Marketing Under Pressure: Federico Kalos on Digital Marketing Leadership, Prioritization, and the Future of Search Engines

In a landscape where attention is fragmented and tech cycles outpace strategy decks, marketing prioritization frameworks are no longer just tactical tools—they’re existential necessities. Federico Kalos, Director of Marketing and Partnerships at Bunker DB, has built his career at this intersection. From scaling Google’s Partner Program across the fragmented digital ecosystems of South America to leading growth at a high-velocity MarTech startup, his experience reflects the kind of digital marketing leadership required in a post-playbook era.

At Bunker DB, he’s focused on designing marketing strategies for 2025 and beyond—systems that prioritize clarity over chaos. Think: quick wins vs. long bets, effort-impact matrices, and OKRs that actually drive outcomes. For teams overwhelmed by activity but lacking alignment, his model offers a refreshingly rigorous approach: cut what doesn’t ladder up to business impact. As he puts it, “doing a lot becomes meaningless without direction.”

In this interview, Federico unpacks how AI and SEO are evolving side by side, the nuanced role of zero-party data in marketing, and why the future of search engines may shift from prompt design to profile-driven discovery. It’s a grounded, forward-facing perspective on what it takes to build resilient marketing systems amid disruption—and lead teams that thrive within it.

The Strategic Weight of Prioritization

Today, in your role as Director of Marketing and Partnerships at Bunker DB, how do you prioritize short- and mid-term initiatives? What would you tell teams who feel like they’re spreading themselves too thin?

In my current role leading a startup’s marketing efforts, I must balance short-term wins with long-term bets. On the one hand, we focus on quick wins and low-hanging fruit: initiatives that don’t require huge effort but can generate a tangible impact fast. On the other hand, we design and invest in strategic bets that might take longer but can redefine our business in the long run.

The most effective way we’ve found to prioritize as a team is through a simple impact vs. effort matrix. Impact isn’t just about business outcomes—it also considers how well an initiative aligns with other teams at Bunker. Effort, meanwhile, refers to the time, people, and resources we realistically have to pull it off. We’re honest about our operational capacity.

We also track quarterly OKRs, which help us understand which initiatives actually ladder up to our bigger goals. That makes it easier to reallocate resources where they matter most.

This whole approach lets us focus on what we should be doing instead of just everything we could be doing. Without strategic direction, doing a lot becomes meaningless. Prioritization means knowing how to say no to what’s merely “nice to have,” so we can reclaim time, energy, and mental space for what’s truly important. For any manager leading a high-activity team, the most valuable move is to pause, extract insights from data, listen to your customers and your team, and realign as needed.

From Google to Bunker DB: Scaling With Focus

When you were Product Marketing Manager at Google, what were the main challenges of running the Google Partners program in South America? How did you measure success?

The program had several pillars—account acquisition, partner education, content tailored to strategic partners, and loyalty systems that recognized top-performing agencies in each market.

Each pillar had its own set of insights, goals, and challenges. But in South America, we also had to navigate varying levels of digital maturity. Some countries had strong, consolidated agency ecosystems—like Argentina, Chile, Colombia, Mexico, and Peru. Others were still starting from scratch.

That’s where the strength of the program really showed: its reach and adaptability. Activating initiatives with strategic partners let us match local relevance with regional scale.

Another key challenge was making the region visible within Google’s global structure. Since Google operates worldwide, we had to show impact in ways that mattered across regions. If the U.S. and Europe led in ad spend, Latin America had to stand out through other metrics—like innovation, engagement, or ecosystem-building.

AI, SEO, and the Changing Nature of Search

What’s your take on how SEO and marketing teams are approaching AI adoption? What’s the upside—and the risk?

The rise of generative AI has changed the SEO game. When ChatGPT launched, many rushed to declare the end of Google, predicting that Answer Engine Optimization (AEO) or Generative Engine Optimization (GEO) would be the new normal.

But not so fast. A recent article in The Washington Post pointed out that the user traffic ChatGPT sends to websites is 379x lower than Google’s. In short: we’re heading into a future where traditional queries and generative responses will coexist—and that’s a good thing. More choice means more user agency.

On the downside, Google’s push to compete directly with ChatGPT via AI Overviews and AI Mode has made SEO less effective as a traffic driver. If users get full answers on the search page itself, why click through? That creates real challenges for businesses reliant on organic search—especially around acquisition, keyword strategies, and backlinks. Many will need to rethink how they attract and convert traffic.

Zero-Party Data and Predictive Modeling

How is the industry evolving in its use of voluntary and conversational data (like zero-party data) to improve user experiences and feed predictive models like performance attribution or media mix modeling?

The digital ad industry boomed thanks to third-party data, enabled by platforms like Google, Meta, TikTok, and LinkedIn. But in the wake of GDPR, CCPA, and growing privacy expectations, the spotlight shifted to first-party data—data you own and collect directly.

Now we’re seeing an even more refined category emerge: zero-party data. This is data that users intentionally share—through surveys, interactive forms, or preference settings. It’s like first-party data, but volunteered with purpose.

Can this type of data feed predictive models like Media Mix Modeling (MMM)? That’s more complicated. MMM needs massive amounts of contextual data, and zero-party data is often the hardest to get. But when used well, it can help calibrate those models, offering a richer understanding of user motivations behind certain behaviors or trends. There’s huge value in blending declarative data with contextual signals to decode what’s really going on.

Beyond the Prompt: Where Search is Headed

What’s the biggest challenge teams face when trying to turn zero-party data into real action? How can they overcome it?

The hardest part isn’t collecting the data—it’s activating it in a meaningful way. Many teams stop at the data collection phase without a clear plan for what comes next.

Here’s what I’d recommend:

• Collect data with a purpose: Don’t ask questions you don’t plan to use. Start with the goal, then design the input.
  
  
• Plug into automation: Integrate your data into tools that allow for dynamic segmentation and personalized customer journeys.
  
  
• Measure beyond conversion: Track how this data improves user experience and long-term retention.
  
  

That’s how you build richer segments, closer to what users actually want. And when you get there, retention and CLV tend to follow.

What Marketing Leadership Looks Like Now

What’s your prediction for how traditional search engines will evolve alongside conversational assistants?

We’re moving from a query-based paradigm to one rooted in conversation and context. That means we’ll likely see a convergence: search engines will become more conversational, and AI assistants will morph into discovery engines.

The future of SEO will look increasingly semantic, contextual, and experience-driven.

And here’s something many haven’t fully grasped yet: we’ll probably start to care less about prompts. Just like Google outpaced legacy search engines by building smart user profiles, today’s AI assistants (ChatGPT, Gemini, Claude, etc.) are just starting to do the same. As these systems learn more about us and refine our profiles, all the frameworks we currently use to craft “great prompts” will gradually become irrelevant.

Where to go next

• Check out our last memo drop for the latest on tech and marketing trends
• Our first PDX Session with Sebastian Galanternik, SR. SEO Manager at MercadoLibre
• Digital detox: a new challenge for marketers? Maybe. 
• Federico’s LinkedIn Profile

👀 Want to know how we approach SEO? Let’s talk → Discover our SEO Sprints

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