What is your job title? How do you use social listening in your work?
At We Are Social, I’ve been working as a Senior Director of Research & Insight for the last three years. My focus is helping grow our reporting effectiveness across sports, gaming and FMCG clients, looking at innovative methodologies that have social intelligence running alongside other quant methods & semiotics.
Social Intelligence and social listening is an integral part of our understanding of culture and the brands we work with, impacting multiple departments such as surfacing brand understanding for strategy and creative inspiration for our editorial teams. Across the wider agency, social intelligence is extremely important in exploring fandoms and communities.
Social Listening has three main purposes that underpin our projects. The first is proving campaign impact, when looking for pre and post-campaign changes around conversations, perceptions and sentiment. The second is understanding consumers - unpacking their conversation drivers and sentiment relevant for our clients and brands. Thirdly, we look at brand acountability - understanding issues, crises and opportunities across the online landscape, to see how and why opinions are forming.
What’s your background? How did you get into social listening?
My journey into social listening started around a decade ago working on understanding public perceptions of Unilever’s FMCG brands, gleaming sentiment drivers and content opportunities. From there I moved to Engine Group, helping drive reporting and analytics for Microsoft Xbox across EMEA. I then spent nearly 5 years at Omnicom Media Group, working across the Walt Disney Company in understanding trends and insights across the kids entertainment space. I then moved into the Group’s Sports & Culture Arm Fuse, where I used social listening and intelligence to assess sponsorship awareness and help deliver audience insights for future partnerships.
What sold me for social intelligence is how much rich data there is available, moving on from simple volume, sentiment and source tracking. Since starting at We Are Social, I’ve also been exposed to more innovative techniques and perspectives that have helped shape both the way we listen on social media, but also in how we define our learnings and insights. Working closely with our Cultural Insights team has been immensely rewarding in decoding online communities to shape culture.
What’s been the project you’ve been most proud to work on?
We work with Activision Blizzard across EMEA, reporting on social and content performance across multiple markets and over 60 channels. When we were tasked with getting our community excited about a new in-game item, social listening was integral throughout, helping identify the opportunity, track campaign progress and more importantly help us measure effectiveness.
The campaign was called Soap Codes, asking fans to reshare soap emojis in exchange for in-game codes. A simple call to action, but one that was targeted at an engaged player base on the right channel. As fans started engaging with our content, we tracked overall sentiment and reached non-fans of the page. We also picked up streamers and unpromoted YouTube content talking about our content, in addition to monitoring growing debates on how to get more codes on reddit. We even picked up soap code charms that were being sold in real life on eBay!
What I’ve been most proud of however, is showing the effectiveness of the campaign and how it helped not only foster community at a time when brand love was low, but also demonstrating the impact that social intelligence has in laddering up to business and brand effects.
What’s the biggest misconception about your work?
Funnily enough, one of the misconceptions that has followed me throughout my time in social media is in regards to visual output. Namely, that social listening is limited to time series analysis (i.e. line charts) and themes of conversation in the form of word clouds. The culprit here is CMD+C and CMD+V - when we snapshot directly from various tools and look to derive some meaning from what we see.
Drawing in quantitative data is only half the story, as through social listening we can build on audience data with behavioral patterns, cultural data from semiotic analysis and emotional data that shows drivers of excitement. Such a variety of data in most cases can’t be represented in simple charts and output, which is where our data takes on a different form through storytelling and narrative.
Is there anything that you’re doing with social data that you don’t see others doing? Any missed opportunities?
My goal over the last 5 years has been to raise the perception of social intelligence as a valuable source for creative inspiration and behavioral insight, demonstrating its importance in providing business and brand insights from an equal seat at the marketing table.
This came through the creation of a bespoke weighting and scoring tool which places social metrics alongside others such as from visits from web analytics, volume and keyword efficiency from search and CPMs from paid. We’ve also used first party data including sales metrics and brand trackers for more holistic and expansive analysis, resulting in social first but not social exclusive insight.
In doing so, we help elevate social data from purely standalone campaign reports and decks into an integral part of brand health tracking. We give more meaning to our fandoms and communities, and the way they respond and react to the brands we work with.
How do you think the social intelligence industry will evolve in the next few years?
We’re constantly witnessing change in social intelligence and listening, from less text-based data in favor of audio-visual, to users not clearly stating what they think to relaying how they feel. As our methods and data diversify and expand, there are two key areas that stand out when looking ahead.
The first is the growing impact of AI and being able to answer more semiotic based questions. A lot of social intelligence and listening tools have used AI elements for the best part of the last decade, helping identify hot topics and conversation peaks. But AI will play a larger role with predictive analytics and trend detection, as well as form queries from question based inputs, perhaps a Boolean 2.0?
The second is around platform capabilities and new data signals, alongside the gradual shift away from an overreliance of X/Twitter to a more varied range for unlocking insight, such as GenZ on TikTok and qual research panels in Quora. An influx of new data however also needs to be paired with greater care in understanding the merits and value of what we analyze. How we place importance across different channels and mediums is as unknown as it is exciting.
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