What does social intelligence mean to you?
Social intelligence, to me, is about leveraging social data to inform decision-making, validate hypotheses, and better understand consumers. It’s where storytelling meets data analysis in perfect harmony. I appreciate the concept that "people don’t talk to researchers the same way they talk to each other," which encapsulates the power of social data and the unique benefits social intelligence can bring to any organization.
What skills do social listeners need to succeed?
Social listeners need to be inherently curious, have strong organizational skills, creativity, and a lot of patience. Effective social listening is nuanced, so adaptability and resourcefulness are especially important traits. While hard skills like query writing can be learned over time, these soft skills are crucial for success.
Biggest challenge to social intelligence adoption in brands?
Social data comes with inherent limitations and requires constant context. Its value isn’t always immediately obvious, which can make it overwhelming or hard to understand. For brands to benefit, they must lean into social intelligence as a strategic resource. Early in my role, adoption was a challenge. Through consistent output and by showcasing the value of actionable insights, I was able to gain exposure and secure a seat at the table with various stakeholders. It’s all about identifying opportunities and delivering the most relevant insights for each team.
Favourite use case for social intelligence and what decisions can the insight help support?
I particularly enjoy using social intelligence to inform product innovation. At a large CPG company, we frequently support the innovation pipeline during its early developmental stages. Social data allows us to identify emerging flavor trends, unique beverage recipes, and viral beverage "hacks." This use case often complements qualitative or quantitative research and serves as an inspiration during the ideation phase.
What piece of advice would you give to those looking to do more with social data than just brand tracking or campaign monitoring?
Categorical research has been a major focus for my team over the past year. Our Brand and Product Innovation teams are as interested in what people are saying about general topics like “iced coffee” as they are in conversations about the coffee brands we own. Expanding into areas like this, alongside social trend tracking, has broadened the scope and impact of our social intelligence program.
Gen AI in social listening: hype or helpful?
Super helpful. AI integrations have significantly improved our ability to identify broader conversation themes, analyze comment sections or threads, and distill large amounts of data quickly. While balancing AI with human intelligence is essential, I’ve been impressed with what I’ve seen so far. One tool, in particular, has drastically reduced the time required for previously labor-intensive tasks. For small teams like mine, constrained by bandwidth, generative AI has been and will continue to be a game-changer.
If we could grant you one wish to help your social intelligence practice succeed, what would you ask for?
Eliminate platform API restrictions. I’d love to have similar access levels to Instagram and TikTok as we do with platforms like X or Reddit. Having more data allows for a more complete picture when developing insights and telling stories.
If you were to start your social intelligence team from scratch what three things would you do first?
First, I’d conduct an organizational deep dive with internal teams and stakeholders to understand their desired insights and information needs. I’d provide sample deliverables and share capabilities broadly to level-set expectations and gauge demand. Next, I’d issue an RFP to select the best social intelligence solution(s) for reliable data, dashboards, and alert capabilities. Finally, I’d work with the chosen technology’s success team to create custom training sessions, dashboards, and alerts tailored to stakeholders’ needs. This would democratize access to social data without overwhelming participants and position the team to handle large-scale, complex projects effectively.
What are you looking forward to in social listening for 2025?
The evolution of AI within social listening tools is particularly exciting. As teams continue to explore generative AI and large language models (LLMs), analyzing vast amounts of data is becoming more feasible. While there are still limitations and nuances to address, the early results are promising. I’m especially eager to experiment further with generative AI to enhance query writing and improve sentiment analysis.
Get Social with SILab
