Blog / Social Listening

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Author: Marta Zwierz

Updated: September 30, 2026

20 min read

Social Listening Trends: Data & Expert Views for 2027

If the start of Q3 2026 has you wondering what the biggest social listening trends for 2027 will be, you’re in the right place.

The top ones to watch are video listening, monitoring brand visibility in AI chatbots, and AI-powered predictive analytics.

I found them by analyzing over 15.7k online mentions using the Brand24 AI Brand Assistant (June – September 2026) and by asking three Brand24 experts what they expect next year.

Below, you’ll find all seven social listening trends, the data behind them, and a checklist to get your marketing strategy ready for the upcoming Q1.

Top 7 social listening trends for 2027

Here is a quick shortlist before we get into the details:

Mikołaj Winkiel, Chief Evangelist at Brand24, explains:

01 Spoken mentions become a key social listening source

Short-form video listening is the most talked-about trend in our data.

It accounts for 17.28% of mentions and nearly a quarter of their reach (23.08%). In practice, this means that in 2027 you’ll want to know what people say in:

• TikToks,
• Instagram Reels,
• YouTube Shorts,
• as well as what they type in the comments.

All three of our experts agree that spoken content matters more and more. Karol Kłaczyński, Head of Product at Brand24, sees that the demand is growing in different formats:

When we asked him which platforms will matter most, he added:

Michał Sadowski, CEO of Brand24, explains why video data is so valuable:

And Mikołaj Winkiel thinks video is the part of AI mentions in social listening that people talk about the least:

Other research shows how much video affects what people buy:

• 50% of US consumers said video made them aware of products or brands. They also say YouTube is 1.7x more likely than other social platforms to influence brand consideration. (Source: Google/BCG, 2025)
• 46% of consumers bought products they discovered on YouTube, with 23% saying that YouTube Shorts are the most convincing format. (Source: Channel Factory via MediaPost, 2025)
• Video analytics is the fastest-growing analytics type in the social listening market, at 13.29% CAGR. (Source: Mordor Intelligence)

02 AI visibility monitoring becomes a standard social listening channel

Keeping track of AI search visibility and what AI models say about brands is the third most discussed trend in our data (11.23% of mention volume), but it comes second when it comes to reach (10.50%).

Why is that?

Because people writing online about monitoring ChatGPT, Gemini, and Perplexity tend to have big audiences, so the topic travels further than the number of mentions would suggest.

For Michał Sadowski, social listening is becoming a big part of AI visibility:

Looking back at 2026, it’s also the change that shaped his thinking about social listening the most:

Mikołaj Winkiel remembers the exact moment in 2026 when he noticed this shift by himself:

He sees LLM monitoring as a natural next step for media monitoring and social listening:

Karol Kłaczyński adds that AI Search visibility also changes which sources you should keep an eye on:

For Karol, it’s all part of a bigger shift he noticed in 2026:

03 Predictive analytics becomes a core social listening feature

AI-powered sentiment analysis and predictive analytics is the second biggest trend in Brand24 social listening data, with 12.04% of share of voice.

People are clearly more interested in what mentions mean (the context) and what might happen next (the forecast and insights) than in simply how many mentions there are.

Michał Sadowski points out that the basics of using social listening tools haven’t changed much. What’s changing is what you get out of it:

He also explains where AI helps the most:

Michał expects social listening to become more predictive in 2027, too.

As he puts it, “social listening products will not only provide data, but will likely drive decisions”.

Karol Kłaczyński focuses on how much cheaper and easier the analysis has become:

He also sees a change in what social listening works on, and in who can do it:

Mikołaj Winkiel doesn’t think AI will replace the classic social listening features:

What AI adds, according to Mikołaj, is the ability of synthesizing data:

The time between getting the data and making a decision is shrinking, too. Mikołaj lists it among the key social listening trends for 2027:

04 Social listening becomes a full market intelligence engine

Social listening as a market intelligence engine takes 9.25% of mentions in our data.

More and more companies use social listening tools outside marketing and PR, for example, in product, sales, investor relations, or leadership teams.

When I asked the AI Brand Assistant to look at which use cases people discuss online, trend detection was the top 1 (33.4% of share of voice), followed by brand mention monitoring (27.6%) and competitive intelligence (24.9%).

Mikołaj Winkiel suggests connecting social listening with the rest of your company’s data:

The social listening market is growing, too:

• 7.58% of people discussing social listening online were also discussing its market growth signals.
• And according to the freshest estimations, the social media listening market is worth $10.91 billion in 2026. It will probably reach $20.51 billion by 2031 (with 11.19% CAGR). (Source: Mordor Intelligence)

05 Real-time crisis detection moves to automation of responses

Mikołaj Winkiel explains where AI can help:

Michał Sadowski expects tools to go one step further and suggest what to do next:

The marketers’ predictions found by the Brand24 AI Brand Assistant in online mentions are even bolder. They expect crisis tools in 2027 to draft responses and notify the right people automatically.

Real-time crisis detection was discussed by 8.44% of people online, but its reach grew by 47.4% between July and August 2026, more than any other trend in our data.

The number of mentions went down in the same period, so fewer people wrote about crisis detection, but those who did had much bigger audiences.

6. Filtering out AI-generated noise becomes a core social listening task

Our experts see AI content slop and AI-generated noise as one of the biggest challenges for social listening in 2027, even though it doesn’t really show up in the online discussions about trends.

Karol Kłaczyński describes how big the problem is getting:

Mikołaj Winkiel warns that brands are often targets, too:

For Michał Sadowski, this changes what makes a social listening tool valuable:

Well… At least people still prefer content made by humans: 43% prefer ads and videos created by people, and only 7% prefer AI-generated ones. (Source: Channel Factory via MediaPost, 2025)

Brand24 social listening analysis found that disinformation as a topic is barely discussed online, but Brand24 experts see it as a serious risk.

All three of them mentioned AI-generated noise, fake news, or bot networks, but disinformation doesn’t show up as a separate trend in the online conversation.

Karol Kłaczyński connects it to how fast AI developed in 2026:

7. Brands monitor more sources as platforms limit access to their data

According to Mikołaj Winkiel, the biggest risk for social listening in 2027 is losing access to data:

On top of that, online conversations are spreading to more and more places:

• Mikołaj points to podcasts and newsletters, “because that’s where expert opinions are shaped, and almost nobody monitors them”.
• Karol Kłaczyński adds that a lot depends on the region, where “smaller social platforms dedicated to specific interests or purposes” are gaining importance.

Which platforms will matter most for social listening in 2027?

According to experts from Brand24, YouTube, TikTok, and Reddit will matter most for social listening in 2027.

That’s where people share their honest and most emotionally loaded opinions, and where AI models learn about brands. LLMs also become a data source of their own.

Mikołaj Winkiel explains why:

Platform / source	Why it matters in 2027	Named by	Expert proof
YouTube	1. A lot of spoken reviews and tests 2. It’s still hard for AI to mimic 3. Has a strong influence on purchases	Michał Sadowski, Karol Kłaczyński, Mikołaj Winkiel	“Sources built around authentic conversations will become increasingly important, particularly YouTube as it is still mostly difficult to mimic by AI” (Michał Sadowski)
TikTok	1. Short-form video is the #1 trend discussed online (17.28% SoV) 2. Many mentions are spoken, not typed	Michał Sadowski, Karol Kłaczyński, Mikołaj Winkiel	“It depends a lot on the region. Globally, ‘spoken’ sources are gaining, mainly TikTok and YouTube, and in my opinion they’ll keep gaining” (Karol Kłaczyński)
Reddit	1. Authentic opinions are formed here 2. Often cited by LLMs and used to train them	Karol Kłaczyński, Mikołaj Winkiel	“Reddit, TikTok, and YouTube [will matter most], because that’s where authentic opinions are and, just as importantly, that’s what models are trained on” (Mikołaj Winkiel)
LLMs (ChatGPT, Gemini, Claude, Perplexity, Grok, Google AI Overviews)	1. They shape purchase decisions 2. It’s a data source that didn’t exist two years ago	Michał Sadowski, Mikołaj Winkiel	“[Another important source are] LLMs themselves as a data source, which two years ago simply didn’t exist” (Mikołaj Winkiel)
Comparison and review sites	1. Frequently cited by LLMs in product answers	Karol Kłaczyński	“Because LLMs are pushing further into the market and taking over the role search engines used to play, Reddit will definitely matter, and so will all the sources LLMs cite, for example comparison sites in the case of products” (Karol Kłaczyński)
Podcasts and newsletters	1. It’s where expert opinions are shaped 2. Monitored by a small number of brands yet	Mikołaj Winkiel	“Podcasts and newsletters [will matter], because that’s where expert opinions are shaped, and almost nobody monitors them” (Mikołaj Winkiel)
Regional and niche platforms	1. Interest-specific communities that differ by market	Karol Kłaczyński	“Regionally, [what will matter are] smaller social platforms dedicated to specific areas of interest or purposes” (Karol Kłaczyński)

How to prepare your social listening strategy for 2027?

A good first step is to check what people and AI models already say about your brand.

As Karol Kłaczyński puts it: “First of all, check where you are now, what you know about your brand, and how you’re able to react to it”.

He also explains that what comes next depends on the size of your brand:

Whatever the size of your brand, you can go through this checklist I prepared based on our experts’ advice:

01 Track AI mentions of your brand and category

“It takes ten minutes and quite often ruins your mood, but it’s better to know”, says Mikołaj Winkiel.

How to do it?

Use AI visibility tools to track your AI brand mentions in answers from ChatGPT, Gemini, Perplexity, and other AI models, in which position, and next to which competitors.

These tools analyze how AI models position your brand, so you can track your AI share of voice and the exact sources they cite.

02 Review your media monitoring setup

Many brand names are also everyday words, people’s names, or places, so a project can quickly fill up with mentions that have nothing to do with your brand.

Mikołaj Winkiel recalls: “When we were setting up monitoring for a cosmetics brand, before the project had only mentions of perfume left, we had to exclude an actor, an airplane, and a few places on the map. And that’s not an exception, just a pretty typical Tuesday”

How to do it?

Some social listening tools have AI features that clean up your results for you.

One of them is Smart Context Search in Brand24:

you describe what you’re looking for in plain words (for example, “Gemini Google’s AI assistant”), and the tool filters out mentions from a totally different context, like in this case, horoscopes.

It’s worth reviewing your setup every few months, because new products and campaigns bring new keywords.

03 Add video transcript and spoken content to your sources

Make sure your TikTok and YouTube monitoring analyzes what’s said in these videos, as well as in captions and comments.

How to do it?

Check whether your social listening tool analyzes what’s said in videos, as well as titles and descriptions.

For example, in Brand24, you can monitor YouTube and TikTok transcripts, so you’ll catch your brand name even if it comes up in the 20th minute of a review.

04 Define what counts as a signal

“Decide what is a signal that needs a reaction and what is just information”, advises Mikołaj.

How to do it?

A signal = a brand mention that needs someone to act. It can be a sudden spike in mentions, a wave of negative comments, or a post from an author with a big reach.

Set up alerts for these situations in your social listening tool and send them to the teams responsible for reacting.

As Mikołaj puts it, “a tool without an owner doesn’t work, no matter how much AI is inside it”.

05 Connect social listening with sales and customer service data

Any brand mention will tell you much more when you can see what was happening in the company at the same time.

With a social listening API, you can send mention data, sentiment, and AI summaries straight to your BI dashboards (like Looker or Power BI) or other internal tools.

Then you can compare spikes in mentions with sales results or the number of support tickets from the same days.

06 Get mentioned where AI models look

Michał Sadowski recommends “actively building the authority and narratives that can improve [brands’] visibility and recommendations within AI answers”.

How to do it?

Check which websites or social media posts are cited by AI chatbots when they answer questions about your category, and which of them mention your competitors but not you.

Sometimes, those are the places worth reaching out to with PR, expert comments, or partnerships.

07 Build your own historical datasets for social listening

Michał suggests creating benchmarks “that cannot be easily reproduced using publicly available AI models”.

How to do it?

Turn the data you own into your original research. For example, we analyzed 46.4k online mentions in our report on AI visibility tracking issues.

Ahrefs did its own research on about 1 million top-ranking pages to check if Google punishes AI content.