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Let’s start simple. Who are you, and what do you do with social data that others might not expect?
I’m Luiza, a Social Intelligence Analyst at cosnova, with a background that started on the platform side — first at Pinterest and then at TikTok — before moving into social listening. Because of that mix, I tend to look at social data through both a performance lens and a behavioral one: not just what people do, but why they do it.
A lot of my work is about making social data easy and approachable for everyone. Sometimes that means showing a product manager which features people love most, helping teams evaluate campaign reactions, or using conversation trends to confirm whether a potential collaboration with a brand or influencer actually fits what our audience wants.
What might surprise people is that while my job involves numbers, the part I enjoy most is translating conversations into something teams can actually use — whether it’s understanding reactions, refining ideas, or spotting early signals worth exploring.
What’s something in our industry we pretend to understand, but don’t?
I think in our industry we often pretend we’re working with clean, complete, and perfectly representative data — when in reality, social datasets are messy, biased, and full of blind spots. We act as if every conversation is captured, every voice is equally visible, and every insight is neatly quantifiable, but that’s far from true.
The truth is: our insights are only as good as the data we manage to collect, and we’re still learning how to navigate data gaps, bot noise, cultural context, and visibility bias. We pretend we’re working with a perfect mirror of reality, but we’re really working with a reflection that needs interpretation and humility.
As analysts, we spend a lot of time separating signal from noise and understanding what the data can genuinely tell us — and what still requires interpretation. Our datasets aren’t perfect, and that’s exactly why context, curiosity, and human perspective matter so much.
What’s a moment this year where social data helped your team do something bolder, faster, or better?
One moment that stands out this year was when social data helped us refine a product concept much earlier in the development process. We were exploring a new idea within a category where consumers are very vocal, so I pulled conversation patterns to understand which features people actually cared about, what frustrated them, and what they felt was missing. The insight helped the product team adjust the concept to better match real consumer expectations — a small shift, but one that made the idea feel much more relevant.
It was a good reminder that sometimes the boldest move is simply listening before building. And this way of working didn’t stop there — we’ve also used social trends to guide campaign timing, like identifying when certain categories peak in interest so paid media can land when people are naturally paying attention.
What’s one belief about your audience that social data completely upended for your teams?
People don’t talk about products the way we expect - A belief many teams have is that consumers talk about products using the same language we do (features, claims, category terms). But your social listening work showed that: They talk about problems, not features. They talk about texture, feel, and routines more than technical benefits. They create their own vocabulary around trends. This often surprises product teams because it reframes what “value” really looks like in consumers’ eyes. Even when looking at platforms like TikTok, where we expected more product-focused discussions, we found that people engage in ways that don’t necessarily mirror how brands frame their categories.
If you could build your dream social intelligence team from scratch, with no legacy and no limits, what roles would you include?
I’d focus on a small group of specialists with complementary strengths, a team that can understand people, structure data, and translate insight into real impact.
Starting with a Social Intelligence Strategist setting the vision and ensuring insights influence decisions at every level of the organization. Alongside that, I’d build an Insights Analyst bringing together quantitative cultural understanding, and trend analysis — someone who can identify patterns, interpret motivations, and spot emerging signals before they become mainstream.
Supporting the technical side, I’d include a Social Data Systems & Taxonomy Lead who owns our data structure, governance, API connections, infrastructure, and tool ecosystem. This role would ensure that the foundations of social intelligence are solid and aligned with the broader company data environment. An AI & Automation Specialist would help us scale our work by building classifiers, automating workflows, and enhancing tagging and trend detection as the field evolves.
I’d also add a Content & Platform Intelligence Researcher, a hybrid role focused on how content performs across different channels and why. This person would understand platform behaviors, formats, editing styles, and audience expectations bridging data with creative thinking and helping teams craft content that truly resonates.
Finally, a Stakeholder Enablement Lead to build literacy, run trainings, and ensure that insights become part of everyday decisions across teams.
With a compact, multidisciplinary, and deeply connected team like this, social intelligence could operate not just as a reporting function, but as a strategic partner shaping creativity, product decisions, and long-term brand direction.
When do you feel like you’re doing your best work?
I feel like I’m doing my best work when I’m turning something complex into something clear. Social data can be noisy and overwhelming, and I really enjoy the moment when I can translate conversations, patterns, or early signals into insights that teams can actually use — whether it’s for a product idea, a piece of content, or a campaign decision.
I also do my best work when I’m connecting dots across different areas: platform behavior, cultural context, trends, and consumer needs. Bringing these pieces together and telling a simple, meaningful story is something that energizes me.
And finally, I feel at my best when I’m helping others build confidence in using social intelligence. Whether through trainings, masterclasses, or quick “bits and bites,” seeing people understand how insights can support their work always reminds me why I love what I do.
What’s your browser history giving away about you this week?
Honestly, my browser history this week probably reveals that I’ve been much more focused on preparing for our company Christmas party than anything work-related. It’s the biggest event of the year for us, and every edition comes with a new theme and a specific color palette — so naturally, I’ve been deep into outfit ideas, makeup looks, and way too many tabs comparing dresses. Not the most “social intelligence” answer, but definitely the most honest one.
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