What does social intelligence mean to you?
It’s like having a backstage pass to the world’s biggest focus group. It takes billions of online conversations and turns them into a treasure map of insights. For me, it’s more than data; it’s the heartbeat of culture. It’s what drives human behavior online—and it’s endlessly fascinating.
What skills do social listeners need to succeed?
Curiosity is key—you’ve got to be nosy in the best way. Add a bit of cultural savviness, a knack for storytelling, and the ability to interpret numbers without falling asleep. A great social listener doesn’t just read numbers—they connect dots, find meaning, and create impact.
Biggest challenge to social intelligence adoption in brands?
Too often, social intelligence is treated like that one friend you only call when there’s drama—reactive, siloed in marketing, and undervalued. But here’s the thing: it’s not just a cost; it’s the secret sauce for innovation, trendsetting, and even saving a few corporate oopsies along the way.
Favourite use case for social intelligence and what decisions can the insight help support?
Turning chaos into clarity, I pulled together insights from online buzz, search behavior, and video trends, letting GenAI uncover patterns I might’ve missed. Adding a layer of semiotic analysis revealed archetypes that perfectly aligned with the product’s needs—it was like connecting the final puzzle pieces.
What piece of advice would you give to those looking to do more with social data than just brand tracking or campaign monitoring?
Stop chasing vanity metrics—they won’t get you far. Focus on uncovering meaning instead. Social data is just the starting point; the real value lies in decoding what people actually mean and transforming those insights into actions that spark conversations and drive real impact.
Gen AI in social listening: hype or helpful?
Gen AI is undeniably helpful, especially for tasks like sentiment analysis and trend detection, bringing speed and scalability to social listening. But it’s only as good as the data it’s fed. While it spots possibilities, you still need sharp human minds to interpret what’s relevant and actionable.
If we could grant you one wish to help your social intelligence practice succeed, what would you ask for?
I’d wish for an AI capable of more than number-crunching—something that connects the emotional and strategic dots. It would decode sentiments in nuanced ways, understand humor, and bridge small cultural shifts to major market trends. Imagine it saying, “This subculture conversation about vintage tech is a sign of nostalgia marketing’s next evolution.” Bonus: it would predict which platforms are about to blow up before the hype hits.
If you were to start your social intelligence team from scratch what three things would you do first?
If I were starting from scratch, I’d take a three-pronged approach:
1. Set a vision: First, align with stakeholders to define the team’s mission. Are we here to uncover trends, predict crises, or drive innovation? Without a clear focus, it’s like sailing without a map. Social intelligence is vast; priorities ensure we’re solving the right problems.
2. Pick tools that spark insights: Choosing the right platforms is crucial. I’d focus on tools handling today’s complexities—video analysis, sentiment detection, and emoji decoding (emojis are practically a language now). The goal is empowering the team with tech that delivers insights fast.
3. Build a diverse, curious team: The team would blend analysts, storytellers, and cultural enthusiasts for fresh perspectives. Starting with small, focused pilot projects—like uncovering niche trends or solving specific challenges—shows quick wins, builds internal trust, and sets the stage for strategic initiatives.
What are you looking forward to in social listening for 2025?
I’m buzzing about predictive analytics evolving to map future consumer behaviors—less reactive, more proactive. Add in advancements in video and voice intelligence, and we’ll be able to analyze TikToks and podcasts like pros. And fingers crossed, ethical data practices will finally become standard, not just buzzwords.
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