Ana Talavera

Let’s start simple. Who are you, and what do you do with social data that others might not expect?

I see myself as a digital culture researcher. I use social data to understand how people make meaning, express emotion, and relate to each other online. What often surprises people is how naturally I move between technical analysis and cultural interpretation. Some days I’m learning code, working with Python, or trying to make sense of how platforms and algorithms decide what gets seen. Other days, I’m reading conversations almost like ethnographic field notes. I don’t really see those as separate skills, just different modes of the same curiosity. That mix helps me look past dashboards and trends and turn everyday digital signals into cultural intelligence teams can actually use, with a bit more context, nuance, and better timing.

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What’s something in our industry we pretend to understand, but don’t?

We still act as if audiences were stable, well-behaved entities, when in reality they’re constantly on the move, jumping between platforms, social roles, cultural references, and fluctuating attention spans. Social data makes that fragmentation pretty obvious, but only if we resist the impulse to immediately squash it into neat personas and tidy segments. The problem isn’t a lack of information. It’s our low tolerance for ambiguity. We simplify too fast because instability is harder to explain, harder to operationalize, and definitely harder to defend in a slide deck. But culture doesn’t move in straight lines and neither do people. The real work now is learning how to read patterns across contradiction, silence, and overlap, and building strategies that can flex with how audiences actually behave, not how we wish they would.

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What’s a moment this year where social data helped your team do something bolder, faster, or better?

We stopped asking what content was performing and started asking what kind of meaning was forming around a topic across platforms. That shift from performance to interpretation, helped us move faster with more confidence, because decisions were grounded in context, not just momentum.

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What’s one belief about your audience that social data completely upended for your teams?

That audiences are something you can “understand” in isolation. Social data made it obvious that behavior isn’t just about people, it’s also about the environments they’re moving through. Algorithms, platform incentives, fatigue, fear, humor, and timing all shape how people show up online, sometimes more than personal preference. Once you start seeing audiences as navigating systems (not just sharing opinions) contradictions stop looking like inconsistency and start looking like adaptation. The question shifts from “Who is my audience?” to “What’s shaping how they’re showing up right now?” And honestly, that reframing changes everything.

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If you could build your dream social intelligence team from scratch, with no legacy and no limits, what roles would you include?

Having worked with global teams and led social intelligence across LATAM, I’ve learned that the best insights usually come from a room where people don’t think alike. Different nationalities and cultural backgrounds make the questions sharper and the blind spots smaller. I’d want a team that’s comfortable with things breaking - platforms changing, data disappearing, AI doing weird things. That’s just the job now. So I’d mix people who speak martech and data engineering fluently with others who are great with language, culture, and nuance. Not for the sake of being fancy, but because that combination tends to turn messy data into decisions that actually make sense.

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When do you feel like you’re doing your best work?

I do my best work when I’m pulling things together, not just analyzing. When I can step back from the volume and the patterns and focus on telling a clear story, what actually matters, how the signals connect, and what it all means. It’s less about finding more insights and more about shaping the right one: what changed, why it matters, and what someone should do differently because of it. I’m at my best when analysis turns into interpretation, and interpretation turns into something people can actually remember and use.

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What’s your browser history giving away about you this week?

A mix of academic papers, Substack essays I’ve been reading to feed Fio da Meada, and an unfinished online class on Hannah Arendt (thinking and acting as conditions of existence). A few tabs about platforms, an Amazon search for botanical LEGO sets, and notes scattered between one idea and the next. Nothing very linear. Just pieces I’m collecting, reading, and sitting with.

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