This article was based on the interview with Daniel Damasio, Senior CRM Analyst at Nestlé Brazil by Greg Kihlström, AI and MarTech keynote speaker for The Agile Brand with Greg Kihlström podcast. Listen to the original episode here:
For any enterprise marketing leader, the tension between global brand consistency and local market relevance is a familiar, and often fraught, balancing act. On one hand, the power of a global brand lies in its recognizable standards, its operational efficiencies, and the trust it has built at scale. On the other hand, we know that true customer connection—the kind that drives loyalty and lifetime value—is forged in the fires of local nuance, cultural understanding, and personalized relevance. To treat a customer in São Paulo the same as one in Mexico City or Zurich is to ignore the very fabric of their identity. The question is no longer if we should personalize, but how we can build an operational and technological foundation that allows for it without fracturing the brand into a thousand unrecognizable pieces.
This is not merely a philosophical debate; it is a complex operational challenge that lives at the intersection of data, technology, and human strategy. For a company with the sheer scale and brand diversity of Nestlé—a portfolio spanning from Purina pet food to Kit Kat chocolate—this challenge is magnified exponentially. It requires moving beyond siloed systems and legacy thinking to create a unified view of the customer that can serve as a single source of truth for a multitude of markets. It’s here that we explore how to build not just a smarter tech stack, but a smarter organization—one that empowers local teams with global intelligence and fosters a culture of shared learning. Insights from Daniel Damasio, Senior CRM Analyst at Nestlé, illuminate a path forward that is less about a single silver-bullet solution and more about a sustained, intelligent effort.
The Ongoing Mandate: Digital Transformation is Not a “One and Done” Project
One of the most pervasive myths in digital transformation is that it’s a project with a defined start and endpoint. A business case is made, a platform is implemented, and a team cuts a ribbon. Leaders in the trenches know the reality is far messier and, frankly, more demanding. The business case for unifying customer data and investing in platforms like a CDP isn’t a one-time sales pitch to the CFO; it’s a perpetual campaign that must be waged every quarter. The value must be continuously demonstrated as market conditions, customer expectations, and corporate priorities evolve.
This shift in mindset from a finite project to a continuous program is fundamental. It requires a different kind of organizational stamina and a constant focus on proving value, not just in terms of flashy campaign metrics, but in tangible business outcomes like operational efficiency and long-term customer equity. Damasio frames this reality with perfect clarity, emphasizing that the work is never truly “done.”
“I would argue that the business case is always there. You know, we are always trying to defend it. It’s not just like one final exam at the end of the semester that, okay, it’s done, one and done. No, it’s always every quarter, every half a year, every year we have to defend that digitalization happening and we make sure that we are providing the value to everybody involved in the system.”
This perspective should resonate with any leader who has fought for budget. The initial implementation is merely the price of admission. The real work lies in the ongoing optimization, the continuous alignment with global strategy, and the relentless defense of the investment. It’s about building an ecosystem that is not just powerful, but resilient and adaptable. This means instrumenting your efforts to measure not just opens and clicks, but also cost savings from streamlined operations, increases in customer lifetime value, and reductions in churn. The “exam” is never over; every quarter presents a new set of questions, and the data is your only study guide.
Beyond the Algorithm: The Human Element of an “Intelligent CDP”
In an industry saturated with talk of AI, machine learning, and automation, it’s easy to believe that the key to unlocking customer data is a sufficiently powerful algorithm. The term “Intelligent CDP” itself conjures images of a self-driving system that magically turns raw data into profitable customer experiences. While the technological capabilities are undeniably exciting, this view overlooks the most critical component of any intelligent system: the human intelligence that directs it. Technology is a tool, and a tool is only as effective as the craftsperson wielding it.
A truly intelligent customer data strategy is not born from AI alone; it is the product of a symbiotic relationship between human insight and machine processing. The strategy, the vision, the purpose—these are human constructs. The machine can execute, optimize, and scale those constructs at a speed and complexity we cannot, but it cannot invent the “why.” Damasio offers a refreshingly grounded definition of an “Intelligent CDP” that puts the emphasis back where it belongs: on the people.
“In my mind, an intelligent CDP requires a lot of people involved to make sure that everybody’s thinking about the system and everybody is doing an intelligent work of using a tool to make it happen… we need to make sure that everybody is skilled enough to use it. Everybody needs to understand what is a tragedy [strategy], what is the vision, what is the purpose. So that for me is the intelligence CDP. You know, it’s the brain behind the power.”
This is a crucial lesson for leaders assembling their MarTech stacks. Investing in a best-in-class platform without concurrently investing in the upskilling of your teams and the clarification of your strategy is a recipe for an expensive, underutilized piece of software. The “brain behind the power” is the collective intelligence of your marketers, analysts, and strategists. Are they asking the right questions? Do they understand the overarching business goals? Are they empowered to experiment, learn, and apply those learnings through the technology at their disposal? The most advanced AI in the world cannot compensate for a lack of strategic direction or a team that doesn’t understand how to translate business objectives into actionable use cases.
The Hive Mind: Fostering Global Collaboration with Local Autonomy
So, how does a global behemoth like Nestlé solve the standardization versus personalization puzzle? The answer isn’t a rigid, top-down mandate, nor is it a free-for-all where every market operates in a silo. Instead, it’s a model of federated intelligence, a “hive mind” approach where local teams are empowered to develop strategies tailored to their unique markets, but are deeply connected to a global network for shared learning and alignment. This framework is encapsulated in a simple but powerful motto: “Together we make Nestlé.”
This approach acknowledges a simple truth: the team in Brazil understands the Brazilian consumer better than an executive in Switzerland ever could. They need the autonomy to act on that understanding. However, the learnings from a successful campaign in Brazil—or the lessons from a failed one—contain valuable insights that could inform a strategy in Mexico or Southeast Asia. The key is building the channels and, more importantly, the culture for that information to flow freely across borders.
“Even though everybody has their own part in the system, we always act together as one big hive mind, kind of like that… we in Mexico, for example, and we in the United States, we in Europe, we always are catching up on each other, sharing information to make sure that what we are doing is something that is working or is not working and what can we learn from their mistakes or what they’re learning from our mistakes to make sure that everybody is evolving together.”
Creating this “hive mind” is an intentional act of organizational design. It requires regular forums for cross-market communication, standardized methods for reporting results so that comparisons are meaningful, and a culture that rewards sharing and collaboration over internal competition. Technology like a globally-instanced CDP can provide the common data language, but the human-to-human connection is what turns shared data into shared wisdom. This model allows for local agility without sacrificing global scale. It’s a system where the whole is truly greater than the sum of its parts, with each market acting as both a unique entity and a vital node in a global intelligence network.
The Path Forward
Ultimately, navigating the complexities of global marketing in the modern era is not about finding a single, perfect answer. It’s about building a resilient, adaptable system—of technology, people, and processes—that can constantly learn and evolve. The insights from Nestlé’s journey underscore that the most powerful tools are useless without a clear vision and purpose guiding them. The work is never finished, the business case is never permanently closed, and the intelligence of the system is a direct reflection of the intelligence of the people running it.
For leaders charting their own course, the advice is both profound and practical. Start with vision and purpose, but don’t wait for a perfect plan to take the first step. Break down monolithic projects into smaller, achievable wins to build momentum and demonstrate value early and often. Foster a culture of connectivity, where teams learn from each other’s successes and failures. In the end, the goal is to create a living, breathing ecosystem where technology empowers human strategy, global scale enables local relevance, and every action is a step toward building more meaningful relationships with the customers who matter most.
