What is your job title? How do you use social listening in your work?
I’m the Insight Analyst of Gravity Road’s Strategy Department, leading the audience understanding side of the business.
We’re a creative digital-first agency that places audiences at the heart of what we do. That being said, social listening is a key part of my day-to-day job and is present across various work streams for both new business and retained clients. The applicability varies significantly depending on the nature of the project, but it includes audience deep dives to understand motivations, preferences, language, and tensions to be solved to inform campaign strategies; brand perception and competitor analysis to guide brand positioning; and audience planning by identifying key emerging communities with growth potential.
What’s your background? How did you get into social listening?
I’ve always been interested in strategy, but more particularly in delving into and identifying the underlying patterns that drive people's behaviours to set clear paths for strategic developments. This interest became even clearer during my academic journey. After completing my studies in Marketing, I received an offer from Ogilvy to join their audience insights team, where I began familiarising myself with social listening hands-on. It's been almost 10 years since then, witnessing significant changes in processes and platforms, but, as far as I can tell, there will be a few more years to come!
What’s been the project you’ve been most proud to work on?
More than one single project, I’d mention the creation of a bespoke audience insight product, which has been a catalyst for key projects and new business wins.
This product has equipped our clients with a fresh strategic perspective on approaching TikTok audiences - identifying and prioritising the most appropriate communities for their brands to engage with, conducting deep dives into their content, staying updated on their latest trends, and identifying creators with cultural momentum. It has generated various business opportunities, from playbooks to new work streams after delivery.
What’s the biggest misconception about your work?
I use tools; therefore, everything must be ready to go. As in, a question pops into your mind, you type it somewhere in the tool, and you have the answer at your fingertips. Yes, I’m exaggerating and oversimplifying to make the point, but there’s still an underestimation of the complexity of social listening as it still stands now. The brief has to be distilled; the research questions and queries have to be carefully crafted to ensure quality in the output; the data has to be interrogated, and to get to the bottom of underlying factors that create patterns in our observations requires some deep thinking that happens off tools.
Any nightmare clients? Why? (No names)
Fortunately, I can't think of any clients whom I'd describe as a nightmare, but there have certainly been a few challenges along the way since I started. Namely:
a) Making some clients understand that, although social platforms can be easily accessed by us as users, when it comes to social listening, some impose restrictions (e.g., data coverage and privacy). Therefore, workarounds are needed.
b) Shifting clients' mindset in the way they approach their audiences, whether it involves moving away from a brand-out-first comms approach or being willing to reconsider changing the way their business operates to best serve their audiences. This point can be a tough task and requires significant effort – we all understand that. However, as you listen to your audience and notice that their behaviours and motivations are changing, the need to adapt accordingly should become paramount.
Is there anything that you’re doing with social data that you don’t see others doing? Any missed opportunities?
A key focus for me in the past couple of years has been exploring and understanding the dynamics of TikTok audiences and going beyond just text analysis, utilising AI for audio and visual analysis.
While some may still claim that TikTok is solely for Gen Z, this viewpoint is far from accurate in 2024. Its users create content in a relatable and authentic manner around shared interests that bring them together - which has reintroduced 'community' as a buzzword into the realm of marketing. So, looking into what happens on this platform not only prompts a new perspective on how to approach audiences in this day and age but also presents a significant opportunity for gaining authentic insights into audience thoughts, feelings and behaviours.
Although not all briefs will get an answer via TikTok or need video content analysis, in my opinion leaving them out can be viewed as a missed opportunity, especially given a) the platform's substantial growth, b) the richness of audience insights it provides, c) the mirroring of similar content look and feel by other platforms, and d) the overarching trend of video content taking centre stage across major social platforms.
Who has made a lasting impression on you? Any SI heroes?
On a large scale, and thanks to the creation of SIL, over the past few years, I’ve had the chance to get to know some great professionals and their work, who gave me new perspectives on social intelligence and fueled my head with thoughts about new avenues to explore.
But if I had to name someone, given what’s been my main focus in the past couple of years and as someone who is passionate about innovation, it would have to be the masterminds behind ViralMoment: Chelsie Hall and Sheyda Demooei. Data providers play a key role in our job, and anyone who embraces innovation, is able to adapt to the current market needs, and works closely with us - social intelligence professionals - to push the tech boundaries to help us navigate the landscape in a more efficient and effective way has my full respect and gratitude.
How do you think the social intelligence industry will evolve in the next few years?
In the short term:
Audio and visual analysis capabilities will continue to grow. The increasing development and incorporation of AI will evolve to a point where a) we can feel comfortable and trust the automation of a few manual tasks without constant data checking, and b) more multidimensional analysis will be able to be done in a quicker and more accurate way.
In the mid to long term:
Predictive analysis will continue expanding, thanks to AI, and move closer to desired levels of confidence (potentially through more data integration with other sources). The shape and form of content creation on the current platform will evolve as they always have, and new platforms are likely to emerge. This evolution will lead us to reconsider and offer a fresh outlook on where, how, and what to look into when conducting social listening, balancing it with the challenges that data privacy may impose.
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