challenge is brand consistency. When generating thousands of automatic descriptions, there is a risk that the brand’s tone of voice becomes diluted or robotic. Human supervision is still necessary to audit random samples of the generated content and ensure the brand’s “personality” remains present, even when the text has been written by a machine.

There is also a risk of creating “content bubbles” where the user only sees products and descriptions that reinforce their previous preferences, limiting their ability to discover alternative options. An overly aggressive personalisation algorithm can reduce the diversity of exposure and impoverish the shopping experience.

Finally, although product personalisation touches on less personal data than marketing personalisation, there are ethical and legal implications. If we use a user’s browsing data to dynamically show them a version of the product page, we must be transparent about the use of cookies and respect privacy regulations like GDPR. The user must feel that the personalisation adds value and is useful, not that they are being watched.

Conclusion: The Atomisation of Content

The future of content on the Digital Shelf is heading towards what we might call the “atomisation of content“. Instead of thinking of a product page as a monolithic block of information, we must see it as a collection of content atoms: discrete fragments of information (attributes, benefits, specifications, visual elements) that can be dynamically recombined according to the context.

Imagine that each feature of your product is an individual atom stored in your database: “Material: certified organic cotton”, “Benefit: regulates body temperature”, “Recommended use: low-intensity outdoor activities”, “Environmental impact: carbon footprint offset”. Each one is a piece of verified information, translated into multiple languages and tagged with metadata about when and how to use it.

When a specific user on a particular channel searches for your product, the system selects and combines the most relevant atoms for that context. It reassembles the information in real time, generating a product page perfectly adapted to that particular situation. Content is no longer static; it is fluid and contextual.

The brands that succeed in breaking down their information into these atoms and using artificial intelligence to reassemble them according to the exact needs of the customer at any given moment will be the ones to dominate the market. They will be able to be present in a relevant way on hundreds of channels simultaneously, speak to each audience segment in its own language, adapt messages to emerging trends in days instead of months, and scale international operations without proportional increases in cost.

The question is no longer whether or not to implement mass SKU-level personalisation, but how long you can afford to wait while your competition does it first. The 2026 Digital Shelf will reward those who understand that every product, in every context, deserves to have its own perfectly tailored story.

The post From 100 to 1 Million SKUs: The Mass Personalisation Revolution on the Digital Shelf appeared first on Flipflow.

Introduction: a Look at the Future of Retail in Spain

The retail landscape in Spain is constantly evolving, and the COVID-19 pandemic accelerated a digital transformation that was already underway. A key figure that will shape the direction of the sector in the coming years is the forecast that online retail will account for 11.2% of total retail sales by 2025. This forecast, taken from the latest “e-retail Index Spain” report by the consultancy Savills, invites us to reflect on the future of retail and the strategies that companies must adopt to remain competitive in an increasingly digitalised market.

While this figure represents significant growth, it is interesting to note that Spain will remain some way behind the European average, estimated at 14.6% for the same year. This suggests that, despite the boom in e-commerce, the Spanish consumer still values the in-store shopping experience, which opens up a range of opportunities for companies that know how to integrate both worlds: the online and the offline.

In this article, we will analyse in depth what this 11.2% means for the retail sector, how we got here, and what trends will shape the future of retail in Spain.

Sustained Growth in E-commerce Following the Pandemic

The 2020 lockdown was a turning point for e-commerce in Spain. The share of online sales jumped by 2.7 points. Since then, growth has stabilised at a steady rate of 0.5 percentage points per year. This indicates a maturing market and a consolidation of the shopping habits acquired during the pandemic.

How has each category evolved since the surge in 2020?

Source: The state of e-commerce in Spain – Savills, October 2025

As Alicia Corrales, Director of Retail Research & Consultancy at Savills Spain, neatly summarises:

“Although the growth of e-commerce versus offline in retail categories seems to be slowing slightly in percentage terms, it continues to gain share and will continue to do so in the medium term, in a new phase of sustained growth and maturity, marked by efficiency, flexibility in the use of channels in the purchasing process, and the emergence of new ways of shopping as keys to success.”

This new phase, although more moderate than the initial boom, demonstrates the resilience of the physical shop. It also reveals the consumer’s preference for a mixed model. In 2024, 72.2% of retail purchases were made on the high street. Meanwhile, 17.4% took place in shopping centres and retail parks. These figures confirm that the bricks-and-mortar retail apocalypse, so often heralded, has not arrived. Instead, we are witnessing an integration of channels that is redefining the shopping experience.

The Resilience of the Physical Shop and the Rise of Omnichannel

Far from disappearing, the physical shop is reinventing itself to offer added value that the online channel cannot replicate. The key to success in the new retail paradigm lies in omnichannel, that is, in the ability to offer a seamless and consistent shopping experience across all sales channels.

A clear example of this trend is the growing number of digital pure players that are opening physical shops. In the last five years, 46 such openings have been recorded on high streets or in shopping centres in Spain. For example, the brand Sepiia, which was founded in 2016 as a completely online brand, has managed to make sales in its physical shops account for almost 15% of its total turnover in 2024. These brands, born in the digital environment, have understood the importance of having a physical space to connect with their customers, build trust and offer memorable experiences.

Shopping centres and retail parks have also demonstrated their ability to adapt. After a fall in 2020, they have partially recovered their market share, holding steady at 17.4%. This has been thanks to strategies to renew their offerings, the integration of leisure and dining, and advances in digitalisation and customer experience.

Trends that will Shape the Future of Retail

The Savills report also points to a series of trends that will define the future of retail in Spain. Efficiency, flexibility and the emergence of new ways to shop will be key to success.

• Last-mile optimisation: Logistics has become a crucial factor for customer satisfaction. Companies are investing in optimising the last mile to offer faster, more flexible and more sustainable deliveries.
• Personalised offerings: Thanks to data analysis, companies can get to know their customers better and offer them personalised products and services, thereby increasing conversion and loyalty.
• Click & Collect: This purchasing method, which allows customers to collect an online order in-store, is a clear example of the convergence between the physical and digital worlds. The rise of click & collect in Spain shows that consumers are looking for convenience and flexibility.
• New sales channels: The digital channel is fragmenting and specialising. Vertical marketplaces, Direct To Consumer (D2C) brands, and live shopping and social commerce strategies are emerging, opening up new opportunities to reach consumers.

Conclusion: a Hybrid Market Led by Innovative Companies

The forecast that online retail will account for 11.2% of retail sales in Spain by 2025 should not be interpreted as the end of traditional retail. Rather, it should be seen as the consolidation of a hybrid model in which the online and offline channels complement and reinforce each other.

In fact, Spanish businesses demonstrate a remarkable ability to adapt in this regard. A revealing figure from the Savills report is that Spanish companies are above (20%) the European average (19%) in online sales. This leading position shows that e-commerce is already a strategic pillar and that the Spanish market is dynamic and competitive.

The future of retail inevitably involves omnichannel strategies, personalisation and the creation of unforgettable shopping experiences. Those companies that know how to adapt to this new scenario, by investing in technology, logistics and, above all, in a deep understanding of their customers, will be the ones to lead the market. In short, the path towards that 11.2% is not just a statistic. It’s a roadmap full of opportunities for Spanish companies to continue to innovate and demonstrate their competitiveness in a global market.

The post The future of retail: online retail to reach 11.2% of sales in Spain in 2025 appeared first on Flipflow.

Every last Friday of November, the same ritual repeats itself: shop windows packed with red signs, discounts promising to be 70% off, endless queues, and a fierce battle to offer the lowest price. For years, Black Friday has operated on a simple premise: whoever discounts the most, sells the most. Shops compete to shout the loudest about their offers, flooding consumers with mass promotions that, in theory, benefit everyone equally.

However, Black Friday 2024 highlighted a paradigm shift: AI and chatbots generated over 14 billion dollars in online sales worldwide. As we can see, the universal discount strategy is beginning to show its cracks. Margins are eroding, customers compare prices in seconds on their smartphones, and, paradoxically, the saturation of offers is breeding mistrust. The competitive advantage no longer lies in discounting more than the competition, but in discounting more intelligently. And this is where Generative AI comes in. As highlighted by estorebrands, in 2024, retailers who leveraged Generative AI in their strategies achieved conversion rates 9% higher than those who did not.

This technology represents a quantum leap from traditional artificial intelligence. While classic analytical systems are limited to processing historical information and detecting patterns, Generative AI takes a step forward: it creates new content. It generates unique offers, writes personalised communications, and designs pricing strategies adapted to each individual customer, all in real time. We are talking about systems capable of understanding each shopper’s context and building, on the fly, the exact value proposition that will maximise conversion without destroying profit margins.

The Role of Generative AI in Personalisation and Creativity

Generative AI’s ability to create original content is opening up a range of possibilities that until recently seemed like science fiction. Its application goes far beyond simple automation, allowing retailers to connect with their customers on an unprecedented level of personalisation.

One of the most direct uses is the creation of content at scale. Imagine receiving an email for Black Friday whose subject line not only includes your name, but also references that product you viewed 3 times last week. The product description on the website could adapt dynamically to highlight the features that interest you most, based on your browsing history. Social media ads would no longer be generic, instead becoming visual and textual recommendations that seem tailor-made for you. All this content, from the text on a banner to the script for a short video, can be generated by generative AI to resonate with each individual during Black Friday.

Some pioneering retailers are already applying these principles. For example, fashion e-commerce platforms use AI to analyse a customer’s style and generate complete, personalised “looks”. If a user often buys minimalist-style clothing, the AI can create a section on the homepage titled “Your Black Friday essentials”, populated with products that perfectly match their preferences and showing how to style them. Amazon, for its part, has implemented generative models that create variations of its product pages based on the user’s browsing history, modifying everything from the order in which features appear to the images that are shown first.

This technology also drives truly innovative shopping experiences. Virtual shopping assistants can hold fluid conversations, understanding the customer’s context and needs to recommend the ideal product.

The Pillars of the New Black Friday Strategy

The traditional approach of fixed discounts is being surpassed by three strategic pillars that generative AI makes possible, transforming the way retailers plan and execute their campaigns.

1. Hyper-personalised dynamic pricing

Dynamic pricing is not new. Airlines and hotels have been adjusting their rates according to demand for decades. However, Generative AI introduces an additional dimension: individual personalisation.

The traditional system modifies prices based on aggregate variables such as stock levels or general demand. Generative AI, on the other hand, can calculate a specific discount for each user. It analyses their purchase history, price sensitivity (how many times they have viewed a product before buying it, whether they usually wait for the sales), their potential value as a long-term customer, and their probability of conversion at different discount levels.

Let’s imagine two customers interested in the same television. The first is a regular, loyal customer of the brand with a high lifetime value. The second is a bargain hunter who has never bought from the brand before and is probably comparing prices on multiple sites. AI can offer the first customer a 12% discount with free delivery, knowing that her loyalty doesn’t require an aggressive price cut. For the second, it presents a 20% discount with one condition: she must complete the purchase within the next two hours. The goal is to convert without unnecessarily giving away margin.

2. Creating bundles and offers “On-the-fly”

One of the most powerful applications of Generative AI is its ability to build product bundles in real time. The system observes what a customer has in their basket and, in milliseconds, generates a complementary offer that is irresistible.

Suppose a user adds a DSLR camera to her basket. Generative AI doesn’t just suggest generic accessories. It analyses what accessories other buyers of that camera usually purchase, reviews the margin on each complementary product, considers the total price of the basket, and builds a specific proposal: “Complete your photography kit: add a 128GB memory card, a professional tripod, and a carrying case for an additional 30% off the complete bundle“.

The key is that this offer is generated exclusively for this customer, at this moment. Another user with the same camera in her basket but a different purchasing profile might receive a different bundle, perhaps one focused on additional filters and lenses if her history indicates an interest in advanced photography.

3. Predictive margin optimisation

The real challenge of Black Friday has always been striking the right balance: discounting enough to drive sales, but without destroying profitability. Perhaps the most strategic pillar is the AI’s ability to act as a large-scale business simulator. Before Black Friday begins, generative AI models can run thousands, or even millions, of discount scenario simulations.

What happens if we offer a 15% discount on laptops for the first 24 hours? What if we increase it to 25% but only for customers who abandoned their basket in the last week? How will offering free delivery versus a direct 10% discount affect the total margin?

The AI runs these simulations considering complex variables: demand elasticity by product category, historical customer behaviour, stock forecasting, logistical costs, and competitor pricing. The result is a much more sophisticated discount strategy than the typical “everything 50% off”. It allows businesses to identify which products should be aggressively discounted to generate traffic (so-called loss leaders), which can maintain higher margins because they have less competition, and which customer segments will respond best to non-monetary incentives like early access or free express delivery.

Understanding the Engine: How Promotions Work Thanks to Real-Time Data and Generative AI

To understand how Generative AI transforms Black Friday promotions, we need to break the process down into two fundamental stages.

Step 1: Real-time data capture

It all starts with the massive collection of information. In milliseconds, the system absorbs 3 categories of data:

• Behavioural data: Every user interaction leaves a digital footprint. The system records which products they examine, how long they stay on each page, which reviews they read, which items they add to their basket, and which they later remove. It also detects patterns: whether the user tends to browse at night or if they have previous abandoned baskets.
• Contextual data: The user’s geographical location provides valuable information, from weather factors to local events, as does the time of day they are browsing. The device also matters: a user browsing on their mobile during their tube journey behaves differently to someone researching on a computer at home.
• Market data: The system constantly monitors the competition. At what price are they offering similar products? Do they have stock available? It also analyses trends on social media: which products are going viral, which features consumers value most in their comments, and what complaints are emerging about competitors’ products.

Step 2: The generative brain

This is where the magic happens. The data on its own is inert; its value emerges when the AI transforms it into actions.

• Scenario simulation: The generative model forms hypotheses. For a customer who has visited the page for a pair of trainers four times, who abandoned their basket two days ago when the price was €89, whose history shows impulse buys when discounts are over 20%, and who has just searched Google for “best running shoes 2025”, the system asks itself: Which offer will maximise conversion? A straight 25% discount? An 18% discount plus free delivery? Access to a higher-end model with only a 15% discount?
• Offer generation: Based on the simulations, the AI creates the optimal response. It can generate a personalised discount code, modify the banner on the website to show those exact trainers with the reduced price, write the text for an email (“Mario, your favourite trainers with a 20% discount, today only“), or even trigger a push notification on their mobile.

Risks and Limitations

Despite its enormous potential, implementing generative AI in pricing and promotion strategies is not without its risks. Over-personalisation can feel invasive to the customer, creating a sense of being watched that can be counterproductive. The line between a useful offer and an invasion of privacy is a thin one.

Poorly calibrated dynamic pricing can cause a reputational crisis. If a loyal customer discovers that a new user is being offered a significantly better price for the same product, the perception of unfairness can irreparably damage trust in the brand. Furthermore, there are regulatory issues related to data privacy (such as GDPR in Europe) and price discrimination that must be managed with extreme care.

Therefore, it is essential to establish clear “safety barriers” (guardrails). Human supervision is needed to define the limits within which the AI can operate, as well as constant trials and A/B testing to ensure that automated strategies are generating positive results for both the business and the customer experience.

Key Lessons for Integrating Generative AI into Retail for Black Friday 2025

The incorporation of generative AI into discount strategies invites retailers to review how they make decisions and build value in an increasingly competitive promotional environment. Technology does not act as a shortcut, but as a tool that expands human capacity to interpret market signals and respond with precision.

The challenge for the coming years will be to integrate these systems maturely: establishing clear limits, reinforcing data quality, and defining what level of automation is appropriate for each business. Retailers who approach this adoption judiciously will strengthen their ability to anticipate demand, better manage their margins, and design more coherent customer experiences.

In a scenario like Black Friday, where every decision immediately affects profitability, having well-governed generative models can be the difference between improvising and acting with intent. The potential is there; the impact will depend on how it is implemented.

The post Black Friday 2025: How generative AI is transforming discount strategies in retail appeared first on Flipflow.

At flipflow we believe information shouldn’t just be available: it needs to be easy to understand, quick to consult, and actionable. Market analysis waits for no one. Opportunities appear and disappear in a matter of hours, and strategic decisions require clear, accessible, and useful data at precisely the right moment. That’s why we’ve redesigned flipflow: so your team can move at the speed the current market demands.

This new design goes far beyond a cosmetic change: it’s a strategic evolution that enhances efficiency, clarity, and usability, boosting the daily work of all teams. Everything is faster, more intuitive, and designed to accompany you into the new era of Artificial Intelligence.

Here’s what awaits you.

Faster and Easier-to-Use Interface

Agile and Accessible Navigation for Everyone

Speed and simplicity are essential when analysing large volumes of data. Data complexity shouldn’t translate into usage complexity. With flipflow’s new design:

• Faster Navigation: find key information in seconds, without wasting time.

• Intuitive and Accessible Interface: any user, regardless of their technical level, can easily explore data.

• Optimised Visual Experience: every panel, section, and data point is organised for clear and understandable reading.

We have simplified the use of the platform, eliminated unnecessary steps, and created an experience that feels natural from the very first moment. These improvements allow users to focus on what truly matters: making data-driven decisions in record time.

New Visualisations and Optimised Workflows

Clearer Insights and Faster Decisions

Data analysis depends as much on the available information as on how it is visualised. Data tells stories, but only if you know how to read them. That’s why flipflow’s new UI introduces:

• Improved Data Visualisation and Readability: customisable dashboards, readable charts, and reports that facilitate data interpretation.

• Clearer Workflows: more intuitive actions within the platform, allowing tasks to be completed in fewer steps and with less effort.

• Compare multiple variables, apply dynamic filters, and explore your data from different angles without losing context.

Thanks to these improvements, insights become clearer, more actionable, and quicker to communicate, driving strategic decision-making across the organisation.

New Features in Report Management

Customised Dashboards and Reports, and More Efficient Teamwork

Market analysis is rarely an individual effort. The best decisions arise when teams work together, combining perspectives and experience. Furthermore, information management is as important as the information itself. With the new flipflow:

• Easier to Generate Customised Reports: create reports from scratch that reflect exactly what your company needs.

• Your most important reports are always one click away, automatically updated and ready to share or present at any time.

• Improved Automations: Now you can choose the exact day you want to receive the report. You can also see which reports are being sent automatically.

These functionalities improve access to information. Because when all teams have access to the same data and can contribute to the analysis, organisations move faster and make better decisions.

New Collaborative Functionalities (coming soon)

Additionally, we are preparing a future rollout that will include new advanced functionalities to boost team productivity:

• Permission Assignment: establish different access levels based on the user for more secure and personalised management.

• Improved Maps: more complete and dynamic visualisations to explore data intuitively.

• View Shared: easily review with whom each dashboard has been shared and maintain control of your information.

These functionalities allow teams to work more coordinately and efficiently, eliminating information silos, accelerating action, and reducing analysis times.

Ready for AI Agents (coming soon)

Coming Soon: Smart Assistance for Faster Decisions

Artificial intelligence is transforming how we analyse and act on market data. The new flipflow is not only ready for this revolution, but it has been specifically designed to leverage it.

We are preparing a future rollout that will include advanced functionalities to boost team productivity:

• Tyrell AI: an intelligent AI Agent that will help interpret data, generate useful insights and reports from scratch by cross-referencing information from Flipflow and your own business data. It will also be able to respond by performing Deep Research on all market data and suggest real-time actions suitable for you and your company proactively.

This technological foundation means that, as we develop new artificial intelligence capabilities, they will integrate naturally into your existing workflow. You won’t have to learn a new tool or change your way of working; you’ll simply find that flipflow becomes increasingly intelligent and useful over time.

Start Enjoying This New Experience

The new flipflow is already available and at your fingertips for you to explore. For current users, the transition will be automatic and seamless: simply log in as usual and discover the new experience. All your data, reports, and settings will be exactly where you left them, but with a completely revamped interface.

If you’re not yet a flipflow user, this is the perfect time to discover how a truly modern market analytics platform can transform the way your organisation makes decisions. Request a demo and we’ll show you firsthand.

We are excited to share this new chapter with you. Explore, experiment, and let us know what you think. Your way of transforming Retail has just evolved. And so has flipflow.

The post Flipflow Gets a Makeover: Faster. Smarter. More Human. appeared first on Flipflow.