What does social intelligence mean to you?
Social intelligence is the difficult task of taking a substantial volume of conversation and distilling it into meaningful takeaways that answer an objective. This often means it is the privilege of properly representing and translating to your company or clients what customers, commentators, and other users say online, especially given the accessibility of online channels. There is the insights focus of the profession, but there is also a responsibility to make sure those insights truly grasp what social users are saying.
What are you doing that no-one else is to drive the social intelligence industry forward?
My team at Emerald is creating custom metrics to measure product and brand satisfaction, as well as providing consultation for which themes make sense to use as satisfaction measures. This approach provides more direction than all-up brand analyses and digs into key insights, such as new customer and churn differences.
Data science is another way we are pushing the industry forward by allowing visuals to map the data in different ways and show the most relevant connections between ideas. Similar to how we use custom metrics to become more specific than all-up analyses, we use data science to not just identify themes, but to show how social users arrived at one idea from a previous, connected idea.
We are also meticulously paying attention to data integrity when answering a business question. This not only comes down to making sure the data is clean and relevant, but does it need to analyze mutually exclusive brand mentions or not? Should we be excluding irrelevant themes? Does this objective require a very specific theme or emerging trend deep-dive?
It's the year 2030: What does the practice of social listening look like?
By 2030, AI will be much more reliable from an analysis perspective. This will significantly cut down the time social teams are spending on analysis and enable them to allocate more time to determining the most actionable outcome of the insights.
Video content is critical to social media, and it will be easier and more common for social intelligence teams to analyze video content in 2030.
What is the most common question you are helping your clients answer?
How is the market responding to our product compared to competitors, and how should we think about adjusting our strategy based on these reactions?
Oftentimes, these questions imply a need for all-up analysis through a variety of different data perspectives, but they also reveal areas for deeper analysis.
Have you got a favourite social intelligence use case or case study from the last year?
Analyzing the development of AI brands between 2023-2024 has been fascinating! Because of the growth of AI, we have been able to analyze which brands are growing the fastest or garnering the most satisfaction in specific categories.
An industry almost never develops this fast while simultaneously receiving as much coverage as it has, and the number of strong opinions that social users have on the topic makes for really enjoyable analysis. It’s those large and opinionated datasets that allow for the most quality insights in the end. I’m always looking to showcase examples for social intelligence, and the rapid movement of the AI industry perfectly matches social intelligence’s agility and flexibility.
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?
There are two books that have really given great perspective to my work:
1) Storytelling With Data by Cole Nussbaumer Knaflic
This book is not specific to social data, but is a key recommendation I would give to any insights and data professional. It helps me think through new or simplified ways of displaying data when telling a story, and it gives me the perspective to think through how the reader of my story will perceive the data.
2) Digital Anthropology by Haidy Geismar and Hannah Knox
This book provides more of a cultural understanding of the intersection between humans and digital interaction, but it provides professionals who work in social media with an understanding of the impacts of social media on the people that use it, specific social behaviors, and perceptions of using social media.
Both of these books allow for more comprehensive and contextual storytelling when translating social media insights to a client.
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?
1. Try to remain as unbiased about customer feedback as possible - this will allow for impactful results when insights are delivered.
2. Make sure to not only understand feedback about your brand online but competitor feedback as well. The significance of themes and sentiment of your brand are relevant to each other, but they are just as important compared to what is discussed in the rest of the market.
3. Understand the importance of data integrity by establishing a quality control process. It is really easy to write a boolean query and capture many irrelevant posts. If this happens, any metrics you deliver as insights may be unreliable and could mislead strategy.
4. Capture data according to the objectives, and play around with differing data capture strategies. Sometimes, a broad data capture strategy is best because a very specific query cuts out many relevant posts, but a broad query may also not specify the conversations that you need if the objective is a narrowed focus.
What are you looking forward to in social listening for 2025?
Continually improving AI and video content analysis! Parts of social intelligence are still manual, and the development of AI will continue to speed up the whole process. What is needed in the AI space is reliable results, so that themes can be quantified using AI with confidence to the same degree as when themes are quantified with boolean queries.
AI is also needed to analyze the mass quantities of video generated and posted to social media. Because traditional social listening tools are behind here, I look forward to utilizing other tools to complement my social listening stack in 2025.
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