Author: Katherine Gortz

Acquiring a new customer costs between five and twenty-five times more than retaining an existing one. And yet, most retail companies continue to direct the majority of their marketing budget toward acquisition.

And yet, most retail companies continue to direct the majority of their marketing budget toward acquisition, even though 65% of their revenue comes from just 8% of their most loyal customers.

The explanation seems obvious. Without acquisition, there is no business.

But framing client strategy as a choice between acquisition and retention is an oversimplification. The real problem is that many companies do not have a precise understanding of when a customer becomes profitable. And without that answer, any debate about budget allocation is, at best, an educated guess.

Striking the right balance between acquisition and retention depends on three factors that vary significantly across businesses: product margin, purchase type and the point in the customer cycle at which real value is generated.

For a premium furniture or appliance retailer, the cost of acquisition may be recovered on the first order. The customer arrives with the decision practically made, clear purchase intent and a high ticket value. In that case, the strategic priority is not necessarily to accelerate a second purchase, but to convert a good experience into a recommendation.

For a fashion brand investing in paid social and offering welcome discounts, the first purchase is likely not to be profitable. Profitability typically arrives with the second purchase, when the customer buys without an incentive.

For a jewelry brand or luxury label, the return can take years to materialize, sometimes not until the third or fourth transaction. Acquisition costs are high and purchase frequency very low. The key to profitability lies in the long-term client relationship.

Without understanding that profitability threshold, it is impossible to decide how much to invest in acquisition, how much in retention, and which levers to activate at each stage of the customer cycle. Yet many companies still cannot answer that question clearly.

WHY FINDING THE RIGHT BALANCE IS SO DIFFICULT

Measurement and attribution present significant challenges.

Customers typically interact with a brand across multiple platforms before making their first purchase. A social media ad, a recommendation from a friend, an organic website visit or an email can all be part of the same decision-making process.

The complexity increases further after the first purchase.

Imagine a customer who is satisfied with their order, joins the loyalty program, receives an email three weeks later, and returns to buy. What brought them back? The product? The loyalty rewards program? The email? A combination of all three?

The effects accumulate over time and rarely appear cleanly in any dashboard. Understanding them requires a longer view of the customer cycle and a different attribution logic.

This is why many marketing decisions are still made based on partial or short-term metrics. And when metrics are incomplete, investment tends to concentrate on what is most visible and easiest to measure: acquisition.

THE REAL COST OF IGNORING RETENTION

The well-known finding that acquiring a new customer costs between five and twenty-five times more than retaining an existing one appears consistently throughout the marketing literature and has been widely cited by Harvard Business Review.

A similarly striking finding comes from relationship marketing research. It is estimated that a 5% increase in customer retention can increase profits by between 25% and 95%, according to research by Frederick Reichheld of Bainand Company.

The potential impact is too significant to treat retention as a secondary priority.

But activating that lever correctly requires more than increasing the volume of CRM campaigns. It requires understanding precisely who your customers are, what value they generate, and where they are in the cycle.

And that is where many organizations run into another obstacle.

HAVING DATA IS NOT THE SAME AS HAVING CUSTOMER INTELLIGENCE

Today’s retail companies accumulate large amounts of information: purchase histories, web behavior, loyalty data, customer service interactions and email opens.

But having data does not mean truly knowing the customer.

In many organizations, information is fragmented across multiple systems. Purchase history lives in Shopify. Loyalty promotions in another platform. Browsing behavior in Google Analytics. Support interactions in Zendesk. Email campaigns in Klaviyo.

Each system knows something about the customer, but none of them actually knows the customer.

Without a layer that unifies those signals, it is impossible to have a clear picture of who that customer is, what interests them, and where they are in the cycle.

That is why the first step toward a solid client strategy is usually not segmentation or artificial intelligence. It is data architecture.

A Customer Data Platform (CDP) makes it possible to unify those sources into a single, actionable customer profile. It is not just a marketing tool. It is the foundation that allows any acquisition or retention strategy to operate with real business logic.

HOW METRICS ARE CONVERTED INTO BUSINESS DECISIONS

When customer data is centralized, segmentation can begin to answer questions that are relevant to the business. Which customers generate the most value? Who is at risk of churning? And who has the greatest growth potential?

Predictive models can identify early churn signals, such as drops in purchase frequency, absence of interaction or a declining average order value.

What distinguishes companies that grow sustainably is their ability to convert operational metrics into business decisions. Many teams still measure email open rates, click-through rates and volume of communications sent. These are useful metrics, but they rarely answer the questions that actually matter.

How many at-risk customers were recovered?

How many moved from a first to a second purchase as a result of a specific initiative?

How much did the lifetime value of customers acquired last quarter increase?

When analysis focuses on the complete customer cycle, the debate between acquisition and retention begins to lose its relevance. Both become levers within a single strategy.

ROADMAP FOR BUILDING A CUSTOMER STRATEGY

1. Identify when your customer becomes profitable. Do not assume it is the same for every business. Knowing the threshold precisely is the prerequisite for everything else.

A premium furniture or appliance retailer may recover acquisition costs from the first order. A fashion brand running paid social with a welcome discount rarely sees profitability on the first transaction: the threshold comes with the second purchase, the one made without an incentive. A jewelry or luxury brand may not see a return until the third or fourth transaction, sometimes years later. When acquisition costs are structurally high and purchase frequency very low, the bet is not transactional but rather relational. 

2. Revisit the segmentation logic based on the business model.

For high-frequency businesses such as online supermarket or pharmacy, the priority is usually detecting early churn signals: small drops in frequency are warning signs that predictive models can identify before the customer is lost. For low-frequency businesses such as furniture or electronics, the key is to identify customers with the greatest potential for recommendation or to upsell at the right moment. If segmentation does not make this distinction, it is not serving the business.

3. Design initiatives for the critical moment in each business’s customer cycle.

For most ecommerce businesses, that moment is the transition between the first and second purchase, the most decisive and most neglected stretch. For high-frequency businesses, it is early churn prevention, where predictive intelligence adds the most value by acting on risk signals weeks in advance. For high-ticket businesses, it is the post-sale experience and the long-term relationship. The question is not “what campaign do we launch?” but “what does this segment need, in this type of business, at this specific moment?”

4. Define who owns the client strategy, with real authority over budget and KPIs.

In many organizations the customer belongs to several teams but to none in particular. Marketing, CRM and ecommerce each work on parts of the cycle, but no one has a complete view of the customer or direct responsibility for their profitability. In a business where the customer becomes profitable on the second purchase, someone has to be accountable for ensuring that second purchase happens.

5. Incorporate advocacy as a growth engine, especially in businesses where paid media shows diminishing returns.

A satisfied customer who recommends the brand can generate new customers at near-zero acquisition cost and with a retention rate higher than any paid channel. For high-ticket, low-frequency businesses, advocacy is not an add-on: it is the most efficient path to growth. For high-frequency businesses, it is the lever that closes the loop between retention and acquisition. In both cases, it is the most systematically overlooked element in marketing plans.

FLYDE TALKS 5

These questions will be at the center of FLYDE Talks 5, on 24 March at 6pm CET via LinkedIn Live, where FLYDE CEO and Founder Paco Herranz and digital strategy expert Enrique Miralda will discuss how to build a true client strategy in retail.

You can register for the event here.  Kindly note that the session will be held in Spanish.

We’ve launched Brain, an AI copilot that brings natural language capabilities to the FLYDE Customer Data Platform. You can now ask questions and get answers directly from your data without needing SQL knowledge or waiting on technical teams.

Ask Brain your questions in natural language. Get actionable answers based on your real business data.

With Brain, you can create datasets, build audiences, analyze results, generate reports, and make strategic decisions powered by predictive intelligence, all by writing in natural, conversational language. Brain also helps you ask better questions, deepen analysis with suggested follow-ups, prepare presentations instantly, and collaborate seamlessly across teams.

BRAIN IN CORE: GENERATE DATASETS WITHOUT WRITING SQL

Core is FLYDE’s app for data storage, conversion, and transformation. It is where you connect data from different sources, consolidate everything into one place, and build the datasets that power your marketing decisions. Historically, creating datasets has required technical knowledge, writing SQL queries, or waiting for your IT team.

Brain changes that entirely.

When creating a dataset in Core, simply describe what you need in plain language; fore xample, “I want sales by user and loyalty points.” Brain interprets your request and automatically generates the SQL query needed to build it.

This enables marketing and business teams to work independently, dramatically shrinks turnaround times, and accelerates data exploration. SQL generation democratizes advanced analytics, allowing more team members to work directly with data.

BRAIN IN MARKET: CREATE AUDIENCIES AND ANALYZE BEHAVIOR

Market is FLYDE’s audience activation and management application. It’s where you build customer segments that fuel your campaigns, activate them across channels, and understand their behavior.

With Brain in Market, you can create new audiences using natural language instead of manually applying filters. Describe what you need and Brain translates it into the appropriate filter logic.

Example: A bookstore has overstock of the novel, A Hundred Years of Solitude, by Gabriel García Márquez and wants to run a targeted promotional campaign via email. Rather than manually configuring filters, you can tell Brain: “Create an audience of customers who are likely to buy A Hundred Years of Solitude and opted in to promotional emails.” Brain generates the audience in seconds, and explains the logic to you, every step of the way. 

In the fourth episode of FLYDE Talks, Paco Herranz, founder and CEO of FLYDE, spoke with Álvaro Pariente, data and enterprise technology expert and founder and CEO of BEOC9, to analyze the key factors that will determine business success this year. The conversation explored crucial topics such as how to organize data, the role of CDPs (Customer Data Platforms), and why many companies are not seeing real results from artificial intelligence.

THE CRITICAL TRIANLGE: BUSINESS, DATA AND IT 

Álvaro began by highlighting a structural issue affecting many organizations. For years, companies have been digitizing processes and collecting data across multiple systems. However, this transformation created a problematic divide between three departments that should be working together:

• IT: decides on architecture and systems
• Business: defines the “what” and how to impact the customer
• Data: often scattered between IT and business, with no clear owner

The result is predictable: data silos, lack of coordination, and multiple departments engaging the same customers as if they were entirely different companies.

The solution is not technological but rather organizational. Before investing in tools or implementing AI, companies need to align these three pillars internally and give them equal importance. Only then can they extract real value from their data.

THE REAL PROBLEM: ATTRIBUTION AND FRAGMENTATION 

A perfect example of this lack of organization is conversion attribution. When multiple departments interact with a customer through different channels (paid media, email, etc.), each one claims the conversion as its own.

The problem becomes even more troublesome in fast-growing companies that are investing aggressively in acquisition, because proving the return on each channel is critical.

THE EVOLUTION OF CDPs

Álvaro explained how the market has evolved from MDM systems (Master Data Management) to the new generation of CDPs. MDM systems required long projects, complex integrations, and the creation of a centralized “Golden Record” that often became invasive for existing systems.

Modern CDPs offer a different approach:

• Less intrusive: they connect to existing systems without disrupting operations.
• Continuous data collection: they unify data from multiple sources in real time.
• Identity resolution: they build a single customer view without requiring a centralized record.
• Fast activation: they allow immediate use of that information in the right channels.
• Compatibility with your tools: they do not require a single-vendor infrastructure and can connect with Adobe, Salesforce, Braze, or other tools.

Paco emphasized the importance of this point: no single vendor can cover every use case a business needs.

THE UNCOMFORTABLE TRUTH ABOUT AI

This was the most critical point of the conversation. Álvaro was direct:

“Without data organization and data scale, AI, in my view, will not take you anywhere.”

The problem is not the AI model. The problem is the data.

WHY MANY COMPANIES ARE NOT SEEING RESULTS WITH AI

ChatGPT works because it has access to a massive encyclopedia of information on the internet. But when a company wants to apply AI to its business, it is not querying the internet. It is querying its own internal data.

And that is where things become complicated:

• If your data is not organized
• If your prompt is poorly structured
• If your systems lack coherent information
• If your data is fragmented into silos

The result will not be what you are hoping for, no matter how much money has been invested in sophisticated technology.

The companies seeing real value from AI all share one thing in common: they organized their data first (customer information, internal processes, organizational knowledge), and only then applied technology. Not the other way around.

AN EXAMPLE: SENTIMENT ANALYSIS

Paco shared a concrete case: a company with millions of customer interactions whose only measure of satisfaction was sending Net Promoter Score (NPS) surveys, which most people do not respond to.

The solution is clear if the data is organized: run those conversations through AI-powered sentiment analysis. The company already has all the information needed to determine whether a customer is happy, frustrated, or about to leave a negative review.

No new data is required. The data is already there. The only missing piece is applying the right technology on top of a well-organized data foundation.

SECURITY AND GOVERNANCE: NON-NEGOTIABLES

A critical point was emphasized: you cannot send private company data into a public LLM without proper safeguards. Doing so would expose employee and customer data.

The solution is to use models (OpenAI, Anthropic, Google) within a secure architecture that includes:

• Data governance policies
• Access control
• GDPR compliance in Europe
• Clear management of what data is served, what is exposed, and what is received

IMPLEMENTATION STRATEGY

The conversation also addressed how implementation timelines have changed. Álvaro was clear: 18-month projects are a thing of the past.

The strategy that works today is:

1. Focus on one single use case (not seven)
2. Implementation in a maximum of 2 to 3 months
3. Measurable impact on a specific KPI (churn, lifetime value, RFM)
4. Iterate and expand once value is proven

This approach has clear advantages:

• Reduces time and costs
• Makes ROI traceable
• Drives adoption and change within teams
• Results improve exponentially with each new use case

As Álvaro said: “If consulting doesn’t deliver value, and value is tied to KPIs, then we shouldn’t be there.”

THE GARTNER MAGIC QUADRANT

The conversation closed with an analysis of the recent Gartner Magic Quadrant for CDPs (2026), the third report since the category was created in 2024.

Key trends identified include:

1. Expansion beyond marketing: CDPs are no longer only for segmentation and campaigns. They are increasingly being used for B2B use cases, customer service, sales, and operations.
2. Composability as the standard: the ability to integrate with multiple systems without requiring a full single-vendor suite is becoming a baseline requirement.
3. AI and natural language access: platforms that allow users to query data using natural language are enabling business users (non-technical teams) to extract insights without needing SQL.
4. The importance of connectors: competition is being defined by the speed and quality of integrations. It is no longer acceptable for a connector to take three months when it should be as simple as “pushing a button.”

CONCLUSIONS: A ROADMAP FOR COMPANIES THAT WILL WIN IN 2026

The main lesson from FLYDE Talks Episode 4 is clear: the companies that integrate data, technology, and business strategy will be the true winners in 2026.

It is not about having the most advanced AI model. It is about:

1. Organizing your internal structure so data, IT, and business teams work together
2. Implementing a CDP that unifies information without being invasive
3. Applying AI to your own data with proper governance and security
4. Starting with specific use cases that prove ROI quickly
5. Scaling iteratively

The question every company should ask is not “What new tool do I need?” but “How do I make my current investment deliver more value?”

HOW FLYDE CAN HELP

Is your company’s data ready for AI? At FLYDE, we will continue driving conversations that help organizations understand this new landscape and take advantage of AI within a secure, results-driven framework. Contact us to explore how you can leverage new technologies within your company.

Artificial intelligence promises efficiency, automation, better decisions and competitive advantages. Yet in practice, many organizations keep asking the same question: If we have so much data, why is it still so hard to generate real business impact?

The challenge isn’t AI itself; it’s how you leverage it. Before talking about predictive modelling, algorithms, or AI copilots, it’s essential to take a closer look at the fundamentals. That’s why we’ve prepared this checklist to assess whether your company is truly ready to apply AI, with impact and ROI.

AI DOESN’T START WITH TECHNOLOGY

One of the most common mistakes is thinking that AI readiness begins when a new tool is added to the tech stack. In reality, it starts much earlier. It starts when data becomes available, structured and connected to real actions. Without this foundation, AI only adds complexity to problems that already exist.

CHECKLIST: IS YOUR COMPANY READY FOR AI?

Anwer the following questions:

Data Foundations

• Do you have customer, marketing, and sales data clearly identified and centralized?
• Do teams trust the quality and reliability of the data they use to make decisions?
• Are there clear, shared definitions of key business metrics across teams?

Data Activation and Real Use

• Is data used to make decisions and take action, not just reporting?
• Can you move from an insight to an action without long intermediate processes?
• Can business teams access insights without constantly depending on IT or Data?

Tech Stack and the Role of a CDP

• Is your data stack designed to evolve and scale, rather than just address problems?
• If you have a Customer Data Platform (CDP), does it have a clear role within your tech stack?
• Can you connect data from different sources without tedious, manual processes?

Advanced Analytics and Forward-Looking Vision

• Do you go beyond descriptive dashboard to use predictive or attribution models?
• Can you answer business questions without creating a new report each time?
• Do you have the ability to anticipate future scenarios, not just analyze the past?

Readiness for Generative AI

• Do you have clear AI use cases that truly add value to your business?
• Can you apply generative AI to your own data, not just generic datasets?
• Are you aiming for impact and ROI in weeks, rather than long, complex projects?

HOW TO INTERPRET THE RESUTLS

Count how many times you answered “Yes.”

0–5
Your company isn’t ready to leverage AI for real impact yet. First, you should focus on building a strong data foundation for activation.

6–10
You have a strong starting point, but are encountering obstacles in coordinating data, technology, and decision-making. AI can help if applied strategically.

11–15
Your company is well-positioned to start monetizing AI, with clear use cases and focus on impact and ROI.

In any case, the goal isn’t to “be ready” in the abstract, but to identify where to unlock value first.

FROM DATA TO IMPACT: THE CONVERSATION THAT MATTERS

These are precisely the topics to be discussed in FLYDE Talks Episode 4: From Data to Impact: Keys to Activating and Monetizing Insights in 2026.

Wednesday, February 4 at 17:00 (CET) via LinkedIn Live.
Sign up here.

In this session, Francisco Herranz, founder and CEO of FLYDE, will speak with Álvaro Pariente, a leading data strategy expert who is the founder and CEO of BEOC9. Key topics include how organizations are restructuring internally around data, the role of the CDP in today’s stack, and how to apply generative AI on your data to produce insights, forecasts, and attribution without friction.

WOULD YOU LIKE TO TALK IN MORE DETAIL ABOUT HOW TO PREPARE YOUR COMPANY’S DATA FOR AI?

Contact us to schedule a conversation and discover how FLYDE can power your growth.

The data ecosystem has undergone a decisive transformation in the last few years, reshaping the daily operations of virtually every business. The end of third-party cookies is no longer a looming threat; it is a concrete, operational reality. Privacy regulations are stricter. Generative AI is now embedded in the day-to-day workflows of most companies. And customers expect hyper-personalized experiences delivered with the highest standards of privacy and transparency.

In this context, Customer Data Platforms (CDPs) have become the essential infrastructure that supports modern marketing, customer experience and business intelligence.
Below are the trends that will truly define the CDP landscape in 2026.

1. THE CDP AS THE BACKBONE OF BUSINESS 

With the deprecation of user-level cookie tracking and tighter consent regulations, the Customer Data Platform has become indispensable for understanding customer behavior. A CDP unifies first-party data from multiple sources (web, apps, physical stores, CRM, campaigns, customer service, etc.) and enriches it with demographic and contextual information. It resolves identities, builds 360º customer profiles, and enables accurate performance measurement.

But its role now extends far beyond marketing. CDPs increasingly support core business intelligence use cases, including:

• Demand forecasting
• Price and promotion optimization
• Multichannel sentiment analysis (including reviews)
• Customer lifetime value, churn, and acquisition modeling
• Omnichannel experience management across physical and digital environments

2. ARTIFICIAL INTELLIGENCE POWERED BY FIRST-PARTY DATA 

AI has become the central engine for data activation and its rapid adoption is directly driving the strategic importance of CDPs. According to a Markets and Markets report, the global CDP market is expected to grow at a compound annual growth rate exceeding 30% in the period between 2025-2030, driven by rising demand for the technology.

AI is only as good as the data it consumes. Many companies that implemented AI without a strong first-party data foundation have had to rebuild their architecture around a CDP. Modern CDPs allow AI to generate predictive insights and personalized recommendations based on reliable, governed, unified data. Read more about data integration as the essential preparation for AI. As a result, business decisions become more accurate, timely, and contextual, boosting campaign performance, customer experience and ROI.

3. PRIVACY AND TRUST AS A COMPETITIVE ADVANTAGE

Stricter regulations and rising consumer concern over privacy have reset the industry’s priorities. Companies are responding in two ways:

• Building data architectures that are based on privacy-by-design
• Using a CDP to provide full transparency and traceability: where data comes from, how it is used, and by whom

Meeting regulatory standards, ensuring traceability and offering transparency do more than protect businesses legally; they build genuine competitive advantage. Customers reward trust, and organizations that treat privacy as a core operating principle cultivate stronger relationships with customers and long-term loyalty.

It’s no longer just about collecting information. It’s about earning trust.

4. USABILITY AND AUTONOMY FOR BUSINESS TEAMS

A CDP’s success no longer depends solely on technical expertise within IT. In 2026, the most effective platforms are combining power with accessibility: intuitive interfaces, automated workflows and visual tools that allow marketing, sales and business teams to work directly with data.

This autonomy removes bottlenecks, accelerates campaign activation, and turns complex datasets into strategic, actionable decisions, without relying on slow or highly specialized internal processes. The differentiator is no longer the technology itself, but the clarity and business relevance of the use case.

And adoption is becoming even easier. Modular CDPs are gaining traction: platforms in which companies activate only the components they need. This reduces the learning curve, eliminates unnecessary complexity and facilitates real adoption across teams.

5. REAL-TIME AS THE NEW OPERATING STANDARD

Updating profiles, segmenting audiences, and activating campaigns in seconds is now an expectation, not a differentiator. Real-time capability reshapes the customer relationship: businesses can personalize experiences instantly, respond to interest or churn signals in the moment, and optimize resources with greater precision.

Modern CDPs turn data into immediate action, closing the loop from insight to decision to execution in one integrated, efficient flow.

HOW FLYDE STANDS OUT

At FLYDE, we know companies want to generate real business impact without long technical processes. That’s why we focus on accelerating time-to-value, helping teams see results quickly. Our platform is intuitive, visual, and powerful, designed for use by marketing and business teams. And with personalized support from day one, every client unlocks the full potential of their data.

Contact us to schedule a conversation and discover how FLYDE can power your growth.

At the third FLYDE Talks event, FLYDE Founder and CEO, Paco Herranz, was joined by Víctor Moreno, Staff Data Scientist at TomTom, to explore the current state of generative artificial intelligence and its technological, professional and social implications. The discussion covered how we got to this point, what is truly changing, and the challenges companies must face in this new phase. A full recording of the event (in Spanish) can be viewed on LinkedIn. 

A TECHNOLOGY THAT WASN’T BORN YESTERDAY

The conversation highlighted that while generative AI is currently trendy, AI itself is not a new concept. Its roots go back to early examples such as data analysis during World War II or the rule-based systems of the 1970s and 1980s.

The recent leap forward is not due to a new idea, but to technological advances that finally made long-standing concepts viable. GPUs enabled massive and efficient parallel computation. Natural Language Processing (NLP) allowed text to be converted into numbers more accurately. And the availability of large volumes of data made it possible to train much more powerful models.

THE DEMOCRATIZATION OF AI

The most recent change has been the democratization of access. Previously, working with AI required specific technical knowledge. Today, anyone can use it through simple interfaces like ChatGPT. This shift goes beyond workplace implications and into the social realm, changing how we perform personal tasks, such as asking an assistant for trivial data.

Víctor highlighted how this change is transforming even the way we ask questions. We rely on assistants to solve doubts, summarize information, or make initial decisions. This change is profound: it effects how we think, evaluate and structure our work.

By lowering the barrier to entry, adoption accelerates. Companies that do not adapt risk falling behind—not due to a lack of technology, but due to a lack of understanding of how to incorporate it effectively.

THE VALUE OF AI IN PRODUCTIVITY AND CREATIVITY

Víctor highlighted two key areas of value:

1. Productivity: AI allows large amounts of information to be processed, content to be summarized, alternatives to be proposed, and tasks that previously took hours to be automated. For example, in programming, AI is improving productivity by an estimated 10–15%.
   
   
2. Creativity: AI enhances creativity by removing the “fear of the blank page” and offering new ways to solve problems or start projects.

SPECIFIC APPLICATIONS IN MARKETING

Marketing is among the areas in which generative AI is growing exponentially. Personalization has been taken to a new level, handling thousands of micro-segments. Content can adapt dynamically. Campaigns can be optimized in real time. The list goes on.

At FLYDE, we’ve developed tools like FLYDE Brain, which proposes audiences from simple descriptions, analyzes behaviors, and suggests campaign optimizations, empowering teams to unlock more of AI’s potential for data-driven marketing.

Other AI applications in marketing include:

• Virtual replicas, which simulate how a customer might react to a message.
• Virtual replica farms, to conduct quick, low-cost surveys and market studies.

KEY RISKS AND CHALLENGES

Despite the progress, generative AI has significant limitations that must be carefully managed.

• Work slop: Poorly generated content can reduce productivity and damage credibility.
  
  
• User responsibility: Models are designed to respond, not to question. As Víctor explained, they can “lie” if the prompt pushes them in that direction. Ultimately, the user is responsible for what is generated. If “the car crashes,” the driver is responsible.
  
  
• Security risks: There is a risk of prompt injection, where the text consumed by the agent can be modified to influence its actions, potentially leading to unwanted access to databases if proper protection is not in place.
  
  
• Legality and data: In Europe, regulations such as GDPR require responsible and secure use. Platforms like FLYDE allow AI to work with real customer data in a controlled environment, avoiding unnecessary risks.
  
  
• Rising costs: Token prices will increase, so responsible and efficient use of AI is necessary.

FINAL ADVICE ON THE IMPORTANCE OF ADAPTING

Víctor emphasized the importance of adapting to the new paradigm, comparing it to the shift from the steam engine to the electric engine: industries took decades to realize they not only had to replace the engine, but completely change their work structures to leverage the new technology.

Looking forward, the challenge for companies will be learning to integrate this technology in a safe, responsible, and strategic way. At FLYDE, we will continue driving conversations that help understand this new scenario and leverage AI within a safe, results-oriented framework.

Contact us to learn more about how FLYDE can help your business leverage AI’s capabilities. 

In this episode of FLYDE Talks, Luis Serrano, Head of Growth at Real Madrid, sits down with Paco Herranz, Founder and CEO of FLYDE, to explore how the concept of Growth Marketing has evolved in an environment shaped by artificial intelligence, extreme personalization, and data privacy—and how it can be applied to the unique context of football.

With this new episode of FLYDE Talks, we continue to bring together leading voices from across the marketing world to discuss, clearly and without jargon, the ideas that are transforming the industry today.

WHAT DO WE REALLY MEAN BY GROWTH?

Paco opens the conversation with a question every growth professional has asked themselves: What exactly do we mean by “growth”?

For Luis, the term has expanded significantly. What once referred to scaling digital channels now means understanding growth from a holistic perspective: digital and physical channels, data, user experience, and brand value.

“We’re no longer just talking about digital channels,” he says. “We’re talking about everything.”

Growth is no longer about funnel optimization alone; it’s about connecting every touchpoint between the user and the brand under one unified objective.

REAL MADRID’S ‘NORTH STAR’: THE SATISFIED MADRIDISTA

Paco and Luis agree that successful growth depends on having a clear metric that guides the overall strategy: the famous North Star Metric.

At Real Madrid, that North Star is the satisfied Madridista: a fan who trusts the club, shares their digital identity, and enjoys a full, consistent experience across online and offline channels. The satisfied Madridista is the “guiding star” behind every growth initiative at the club.

To measure that satisfaction, the team tracks KPIs that range from fan acquisition and retention, including engagement metrics, NPS (Net Promoter Score), and churn. The challenge lies in turning every interaction into a source of value, for both the fan and the brand.

‘ONE FAN, ONE EXPERIENCE’: UNIFYING DATA FOR ONE-ON-ONE PERSONALIZATION

From FLYDE’s perspective, growth can only scale if data is unified. It starts with data collection—first, second, and third party—and continues with data unification to create a single customer profile, the key to enable precise segmentation, activation, and measurement.

The unified customer profile is the foundation of any growth strategy. It allows teams to move from analysis to action: building micro-audiences, orchestrating omnichannel campaigns, and, most importantly, measuring attribution accurately. The real challenge isn’t gathering more data, but rather knowing where each impact truly comes from.

Real Madrid applies this philosophy with a simple vision: One fan, one experience.
From email to app, store to stadium, every interaction is tracked and optimized to deliver the best possible experience within the club’s ecosystem.

The ultimate goal is true micro-segmentation, evolving from “many-to-many” to “one-to-one,” offering each fan exactly what they need. As Luis puts it simply: “If I have a cat, why are you offering me dog food?”

Read more about the importance of data unification.

‘SEO IS NOT DEAD, AND GEO IS SEO.”

“SEO isn’t dead—and GEO is SEO.”

Through experiments with LLMs and metasearch engines, Luis found that generative AIs don’t search websites directly—they search search engines. In other words, for an AI to index your content, you still need to rank well on traditional search engines first.

So optimizing for visibility in AI results still means doing SEO: paying attention to microformats, structured data, and quality content. New tools, like Adobe’s LLM Optimizer, can even estimate how readable and indexable your content is for AI.

The takeaway is clear: the future of organic traffic will be hybrid and those who master SEO today will remain visible in the age of AI. At least based on what we know today.

MACHINE LEARNING AND GENERATIVE AI: THE NEW MARKETING DUO

Luis asks Paco how FLYDE integrates AI, and Paco explains that for him, AI isn’t a trend but a natural evolution of data-driven marketing.

FLYDE uses Machine Learning for key tasks:

• Measuring KPIs
• Detecting customer value patterns and projections
• Predicting churn
• Recommending products or audiences

On top of that, FLYDE has developed Brain, a generative AI layer across the platform. Brain acts as a data assistant, enabling any user, technical or not, to interact directly with their data ecosystem: building audiences, suggesting actions, analyzing campaigns, or even generating complex queries.

Its mission is to democratize access to data and remove the “blank page fear.”

As Luis jokes: “AI is like a shrimp cocktail—we have so many things to pick from that we don’t know where to start.”

THE CDP: THE NATURAL EVOLUTION OF THE CRM

Both speakers agree that a Customer Data Platform (CDP) like FLYDE is the strategic backbone that ties everything together.

At Real Madrid, the CDP is built around the Madridista Community, integrating data from e-commerce, the app, the Bernabéu tour, RMP Play, social media, and even in-stadium activity.

Thanks to this integration, the club can microsegment and activate data in real time. For instance, if a user is near the stadium, the system can trigger a personalized app notification with an offer or reminder.

The result is a coherent, contextual, and measurable experience—where data powers emotion.

Contact us to learn more about what the FLYDE CDP could do for your business. 

PRIVACY AND REGULATION: GROWTH WITH RESPECT FOR THE USER

The new era of marketing comes with a non-negotiable condition: privacy.

Luis emphasizes that Real Madrid applies a strict transparency policy because trust is part of the fan experience itself.

Meanwhile, FLYDE advocates for ethical data usage. Its technology supports privacy-safe attribution using inferred data (such as average age, income level, or household type) to improve performance without compromising user trust.

The goal isn’t to know more, but to use what we already know better.

TOWARD A MORE HUMAN, MEASURABLE MARKETING

Growth marketing in 2025 operates at the crossroads of AI, CDPs, and customer experience.

But beneath it all lies a single principle: brands grow when they understand that data only matters when it creates satisfaction, trust, and real value.

Paco leaves us with an important conlcusion. Sustainable growth is born from the connection between data and people—and when done right, that connection is the future of marketing.

Growth marketers today need to be able to optimize campaigns across multiple channels, unify fragmented data, manage acquisition costs, and adapt to rapid industry changes. The challenge is not just executing campaigns but building a scalable, data-informed growth engine that drives sustainable results. The world of marketing has never been more complex… nor full of opportunity!

In this blog, we explore five critical challenges marketers face and how leveraging data activation and analytics can turn these obstacles into growth opportunities. By addressing these critical areas, marketing professionals can implement measured, scalable strategies that drive both immediate performance and long-term customer value.

For those who want to explore solutions to these challenges in depth, our upcoming webinar with Luis Serrano, Head of Growth for Real Madrid, offers a chance to engage directly with a growth leader. Click here for more information.

CHALLENGE 1: BALANCE SUSTAINABLE LONG-TERM GROWTH WITH SHORT-TERM GAINS

Marketing teams often face tension between demonstrating immediate results and nurturing long-term value. Sacrificing customer retention and lifetime value in favor of marketing qualified leads (MQL) or short-term revenue can create the illusion of growth while undermining sustainable performance. Advanced analytics can quantify the impact of retention versus acquisition, allowing leaders to defend their strategy with data rather than intuition. By modeling customer lifetime value alongside near-term KPIs, teams can make informed trade-offs that satisfy stakeholders without compromising long-term growth.

CHALLENGE 2: UNIFYING FRAGMENTED DATA

A single, reliable view of the customer is foundational for effective growth marketing, yet most organizations struggle with siloed systems, from CRM and ads platforms to product analytics and web tracking. Fragmentation reduces visibility and often biases measurement toward easily attributable channels.

Centralizing data enables marketers to track the full journey, uncover hidden opportunities, and deploy more precise targeting strategies. Tools that integrate data in real time and provide actionable segmentation allow for campaigns that are both sophisticated and measurable. If you are looking to build a sustainable and scalable growth strategy, unified data is an absolute must.

CHALLENGE 3: CHANNEL SATURATION AND RISING ACQUISITION COSTS

Undoubtedly many growth marketers are feeling the pressure of escalating customer acquisition costs (CAC) and formerly profitable channels becoming less cost ineffective. Growth marketers need frameworks for modeling CAC sensitivity and simulating different channel strategies to stay ahead. By forecasting cost changes and evaluating alternative acquisition levers, teams can anticipate disruptions and allocate budget dynamically, rather than reacting when profitability declines. This analytical rigor separates reactive teams from those driving consistent, scalable growth.

CHALLENGE 4: AI ADOPTION THAT ADDS TRUE VALUE 

Artificial intelligence can accelerate campaign execution and uncover new insights, but its effectiveness depends on thoughtful application. Simply using AI to automate routine tasks does not differentiate a brand. Leading teams integrate AI into predictive modeling, hyper-personalization, and attribution analysis. To maximize impact, efficient algorithms must be used together with human creativity. The key is leveraging AI to provide insight and support smarter decision making rather than merely speed or volume.

CHALLENGE 5: CONTINUOUS INDUSTRY EVOLUTION

Growth marketing operates in a dynamic environment where technological, regulatory, and behavioral shifts can rapidly alter the rules of engagement. Strategies must be adaptive, incorporate scenario planning, and operate within agile measurement frameworks. Teams that continuously stress-test assumptions and adapt to emerging trends are better positioned to respond to disruptions while maintaining momentum.

LEARN MORE FROM AN INDUSTRY LEADER

The challenges of growth marketing are complex, but actionable strategies exist. Join FLYDE’s webinar with Luis Serrano, Head of Growth at Real Madrid, to explore these topics in depth. This is your chance to gain practical insights, discuss real-world solutions, and engage directly with a seasoned growth leader.

📅Wednesday, October 29, 17h CET / 9h CST
📍LinkedIn Live

Confirm your attendance at this link

Data integration is the essential first step for any business looking to implement artificial intelligence technology. Everyone is talking about AI right now. Marketing campaigns that adapt in real time. Customer service that anticipates needs before they are expressed. Predictive models that make complex business decisions feel effortless. The possibilities sound endless. But here is the part that does not always make the headlines: AI cannot deliver results without the right foundation. That foundation is reliable, complete and accurate data.

According to Gartner’s 2025 Hype Cycle for Artificial Intelligence Goes Beyond GenAI, 57% of organizations believe that their data is not AI-ready. When customer data is scattered across platforms, presented in disconnected reports, and divided into silos, no algorithm, no matter how advanced, can make sense of it. The Gartner report also indicated that less than 30% of AI leaders report that their CEOs are satisfied with the return on AI investments. When AI ambitions clash with siloed data ecosystems and infrastructure constraints, AI will fail to deliver results.

THE HIDDEN WORK: DATA INTEGRATION

Many organizations want to explore AI but quickly discover that their data is not ready. Information lives in CRMs, ecommerce platforms, analytics tools, and support systems. Without a single source of truth, it is impossible to build accurate models or generate reliable insights.

The less glamorous side of AI innovation is the behind-the-scenes work of data integration. Without centralizing data, records are incomplete or duplicated, transactions are disconnected from behaviors, and marketing touchpoints are measured in isolation. The result is noise, not intelligence.

Data integration means more than storing data in one central place. It means connecting, cleaning, and structuring information across all your businesses’ systems, applications, and data sources into a unified, usable format. This unified dataset transforms fragments into full customer profiles. It reveals the journey from the first interaction to the most recent purchase. Most importantly, it provides the context that makes AI accurate and actionable.

HOW FLYDE CAN HELP

The FLYDE Customer Data Platform (CDP) is designed to solve the integration challenge and prepare data for AI-driven use cases. FLYDE connects your data sources, from marketing tools and sales systems to customer service platforms. It collects, standardizes, and combines data into complete profiles that update in real-time.

Once centralized in FLYDE, your data is no longer trapped in spreadsheets or siloed reports. It becomes AI-ready data, structured for insights and accessible across your business units.

With FLYDE you can:

• Build a reliable single view of each customer.
• Feed clean, structured data into AI and machine learning models.
• Provide your marketing, sales, and operations teams with a consistent source of truth.

Once your data is unified, AI can finally do its job. Some of the most powerful opportunities include:

• Smarter personalization: recommending the right product at the right moment, based on actual behavior patterns.
• Leveraging predictive models: forecasting churn, customer lifetime value, or seasonal demand with confidence because the data feeding the model is complete.
• Optimized decision-making: allocating marketing spend where it produces measurable ROI, informed by a complete customer journey.
• Operational efficiency: reducing duplicated work and aligning teams around consistent data.

THE REAL AI MINDSET

AI is not the starting point. It is the outcome of disciplined data integration and unification. Businesses that centralize and structure their data today will be the ones leading with AI tomorrow. Without that preparation, even the most advanced algorithms will fail to deliver meaningful results.

So, if you are excited about AI, and who is not, start with the foundation. With FLYDE, you will not just join the conversation about AI. You will be ready to put it into action. Contact us to schedule a demo and we can show you the possibilities your data holds for AI implementation.

For many businesses, Black Friday–Cyber Monday (BFCM) is the most intense moment of the year for the business’s data. Traffic surges, transactions peak, and first-time buyers arrive in waves. For many brands, this weekend generates a huge portion of their annual revenue.

But the real objective shouldn’t be just to make the sale. The goal should be to convert those new buyers into long-term customers. Without a way to unify and activate data, brands often miss the opportunity to build loyalty after the sale, leaving a massive amount of valuable customer information and opportunity for growth on the table.

THE DATA CHAOS OF BFCM

During BFCM, data flows in from every direction: websites, mobile apps, paid ads, emails, and ecommerce platforms. The omnichannel nature of data sources presents a significant challenge. Customers appear under different IDs, creating fragmented and duplicated records that are almost impossible to activate for retargeting or loyalty campaigns later on. Instead of starting the new year with a stronger customer base, many brands are stuck cleaning up a data mess.

This is where a Customer Data Platform (CDP) becomes an essential tool. A CDP like FLYDE is built to handle this exact challenge by bringing all your customer data into one unified, intelligent platform.

HOW CAN FLYDE HELP?

Real-Time Identity Resolution

One of the most pressing technical challenges of BFCM data management is identity resolution. With traffic and transactions peaking, businesses need a way to link anonymous browsing sessions to known customer profiles.

A CDP like FLYDE combines first-party data such as emails, phone numbers, and loyalty IDs with anonymous digital signals. By resolving identities in real time, the platform eliminates duplicate records and builds a single, accurate profile of each customer. This ensures that even when activity spikes, businesses maintain a complete and coherent view of their customers’ journeys.

Smarter Segmentation

Not all BFCM buyers are equal. Some are loyal customers taking advantage of promotions. Others are deal hunters who may never return without the right follow-up. Treating both groups the same reduces efficiency and limits retention.

McKinsey research shows that companies excelling at customer personalization generate 40% more revenue from those activities than their peers. Advanced segmentation supported by a CDP enables businesses to separate high-value customers from bargain-driven shoppers. For example, FLYDE allows marketers to distinguish between customers who only purchase discounted items and those who also explore full-price collections. This insight shapes tailored post-purchase communication that increases the chance of long-term retention.

Omnichannel Activation

Clean, segmented data is only valuable when it can be activated across the right channels. Modern CDPs sync enriched profiles with platforms such as Meta Ads, Google Ads, email marketing tools, and SMS systems. This allows marketing teams to stop wasting spend on customers who already converted, deliver personalized journeys in the channels where customers are most active, and build targeted retargeting campaigns that deliver higher returns.

By closing the loop between data collection, unification, and activation, businesses ensure that the customer relationships formed during BFCM extend beyond a one-time transaction.

A PRACTICAL EXAMPLE

A consumer electronics retailer uses FLYDE ahead of BFCM to connect its Shopify store, email marketing platform, and Meta Ads. They create unified profiles for 120,000 customers and segment them by purchase margin, that is, those who buy discounted items versus those who pay full price.

After BFCM, the retailer can use FLYDE to trigger automated post-purchase journeys:

• High-value buyers receive loyalty rewards and exclusive early access to new products.
• One-time bargain hunters receive special re-engagement offers to encourage a second purchase.

Impact:

• Reduced duplicate ad spend.
• Higher retention rate for BFCM buyers compared to the previous year.
• Increased email engagement with tailored post-BFCM messaging.

READY TO GET STARTED?

BFCM is more than just a sales spike; it’s a data spike. Without a unified view of your customers, you’re missing a massive opportunity for long-term growth. With a CDP like FLYDE, brands can transform this sales surge into structured intelligence, ensuring they build a loyal customer base instead of just generating short-term revenue.

Ready to maximize your next BFCM? Contact us at FLYDE to book a demo and see how a our intuitive CDP can revolutionize your BFCM data strategy.