AI has changed how we do nearly everything, and work is no exception. As a company specializing in social media listening, we've seen how AI has changed workflows and even our product. (Even though, we were AI before it was cool.) So what have AI and chatbots done to the value of social listening? Does AI make it less valuable? How is it valuable right now, and how can you keep getting value from it?
At its core, social listening is valuable because of its data. What are folks talking about online? In these organic spaces, what are real people saying about people, products, ideas, and cultural moments, and how are they saying it? The only place to truly gather these insights is within social media data.
Yes, chatbots were built on models trained on huge swaths of the internet. But that doesn't mean they have that knowledge ready to go. If you need a broad sample of what consumers are saying about your brand for brand health reporting, a chatbot won't review a broad sample of posts to build its analysis. That means its answer shouldn't be trusted.
We hear more and more folks say they can just do social listening with [fill in your favorite chatbot here]. In our AI Vibes vs. Social Listening Data eBook, we dig deep into that claim. We ran our own side-by-side comparison, and the result was clear: the claim is categorically false.
AI tools simply don't recall the breadth and depth of data that a social listening tool like Infegy Starscape provides. In our testing, we found chatbots drawing broad conclusions from just a handful of Reddit posts, with no wide, diverse view across social platforms.
Social listening still gives you crucial insight into how public opinion changes. Chatbots aren't built for this. Sure, they were trained on millions of tweets and posts, but they can't quickly reference or query them. And you need that to get accurate answers for the work that shapes your business and strategy.
Synthetic data can try to fill the gap. But real social media data can provide early indicators of shifts in people's behaviors and attitudes worldwide. It still lets you peek into people's organic views in real time, more affordably and with less effort than traditional market research.
That said, the picture isn't all negative. AI can actually make insights easier to find, isolate, and report. Here's how.
Without expertise, finding strategically significant insights in social media can feel like finding a needle in a haystack. The right AI tools help by giving you a sieve to sift through enormous amounts of data.
Infegy's Narratives and AI Summaries make it easy to pull out the core of a conversation, and even its unique parts, so you don't have to toil over graph after graph. Infegy Starscape also lets you dig into those highlighted narratives with drill-down capabilities, which makes analysis and follow-up questions easier to answer. Starscape can even build out full Personas for your audience at the click of a button.
AI lets you get to the meat of your insights fast. But it's nothing without the social media dataset underneath. That's why we offer our API, so you can pair our data with the power of AI in your own workflows.
So, does AI make social listening less valuable? Not at all. If anything, it makes the data matter more. AI speeds up analysis, but it can only be as good as the information it works from. A chatbot guessing from a few Reddit threads is no substitute for a broad, real-time view of what people are actually saying across platforms.
The winning approach isn't AI or social listening. It's AI on top of social listening. Pair real social data with smart AI tools, and you get insights that are both trustworthy and fast to find. That's how you keep social listening valuable now and in whatever comes next.