What does social intelligence mean to you?
Social analytics, to me, represents the dynamic intersection of data, human behavior, and strategic insight. It’s about transforming raw digital conversations into meaningful narratives that drive decision-making. Social analytics goes beyond monitoring metrics—it’s the art and science of decoding trends, predicting risks, and uncovering opportunities in the ever-evolving digital world. It empowers businesses to listen with intent, respond with relevance, and innovate with purpose, fostering deeper connections with their audiences while staying ahead in a competitive landscape.
What skills do social listeners need to succeed?
Social listeners need a mix of analytical, strategic, and interpersonal skills to excel. They must be proficient in data analysis, detect patterns, trends, and emerging narratives. Crafting precise Boolean queries is crucial for filtering relevant conversations across platforms.
Critical thinking and contextual awareness are essential for interpreting data within cultural and industry-specific contexts. This helps transform raw data into actionable insights and coupled by strong communication skills, social listeners can craft compelling narratives that inform business strategies and drive decision-making.
Equally important are adaptability and a continuous learning mindset. Since the social media landscape evolves rapidly, social listeners must stay curious, embracing new tools, platforms, and techniques. This proactive approach ensures they remain ahead of trends and deliver meaningful insights that impact business outcomes.
In essence, successful social listeners blend technical expertise with human-centered interpretation, enabling businesses to navigate the ever-changing digital world with clarity and purpose.
Biggest challenge to social intelligence adoption in brands?
The biggest challenge to social intelligence adoption in brands lies in bridging the gap between data collection and actionable insight. Many brands struggle with integrating social intelligence into their broader business strategy due to siloed teams, limited technical expertise, and a lack of clear ROI measurement.
Data overload is another key barrier. Social media generates massive amounts of data, making it challenging to filter noise and focus on relevant insights. Without proper tools or skilled analysts, brands risk missing critical signals that could drive decision-making.
Organizational buy-in is equally important. Decision-makers may not fully understand the potential of social intelligence or see it as complementary to traditional research methods. Demonstrating the business value through clear, data-driven case studies can help overcome this resistance.
Finally, keeping up with platform changes, privacy regulations, and evolving consumer behaviors adds complexity. Brands must adopt a flexible, future-forward approach to stay relevant while balancing compliance and ethical considerations.
Favourite use case for social intelligence and what decisions can the insight help support?
One use case I would like to bet on for social intelligence is to uncover multivariate intents and root causes from customer conversations, to fragment them into related and disparate insights for various business teams to take appropriate action. The current tools have capabilities to decipher sentiment and issues at the primary and secondary level but not at a tertiary level and those intents which are closely related i.e. cracked phone screen and overheating to a potential OS upgrade.
What piece of advice would you give to those looking to do more with social data than just brand tracking or campaign monitoring?
Start by defining clear business objectives—think beyond metrics like engagement rates and consider broader goals such as market expansion, product innovation, or crisis management.
Explore cross-functional collaboration by integrating social data into areas like customer service, product development, and policy/risk management.
Invest in advanced social listening tools that enable deeper analysis, including emotion tracking, trend prediction, competitive benchmarking and experience measurement.
Activate opportunities to share key insights with leadership via executive dashboards and metric barometers that help them stay aware of the customer resonance to product/brand strategy.
Gen AI in social listening: hype or helpful?
Extremely helpful if utilized in the right areas by brands and vendors; and not simply sold as a capability to fix a short term problem.
If we could grant you one wish to help your social intelligence practice succeed, what would you ask for?
An all encompassing tool, with the right support for data sources, languages and key insight discovery backed by AI; at a competitive price.
If you were to start your social intelligence team from scratch what three things would you do first?
1. Understand the brand’s appetite to invest in tooling infrastructure that supports their short- and long-term strategy
2. Identify teams that share similar objectives in deriving social insights and reduce redundancy by bringing their KRAs into my ambit to deliver at scale
3. Hire the right set of experts who have skills beyond traditional social listening and expand the boundaries to bring value to the data by stitching together insights from other sources.
What are you looking forward to in social listening for 2025?
I am personally looking forward to witnessing how AI can bring forth innovation in social media data and address the data gaps, unearth complex behavioural patterns and recommend the right strategies for brands to deliver solutions proactively. Wouldn’t it be awesome to have an AI-based Influencer Metric that will proactively inform the influencer cohorts to work with based on their interests, passions, content-type, affinity towards a cause, campaign or product, etc ??!!
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