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Generative Engine Optimization (GEO) Guide

Generative Engine Optimization (GEO) is transforming how brands show up in AI-powered search. Explore insights, strategies, and best practices to help your content rank and resonate across conversational engines like ChatGPT, Gemini, and Copilot.

Explore insights and strategies for Generative Engine Optimization (GEO) to help your brand stay visible and discoverable in AI-powered search.

Generative Engine Optimization (GEO) Blog Collection | Meltwater

Media monitoring helps organizations stay informed about what’s being said across online news, print, broadcast, podcasts, and other media channels. Whether you're tracking brand mentions, measuring PR performance, monitoring competitors, or identifying emerging trends, our expert guides, best practices, and industry insights will help you build a smarter media monitoring strategy and make more informed communications decisions.

Discover expert media monitoring guides, best practices, and industry insights to track brand mentions, monitor competitors, and stay ahead of the news.

Media Monitoring: Guides, Best Practices & Industry Insights

Every day billions of conversations take place on social media: tweets, posts, comments, blogs, reviews, podcasts, and much more.

Learn how to use social listening to make sense of all of that data.

On our social listening category page, you find all our blogs covering topics around social listening and social media monitoring. Read more.

Social Listening Blogs | Category

Business Reputation Management: What does it take to add reputation management to your marketing strategy? More importantly, how do you keep your reputation sparkly and shiny? Here’s your all-access guide to online reputation management for the long term.

On our reputation management category page, you find all our blogs covering topics around business reputation management. Read more.

Reputation Management Blogs | Category

From your brand's logo to your website, your social media presence to your customer support—these elements combined are what constitutes a brand in the minds of customers. But, there are thousands of other businesses that have a logo, website, social media presence, and website. So, how can you position your business on the market and make it stand out from the competition?

The key to success is branding & brand management!

On our brand management category page, you find all our blogs covering topics around brand management. Build your strategy and reach your goals!

Brand Management Blogs | Category

Competitive intelligence and the act of collecting competitive data can be seen as growth drivers for a company. Our guide will help you understand the concept of competitive intelligence (CI) by answering questions such as: What is the definition of competitive intelligence? How is competitive intelligence useful to organizations? What is the goal of competitive intelligence? And more.

On our competitive intelligence category page, you find all our blogs covering topics around competitive intelligence. Learn how to stay ahead.

Competitive Intelligence Blogs | Category

Let’s dive into the customer journey framework and how to optimize the process by creating a customer journey map and using metrics that matter when analyzing the customer journey.

On our customer journey category page, you find all our blogs covering topics around mapping and understanding the customer journey.

Customer Journey Blogs | Category

How do customers interact with my newly launched product?

How do I increase the productivity of my employees?

How do I know if my marketing efforts are working?

We have just two words for you...Data analytics!

On our data analytics category page, you find all our blogs covering topics around AI and data analytics. Technical and still easy to understand.

AI & Data Analytics Blogs | Category

Public relations and media relations can add impact to any marketing strategy. It’s an opportunity for brands to grow their reach beyond traditional sales messages. PR helps to shape the image you want people to have of your brand.

So, what is PR and how do you use it? This guide shows you everything you need to know to build a strong public relations foundation.

On our public relations (PR) category page, you find all our blogs covering public relations and communications topics. Step up your PR game.

Public Relations (PR) Blogs | Category

We all know exactly what the roles of sales or accounting are in a company, right? We might even have a slight idea of what the IT guys are doing.

But there is another business discipline, that plays a crucial role in organizations, even more so during the pandemic – internal communications!

But what exactly do we mean by that, what purpose does it serve and what steps can you take to ensure you and your employees will communicate effectively?

On our internal communications category page, you find all our blogs about internal comms topics. Learn about the intranet, internal newsletters, and more.

Internal Communications Blogs | Category

As the internet has taken root in more areas of our lives — everything from entertainment to shopping to paying bills and more — traditional marketing is becoming less impactful. As any marketer knows, you need to focus on where your audience is if you want to reach them. Since the average person spends about seven hours a day online, it’s no surprise that content has maintained its hold on marketers.

Here's a closer look at what content marketing is and why it matters more than ever in our digital-first economy.

On our content marketing category page, you find blogs about content marketing topics. Learn about strategies, KPIs, tips, and more. Make your content king!

Content Marketing Blogs | Category

The rise of the influencer marketing space – today a $10 billion industry, growing 50% per year – is one of the clearest examples of how social media is transforming traditional marketing. These days having a business website, presence on social, PR coverage, and your own content isn’t enough to compete.

We'll dive into the intricacies of influencer marketing to help ensure that you're equipped with the insights needed to be successful in this space.

On our influencer marketing category page, you find blogs about influencer marketing topics. Build your strategy, find influencers, and measure results.

Influencer Marketing Blogs | Category

Have you just launched a new product or service that you want to get the word out about? Maybe you want to share with consumers why it is awesome and how it is so much better than the one your competitors offer.

Well, then, there is one thing you can't do without...Marketing!

On our marketing category page, you find blogs about marketing topics. Learn about all the different angles and types of marketing and improve your results.

Marketing Blogs | Category

Building a following and using social media platforms to reach a wider audience requires a well-planned social media marketing strategy. In this guide, we’ll be looking at why social media marketing is so essential and how you can make it work for your business.

On our social media marketing category page, you find blogs about social media marketing topics. Learn how to get the highest paid social ROI!

Social Media Marketing Blogs | Category

In the fast-evolving realm of digital marketing and public relations, utilizing the right tools is crucial for success. Our interdisciplinary category showcases all the pertinent tools for digital marketing & PR. These tools help in enhancing your online presence and effectively reaching target groups, whether through reputation management, influencer marketing, or social media management.

On our digital marketing and PR tools category page, you find all our blogs covering topics around mapping and understanding the customer journey.

Digital Marketing & PR Tools Blogs | Category

Kim Cattrall takes the lead in a campaign celebrating the intelligence behind confident brand decisions.

Intelligence is always in style: Kim Cattrall stars in Meltwater’s new campaign

AI adoption is no longer the challenge—trusted context is. Most organizations have AI tools, but many still rely on disconnected, stale, or unverified data, limiting the quality and trustworthiness of AI-generated outputs. Meltwater MCP brings trusted, real-time intelligence into AI assistants.

Your Best Context is Already in the Room

See how one platform can power every decision across PR, communications, and marketing.

The Meltwater Blog

Blog Topics: Generative Engine Optimization, Media Intelligence, Media Relations, Social Listening, Consumer Intelligence, Influencer Marketing

Find out how you can leverage Facebook to boost your brand's online presence and gain a competitive edge. Explore the Meltwater category page today!

Facebook Blog | Meltwater

Find out how you can leverage Instagram to boost your brand's visual appeal and gain a competitive edge. Explore our category page today!

Instagram Blog | Meltwater

Find out how you can leverage LinkedIn to grow your professional network and gain a competitive edge. Explore the Meltwater category page today!

LinkedIn Blog | Meltwater

Find out how you can leverage TikTok to elevate your brand with creative content and gain a competitive edge. Explore the Meltwater category page today!

TikTok Blog | Meltwater

Find out how you can leverage X / Twitter to engage your audience effectively and gain a competitive edge. Explore the Meltwater category page today!

X / Twitter Blog | Meltwater

Find out how you can leverage YouTube to create engaging video content and gain a competitive edge. Explore the Meltwater category page today!

YouTube Blog | Meltwater

Brands have more social data than ever, but collecting signals is not the same as understanding them. A connected social intelligence stack brings listening, benchmarking, audience insights, and action together so teams can see what matters and make better decisions about what comes next.

Why responsiveness is not the same as trend chasing

Most social teams do not have a data problem. They have a context problem, and unfortunately, another dashboard usually does not solve it.

A social intelligence stack is a connected system for turning social signals into decisions. It has four stages: listen to identify a signal, benchmark it for context, understand the audience and drivers behind it, and act on what the analysis reveals.

Teams use different platforms and capabilities for content performance, listening, competitive reporting, audience research, sentiment, and just about every other signal a marketer could ask for. The harder part is knowing which signals actually deserve attention and which ones just happen to look good in a deck.

That is the difference between social data and social intelligence. Social data tells you what happened, while social intelligence helps you understand what it means and whether it should change what you do next.

The most useful way to think about that process is as a stack: Listen → Benchmark → Understand → Act. None of those layers is especially useful in isolation, but together they give teams a much clearer read on what deserves a response.

<table>

  <thead>

    <tr>

      <th>Stage</th>

      <th>Core question</th>

      <th>What it examines</th>

      <th>Decision output</th>

    </tr>

  </thead>

  <tbody>

    <tr>

      <td>Listen</td>

      <td>What is happening?</td>

      <td>Conversations, mentions, trends, sentiment, and emerging themes</td>

      <td>A relevant signal</td>

    </tr>

    <tr>

      <td>Benchmark</td>

      <td>Is it meaningful?</td>

      <td>Historical, competitive, category, and content performance</td>

      <td>Context and significance</td>

    </tr>

    <tr>

      <td>Understand</td>

      <td>Who or what is driving it?</td>

      <td>Communities, affinities, markets, behaviors, and cultural context</td>

      <td>An explanation</td>

    </tr>

    <tr>

      <td>Act</td>

      <td>What should change?</td>

      <td>Business objectives, brand fit, opportunity, and risk</td>

      <td>A decision, test, or deliberate non-action</td>

    </tr>

  </tbody>

</table>

Social listening is the first layer of the stack, not the entire stack. It tells you what is happening around your brand, competitors, category, products, campaigns, and the culture surrounding them.

The goal is not to capture every possible mention. It is to make sure the conversations you are tracking still resemble the way people are actually talking.

That takes maintenance because internet language does not sit still. Product nicknames appear, creators introduce new terminology, memes mutate, and conversations move into places the original query never anticipated. Sentiment has the same problem, since sarcasm, fandom language, slang, and cultural differences have a way of making a clean positive-or-negative classification look much more useful than it really is.

The point is not to turn every marketer into a query-design specialist. It is to make sure the first layer of the stack is giving the team a signal worth spending time on.

A post generated 100,000 engagements, which sounds impressive until you ask the obvious question: compared with what? Maybe it crushed the brand's usual performance, maybe every competitor in the category had an even bigger week, or maybe Instagram went down that afternoon and half the internet wandered over to TikTok.

A big number is not a strategy. Without context, it is just a number that happens to look good in a deck.

Benchmarking gives that number somewhere to live. Historical benchmarks show whether the brand is improving, competitive benchmarks show how it is moving within the category, and content benchmarks reveal which formats or topics consistently punch above their weight.

This is also where teams should resist the urge to make every available metric important. The best benchmark is not the fanciest number in the dashboard, but the one that helps answer the business question in front of you.

For one campaign, that might mean engagement or video views. For another, it could be audience growth, share of voice, response rate, or performance against a very specific competitive set.

Listening tells you something is happening, while benchmarking tells you whether it stands out. The next layer is where things get more interesting, because it asks who is driving that behavior and why.

Audience intelligence can surface communities, affinities, geography, language, demographics, and the other interests competing for an audience's attention. Those signals often explain performance more clearly than the performance metric itself.

Suppose a true-crime audience also over-indexes on dog accounts. That might sound like trivia until someone on the paid team realizes it opens up an entirely new targeting or creative angle, and it could lower your CPC to boot. Suddenly, the weird little affinity buried in the data has a job to do.

Maybe a conversation is growing because an unexpected fandom has adopted the product. Maybe a campaign is landing differently across markets, or a creator is pulling a brand into a community it has never deliberately targeted.

This is also where human analysis still earns its place. Automation can organize a lot of audience information, but understanding humor, cultural context, language nuance, and community norms still requires knowing more than what appeared in the data field.

The final layer is also the one teams are most likely to skip. Social organizations can become extremely good at explaining what happened without ever letting that explanation change what happens next.

Action does not always mean jumping on the trend. It can mean shifting the publishing calendar, changing creative, increasing support behind a format, pursuing a creator partnership, adjusting messaging, investigating a new audience segment, or deciding that an interesting spike is not strategically important enough to chase.

That last option matters more than marketers tend to admit. A good social intelligence system should make teams faster when speed matters, but it should also make them more comfortable leaving noise alone.

If the analysis ends with a recap, you have reporting. Social intelligence should make the next decision sharper.

The social strategy behind DexterDexter: Resurrection is a useful example because the intelligence loop was not happening after the campaign as a reporting exercise. It was actively feeding what the team published next.

The Listen layer came from daily tracking of UGC trends and emerging themes. Fan edits, memes, scene lifts, and recurring conversations became an ongoing source of information about what audiences were choosing to play with.

The Benchmark layer gave those signals context. The team used ListenFirst to understand how Dexter was pacing against other scripted dramas, which made it easier to tell the difference between an interesting spike and something worth acting on.

The Understand layer came from looking across those signals to see what kept resurfacing. Particular scenes, legacy memes, language choices, and fan behaviors helped show which parts of the franchise audiences were most interested in carrying forward.

Then came Act. The team said its daily tracking helped it respond with high-performing content within 24 hours, while ListenFirst data also informed posting times, wording, and broader publishing strategy.

That is the social intelligence stack doing what it is supposed to do. Audience behavior was not something to summarize later; it became an input into the next creative decision. The acronym, LBUA, is admittedly almost aggressively on the nose for a framework this literal. We are choosing to pronounce it “el-boo-ah” until someone gives us a better option.

Sinners shows why cultural context matters

Sinners offers a different view of the same discipline. Some of its strongest social content worked because the campaign understood that different audience moments called for very different kinds of participation.

At the London premiere, the cast leaned into the “I Got Something in My Teeth” trend with vampire-inspired grillz, bringing the film’s branding and themes into a platform-native TikTok moment. That approach reflected the broader success of Sinners on TikTok, where the film generated 77.1 million video views and 152,200 shares during the period analyzed. TikTok accounted for 90% of all shares across the platforms studied, demonstrating how effectively casual, trend-driven content extended the film’s reach.

The campaign also made room for something considerably less trend-driven. Director Ryan Coogler appeared in a 10-minute YouTube video discussing aspect ratios and viewing formats, giving the more invested part of the audience exactly the kind of detail it wanted.

Those are very different creative choices, and that is precisely what makes the example useful. Social intelligence should not produce one universal definition of good social content; it should help teams understand what the audience is signaling in a specific moment.

Sometimes people want to participate in a joke. Other times, they want ten minutes of Ryan Coogler talking about projection formats. And sometimes they want fan edits of Michael B. Jordan with star wipes and SZA's “Big Boy” playing. Pretending those are all the same audience need is how brands end up making content nobody asked for.

Creators have an advantage on social because many of them live inside a constant feedback loop. They publish, watch what happens, adjust, and try again without turning every change into a quarterly strategy exercise.

Brands cannot operate exactly like creators, nor should they. They have approval processes, established identities, multiple audiences, legal considerations, and significantly more institutional weight attached to every post.

What they can borrow is the feedback loop. A strong social intelligence stack gives a larger organization a way to become more responsive without pretending it has the same freedom as an individual creator with a phone.

That distinction matters because engagement is not permission. A trend performing well does not automatically mean the brand belongs in it, and a community discussing the brand does not automatically mean it wants an official account joining the conversation.

The job of social intelligence is not to make brands faster at copying whatever worked yesterday. It is to give them enough context to understand why something worked, whether that logic applies to them, and whether participating would actually add anything.

The Dexter example gets this right because the team was not simply collecting viral posts and recreating them. It was looking for repeated audience behavior, evaluating those signals against performance and competitive context, then feeding the strongest ones back into a content system.

That is a much more durable model than chasing spikes. It turns responsiveness into an operating discipline instead of a personality trait.

Think in terms of the full stack: Listen → Benchmark → Understand → Act. Listening identifies the signal, but the other layers determine whether it matters and what the business should do with it.

Do not confuse more data with more intelligence. A smaller set of connected signals can be more useful than a giant dashboard full of metrics that never change a decision.

Benchmark before declaring a win. Performance needs historical, competitive, or category context before a team can tell whether something is genuinely unusual.

Look at the people behind the performance. Communities, affinities, language, geography, and recurring behaviors often explain why a result happened more clearly than the engagement number alone.

Treat audience behavior as an input to creative strategy. The Dexter example shows how UGC and emerging themes can feed directly into what a team publishes next.

Remember that action can also mean restraint. Social intelligence should make it easier to spot a real opportunity, but it should also make it easier to leave an irrelevant trend alone.

The social intelligence stack is useful because none of its individual parts are especially revolutionary on their own. Brands have been listening, measuring performance, studying audiences, and making marketing decisions for a long time.

The shift is in treating those activities as one connected system instead of four separate jobs. Listening without benchmarking can overstate a signal, benchmarking without audience context can miss the reason behind it, and insight without action becomes another deck that everyone politely reviews before moving on.

The point is not to know more about what happened on social last week. It is to make the next decision with more context than you had before.

A social intelligence stack is the combination of data, tools, analysis, and workflows used to move through four connected stages: Listen → Benchmark → Understand → Act. Each layer adds context to the one before it, helping teams identify relevant social signals, determine whether they matter, understand the audiences behind them, and translate those insights into an informed business or marketing decision.

What is the difference between social listening and social intelligence?

Social listening is one layer of social intelligence. It captures conversations, mentions, topics, sentiment, and other signals that help a brand understand what people are discussing. Social intelligence takes those signals further by adding competitive and historical benchmarks, audience context, analysis, and business objectives. Listening tells you what is happening, while social intelligence helps determine what it means.

How do you turn social data into actionable intelligence?

Turn social data into actionable intelligence by moving through the full stack: listen to identify the signal, benchmark it to establish context, understand the audience and behavior behind it, then act on what those layers reveal. Starting with a clear business question keeps the process focused. If the analysis does not help change, test, accelerate, investigate, or dismiss something, it is still reporting.

What should a social intelligence stack measure?

A social intelligence stack should measure the signals that help answer the organization's actual business questions. Depending on the objective, that could include content performance, competitive performance, conversation volume, sentiment, share of voice, audience growth, affinities, or community behavior. There is no universal metric set, because the useful measures are the ones that provide enough context to improve the decision at the end.

Do you need a social intelligence platform?

A social intelligence platform becomes more valuable as a brand's social presence, competitive environment, and measurement needs become more complex. Native analytics may cover basic owned-channel reporting, while broader listening, cross-platform benchmarking, competitive analysis, and audience intelligence usually require a more connected setup. The deciding factor is whether the technology and analysis together help teams make better, faster, more informed decisions.

Connect the signals. Improve the decision.

The social intelligence stack: Turning social data into better decisions by ListenFirst

Scroll through your favorite video app and they’re everywhere: Point-of-view (POV) videos of everything from absurd pranks to impressive athletic feats, no camera in sight. 

Welcome to the advent of smart glasses (also known as AI glasses), the wearable devices that combine familiar eyewear with filming, listening, recording, and AI capabilities. 

Videos filmed from eyewear have taken over digital content creation, driving engagement and raising serious questions about consent in the process. From January 1 to September 28, 2026, the technology appeared in about 805,000 mentions across print, digital, and social media sources. However, the sentiment of that conversation flipped from largely positive to largely negative from the first half of the year to the second as consumers have increasingly focused their attention on the technology’s risks.

We used Meltwater's social listening capabilities to better understand the current smart glasses conversation and what it means for brands, marketers, and technology companies. Here are the biggest takeaways anyone interested in the topic should know.

Click here to view a one-page summary of our findings.

Smart glasses criticism peaked in August as consumer conversation grew.

Privacy and covert recording are now the leading smart glasses topics.

Smart glasses are scrutinized on Reddit and embraced on TikTok.

Creator content is mostly positive, but audience reactions are mixed.

FAQ: Smart glasses sentiment, media coverage, and consumer conversation

<table class="table-primary">
<thead>
<tr>
<th>Smart glasses analysis methodology</th>
<th></th>
</tr>
</thead>
<tbody>
<tr>
<td>Capability</td>
<td><a href="https://www.meltwater.com/en/capabilities/social-listening">Meltwater Social Listening</a></td>
</tr>
<tr>
<td>Analysis window</td>
<td>January 1 to September 28, 2026</td>
</tr>
<tr>
<td>Data sources</td>
<td>Print and online news, forums, and 17 social media platforms, including Bluesky, Instagram, Facebook, LinkedIn, Pinterest, Reddit, Snapchat, TikTok, X, and YouTube</td>
</tr>
<tr>
<td>Keywords tracked</td>
<td>Smart glasses and related keywords, brands, and hashtags</td>
</tr>
<tr>
<td>Total number of posts analyzed</td>
<td>~805,000</td>
</tr>
<tr>
<td>Sample groups analyzed</td>
<td>The qualitative analysis covers two datasets: the top 1,000 posts by engagement, which shows what content captures the most attention, and 1,000 randomly selected posts, which provides a view of the broader everyday conversation.</td>
</tr>
<tr>
<td>Key term definitions</td>
<td><strong>Engagement:</strong> The number of shares, comments, likes, retweets, replies, direct messages, etc.<br><br><strong>Post:</strong> A single piece of content that can include multiple mentions.<br><br><strong>Mentions:</strong> The number of instances in which keywords and phrases appeared within a post.<br><br><strong>Share of posts:</strong> The proportion of posts within our topic-coded, 2,000-post sample</td>
</tr>
<tr>
<td>Added data notes</td>
<td>Every post in both sample datasets was coded for its primary topic, brands mentioned, type of author driving the conversation, and stance toward smart glasses; these codes were then aggregated by month and dataset.<br><br>September covers only September 1–28, so month-on-month comparisons slightly understate the full month.<br><br>Sentiment is based on Meltwater's automated tone classification, applied consistently across all mentions. It is complemented by a read of the post sample, which adds context on tone in content such as sarcasm, humour, and prank videos.</td>
</tr>
</tbody>
</table>

This year, public conversation about smart glasses began with optimism. News media drove the conversation, with coverage focusing on company and business topics like product launches and market reports. 

In particular, Meta, whose products were named in a stunning 64% of our sample posts, started the year off with a bang with its launch of new AI glasses features at the Consumer Electronics Show in January. At the time, positive sentiment outweighed negative sentiment by nearly 4 to 1.

A lot changed in the smart glasses discourse as we entered the second half of this year. Negative sentiment grew, spiking in August as higher proportions of consumers drove the conversation in our sample and discussed concerns with the technology. (More on that in the next section.)

So while sentiment was largely positive when news media was driving the smart glasses conversation, as consumers have gained share of voice, that initial optimism has tanked. 

From July to September, privacy concerns about smart glasses, particularly how they can be used to secretly film and harass people, became the leading topic in our sample of posts. 

Collectively, they peaked at 58% share of posts in August, nearly triple what they were in January. The topic of privacy and covert recording specifically grew to a 25% share. 

In that time, the nickname “pervert glasses” entered mainstream discourse. The word "perv" was absent from our sample before May, but appeared in 5% of July to September posts. This rising keyword signalled just how much negative sentiment around the devices’ controversial filming capabilities was extending to those who wear them. 

Meanwhile, discussion of bans and regulation also tripled in share in our sample, comprising one in ten of all posts from July to September. That period included news of several high-profile bans that were passed or proposed, including those in Australia, the US, and the UK. 

On the commercial side, some brands have turned the trending topic into a marketing hook. In August, internet privacy company and search engine DuckDuckGo released a collaboration with sunglasses brand Knockaround that it called “Normal F***ing Sunglasses.” The product listing touted: “These ‘smart’ glasses come with zero AI and zero cameras. Designed to block the sun, not send data to the cloud.” They reportedly sold out in one week.

Smart glasses are scrutinized on Reddit and embraced on TikTok. 

About 30% of smart glasses posts were published on Reddit. There, sentiment towards the gadgets is 36% negative and only 10% positive, with conversation concentrated in subreddits like r/technology, r/gadgets, and r/news. In r/technology, two of the most engaged posts shared news articles about the privacy risks of smart glasses, specifically omnipresent surveillance and covert recording. 

The same behaviors that consumers complain about on Reddit are the ones rewarded with engagement on TikTok, where prank, POV, and comedy clips comprise more than a third of the top 1,000 most engaged posts. 

Instead of being the topic of conversation, as they are on Reddit, on TikTok, smart glasses deliver the content, textually indicated with hashtags like #raybanmeta. 

With 71% share of engagement, TikTok was the primary platform where audiences interacted with smart glasses content. In our sample overall, covert prank and POV clips generated about 1.5 times more engagement than the average. 

Creator content is mostly positive, but audience reactions are mixed. 

Ray-Ban Meta’s campaigns with Kylie Jenner in June and Lisa in September drove the year’s biggest smart glasses brand moments, but about a third of posts mentioning them in our sample were negative or mixed. Lisa’s launch mostly drew fan disappointment, while criticism of Kylie's collection fell into three general themes: glamorizing surveillance, hypocrisy around privacy, and questioning the endorsement as a whole. 

Apart from these campaigns, creators had their highest share of posts from May and June, just as public sentiment toward smart glasses appeared to be souring. Most were lifestyle creators filming hobbies, travel and sport, often as paid partners, with 69% of their posts being positive. A minority were critical of the technology, emerging as privacy-first advocates and offering guidance on how to protect yourself from being filmed covertly. 

Our analysis of both the overall conversation and our post samples surfaced these key points:

Everyday consumers are now driving the narrative around smart glasses, not news media or brands. 

Consent is now the primary topical frame for smart glasses. Any related product, launch, or campaign story is now read through that lens.

Covertly filmed content draws both criticism and engagement. Reddit is where consumers take their complaints and TikTok is where audiences interact with smart glasses-created content.

Positive creator coverage hasn’t proven to be a proxy for audience acceptance. Brands should measure campaigns against the broader conversation, especially around concerns about privacy and surveillance. 

For brands connected to smart glasses, consumer privacy, and even standard eyewear, staying ahead of the buzz around smart glasses will be crucial moving into 2027. 

Use social and media intelligence to track sentiment shifts, identify emerging concerns, and understand how audiences respond to new products and campaigns. See how with a tour of the Social Listening capabilities we used to analyze this cultural moment.

FAQ: Smart glasses sentiment, privacy, and consumer conversation

Public sentiment became increasingly negative during 2026. Meltwater Social Listening data shows that positive sentiment outweighed negative sentiment by nearly 4 to 1 early in the year, before criticism peaked in August as consumers played a larger role in the conversation.

What are the main concerns about smart glasses?

Privacy and covert recording are the leading concerns. According to Meltwater Social Listening analysis, privacy and covert recording accounted for 58% of sample posts in August, nearly triple their share in January.

Which platforms drive smart glasses conversation?

Reddit and TikTok drive different parts of the smart glasses conversation. Meltwater Social Listening data shows that Reddit accounted for about 30% of posts and featured criticism of surveillance and covert recording, while TikTok rewarded POV, prank, and comedy content filmed with smart glasses.

Does smart glasses content receive high engagement?

Covertly filmed POV and prank content generates above-average engagement. Meltwater Social Listening analysis of a 2,000-post sample found that these formats received about 1.5 times more engagement than the average post and made up more than one-third of the most-engaged TikTok content.

How are creators affecting smart glasses sentiment?

Creator content about smart glasses is mostly positive, but audience reactions are mixed. Meltwater Social Listening data shows that 69% of creator posts were positive, while reactions to major celebrity campaigns included criticism related to privacy, surveillance, women’s safety, and paid endorsements.

Why should brands monitor smart glasses conversation?

Brands connected to smart glasses and other wearable technology, standard eye wear, AI, and privacy need early visibility into changing public sentiment. Meltwater Social Listening helps teams understand how consumers respond to emerging technology and assess how product launches or creator campaigns are being received.

Nine months of social and media data reveal how smart glasses shifted from a technology story to a broader debate over privacy, consent, and surveillance.

Smart Glasses: What Social and Media Intelligence Reveals About Public Sentiment

Trend detection helps teams identify patterns and shifts in data early enough to investigate what's driving them, how quickly they're moving, and whether they deserve a response.

A sudden spike in mentions will get your attention, but it won't necessarily tell you what to do next. Maybe one creator with a huge following mentioned your brand. Or perhaps a conversation that started on social media has reached journalists and is turning into a broader reputation problem. Trend detection helps you tell the difference.

For marketing and communications teams, cross-channel problems are increasingly common. Stories move between social platforms, news, forums, broadcast, and AI-generated content. Finding the momentum behind the first spike is where trend detection gets interesting.

How can businesses use trend detection algorithms?

What to look for in a trend detection platform

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Smart Glasses: What Social and Media Intelligence Reveals About Public Sentiment

Trend Detection Methods & Algorithms Guide

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