What does social intelligence mean to you?
I would liken social intelligence to the difference between knowledge and wisdom. Knowledge is information or awareness; wisdom comes from experience and is the ability to use knowledge to make judgements. Social intelligence is not simply gathering information from social media and gaining ‘findings’, ‘trends’ or ‘insights’. Social intelligence could be defined as knowing how to apply social media insight, with discernment, based on experience.
What are you doing that no-one else is to drive the social intelligence industry forward?
As a researcher, I not only went straight into the subspeciality of social intelligence, I also went straight into healthcare and I am now in my ninth year of working in social intelligence for the healthcare industry. I’ve seen a lot in terms of the briefs I’ve worked with and the type of data I have played with. These have ranged from fishing for very specific conversations from needle-in-a-haystack audiences to analysing vast quantities of data about public health issues.
Much of the work over that time has ultimately been about identifying what drives behaviours in health, from why doctors prescribe the way they do to why patients make certain care decisions.
Many clients have wanted to discover who the most influential individuals are. I’ve been pushing forward in the field of influencer identification in niche medical areas, often working with a lot of client determined factors to integrate into analytic frameworks. This has had me going far beyond just who is making the most noise, is the most followed and getting the most engagement.
It's the year 2030: What does the practice of social listening look like?
In five years, I suspect the amount of heavy lifting humans are doing will be vastly reduced. Machine automation will get rid of many uninteresting, repetitive tasks, giving more space for intelligent social analysts to use their human expression and flair for creative tasks like methodology design and data interpretation.
Artificial intelligence tools will keep improving in their ability to summarise and interpret data. As AI tools become more accessible, it will be important for social intelligence professionals to stay up to date and leverage AI in ways that are tailored to their specific needs. Social intelligence platforms could focus on refining their training data for particular industries or sectors. Instead of relying on generic, off-the-shelf tools that simply summarize large volumes of text data from social media posts, these tools could be customized to understand the context of the data. This could include factors like who the author segments are, the social media platforms used, the queries used to collect the data and even the research objectives.
With all the likely growth in technology assisted analysis and interpretation in mind, social intelligence professionals will continue to be adding the human-touch and the ‘so what’.
What is the most common question you are helping your clients answer?
What are the unmet needs?
In my industry clients love to ask, ‘What are the unmet needs [of healthcare professionals / patients]?’.
When setting up a social media research program, I will want to get to the root of what clients want to know and why. Of course, we can look to use data to answer the unknowns. But there are questions we need answers to that we don’t yet know to ask. ‘What are the unmet needs?’ works well as a catch-all for these, essentially ‘is there anything else we can learn from social media conversations that didn’t anticipate’.
It’s the beauty of the unprompted nature of the online conversations that we as social researchers analyse – we can find answers to questions we didn’t know we should have been asking.
Have you got a favourite social intelligence use case or case study from the last year?
I’ve got a soft spot for any analytics that require a nice data flow. A really nice piece of work I was involved in last year focused on the extraction of large data volumes of social media data and automated analysis of the data.
The concept was simple: extract all social media posts about individuals’ experiences of a certain healthcare intervention and cross-reference that with a dictionary of all known diseases and you’ve got an automated, comprehensive tool tracking side-effects reported on social media.
In practice, it required a team of talented individuals, lots of creative thinking, and overcoming various challenges to create a complex yet beautiful data flow that resulted in a simple and impactful outcome.
They say to be great you need to read around your subject – what are you currently reading or your favourite book and what insights have you been able to apply to your work?
Storytelling with Data, Cole Nussbaumer Knaflic. When working with a wide range of stakeholders, insights drawn from quantifiable data are only useful if they can be easily understood. Data presented in a visually pleasing manner is often more reassuring and even believable, although this is not an excuse for us to beautify bad data!
In Storytelling with Data, Knaflic has put together a fantastic handbook on the underlying principles of charting data to effectively communicate a story. I have often used it as a reference for my own work and as a guide when teaching new analysts. Sometimes choices relating to chart-type, colours, positioning and font styles can feel arbitrary or unimportant, but I have learned through experience they are anything but.
Right now, I’m reading The Art of Statistics: Learning From Data, David Spiegelhalter. It’s a very accessible read demonstrating the application of statistical thinking to real-world problems and decisions. Spiegelhalter emphasises the importance of understanding data, asking the right questions, and avoiding common pitfalls in interpreting statistical results. It has been both practical and intellectually stimulating further considering how statistics could be applied to social data and good reminder about how to communicate statistical outcomes.
If you had to share three emojis that summed up social intelligence, what would they be?
🎣🧹🕵️♂️
What advice would you give to a brand who wanted to create an internal social intelligence team?
Team is the key word – I have been fortunate enough to work in good sized social intelligence teams (relative to what I hear from peers in the industry). There is so much richness in being able to collaborate on social intelligence initiatives, to bounce around the technical and creative aspects of the work with specialist peers.
For a team to succeed long term, I would say find someone who can lead with vision, energy and compassion. Team members should have a natural curiosity as well as a passion and knack for data analytics, stories and the power of social media.
An internal social intelligence team is likely to flourish if the members not only have these traits and skills but are also naturally results-driven, have a tendency towards building relationships across teams, drive for excellence and are willing to serve a bigger vision.
What are you looking forward to in social listening for 2025?
I have been closely monitoring the steady rise in the use of Bluesky among healthcare professionals and patient advocates. I am interested to see how things develop – we’ve seen other platforms seem like they were going to take a serious share of healthcare microbloggers from Twitter, but not lived up to their initial hype. I am curious to see if Bluesky, which currently is being touted as learning from the errors of those before, will do this. Right now, it is an exciting phase of discovering how to access and analyse this new source of intelligence, in 2025 it may well become a standard part of the mix.
We have moved past the buzzword phase of AI and are now witnessing its tangible impact on social intelligence. I'm eager to see how this evolves this year, particularly in how social media researchers can leverage AI tools and how social intelligence platforms will continue to integrate AI capabilities into their platforms.
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