The Top 15 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

How can you get started with GEO? Test your GEO readiness

Which media sources to prioritize for GEO

What's the difference between GEO and SEO?

8 essentials of generative engine optimization

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, which can lead to zero-click searches, and that number keeps rising. 

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.

If you’re not optimizing for generative engines, you just might never reach your audience at all.

Kelly McKenna, Regional Director, Account Management at Meltwater

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.

Tip: Learn more about the citation layer.

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.

Reading tip: Learn how a website rebuild drove a 73% citation increase.

Test your GEO readiness: a 2-minute self-assessment.

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 brand 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 digital 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, understand how to report on LLM visibility, and take a look at executive report for AI search.

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:

GEO helps your brand to appear in AI platforms — but how does it work? This guide has everything you need to know to get started with GEO.

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

There is no shortage of brand content competing for attention on social media. So what is it that makes a social media campaign break through? Strategies that give audiences something more to do than simply watch tend to cut through the noise.

The top social media campaigns of 2026 show just how many forms that participation can take. Audiences are inspired to vote, build, remix, share, compare, or create — contributing to brand success and engagement on social.

We used Meltwater social listening data (2026 YTD) to look beyond the campaign concepts themselves and more deeply examine the conversations they encouraged.

What to look for in a social listening platform for campaign tracking

A social media campaign is a coordinated series of posts and activities on social platforms, usually run over a defined period to achieve a specific measurable outcome.

It often sits within a broader marketing campaign or social media marketing strategy, but the driving force behind it should account for how your audience actually behaves on social. A TikTok challenge, for example, asks something different of its audience than a LinkedIn thought-leadership campaign or an X conversation tied to a live sporting event.

Simply distributing the same creative across every platform is typically ineffective for getting meaningful results and participation in your campaign

All social media campaigns should start with a clear goal. A brand might want to build awareness, support a product launch, generate user-generated content, reach a new audience, or change how people think about an existing product.

That goal then shapes the creative idea and the action you want the audience to take. That could mean sharing their own version of a piece of content, using a campaign hashtag, demonstrating a product, entering a competition, or posting something personal that inspires other people to compare their own experience. From there, social marketers decide which platforms are best suited to the campaign, what formats to use, and where and when to post.

Measurement and KPIs should be part of this planning stage, not something added once the campaign ends. Social listening can show how conversation changes as a campaign unfolds, which content drives engagement, whether audiences are adopting the intended message, and where unexpected themes or trends are emerging. That context is often more useful than a final engagement total on its own.

What counts as a successful social campaign depends on the goal, so this list is intentionally varied. Some campaigns generated enormous conversation volumes. Others created disproportionate engagement or reach from relatively small communities. The common thread is a social call to action people actually want to participate in and engage with.

<table class="table-primary alternate-color">
  <thead>
    <tr>
      <th>Brand</th>
      <th>Platform</th>
      <th>Campaign hook</th>
      <th>Why it worked</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>Pepsi</td>
      <td>X + cross-platform</td>
      <td>Turn a Super Bowl rivalry into a taste challenge</td>
      <td>Combined memorable creative with an immediate participation mechanic</td>
    </tr>
    <tr>
      <td>Cisco</td>
      <td>Cross-platform</td>
      <td>Turn Cisco Live into shareable event conversation</td>
      <td>Mixed product news with learning, creators, and community</td>
    </tr>
    <tr>
      <td>Spotify</td>
      <td>Cross-platform</td>
      <td>Make personal listening data shareable</td>
      <td>Turns data into identity and social comparison</td>
    </tr>
    <tr>
      <td>Figma</td>
      <td>X + Instagram</td>
      <td>Invite creators to build with Figma Make</td>
      <td>Made the product itself the creative medium</td>
    </tr>
    <tr>
      <td>Lay's</td>
      <td>X + TikTok</td>
      <td>Connect the brand to FIFA World Cup conversation</td>
      <td>Gave fans and creators a timely cultural hook</td>
    </tr>
    <tr>
      <td>Parker</td>
      <td>LinkedIn + Instagram</td>
      <td>Let an unsolicited anti-AI ad inspire the campaign</td>
      <td>Responded to organic creative momentum instead of manufacturing it</td>
    </tr>
    <tr>
      <td>Salesforce</td>
      <td>LinkedIn</td>
      <td>Ask users to demonstrate Agentforce solutions</td>
      <td>Turned customer builds into peer-led product proof</td>
    </tr>
    <tr>
      <td>Coca-Cola</td>
      <td>Cross-platform</td>
      <td>Personalize the product itself</td>
      <td>Creates an endlessly adaptable social artifact</td>
    </tr>
    <tr>
      <td>CeraVe</td>
      <td>TikTok + Instagram</td>
      <td>Turn skincare education into a creator competition</td>
      <td>Left room for creators and markets to interpret the idea</td>
    </tr>
    <tr>
      <td>TOEFL</td>
      <td>TikTok + Instagram</td>
      <td>Turn a global brand message into a dance challenge</td>
      <td>Made an abstract message participatory</td>
    </tr>
  </tbody>
</table>

<table class="table-primary">
<thead>
<tr>
<th>Metric</th>
<th>Value</th>
</tr>
</thead>
<tbody>
<tr>
<td>Mentions</td>
<td>46.5K</td>
</tr>
<tr>
<td>Reach</td>
<td>198M</td>
</tr>
<tr>
<td>Engagement</td>
<td>125K</td>
</tr>
</tbody>
</table>

 Pepsi took one of advertising's oldest rivalries back to the Super Bowl with “The Choice,” a Taika Waititi-directed spot in which a cola-loving polar bear chooses Pepsi Zero Sugar in a blind taste test. It then extended the idea onto social, including an X participation mechanic tied to cash prizes.

The interesting part is how differently the creative and promotional sides performed. Meltwater's analysis found that high-engagement posts revolved around jokes and meme-style reactions to the polar bear, while many lower-engagement posts were formulaic contest entries. Overall, #PepsiTasteWins generated 46,500 mentions, an estimated 198 million reach, and 125,000 engagements in the conversation period analyzed.

<table class="table-primary">
<thead>
<tr>
<th>Metric</th>
<th>Value</th>
</tr>
</thead>
<tbody>
<tr>
<td>Mentions</td>
<td>11.5K</td>
</tr>
<tr>
<td>Reach</td>
<td>962M</td>
</tr>
<tr>
<td>Engagement</td>
<td>281K</td>
</tr>
</tbody>
</table>

Cisco on Instagram: "WOW powered by the NOC at #CiscoLive 🤩"

 Cisco Live shows that B2B social campaigns do not need to abandon technical substance to generate participation. The 2026 event put major AI infrastructure, security, and AgenticOps announcements at the center of the conversation, while attendees and creators added training, meetups, booth experiences, career development, and behind-the-scenes event content.

That combination gave people more reasons to post than product news alone. Cisco Live conversation produced 11,500 mentions, an estimated 962 million reach, and 281,000 engagements.

<table class="table-primary">
<thead>
<tr>
<th>Metric</th>
<th>Value</th>
</tr>
</thead>
<tbody>
<tr>
<td>Mentions</td>
<td>196K</td>
</tr>
<tr>
<td>Reach</td>
<td>29.8B</td>
</tr>
<tr>
<td>Engagement</td>
<td>35M</td>
</tr>
</tbody>
</table> 

I’m scared of Spotify wrapped #gymmusic #fyp #funny #gymtok #gymplaylist 

Spotify Wrapped remains one of the best examples of what happens when a brand makes its own customer data inherently shareable. Spotify packages listening behavior into individualized stories designed to encourage participation, turning something as pedestrian as your most-listened-to artist into a statement about taste, identity, or mild embarrassment (don’t worry, though. Guaranteed others listen to them too. You’ll find your people). Spotify described its 2025 edition as a global campaign built around personalized, shareable experiences for more than 700 million fans.

And although the campaign is centered around the New Year period, the conversation doesn’t disappear after January. Meltwater social listening found Wrapped still appearing in jokes, fandom posts, song promotion, and social comparisons going further into the start of the year. The conversation analyzed generated 196,000 mentions, an estimated 29.8 billion reach, and 35 million engagements.

<table class="table-primary">
<thead>
<tr>
<th>Metric</th>
<th>Value</th>
</tr>
</thead>
<tbody>
<tr>
<td>Mentions</td>
<td>4.3K</td>
</tr>
<tr>
<td>Reach</td>
<td>45.1M</td>
</tr>
<tr>
<td>Engagement</td>
<td>70.8K</td>
</tr>
</tbody>
</table>

Figma's Makeathon invited its community to create with Figma Make, with winning categories spanning craft, new interactions, boundary-pushing ideas, and a fan favorite selected through social response. The resulting projects included a wide variety of playful, highly interactive experiences.

The creative freedom the campaign encouraged was its advantage: participants demonstrated what the product could do while simultaneously producing content people wanted to explore and share. Meltwater recorded 4,300 mentions, an estimated 45.1 million reach, and 70,800 engagements around the Makeathon.

<table class="table-primary">
<thead>
<tr>
<th>Metric</th>
<th>Value</th>
</tr>
</thead>
<tbody>
<tr>
<td>Mentions</td>
<td>38.2K</td>
</tr>
<tr>
<td>Reach</td>
<td>704M</td>
</tr>
<tr>
<td>Engagement</td>
<td>2.04M</td>
</tr>
</tbody>
</table>

We are World Cup Ready Lets go Mexico😁😁 @lays #LaysFWC26 #jennyv004 #momsoftiktok #momlifebelike 

Lay's used its FIFA World Cup sponsorship in 2026 to connect the brand with the rituals surrounding the tournament, from watching matches together to game-day snacking. Meltwater recorded 38,200 mentions, an estimated 704 million reach, and 2.04 million engagements around the #LaysFWC26 campaign.

The campaign benefited from joining a conversation audiences were already highly motivated to have rather than trying to create a cultural moment from scratch. 

6. Parker's crowdsourced anti-AI campaign

<table class="table-primary">
<thead>
<tr>
<th>Metric</th>
<th>Value</th>
</tr>
</thead>
<tbody>
<tr>
<td>Mentions</td>
<td>846</td>
</tr>
<tr>
<td>Reach</td>
<td>125M</td>
</tr>
<tr>
<td>Engagement</td>
<td>27.9K</td>
</tr>
</tbody>
</table>

Parker Brand Moment Sparks Global Creative Challenge | Newell Brands posted on the topic | LinkedIn

Parker's campaign is unusual because the brand did not originate the idea. Freelance copywriter Kushagra Oberoi posted an unsolicited ad reframing a Parker pen for the AI era, which helped inspire a public creative challenge that attracted more than 350 submissions. Parker's parent company, Newell Brands, ultimately backed the momentum and put shortlisted concepts on a Times Square billboard. The ensuing conversation generated only 846 mentions, but an estimated 125 million reach and 27,900 engagements.

The lesson is not simply “crowdsource your advertising.” It is that brands need enough cultural awareness and flexibility to recognize when organic attention is worth joining. 

Learn more about how social listening can help you spot trends

<table class="table-primary">
<thead>
<tr>
<th>Metric</th>
<th>Value</th>
</tr>
</thead>
<tbody>
<tr>
<td>Mentions</td>
<td>57.7K</td>
</tr>
<tr>
<td>Reach</td>
<td>14.2B</td>
</tr>
<tr>
<td>Engagement</td>
<td>630K</td>
</tr>
</tbody>
</table>

#agentforceinaction #agentforceinaction | Trailhead

 Salesforce's Agentforce In Action challenge asks builders to create or showcase an Agentforce agent, record a short demonstration of the problem it solves, and post the video publicly on LinkedIn with #AgentforceInAction.

It is a strong B2B campaign mechanic because participation doubles as product education: instead of Salesforce simply telling an audience what Agentforce can do, customers and builders provide concrete use cases. Conversation captured around Agentforce In Action and the wider Agentforce discussion generated 57,700 mentions, an estimated 14.2 billion reach, and 630,000 engagements.

<table class="table-primary">
<thead>
<tr>
<th>Metric</th>
<th>Value</th>
</tr>
</thead>
<tbody>
<tr>
<td>Mentions</td>
<td>6.13K</td>
</tr>
<tr>
<td>Reach</td>
<td>12B</td>
</tr>
<tr>
<td>Engagement</td>
<td>634K</td>
</tr>
</tbody>
</table>

Hanamade Cookies ~ Cookie Artist on Instagram: "Not the husband hitting us with the “would you rather” question🥤happy national share a coke day! 

#cookiedecorating #husbandvoiceover #sugarcookieart #satisfying #cookieideas"

“Share a Coke” is an excellent example of an evergreen social media campaign. Coca-Cola revived the popular tagline for a new generation in 2025, returning to the deceptively simple idea of replacing its logo with names and giving people a reason to find, personalize, photograph, and share the product.

In 2026, Meltwater's analysis found the format still being repurposed across fandoms, jokes, friendships, celebrations, and even tribute posts. That adaptability helps explain its longevity: the packaging provides a template, while the audience supplies the meaning. Share a Coke conversation generated 6,130 mentions, an estimated 12 billion reach, and 634,000 engagements.

<table class="table-primary">
<thead>
<tr>
<th>Metric</th>
<th>Value</th>
</tr>
</thead>
<tbody>
<tr>
<td>Mentions</td>
<td>3.61K</td>
</tr>
<tr>
<td>Reach</td>
<td>373M</td>
</tr>
<tr>
<td>Engagement</td>
<td>2.93M</td>
</tr>
</tbody>
</table>

CeraVe turned creator content into the centerpiece of the CerAwards, culminating in its first Global CerAwards event with 111 award-winning creators from 22 countries. Local executions gave creators room to interpret the campaign through formats including acting, humor, and culturally specific references.

That flexibility created more than contest entries; it gave the campaign several different avenues into broader social culture. CeraVe generated 3,610 mentions but 2.93 million engagements, alongside an estimated 373 million reach—a clear of why mention volume should never be evaluated in isolation.

<table class="table-primary">
<thead>
<tr>
<th>Metric</th>
<th>Value</th>
</tr>
</thead>
<tbody>
<tr>
<td>Mentions</td>
<td>383</td>
</tr>
<tr>
<td>Reach</td>
<td>118M</td>
</tr>
<tr>
<td>Engagement</td>
<td>145K</td>
</tr>
</tbody>
</table>

Weeks of focus lead to bigger possibilities. If studying in Dubai is on your mind, this is where confidence begins — with @TOEFL @toefl.middleeast  🎵 You Speak World #TOEFL, #YouSpeakWorld, #StudentLife, #Dubai Paid Partnership

TOEFL's You Speak World campaign started with a broader message: language skills can unlock education, work, confidence, and connection. It then made that positioning participatory through a global dance promotion asking users to create short-form videos with an official sound and using the #YouSpeakWorld hashtag on TikTok or Instagram Reels.

The campaign translated abstract brand positioning into something tangible audiences could actually join in on. Although Meltwater recorded just 383 mentions—the smallest conversation in this group—the campaign still generated an estimated 118 million reach and 145,000 engagements.

A social listening platform should help you answer more than “How many people mentioned us?” Because as we can see, that’s only part of the story. Campaign teams need enough coverage to see conversations across the channels where audiences actually participate, and then they need enough context to understand what’s driving the numbers.

Look for the ability to track conversation volume and engagement alongside sentiment, themes, and share of voice.

Speed matters too. Social campaigns can change direction within hours, particularly when creators or communities start interpreting the idea in unexpected ways. AI-powered analysis can surface changes in volume, sentiment, and themes quickly, while marketers provide the judgment needed to decide whether those changes are meaningful, and how to react.

Meltwater's social listening capabilities bring social, news, forums, and other signals into one unified intelligence platform, with AI-powered analysis for themes, sentiment, competitive intelligence, and reporting. 

The point is not simply to collect more campaign data. It is to understand which campaigns are gaining momentum, what audiences are responding to, and why. It's gaining intelligence your team can actually use while there is still time to act.

Book a demo to see how Meltwater can help you find emerging campaigns and measure the conversations around your own.

A social media campaign is a coordinated set of posts and activities created to achieve a specific goal on social platforms. Unlike an ongoing social media strategy, a campaign usually has a defined objective, creative concept, audience, measurement framework, and time period in which the activity takes place.

How do you measure the success of a social media campaign?

Measure success against the campaign's original goal. Useful metrics can include mentions, reach, engagement, conversions, sentiment, share of voice, audience growth, or traffic. Social listening adds context by showing what people are actually saying, which themes are gaining traction, and what is driving changes in performance.

What makes a social media campaign go viral?

Viral social media campaigns usually combine a timely or distinctive idea with content people have a reason to share or recreate. Participation hooks, platform-native formats, recognizable cultural references, and good timing can all help. Virality itself should not be the objective, though; attention only matters if it contributes to the campaign's goal.

How long should a social media campaign run?

There is no universal campaign length. A campaign tied to a live event may peak within hours, while a product launch, creator program, or challenge may run for weeks or months. Track conversation and engagement throughout the campaign and adjust the timeline when audience interest starts to decline or the original objective has been achieved.

What is the difference between a social media campaign and a social media strategy?

A social media strategy is the ongoing framework guiding how a brand uses social platforms, including its audiences, objectives, channels, content, and measurement approach. A social media campaign is a more focused initiative within that strategy, created around a particular goal, message, launch, event, or period of activity.

Do social media campaigns still work in 2026?

Yes, but audiences expect more than branded posts placed in their feeds. The strongest campaigns give people a reason to participate, personalize, create, or respond. Spotify Wrapped, for example, generated 35 million engagements in the conversation analyzed by Meltwater, showing the scale a genuinely shareable campaign idea can still achieve.

What should I look for in a social listening platform to track campaigns?

Look for broad cross-channel coverage, reliable campaign and competitor tracking, sentiment and theme analysis, real-time trend detection, and reporting that connects activity to campaign outcomes. AI-powered analysis can reduce manual work, but marketers still need source-level context to understand why a conversation changed and decide what action to take.

Get inspired by 10 of the top social media campaigns of 2026, plus how to track your own with social listening.

10 Top Social Media Campaigns of 2026

Social media monitoring is the real-time tracking of brand, product, competitor, and industry conversations across social platforms. It gives teams an early view of complaints, emerging stories, campaign reactions, and customer questions—including those posts that never tag brands directly.

That speed matters because conversations online rarely stay neatly inside one channel. A frustrated customer might post a video, other users may add similar experiences, and a journalist could begin reporting on the pattern before the company has connected the incidents. Monitoring gives marketing, PR, communications, and customer experience teams a chance to understand what is happening while there is still time to shape the response.

The strongest programs are then able to connect those social signals with wider media coverage, apply AI-powered analysis, and route actionable insights to the people responsible for responding.

Why social media monitoring matters for business leaders

Key components of an effective monitoring strategy

How social media monitoring works in practice

Choosing the right social media monitoring tools

How to turn social media data into strategic action

Building your social media monitoring roadmap

What to look for in a social media monitoring platform

Social media monitoring is the real-time process of finding and organizing public conversations about a brand, product, person, competitor, campaign, or topic across social platforms. It is the foundation beneath social listening and broader intelligence: monitoring captures the signals, listening interprets the pattern, and intelligence clarifies what to do next.

A monitoring query looks for more than direct @mentions. Some customers may tag a company when confused, but others will post screenshots, abbreviate the product name, or describe a problem without addressing the brand at all. A well-built social media monitoring search gathers those variations alongside product names, misspellings, regional nuances, campaign terms, executives, and relevant industry language.

Social media monitoring vs. social listening: what's the difference

Social media monitoring tracks individual mentions and changes as they happen. Social listening analyzes the conversation over time to explain themes, attitudes, and behavioral shifts. 

Monitoring might show that delivery complaints doubled this morning; listening reveals that customers increasingly describe the service as “unreliable” and criticize the lack of updates. The resulting intelligence helps teams come up with a response plan, such as publishing a service update and equipping support teams with accurate language.

Managing reputational risk is why many organizations begin monitoring, but it is only one use case. Real-time signal streams also expose high-intent conversations, competitor movements and weaknesses, and changes in market language before they appear in formal reports.

Reputation problems often begin as small, ambiguous signals: a customer reports a defect, a niche creator questions an executive statement, or employees share the same story with critical commentary. Real-time monitoring helps PR and communications assess the combination, velocity, and influence behind those posts before internal stakeholders begin forwarding screenshots asking what happened.

Improving customer experience and support

Customers do not always open a ticket when something goes wrong. They post a video, reply under an ad, or ask other users whether a problem they're experiencing is normal. Monitoring gives customer experience teams another intake channel for fielding and responding to issues in a timely manner: a shipping complaint can go to support, repeated confusion about documentation can reach the content owner, and a cluster of defect reports can be escalated to product and operations.

Uncovering high-intent sales opportunities

Some of the clearest buying signals look like ordinary conversation: “We need an alternative” or “Has anyone found a platform that handles both?” Sales teams need guardrails—an immediate pitch under a frustrated post can feel intrusive—but monitoring lets them assess the context and choose between a useful public answer, direct outreach, or a better-timed follow-up.

Mitigating PR crises before they escalate

Ongoing monitoring establishes a baseline; threshold-based alerts flag a sudden rise in volume, negative sentiment, or engagement around a high-risk topic. Cross-channel context shows when a customer complaint is becoming a press story that requires PR coordination. Crisis monitoring works best when teams can trace that movement and brief decision-makers from shared evidence.

An effective monitoring strategy has four connected parts: brand and topic tracking, competitor and industry tracking, sentiment analysis, and identification of influential voices. Weak coverage in any one area leaves teams with a distorted picture of what is happening.

1. Tracking brand mentions and direct tags

Start with the language people actually use: brand names and handles, products, campaigns, senior leaders, abbreviations, misspellings, and unbranded terms such as a recurring error message. Use language, geography, source, proximity, and exclusion filters to catch unexpected mentions without flooding analysts with unrelated posts.

2. Monitoring competitors and industry keywords

Competitor tracking shows where customers see gaps and keeps teams from mistaking a market-wide problem for a brand-specific one. Industry keywords reveal opportunities with no brand names attached: rising discussion about a compliance requirement, packaging preference, or customer workflow could shape campaign messaging, sales enablement, or the product roadmap.

AI-powered sentiment analysis makes shifts in tone easier to detect, including cases where volume stays stable while negative posts rise. Sarcasm, slang, and quoted criticism complicate automated classification, so analysts should review the posts behind consequential changes carefully. Customers criticizing a problem the brand has just solved tells a different story from customers criticizing the solution.

4. Identifying key influencers and brand advocates

Who drives a conversation often matters just as much as its size. Monitor reach, relevance, engagement, and each account’s role so communications can prepare for an influential critic, marketing can identify credible advocates, and customer experience can recognize the community members people already trust.

In practice, social media monitoring combines AI-assisted data collection and analysis with deliberate keyword architecture and a response process that routes findings to the right team. Technology finds and prioritizes signals at scale; people provide judgment and decide how to act.

Social media monitoring tools collect available posts and metadata through permitted sources. Natural language processing identifies entities, topics, sentiment, and emerging themes; analytics compare activity with historical patterns; and alerts flag unusual volume or tone. Because access differs by network, buyers should ask precise questions about channels, markets, languages, historical depth, and data types.

Build each search around a clear monitoring goal. A reputation search might combine the company name with safety, service, leadership, and trust language; a campaign search needs its hashtags, spokespeople, and creative phrases; a product search may include model numbers, known errors, capability names, and comparison terms. Separate searches by owner, then review them after launches or naming changes as customer language evolves.

Establishing response protocols across teams

Every priority alert needs an owner, a response window, and an escalation rule. Customer care can handle individual service complaints; Sales can review recommendation requests; PR should own media inquiries and narratives moving into press; and legal, security, product, or operations need clear triggers for high-risk topics. Record owners and backup contacts in a routing matrix so alerts do not sit in a shared inbox.

The right social media monitoring tool depends on coverage breadth, alerting speed, sentiment quality, reporting requirements, and the scale of the team using it. Begin with the decisions and workflows the technology must support, then compare vendors against those requirements.

At minimum, evaluate coverage of the social platforms and markets that matter to the organization. Features like real-time alerting, sentiment analysis, historical data, query flexibility, and customizable reporting options are also extremely valuable. Check what collaboration and workflow tools are available, so customer service needs, business intelligence, or executive reporting can be conducted without duplicate exports and manual reformatting.

Test difficult cases during a trial or demo period. 

Can the platform distinguish the brand from an unrelated common term? 

Does it capture untagged references and relevant regional language? 

Can an analyst easily move from an alert to the posts behind it, then produce a concise briefing with sources? A polished dashboard is less useful if the data or workflow fails under routine pressure.

Social Listening

10 Top Social Media Campaigns of 2026

What Is Social Media Monitoring And How Does It Work?

What 2.47 Million Posts Reveal About 2026 Summer Movie Audiences

The Best Talkwalker Alternatives for Social Listening

Best Brandwatch Alternatives for AI Visibility (2026)

10 Best Brand Tracking Software & Tools

Black Friday and Cyber Monday Consumer Trends 2026

Competitor Product Launch Tracking: Monitoring Competitor Feature Releases

Trendspotting: meaning, examples, and tips

The Top 15 Social Media Monitoring Tools 2026

Executive Marketing Reporting: What Executives Care About

How AI Recommends Saving Money on Groceries: Analysis of 8 Leading AI Models

Social Listening

10 Top Social Media Campaigns of 2026

What Is Social Media Monitoring And How Does It Work?

What 2.47 Million Posts Reveal About 2026 Summer Movie Audiences

The Best Talkwalker Alternatives for Social Listening

Best Brandwatch Alternatives for AI Visibility (2026)

10 Best Brand Tracking Software & Tools

Black Friday and Cyber Monday Consumer Trends 2026

Competitor Product Launch Tracking: Monitoring Competitor Feature Releases

Trendspotting: meaning, examples, and tips

The Top 15 Social Media Monitoring Tools 2026

Executive Marketing Reporting: What Executives Care About

How AI Recommends Saving Money on Groceries: Analysis of 8 Leading AI Models

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