AI-powered social listening, but focused on visual behaviour instead of sentiment analysis
Hey guys, a data engineer here with close to 5 years experience in social media and crisis management (pretty weird combo of experience I know). ’ve been thinking about building an AI-powered social listening tool that analyses reels, TikToks, and videos frame-by-frame instead of relying on captions, hashtags, or comments. Social media managers currently have to manually watch huge volumes of content to understand what actually performs; this tool would automate that by identifying visual and behavioural patterns across thousands of videos, such as hook timing, pacing, camera movement, product placement, and recurring themes behind viral content.
The idea sits between Sprout Social and Sprinklr, but powered by AI computer vision rather than text-based analysis.
Beyond marketing, the same system could be used for public activity intelligence in the security space; analysing publicly available social content to detect emerging gatherings, protests, or disruptions based on visual crowd patterns and location signals, helping organisations better forecast and respond to real-world events.
In short, it’s social listening that actually watches content instead of just reading it.