The Top 22 Social Media Monitoring Tools 2026

As generative AI reshapes how people research, learn, and make decisions, a new discipline is emerging: Generative Engine Optimization (GEO). Just as SEO helped brands get discovered on Google, GEO ensures they appear accurately and positively within AI-powered platforms like ChatGPT, Gemini, and Copilot. With millions of consumers now turning to generative engines instead of search engines, GEO is fast becoming essential for marketing and PR professionals looking to influence how their brand shows up in this new discovery layer, where conversations, not clicks, determine visibility.

What is Generative Engine Optimization (GEO)?

Why Should Marketing & Insights Teams Care About GEO?

How Does GEO Work? Key Mechanisms & Signals

What's the Difference Between GEO and SEO?

Increase Your GEO Readiness with Meltwater

Generative Engine Optimization (GEO) is the practice of ensuring that AI platforms such as ChatGPT, Google Gemini, Llama, etc., provide accurate, positive, and up-to-date information about your brand when users ask questions. These platforms are referred to as Generative Engines, Answer Engines, or Large Language Models (LLMs). They are increasingly used by consumers to research purchases and make decisions.

GEO is a way of making sure that AI platforms give people the right information about a company’s brand and products. 

For example, if a person asks ChatGPT: “What is a good family car for camping trips?” then the auto manufacturers would want ChatGPT to suggest their SUV models, and list the benefits. To make sure that happens, the auto brands need to use GEO.

GEO ensures your brand shows up correctly within these AI-generated responses.

The practice of GEO involves several steps, but it is mostly focused on creating, structuring, and publishing content in the best way to influence the responses given by AI Generative Engines. 

In this article we’ll go into the detail of how GEO works, why it’s important, and how you can use it to make sure your brand is featured positively in AI platforms.

Sometimes, generative engine optimization (GEO) is referred to as answer engine optimization (AEO). Learn more about the differences and similarities of GEO and AEO, and take a look at the best AEO tools.

For a long time marketers have been able to rely on the fact that consumers almost exclusively use Google to research buying decisions. So they have been able to use Search Engine Optimization (SEO) to ensure their brand’s website appears in the organic search results, or use paid search advertising to buy ads on relevant search results. 

This is a highly effective way of targeting the right audience at the right time. But now things are changing.

LLMs aren't just another channel. They sit on top of this ecosystem. They synthesize everything into a single conversation.

Allie Konchar, Partner & Chief Client Officer, Omniscient

Changing user behavior: AI + conversational search

Increasingly, consumers are using tools like ChatGPT to research their buying decisions. Data from Meltwater’s 2026 Global Digital Report shows that ChatGPT.com is now the fifth most visited website on the web.

While search engines remain popular, many search queries now produce an AI generated summary that often provide enough information to divert users away from clicking through to websites, because their question has already been answered. McKinsey reports that around half of all Google search queries already produce AI generated summaries, and that number is increasing all the time. 

With conventional web search, consumers are performing research manually, trying to find trustworthy sources and sifting through information to reach the answers they seek. But with Generative Engines, the AI is performing the research automatically, using its existing base knowledge alongside supplemental information pulled from more recent online sources. A search engine shows users where to find answers, while a Generative Engine just gives them the answer. 

For marketers, the key takeaway is that few top-of-funnel consumers are visiting your website, because during the awareness phase their information needs are being met by Generative Engines. This makes it more difficult to move them down into the consideration phase. 

TIP: For more data around growing AI usage and online consumer behavior, download our 2026 Global Digital Report, featuring nearly 700 pages statistics to help inform your GEO strategies next year.

You already know that everybody is talking about AI, and all of your competitors are having the same discussions as you about what it means for their marketing strategy. Those who move decisively to implement GEO, ensuring their brands are represented clearly and positively in Generative Engines, will capture the largest share of those consumers who start their buying journey with an AI query. 

Those who ignore GEO will lose ground, as growing numbers of consumers turn from search engines to Generative Engines, the size of the audiences that can be reached through conventional search marketing will decrease. 

How do generative engines (LLMs) surface content?

It’s important to understand that while Generative Engines are based on similar technology, they all work a little differently. Broadly speaking they all use two different sources of knowledge to provide an answer to a query: 

<table class="table-primary alternate-color">
  <caption>How Generative Engines (LLMs) Surface Content</caption>
  <thead>
    <tr>
      <th>Generative Engine</th>
      <th>Primary Retrieval Method</th>
      <th>Sources Most Often Cited</th>
      <th>Sources Less Likely to Be Cited</th>
      <th>Notes on Behavior</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>ChatGPT</td>
      <td>Bing search + internal training data</td>
      <td>Reuters, AP News, Wikipedia, Encyclopedic sources</td>
      <td>Social media platforms (X/Twitter, Instagram)</td>
      <td>Prefers authoritative, neutral, structured sources with high trust signals.</td>
    </tr>
    <tr>
      <td>Google Gemini</td>
      <td>Google Search + YouTube + Knowledge Graph</td>
      <td>Reddit, YouTube, Google-indexed blogs</td>
      <td>X/Twitter</td>
      <td>Strongly favors user-generated content, community threads, and Google-owned properties.</td>
    </tr>
    <tr>
      <td>Perplexity</td>
      <td>Real-time web crawling + citation-first retrieval</td>
      <td>News publishers, reputable blogs, research papers</td>
      <td>Low-trust UGC</td>
      <td>Most transparent engine — always cites sources and updates in real time.</td>
    </tr>
    <tr>
      <td>Claude</td>
      <td>Internal training data + selected retrieval</td>
      <td>Academic sources, reputable news, long-form articles</td>
      <td>Short-form social media</td>
      <td>Prefers long-form text and well-structured explanatory content.</td>
    </tr>
  </tbody>
</table>

Training Data: All LLMs begin by being trained on a huge volume of existing content and data — we’re talking about dozens of terabytes (a terabyte is 1,000Gb). This training data comes from a wide variety of sources (including your website), and gives the LLM its base knowledge about the world. The LLM does not have any knowledge of anything that happened after its initial training. 

Live Web Search: To overcome the knowledge cut-off problem, the training data is supplemented with fresh information gathered from the internet. If the Generative Engine thinks that a user’s query would benefit from more up to date information than it already has, it fetches new content from trusted online sources and works that into its response. Google uses its own search engine to find fresh information, while ChatGPT uses various sources, including Microsoft Bing.

It’s also important to note that AI does not quote any of this content verbatim in its responses. Much like a human, it uses the information it has learned to inform its own answer, and that can include information from various sources, including the press, competitors, consumer reviews. So don’t expect it to always be on-message!

Another key point is that unlike a search engine, an LLM does not have an index of content which it searches to find answers. It would be impossible to search ChatGPT for all mentions of your brand — that’s simply not how it works. 

An LLM is more similar to a human brain, in that it has a lot of knowledge stored in patterns and relationships between words and concepts. It is extremely difficult, verging on impossible, to examine and understand the detail of an LLM’s learned knowledge because of the sheer scale and complexity; this is a challenge referred to as Black Box AI. 

But we do understand how Generative Engines work at a high level, and we can analyze the kind of responses they produce for relevant queries, which gives us insight into how we should optimize our content for increased visibility.

What content features improve GEO-visibility?

Bear in mind that when you’re optimizing content for Generative Engines, the goal is to write copy that is easier for AI to digest and incorporate into its responses.

Clarity: Avoid overly elaborate language. Do not use corporate-jargon. Keep it simple, professional, and to the point. Leave no room for ambiguity. 

Authority: Wherever possible back up your statements with data from reputable sources, quotes from experts or industry leaders, and reference-able proof points. 

Structure: Organize your pages well with clear titles, headings, and subheadings. Use heading tags (H1, H2, etc) correctly to specify the hierarchy of your content. 

Recency: AI platforms look for more recent information from trusted sources to supplement their base knowledge, so in both owned and earned media, aim to publish fresh content recently.

In many respects GEO shares principles with good SEO practice. If you write consistently high quality content which addresses the needs of your target audience, and structure it correctly on well designed, standards compliant web pages, you will succeed.

First you need to understand your starting point. Meltwater’s GenAI Lens is a tool that gives brands insight into how they are discussed by all major Generative Engines, including ChatGPT, Claude, Gemini, Perplexity, Grok, and Deepseek. 

With GenAI Lens you’ll be able to understand how your brand is already featured in LLMs, what source websites are used in those responses, and whether outdated or inaccurate information is being used. 

We know that LLMs pull content from the web, which they use to inform their responses. So whatever is said about your brand online will significantly affect how Generative Engines talk about your company. 

Start with your own website, this is the first place LLMs will look for information about your organization. But also focus on trusted, high authority third party sites like the mainstream news and specialist media within your industry, because these are the kinds of sources that LLMs will use. GenAI Lens can show you which websites the leading LLMS use to source information about your brand. 

Once you have a comprehensive audit of how your brand is currently portrayed online, you can perform a gap analysis against your desired messaging, and build a plan for how to reach that objective.

Tip: AI brand monitoring, AI media monitoring, and LLM monitoring will help you understand your online footprint. Learn how to track your LLM visibility and how to track LLM brand mentions.

An important difference between GEO and SEO is understanding how people search differently when using Generative Engines. Users interact conversationally with AI, and are likely to ask more complex questions in natural language, compared to simple keywords or short queries in a search engine. So it’s useful to get an idea of what kind of questions people will ask about your brand or industry, to help plan your GEO content.

Tip: Learn more about AI visibility for retail brands.

Unlike search engines, at present the leading Generative Engines do not share data on popular user queries, so it’s not easy to find out exactly what people are asking about your business. But you can look at popular keyword searches associated with your brand, and brainstorm the most likely questions people will ask Generative Engines. 

You can also use a social listening platform, like Meltwater Explore+ to analyze social media conversations around your brand and industry, to gain insight into common questions. Once you have mapped out all of the most likely questions people might ask, you can start creating content that answers those questions.

Tip: Learn how to connect social listening with generative engine optimization. 

Conventional SEO was built around search queries but GEO requires thinking in concepts, context, and authority — you need to focus on the intent of the query, rather than simply trying to match keywords. 

LLMs prioritize sources that provide comprehensive, well-structured, and contextually rich content. Focus your content strategy on:

Educational depth: Long-form resources that answer questions end-to-end. Publish explainers, FAQs, and data-backed insights that answer “how” and “why.”

Credibility signals: Citations, quotes, and data from reputable sources (analyst studies, thought leadership, or trusted media).

Rich media: Generative Engines pull information from videos and images as well as text content, so make use of varied content formats. 

Consistency across channels: LLMs learn from media, social, and owned content together; ensure your narratives are aligned across them.

The key thing is to ensure that your content is genuinely helpful in answering those questions you mapped out. If your content is too focused on sales messages, it’s less likely to be used by the LLMs.

TIP: Discover innovative AI-generated content examples to enhance your digital strategy.

You can optimize the content published on your website and owned channels, but LLMs also source information from trusted third party websites. That means PR has a key role to play in ensuring your brand is featured in high authority earned media, including news features, expert comment from your spokespeople, product reviews, and any other kind of brand story traditionally generated through a media relations campaign.

Tip: Learn more about the importance of earned media for GEO and about PR Pitch GEO optimization.

The tricky part is that unlike advertising, which can tell exciting and attention grabbing stories, PR professionals are limited to working only with the facts. But while you cannot always control the outcome of media outreach activity, ensuring that PR and GEO are aligned will help increase the volume of third party sources that feature the right messaging.

Tip: Learn how GEO is reshaping PR strategies.

Meltwater’s GenAI Lens gives you the ability to track your GEO performance over time, so you can understand whether your strategy is working well and spot areas where you need to improve. The tool provides visualizations that show brand sentiment, emotion, key phrases, people, products and things mentioned, alongside citations.

Armed with this information you can identify gaps in your GEO strategy where you might need to create more or better content. You can also discover which third party sources have the greatest impact on your GEO performance, and use that information to optimize PR outreach to focus on the most important media. 

Like SEO, this is a process of constant iteration and improvement. GEO should not be seen as a one-off project that will generate positive results in perpetuity, but rather an ongoing activity that needs to be integrated with the broader marketing mix.

Tip: Learn How to Measure PR Performance Across LLMs and Generative Search, and understand how to report on LLM visibility.

Which Media Sources to Prioritize for GEO

When an LLM processes a user query, it can often detect that the response might require more recent information than it has access to in its original training data. In that situation it will look online for more up to date content that will help it to form a more accurate answer, but where exactly do Generative Engines look for this information?

At Meltwater we used GenAI Lens to research which content sources the leading AI platforms were most likely to reference in their responses, and there were distinct differences between them all:

Open AI ChatGPT: Heavily favors text-based news and newswires (Reuters, AP, PR Newswire) and reference sites (Wikipedia). Much less likely to cite social media and UGC. 

Google Gemini: Leans towards high quality UGC from sites like Reddit and YouTube, as well as other online sources within the Google ecosystem. Does not index X/Twitter content. 

Google Search AI Overviews: Highly focused on UGC from Reddit and YouTube, as well as Facebook, Yahoo and LinkedIn. 

xAI Grok: Strongly skewed towards conversational UGC from X and Reddit. Less likely to cite traditional reference sources like Wikipedia, YouTube or academic sites. 

Unlike SEO, where most practitioners were happy to optimize only for Google, in GEO we have to consider the nuances of several different platforms; at the very least ChatGPT and Google AI Overviews. In short, it’s good practice to ensure you have up to date content propagated across a wide range of platforms where LLMs might look for supplemental information.  

In terms of which online sources are most likely to be referenced overall, we looked at several categories and charted the most frequently cited websites:

<ul class="medium">
	<li><b>Social Media & UGC</b></li>
    <ul>
		<li>reddit.com: 43.1%</li>
		<li>youtube.com: 17.9%</li>
        <li>facebook.com: 11.1%</li>
		<li>linkedin.com: 9.2%</li>
        <li>quora.com: 5.6%</li>
	</ul>
	<li><b>Consumer Reviews</b></li>
	<ul>
		<li>glassdoor.com: 21.6%</li>
		<li>indeed.com: 20.6%</li>
        <li>trustpilot.com: 15.7%</li>
		<li>bbb.org: 9.9%</li>
        <li>yelp.com: 8.0%</li>
	</ul>
	<li><b>Travel</b></li>
    <ul>
		<li>tripadvisor.com: 83.2%</li>
		<li>expedia.com: 10.0%</li>
        <li>booking.com: 6.8%</li>
	</ul>
	<li><b>News & Media</b></li>	
    <ul>
		<li>yahoo.com: 26.5%</li>
		<li>prnewswire.com: 10.8%</li>
        <li>reuters.com: 9.0%</li>
		<li>forbes.com: 6.7%</li>
        <li>usnews.com: 6.7%</li>
	</ul>
    <li><b>Academic & Science</b></li>	
    <ul>
		<li>nih.gov: 53.6%</li>
		<li>researchgate.net: 14.5%</li>
        <li>sciencedirect.com: 10.0%</li>
		<li>jhu.edu: 7.5%</li>
        <li>cdc.gov: 5.8%</li>
	</ul>
    <li><b>Market Research & Consulting</b></li>	
    <ul>
		<li>statista.com: 18.8%</li>
		<li>mordorintelligence.com: 16.3%</li>
        <li>gartner.com: 14.9%</li>
		<li>mckinsey.com: 13.5%</li>
        <li>cbinsights.com: 13.0%</li>
	</ul>
    <li><b>Business & Financial</b></li>	
    <ul>
		<li>investing.com: 14.1%</li>
		<li>morningstar.com: 13.2%</li>
        <li>nasdaq.com: 11.4%</li>
		<li>nerdwallet.com: 10.4%</li>
        <li>seekingalpha.com: 8.8%</li>
	</ul>
    <li><b>Government & Public Sector</b></li>	
    <ul>
		<li>weforum.org: 20.6%</li>
		<li>europa.eu: 17.8%</li>
        <li>canada.ca: 12.7%</li>
		<li>imf.org: 11.5%</li>
        <li>sec.gov: 10.1%</li>
	</ul>
</ul>

Many teams focus on keywords, backlinks, and meta tags, but LLMs prioritize context, authority, and relevance. GEO requires content that answers full questions with clear, verifiable information, not keyword stuffing or link chasing.

2. Ignoring source credibility and transparency

AI models reward trustworthy, well-cited content. Publishing unverified claims, outdated statistics, or missing citations can lower visibility or lead to inaccurate AI summaries of your brand. Always include reputable data sources, authorship, and dates.

3. Failing to monitor how your brand appears in LLMs

Without ongoing media monitoring, brands miss when GenAI models misrepresent their products or replicate misinformation. LLM tracking tools like Meltwater’s GenAI Lens can surface these blind spots and help correct or update narratives quickly.

What is Generative Engine Optimization (GEO)? & How to Do It

Twitter (now X) continues to be a mouthpiece for businesses and brands. Its rapid-fire, no-holds-barred reputation allows its users to share anything and everything — and they don’t hold back. If you’re using Twitter social listening, you can capture the fine details of what people are saying on Twitter and use it to your advantage.

Social listening on Twitter gives you a front row seat to every conversation you care about. People post just about anything here, like real-time updates, opinions, breaking news, and other trending topics. Having these conversations all in one place makes it easy to keep your ear to the ground, especially if people are talking about your business.

Here’s how you can use Twitter’s real-time advantage to stay ahead of the curve.

Why Does X / Twitter Social Listening Matter?

What Are the Top Tools for X / Twitter Social Listening?

What Are the Best Strategies for Effective X / Twitter Social Listening?

How Can Meltwater Support Your X / Twitter Social Listening Strategy?

Twitter social listening lets you monitor millions of conversations in real time on Twitter. Using social listening and analytics tools, you can set up searches for keywords, brand names, or phrases you care about, then get alerts whenever someone posts about those topics.

Twitter listening is one piece of the much bigger social listening puzzle. It’s specific to the Twitter platform, giving you insights into what Twitter users are discussing.

Since Twitter has a highly engaged user base, it’s worthwhile to see what’s trending here. You’ll need to tailor your social listening strategy to the platform’s format and audience to get the best read on conversations.

TIP: Download our free Definitive Guide to Social Listening for a deep-dive on the many benefits and use-cases of social listening solutions!

Information moves faster than ever. A single post has the power to shape opinions and spark emotions and new ideas. If your business isn’t actively listening, you’re not just losing out on conversations — you’re missing signals that could define your next big opportunity or warn of an impending crisis.

X / Twitter ranks in the top 5 social media platforms globally (Statista, 2025). While some marketers are shifting time away from X, its role in brand discovery remains significant. X (formerly Twitter) currently has a potential advertising reach of 557 million users, and 38.1% of active users on the platform use it specifically to follow or research brands and products (Meltwater, 2026).

Adding social listening on Twitter to your social media marketing can give you an advantage in this world of instant knowledge. 

People feel comfortable sharing their real thoughts on social media platforms, especially Twitter. It contains a variety of thoughts and views (sometimes heated and controversial), brand mentions, humor, and influencer content. 

Tapping into Twitter conversations can give you a fuller perspective of who your customers are and what makes them tick. You’ll gain raw and real expressions from your audience, even if their posts have nothing to do with your brand.

These honest posts can help you pinpoint your customers’ frustrations, desires, and needs, allowing you to adjust your products and positioning to meet their needs.

TIP: Check out our blog on the top Customer Intelligence platforms and tools to help you learn more about your audience and their unique needs.

If people were talking about your brand (and potentially spreading misinformation or negativity), you’d want to know about it. With Twitter being a place where users keep nothing sacred, it’s the prime place to air their feelings or vent frustrations. 

Your brand might end up in their crosshairs, and Twitter listening can reveal when a comment or mention might hurt your reputation. 

You can also use Twitter social listening to monitor your industry as a whole. For example, supplement companies might be impacted by new research studies on specific ingredients they use. Monitoring for these mentions can help them stay ahead of potential shifts in sentiment.

TIP: Don't miss our blog on the top brand monitoring tools to help you safeguard public sentiment towards your organization!

Social listening tools let you monitor your competitors as well as your own brand. Learn why other people are praising or complaining about competitors. You can use this knowledge to improve your own products or services, find where customers aren’t being properly served, and position yourself accordingly.

You might also get inspired by your competitors’ content. Track what they post and pay attention to how their customers respond to it (e.g., retweets, comments). This can give you an idea of what your audience might find appealing so you can create content that resonates with them.

The data that Meltwater allows us to access is valuable to our research and deciding what stories we want to take on. It is integral to our objectives as a business and as Andariya.

Social Listening Goals, Keywords, and Metrics

<table class="table-primary">
<thead>
<tr>
<th>Listening Goal</th>
<th>Keywords to Track</th>
<th>Metrics to Measure</th>
</tr>
</thead>
<tbody>
<tr>
<td><strong>Brand Reputation Management</strong></td>
<td>Brand name, product names, executive names, branded hashtags</td>
<td>Sentiment trends, volume of mentions, negative mention spikes</td>
</tr>
<tr>
<td><strong>Competitor Intelligence</strong></td>
<td>Competitor brand names, competitor product names, competitor campaigns</td>
<td>Share of voice, competitor sentiment, engagement on competitor content</td>
</tr>
<tr>
<td><strong>Customer Understanding</strong></td>
<td>Industry pain points, product category terms, questions your audience asks</td>
<td>Recurring themes, sentiment by topic, frequently mentioned frustrations</td>
</tr>
<tr>
<td><strong>Trend Spotting</strong></td>
<td>Industry keywords, trending hashtags, emerging topic terms</td>
<td>Mention velocity, trending keyword volume, content engagement rates</td>
</tr>
<tr>
<td><strong>Crisis Detection</strong></td>
<td>Brand name, negative sentiment terms, complaint language</td>
<td>Spike in mention volume, sentiment shift, rate of content spread</td>
</tr>
<tr>
<td><strong>Content Strategy</strong></td>
<td>Topics your audience discusses, hashtags in your niche, influencer content themes</td>
<td>Engagement rates on tracked topics, most shared content formats, peak posting times</td>
</tr>
</tbody>
</table>

Twitter social listening tools lets you automatically “listen” to conversations on Twitter without having to scroll through countless feeds. You can set up your social listening tools to look for specific keywords or phrases, then get alerts and reports when users post new content. 

Here are five of the best social listening Twitter tools and how they can support your strategy.

Meltwater offers the most comprehensive social listening technology. Meltwater’s AI-powered insights now process over 1.3 billion social media posts, including tweets, news articles, and blog posts every single day, ensuring your brand never misses a mention in the massive volume of global conversation (Meltwater, 2026).

More important than seeing mentions is knowing what they mean. Meltwater uses consumer sentiment analysis and natural language processing to understand the context behind Twitter posts. This allows companies to know how to respond and engage authentically, which aligns with one of Twitter’s key strengths.

See Meltwater's AI-powered social listening and analytics solution in action! Click here and fill out the form below to request a personalized demo.

Radarr by Genesys includes social listening as part of its brand management platform. Users can connect their social accounts, set up keywords, and start getting insights in a single feed. Radarr covers the most popular social media platforms, including Twitter, so you can get a better idea of your share of voice across channels.

The platform combines analysis, engagement, and content posting to help marketers simplify their work. You can get deeper insights into your owned media, respond to comments and DMs, and even plan and publish new content to your channels. 

Sprout Social offers a user-friendly interface to set up topic tracking. You don’t need experience with social listening or Boolean queries to start collecting insights. Users can keep tabs on everything from post engagement to customer feedback and sentiments from within the same tool. 

Sprout Social will provide alerts when someone mentions your keyword or when there’s a spike in mentions, which might indicate a brewing crisis or trend. It’s also a highly visual tool, allowing you to make sense of your data in different ways. For example, you can generate word clouds to spot your most popular keywords or mentions at a glance.

Tip: Take a look at other Sprout Social alternatives.

Keyhole by Muck Rack is a social media analytics tool that includes social listening as a feature. Like other social listening tools, Keyhole lets you select keywords and brand mentions to monitor across your channels. You can spot what’s trending, keep an eye on competitors, and learn more about the topics your audience cares about.

Keyhole also includes audience and sentiment analysis. Knowing the context behind mentions is key in crafting an appropriate response. Compared to other social listening tools, this one is a bit limited in terms of the networks it monitors. It currently supports Twitter, Instagram, TikTok, Facebook, and YouTube, along with non-social media like blogs and forums.

BuzzSumo specializes in trending topic investigation. It excels in helping you develop content based on what’s already popular. You can tap into people’s conversations to know what to post and when to share it with your audience.

BuzzSumo isn’t specific to Twitter, but it does capture content and insights from the platform and other social networks. You can see what others are posting or saying about competitors, relevant products, or other trends and see how those mentions evolve over time. It’s also a handy tool for finding journalists or influencers in your niche who can help to amplify your voice.

It’s not just about the social listening tool you use, but also how you use it to get results. Twitter social listening tools often come with a learning curve and multiple ways you can use them.

Here are some helpful hints to get you started.

Twitter social listening can help you accomplish many things: monitoring competitors, improving brand reputation, shaping your content strategy, and finding new trends, for example. The key is to know what you’re looking for so you can spot those insights right away and act on them.

Be specific about what you want to accomplish with Twitter listening. This will help you track the right keywords and use the data you collect. 

Use advanced filters to focus on relevant conversations

When you set up keywords to track on Twitter, you might get a tsunami of data telling you more than you need to know. Learn how to use your Twitter listening tool’s filter options so you can skip right to the important stuff.

For example, Meltwater lets you filter your data in different ways. Plus, you can get spelled-out insights to know what the data means. It’s like reading a report with the juiciest info upfront instead of relying on graphs and numbers alone.

Engage with users strategically and authentically

When the opportunity arises, be prepared to respond to comments and brand mentions. Engaging directly with your audience shows you’re paying attention, plus it helps clarify questions or comments.

Pay close attention to feedback or negative opinions. These can be opportunities to set the record straight and reposition your brand in a positive light.

For social listening, Meltwater provides a comprehensive solution in a single platform. Gain insights into your Twitter performance and monitor mentions that matter to your brand. You’ll get alerts when someone posts content about the keywords you’re tracking, along with insights on why those posts might be worth a look.

The Ultimate Guide to X / Twitter Social Listening

Businesses don’t need to solicit reviews and survey answers to learn more about their customers. The goldmine of insight they’re searching for is on social media, where consumers unleash their most unfiltered opinions and ideas. According to Meltwater's Global State of Social Media Report, 87% of marketers cite monitoring brand reputation as their top priority for social listening (2026).

This is especially true for fashion consumers and Twitter. That’s why Twitter and Meltwater teamed up to analyze millions of fashion community Tweets and learn more about evolving consumer attitudes and rising trends. Some of the questions we wanted to answer were:

What subtopics are most prevalent in the global fashion conversation?

What macro and micro fashion trends are emerging?

Who are the Twitter authors leading those conversations? 

What opportunities exist for fashion brands?

We gained insights into these topics and more using Explore, our social listening platform, in conjunction with other Meltwater solutions. Beginning with more than a dozen complex Boolean queries created by the insights services team at Linkfluence, a Meltwater offering, we narrowed our searches down to English-language Tweets posted between March 2021 and February 2022. 

The team identified the macrotrends and microtrends taking over fashion Twitter conversations by comparing the volume of Tweets about specific fashion subjects published in the first six months to those published in the second six months. Our resulting report, The Fashion Industry’s New Era, offers insight into the fashion industry, but its main question — what do consumers want — is universal. “The insights shared within the report provide fashion marketers and advertisers with a solid foundation they can use to build out their future marketing strategies," says Lauren Jenkins, Head of the Twitter Official Partner Program. Here’s a closer look at how we did it.

To create innovative and impactful marketing strategies, you must have a comprehensive understanding of your target audience. 'The Fashion Industry's New Era,' developed in partnership with Meltwater, taps into the hundreds of millions of conversations Twitter users had around fashion the past year to identify meaningful insights and emerging trends within the industry. 

Lauren Jenkins, Head of the Twitter Official Partner Program

How can social listening be used for market research?

How can keyword searches and trendspotting uncover insights?

How do you identify conversation leaders?

How can social listening power sales and consumer insights?

The Fashion Industry's New Era is the forward-thinking marketer's guide to the fashion industry. Read on to learn more about how we created the report and used social listening for market research. But first, here's a brief look at our methodology:

<div style="background-color: #c4f4f4; padding: 20px;">
• <b>310,548,010</b> English-language fashion community Tweets posted between March 2021 and February 2022<br><br>
• <b>8.7%</b> growth in the global fashion conversation in that time<br><br>
• <b>5</b> macrotrends and <b>10</b> microtrends identified </div>

The Fashion Industry's New Era was created using Twitter data sourced through Explore, our social listening platform. We also used two of Meltwater's consumer insights offerings: Linkfluence and Audiense.

The Fashion Industry's New Era is based on data sourced from Boolean queries, conducted on Explore, of English-language Tweets published between March 1, 2021 and February 28, 2022.

The macrotrends and microtrends discussed in the report were discovered via an analysis of mentions volume via Explore, the Twitter explore feature, additional desk research, as well as other fashion-related studies currently underway at Linkfluence. We compared keyword mention volume evolutions between the first half and second half of the 12 months measured (i.e. 3/21 to 8/21 compared to 9/21 to 2/22).	

Our analysis led us to a number of rising fashion trends, including meta fashion and inclusive fashion. See the full list of trends by downloading the report.

<table class="table-primary"> 
<thead>
<tr>
<th>Technique</th>
<th>What it involves</th>
<th>Insight gained</th>
</tr>
</thead>
<tbody>
<tr>
<td><strong>Keyword Searches</strong></td>
<td>Using Boolean queries to capture relevant fashion conversations at scale</td>
<td>Built a large, relevant dataset of social media discussions</td>
</tr>
<tr>
<td><strong>Trendspotting</strong></td>
<td>Monitoring changes in conversation volume and patterns over time</td>
<td>Identified emerging trends and spikes in interest</td>
</tr>
<tr>
<td><strong>Conversation Analysis</strong></td>
<td>Grouping discussions into themes and recurring topics</td>
<td>Revealed key topics and consumer interests</td>
</tr>
<tr>
<td><strong>Influencer Identification</strong></td>
<td>Tracking high-engagement accounts and frequently mentioned voices</td>
<td>Highlighted key influencers shaping conversations</td>
</tr>
<tr>
<td><strong>Data Refinement</strong></td>
<td>Iteratively improving queries to remove irrelevant data</td>
<td>Increased accuracy and relevance of insights</td>
</tr>
<tr>
<td><strong>Insight Synthesis</strong></td>
<td>Combining trends, themes, and influencer data into findings</td>
<td>Generated actionable insights for strategy and reporting</td>
</tr>
</tbody>
</table>

With keyword searches in place, we at Meltwater dug into the data using Explore’s analytic charts. Keyword clouds and bar graphs of the top hashtags revealed the most-talked-about subjects and entities for each trend, showing us where we needed to dig further.

Keyword searches and mention tracking are straightforward ways marketers can use social listening to tap into consumer conversations and industry trends. Social listening doesn’t just tell you who’s in on conversations about your brand and market, it also shows you the topics catching their attention. From there, top social listening platforms surface the words and phrases showing up most often in their social media posts, reposts, and comments. 

At times, the same keywords popping up across different conversation topics can point you to commonalities and trends across audiences, helping you find and define the different communities and personas that make up your general audience. For example, the phrase “out this listing” popped up in keyword clouds across multiple queries. They pointed us to valuable Twitter conversations about fashion resale where users were encouraging people to check out their listings. 

While manually combing through individual social media posts might slowly clue you into current hot topics, social listening provides a bird’s-eye view that lets you tap into rising trends without much lift.

While making The Fashion Industry’s New Era, we sought to understand the people and entities driving conversations around emerging fashion trends. Using Explore’s analytic dashboard widgets, we looked at the most retweeted Tweets, the most-followed Tweet authors, shares of voice by keyword mentions, and the top professions of Tweet authors in each conversation. High-level insights like these revealed the different communities driving fashion conversations on Twitter, as well as the influencers those different groups trust for recommendations, commentary, and inspiration. 

We also used the platform’s timeline visualizations to pinpoint conversation spikes. Because they are dynamic, we were able to click on specific data points to see more in-depth analytics for specific days and times. That’s how we learned more about how the inclusive fashion communities rally around Twitter authors and Tweets that highlight plus-size, modest, non-Western, and accessible fashion.

Combined with geographic and topic filters and narrowed-down search terms, social listening saves essential time when it comes to scouting ideal marketing partners and influencers. By letting data — sourced directly from your audience — drive partnerships and collaborations, marketers can increase overall engagement and better align with company goals.

Social listening plays a key role in understanding the customer journey. 50.4% of internet users research brands online before purchasing, meaning brand perception is increasingly shaped by what people see and say online (Meltwater, 2026). Social listening takes the mystery out of website traffic and sales surges. Spikes in relevant keywords and conversations that match up with sales rises and dips offer valuable context that just may reveal untapped marketing opportunities. This goes double for marketers analyzing their own brands and competitive ones. The data insights social listening reveals help marketing professionals invest in and maximize ROI-generating projects and programs. 

Outside of insights on sales trends, social listening extracts invaluable data for consumer insights research and compatible tools. Social media users tell the world about themselves in two places: their published posts and their profile bios; social listening picks up information from each area. Done manually, researching social media users’ bios is a time-consuming, data analysis nightmare. However, social listening platforms that are part of all-in-one suites eliminate the legwork. 

We used our social listening platform, Explore, in conjunction with our consumer insights platform to learn more about the audiences of five macrotrends. The compatible platforms use easy-to-use download and upload functions to simplify the process of transferring data from tool to tool. Along with giving us a closer look at their online habits and most-followed influencers, Audiense (powered by IBM Watson) generated a deep dive on each community’s personality traits and purchase influence factors. For example, we learned that meta fashion enthusiasts are more likely to be influenced by a product’s utility than the general public when it comes to purchasing decisions. 

Social listening doesn’t just provide visibility; it drives performance. Companies that effectively leverage customer data outperform competitors by up to 85% in sales growth, highlighting the value of turning social insights into actionable strategy (Forbes, 2025).

Combined, the benefits of social listening point marketers to new opportunities and stronger ways of connecting with consumers. Unfortunately, many businesses don’t have the time, tools, or resources to get started. Especially for global brands, there aren’t enough hours in the day to manually keep up with, contextualize, and draw insights from every social media mention of your name — let alone those of your competitors. This is where time- and money-saving platform features, like Explore’s unlimited keyword searches and dynamic data visualizations, take marketers the extra mile.

Despite the widely recognized value of data, 50% of business decisions are currently being made without consumer insights (GWI AI White Paper, 2025). This "execution gap" highlights a massive opportunity for brands that successfully embed social listening into their daily workflows. We used the power of social listening to analyze fashion, but the methods and tools we used are invaluable across industries. Download The Fashion Industry’s New Era for our full findings, methodologies, and more than a dozen new insights for marketers. 

Complete the form below to schedule a demo or take a self-guided Social Listening product tour to see how you can uncover trends, track conversations, and turn data into insights in minutes. Explore the platform at your own pace and discover how to make smarter, data-driven decisions.

FAQs about Using Social Listening for Market Research

How do you start a social listening project for market research?

It usually begins with defining what you want to learn, then building keyword queries around your industry, products, and trends. From there, you collect a large dataset of conversations and refine it over time to ensure relevance and quality.

How do you avoid irrelevant data when analyzing social conversations?

Noise is one of the biggest challenges in social listening. The key is continuously refining your Boolean queries by adding exclusions, testing variations, and narrowing your scope so you’re left with conversations that truly reflect your audience and topic.

How do you spot meaningful trends in large volumes of social data?

It’s less about total volume and more about movement over time. By tracking spikes, shifts, and recurring themes in conversations, you can identify trends as they emerge rather than after they’ve already peaked.

How can you tell which voices actually matter in a conversation?

Not all mentions carry the same weight, so it’s important to look at engagement, true reach, and consistency. Identifying the accounts that repeatedly drive conversation helps you understand who is shaping opinions in your space.

How do you turn social data into something your team can actually use?

The real value comes from synthesizing the data into clear themes and insights. This often means grouping conversations, identifying patterns, and translating findings into simple takeaways that marketing, product, or strategy teams can act on.

Can social listening really connect to business outcomes like sales?

Yes. When you compare conversation trends with real-world performance, useful patterns can emerge. For example, increased discussion around certain topics or products can often align with shifts in consumer demand or interest.

How quickly can you get insights from social listening?

Unlike traditional research, you don’t have to wait weeks for results. One of the biggest advantages of social listening for research is speed. Once your queries are set up, you can start seeing patterns and insights almost immediately, making it much faster than traditional research methods like surveys or focus groups.

Schedule a demo today to learn more about what Meltwater solutions can do for you:

Using Social Listening for Market Research: How We Made 'The Fashion Industry's New Era'

We get it! You're busy scheduling content and engaging with your followers, so it can be difficult to make time to sit down and read about the latest Facebook algorithm update or how brands are leveraging TikTok. But, hey, it's also important to carve out time to learn about new ways to improve your social media strategy. So, put down your phone (we know: it's a big ask!) and indulge in reading about recent social media updates. 

Top Social Media and PR News Stories This Week

If you work in social media marketing, these are the stories you need to read this week!

LinkedIn Experiments With AI-powered Candidate Screening

New Reddit Report Highlights B2B Marketing Opportunities

New Snapchat Reports Showcase How the App Influences Consumer Behavior

You heard right. Instagram is in the early stages of testing the option for certain users to add a link to post captions. From Instagram: “The ability to add links in Instagram posts is one of the top requested features from our subscriber community. We’re excited to test what new value this benefit brings.”

AI could soon be helping recruiters screen more candidates for positions. LinkedIn is reportedly testing an AI interview option for Hiring Pro users which screens applicants based on AI recommended questions and answers.  

A new Reddit report, in partnership with Survey Monkey, is aimed at B2B marketers and showcases ways that the platform can help develop leads for B2B services. Included in the report how various communities are leveraged to answer questions, types of content that influence decisions, and much more. 

Two recent Snapchat reports highlight the power of the platform in influencing consumer behavior and purchase decisions. The first details how creators steer users toward certain streaming services through ads for new shows while the second looks specifically at how social drives telco purchases.

Thumbnail Editing Now Available on Instagram

X/Twitter Blog

The Ultimate Guide to X / Twitter Social Listening

Using Social Listening for Market Research: How We Made 'The Fashion Industry's New Era'

Social Media News: The 5 Biggest Stories of the Week

Influencer Marketing Costs 2025: Influencer Rates per Channel

Twitter Management for Beginners

Guide to Posting Videos on Twitter

How to Find Twitter Influencers to Grow Your Brand

The Barney Stinson’s Playbook for Cold Tweeting Influencers

Best Times to Post on Social Media in 2024 [Infographic]

What Is Meta Threads and How Can You Use It for Your Business?

What Are the Most Used Social Media Platforms in the Philippines 2025?

X: What Are Twitter Impressions & Reach?

X/Twitter Blog

The Ultimate Guide to X / Twitter Social Listening

Using Social Listening for Market Research: How We Made 'The Fashion Industry's New Era'

Social Media News: The 5 Biggest Stories of the Week

Influencer Marketing Costs 2025: Influencer Rates per Channel

Twitter Management for Beginners

Guide to Posting Videos on Twitter

How to Find Twitter Influencers to Grow Your Brand

The Barney Stinson’s Playbook for Cold Tweeting Influencers

Best Times to Post on Social Media in 2024 [Infographic]

What Is Meta Threads and How Can You Use It for Your Business?

What Are the Most Used Social Media Platforms in the Philippines 2025?

X: What Are Twitter Impressions & Reach?

Interested in learning how Meltwater can help you? Fill out the form to learn more.