What does social intelligence mean to you?
Social intelligence is more than just vanity metrics to me. It's about strategically leveraging the wealth of data available on social media platforms to gain a deep understanding of the social landscape and inform decision-making. It definitely goes beyond just listening & monitoring. It is also about how the data is used for actionable insights by reading user patterns & behaviors. It has evolved from ‘what’ the audiences are saying to ‘why’ they are saying & feeling a certain way. And all of this put together helps in not just understanding brand health, but also the competitor landscape, the under-currents around certain hot topics, mitigating risks and so much more.
In essence, social media intelligence is about harnessing the power of social data to make informed decisions, build stronger relationships, and achieve business objectives in a responsible and ethical manner.
What skills do social listeners need to succeed?
Beyond the foundational skill of understanding the brief and constructing the boolean query, the ability to pose relevant questions—the why and the what—is the most critical skill in my view. The why is necessary to understand the business problem we are trying to solve, and the what is necessary to understand the business metrics that this will impact. In addition to this, understanding the cultural context of the discussions we analyze is a highly underestimated but essential skill. Lastly, the ability to connect the dots between business impact and social data is crucial.
Biggest challenge to social intelligence adoption in brands?
Despite the clear advantages of social intelligence, there are still challenges that prevent its adoption by brands. Acquiring the necessary tools, managing the vast influx of social conversations, and finding skilled analysts are ongoing hurdles. However, the most pressing challenge lies in demonstrating the tangible business value of social intelligence.
Businesses are increasingly demanding clear evidence of ROI and want to understand how social insights directly impact key business metrics. Despite the longstanding recognition of these questions, they continue to challenge the adoption of social intelligence initiatives. Bridging the gap between social data and business outcomes continues to be a crucial challenge for organizations seeking to leverage social intelligence effectively.
Favourite use case for social intelligence and what decisions can the insight help support?
Ahh! It will be tough selecting just one use-case but I always find myself going back to this example every now & then. It's from one of my previous roles where we had to find different ways AI could be used in various sectors (healthcare, agriculture, banking, defense, education to name a few) across the European market, and then break it down by country. The really interesting part was seeing how different countries used AI in completely different ways to help uplift certain sectors. Contrary to how we assumed, some of the smaller countries were way ahead in adopting AI versus the bigger countries! For example, Austria was way ahead in adopting AI for agricultural advancements versus Switzerland.
The country leads took this information to inform their AI penetration market strategies for each country. This analysis empowered them with each market's industry and the degree of competitor AI adoption. Consequently, informing the leads sectors to invest in (where competition penetration was low) and sectors to steer clear from.
What piece of advice would you give to those looking to do more with social data than just brand tracking or campaign monitoring?
Social data is a treasure trove of insights waiting to be discovered! My only piece of advice is and has been to truly go beyond just monitoring & tracking. There is so much more that anyone can do with social data - insights like customer experience, new product ideas etc. If we truly embrace advanced analytics like sentiment analysis and audience segmentation, this will not only help the marketers understand customer emotions but will also help them create targeted campaigns, making measurement an easy outcome. Then there is also the potential of integrating social data with CRM data for a 360 degree view of the customers.
It entirely depends on how creative we get with the data. The more out of the box we think, the more competitive advantage we get.
Gen AI in social listening: hype or helpful?
This has been one of my favourite topics of discussion these days - Gen AI: helpful or hype. And in my opinion it’s a bit of both. The reason I say it’s a hype is because over-reliance on AI generated insights without critical thinking can lead to flawed conclusions. Can't deny that AI helps in automating tasks but nuanced tasks like sentiment analysis, contextual understanding can only come with human intervention and expertise.
Coming to why I find AI helpful, not only does it help analyse large data sets swiftly but also helps in bringing efficiencies through time saved on what otherwise would have gone in manually analyzing these large data sets. Identifying drivers of conversations have become increasingly easier and with its advanced capabilities of training the large data sets leading to potentially more accurate analysis.
In a nutshell, the real value lies in combining AI capabilities with human intelligence to achieve more efficient, accurate, and insightful analysis.
If we could grant you one wish to help your social intelligence practice succeed, what would you ask for?
Get me that LinkedIn data access for social intelligence! For real! Brands are now increasingly finding LinkedIn as a popular platform to understand what professionals talk about their experiences with certain products or with their own services. Searching for this data manually is time-consuming and may lead to overlooking several perspectives on the topics at hand.! So my only wish for the last few years has been LinkedIn data :)
If you were to start your social intelligence team from scratch what three things would you do first?
To build a solid foundation for the team, I would do the following:
1. Define clear objectives & KPIs: Understand the core business objectives we want to achieve with social intelligence - is it crisis management, is it understanding the competitor landscape, new areas of opportunity, brand perception etc. Identify the right KPIs for defining success - share of voice, sentiment, engagement etc.
2. Getting a diverse team with the right skill sets - be it analysts, visualizers, social media domain experts, storytellers etc
3. Finally choosing the right set of tools and technologies that will enable the team to deliver on business goals. Platform coverage, sentiment accuracy, possibility of integrating with other existing marketing data sources, visualizations etc make up for some critical evaluation criterias
What are you looking forward to in social listening for 2025?
For starters, I'm eager to see how AI can improve social listening for testing and building use-cases like early crisis prediction and spotting micro trends, ultimately saving time.
Secondly, and this is something that I have taken up as a goal for 2025 for my current role as well - how listening, campaign, and product data together show overall campaign or content performance and what decisions this overview helps with.
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