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.

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.

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, 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

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

Kickoff for the FIFA World Cup 2026 starts on June 11, but the hype around the high-profile tournament started much earlier with input from fans and brands around the globe. As we saw previously with the Super Bowl, this pre-event period is a critical one for brands looking to understand which marketing strategies are resonating with audiences most. In particular, as sponsorship costs rise and brand collaborations grow more competitive, marketers need to know which activations can give them the strongest ROI. 

To understand these factors, we used Explore+ to analyze digital, traditional, and social media content about the World Cup with a focus on identifying the highest-performing brands, campaigns, and individuals. Overall, between January 1 and June 1, 2026, this content generated 2.4 million mentions and 1.3 billion engagements across all tracked source types. However, awareness did not always equal engagement. Instead, the findings show that cultural relevance and audience responsiveness, not sponsorship status, are the main determinants of success during major global events.

Download a one-page summary of this analysis

Why non-sponsor brands generated more engagement than official World Cup sponsors

How Coca-Cola used global influencers to become the most engaging World Cup sponsor

How LEGO's product-led campaign became the most successful World Cup brand collaboration

How Lamine Yamal's TikTok became the biggest World Cup social media moment before kickoff

Why the World Cup song and halftime show drove outsized engagement

How Meltwater helps brands win attention during major cultural events

FAQ: World Cup marketing, sponsorship effectiveness, and social media engagement

<table style="width:100%; border-collapse:collapse; font-family:Arial, sans-serif; font-size:14px;">
  <tbody>
    <tr>
      <td style="padding:12px; border:1px solid #ccc; font-weight:bold; width:30%;">Capability</td>
      <td style="padding:12px; border:1px solid #ccc;">Explore+</td>
    </tr>
    <tr>
      <td style="padding:12px; border:1px solid #ccc; font-weight:bold;">Analysis window</td>
      <td style="padding:12px; border:1px solid #ccc;">January 1 – June 21, 2026</td>
    </tr>
    <tr>
      <td style="padding:12px; border:1px solid #ccc; font-weight:bold;">Data sources</td>
      <td style="padding:12px; border:1px solid #ccc;">
        30 sources, including broadcast television and radio, online and print news, blogs, comments, reviews, forums, podcasts, TikTok, Instagram, Reddit, Facebook, Pinterest, X, Douyin, Red, YouTube, and more
      </td>
    </tr>
    <tr>
      <td style="padding:12px; border:1px solid #ccc; font-weight:bold;">Brands / entities tracked</td>
      <td style="padding:12px; border:1px solid #ccc;">
        FIFA World Cup 2026 and related terms and hashtags, official sponsor brands, and select athletes, celebrities, events, and most discussed brand collaborations 
      </td>
    </tr>
    <tr>
      <td style="padding:12px; border:1px solid #ccc; font-weight:bold;">Key term definitions</td>
      <td style="padding:12px; border:1px solid #ccc;">
        <strong>Engagement:</strong> The number of shares, comments, likes, retweets, replies, direct messages, etc.<br><br>
 <strong>Engagement per mention (EPM):</strong> The total number of engagement actions divided by the number of mentions<br><br>
      <strong>Mentions:</strong> The number of instances when keywords and phrases appeared within a piece or collection of content.<br><br>
      <strong>Share of Voice (SOV):</strong> The percentage, or share, of total mentions attributed to a particular brand, market, or entity.
      </td>
    </tr>
  </tbody>
</table>

Official World Cup sponsor brands generated about 30% more mentions than non-sponsoring brands that launched campaigns around the event. However, the latter group dominated in terms of audience interaction, generating nearly double the total engagement and 2.8 times the EPM of official sponsors. 

So while official sponsors like Coca-Cola and Adidas won conversation volume, non-sponsor collaborators like LEGO, Nike, and Puma won audience attention. As we explore more thoroughly below, high-production value ads and strategic influencer activation were key factors in differentiating brands within oceans of World Cup content. 

Why it matters: Sponsor or not, earning attention is often more challenging than earning awareness. This year's World Cup demonstrates that a well-executed collaboration, product launch, or influencer strategy can deliver stronger engagement than official sponsorship rights alone.

Of the official World Cup sponsors and partners, Adidas and Coca-Cola were neck-in-neck in terms of discussion, together generating about half of all mentions. However, Coca-Cola emerged as the winner when it came to audience action with over 43% of total engagement compared to Adidas’s 37%.

Its partnership with soccer megastar Lamine Yamal included a wildly successful post on his personal Instagram account that drove 0.8% of all sponsor-period engagement. However, Coca-Cola’s success was also thanks to a number of successful social media activations featuring influencers from around the world. 

So although about half of tracked World Cup conversations originated in the US, the soda brand’s campaign generated high-engagement posts from a wider range of countries. Standouts include: 

this TikTok from a Brazilian humor and lifestyle influencer (2% of total engagement)

this Instagram post from an Indonesian soccer influencer (1.4%)

this TikTok from a US- and Ghana-based dancing influencer visiting Côte d'Ivoire (1.1%)

and this Instagram post from a Thai actor (0.8%)

These and other posts from influencers across Latin America, Africa, and Asia helped Coca-Cola tailor a global campaign to local audiences, in line with the kind of national pride the World Cup naturally inspires. That approach attracted audiences and helped the brand achieve 40% positive sentiment, higher than any other official sponsor. 

Why it matters: Audiences experience global events like the World Cup and the Olympics through local lenses. Coca-Cola's influencer strategy shows how brands can scale campaigns across markets without sacrificing brand identity or consistency.

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LEGO outperformed other top World Cup brand collaborators like Nike and Puma thanks to a coveted new product and partnerships with the world’s leading players.

Instead of being a sponsor, LEGO got in on the event with an official product licence for the iconic trophy. The brand’s resulting World Cup Official Trophy set, part toy, part collector’s item, was the focus of its Everyone Wants a Piece campaign. 

With ads featuring the 2,842-piece set, Cristiano Ronaldo, Lionel Messi, Kylian Mbappé, and Vinícius Jr. (and their toy counterparts), the campaign went viral. But it wasn’t just star power and a flashy product that drove its success. 

The ad’s impressive giant lazy Susan got audiences debating over whether or not the video was created with AI. In response, LEGO released a behind-the-scenes video captioned “Still think it’s AI?” showing how the original video was created with practical effects. 

As a result of a multi-wave campaign that tuned into audience conversations, the toy brand generated 82% share of engagement of the top 50 most engaging brand collaborator posts and 13% of the 50 most engaging World Cup posts overall.

Why it matters: LEGO showed that brands don’t necessarily need official sponsorship status to be a leading voice in major cultural moments. By combining a multi-stage launch with big stars and audience interaction (as well as appealing to overlapping football and LEGO collector audiences) the brand turned a licensing deal into one of the tournament's most talked-about campaigns.

<blockquote class="tiktok-embed" cite="https://www.tiktok.com/@lamine.yamal/video/7645346910550691094" data-video-id="7645346910550691094" style="max-width: 605px;min-width: 325px;" > <section> <a target="_blank" title="@lamine.yamal" href="https://www.tiktok.com/@lamine.yamal?refer=embed">@lamine.yamal</a> <a title="fifaworldcup" target="_blank" href="https://www.tiktok.com/tag/fifaworldcup?refer=embed">#FIFAWORLDCUP</a> <a target="_blank" title="♬ sonido original - Lamine Yamal" href="https://www.tiktok.com/music/sonido-original-7645346922064136982?refer=embed">♬ sonido original - Lamine Yamal</a> </section> </blockquote> <script async src="https://www.tiktok.com/embed.js"></script>

Spain’s Lamine Yamal posted a TikTok on May 29 that far outperformed all other FIFA, brand, and athlete posts about the tournament. The video, which uses an official, gamified World Cup 2026 filter, shows him attempting to correctly pronounce the names of other competing players. 

In a funny twist, the filter fails to register his pronunciation of his own name as correct, causing him to lose the game. That single TikTok has generated 19.6 million likes and counting, along with over 196,000 comments, one million saves, and 1.5 million shares. Its success highlights how unpolished, personality-led content (along with interactive filters, as we saw in our Lunar New Year analysis) can be a magnet for audience participation. 

The most strategically significant planned post is Lamine Yamal's @lamineyamal February partnership, generating 0.8% of all sponsor period engagement from 40M reach off a single post. Yamal's personal TikTok generated 12.6% of all event-wide top-50 engagement, more than any brand, FIFA account, or other athlete in the full tournament conversation. A single February partnership post converting that audience into sponsor engagement is the clearest example in the data of athlete reach translating directly into sponsor equity.

Among players driving World Cup engagement, Messi was Yamal’s closest competitor, thanks to his starring role in both the LEGO and Adidas campaigns, as well as Michelob Ultra and Lay’s. The Argentine player is the star of Adidas’ collaborative campaign with fashion brand Kith. A fancam TikTok featuring clips from the main Adidas ad along with Messi’s on-field highlights proved to be the highest-engagement post across all sponsor mentions, accounting for 5.9% of all sponsor-period engagement.

Why it matters: Yamal and Messi's success shows that both authenticity and strategic sponsorships can deliver outsized attention when they align with how fans already consume content online.

The World Cup song, “Dai Dai” by Shakira and Burna Boy, captured 20% of the total engagement of the top 50 most engaging posts, making it the single biggest cultural asset of the pre-tournament period. Ahead of its premiere, audiences around the world were already anticipating the release of a World Cup anthem, a tradition since 1990. So when “Dai Dai” officially dropped in May, it did so to an already involved fan base.

Building on that momentum, the May 14 announcement of the Cup’s first-ever halftime show, headlined by Madonna, Shakira, and BTS, also had a huge impact. Together, it and the World Cup song generated 37% of the engagement of the top 50 posts. So while the sport was the obvious backbone of pre-World Cup hype, the entertainment side of the event expanded its reach beyond die-hard sports fans.

Why it matters: Brands looking to capitalize on major sporting events shouldn't focus exclusively on the game. Some of the tournament's biggest engagement drivers came from adjacent cultural moments, suggesting that entertainment partnerships can be just as effective as sports-focused activations for reaching broad audiences.

Use Case 1: Turning Cultural Moments Into Marketing Opportunities

The Problem: Some of the biggest World Cup conversations emerged from creator content and audience debates.

Monitor emerging conversations, viral trends, and breaking cultural moments with Meltwater Explore+.

Set alerts for sudden spikes in discussion around athletes, creators, campaigns, competitors, and event-related topics.

Identify opportunities to join conversations while audience interest is still growing.

Business Outcome: Increase campaign relevance and earn attention by participating in cultural moments before competitors do.

Use Case 2: Identifying Which Content Resonates Most on Each Social Platform

The Problem: Content that performs well on one platform may underperform on another, making it difficult to know where to invest resources.

Use Meltwater Explore+ to compare engagement, share of voice, and engagement per mention across TikTok, Instagram, X, YouTube, and other social channels.

Identify which content formats—from influencer videos and product launches to athlete partnerships and entertainment activations—are generating the strongest results on each platform.

Analyze audience sentiment and interaction patterns to understand why specific posts resonate with users on different channels.

Business Outcome: Optimize platform-specific content strategies and allocate resources toward the channels and formats most likely to drive engagement.

Use Case 3: Activating the Right Influencers in Every Market

The Problem: Global events create worldwide audiences, but engagement often depends on local relevance.

Use Meltwater Influencer Marketing to discover creators by country, audience demographics, interests, and engagement rates.

Evaluate influencer performance across regions to identify the creators generating the strongest audience response.

Measure campaign impact across markets to determine which partnerships are driving awareness, engagement, and positive sentiment.

Business Outcome: Build globally consistent campaigns that feel locally authentic and generate stronger engagement across priority markets.

The lead-up to the World Cup proved that visibility is important, but audience attention and cultural intelligence differentiate leading brands from the rest of the pack. This is especially true for global events, where every brand is fighting for relevance in an oversaturated playing field.

Coca-Cola, LEGO, Yamal, and others proved that audiences are eager to engage in campaigns that give them something to relate to and discuss in digital arenas. Inviting fans into the action can have a greater impact than just giving them something to watch. As the event unfolds, the brands that succeed will be those that can identify and quickly adapt to emerging conversations. 

Want to move beyond awareness and measure what truly captures audience attention? Discover how Meltwater helps brands track engagement, uncover emerging trends, and understand which campaigns are driving meaningful audience participation.

How did non-sponsor brands perform compared to official World Cup sponsors in pre-event conversation and engagement?

Some non-sponsor brands like LEGO generated significantly higher engagement despite lower mention volume. According to Meltwater Explore+ data, LEGO’s campaign drove stronger audience interaction than those of official sponsors through creators, product launches, and shareable content.

Which World Cup sponsor generated the most engagement?

Coca-Cola generated the largest share of sponsor engagement. Meltwater’s Explore+ analysis shows the brand captured more than 43% of total sponsor engagement, outperforming Adidas despite similar levels of conversation volume.

Why were influencer campaigns so successful during the World Cup?

Influencers helped brands connect global events to local audiences. Meltwater’s Explore+ insights show that creators across Latin America, Africa, and Asia played a key role in extending Coca-Cola’s campaign reach and increasing audience participation.

What was the most engaging World Cup-related social media post?

A TikTok from Spain's Lamine Yamal generated the highest engagement of any World Cup-related post during the reporting period. According to Meltwater Explore+ data, the video accumulated millions of likes, shares, saves, and comments by combining humor with a platform-native, interactive filter.

What made LEGO's World Cup campaign successful?

The campaign combined a premium product launch, global football stars, and audience participation. Meltwater’s Explore+ analysis found that LEGO's multi-stage campaign generated the largest share of engagement among major World Cup brand collaborations.

How important was entertainment to World Cup engagement?

Entertainment content became one of the largest engagement drivers before the tournament began. Meltwater Explore+ data shows that the World Cup anthem and halftime show announcement accounted for more than one-third of engagement across the 50 top-performing posts.

What can brands learn from World Cup social media trends?

Audiences increasingly reward relevance and opportunities for participation. According to Meltwater’s Explore+ analysis, campaigns that aligned with creator culture, local audiences, and platform-native behaviors tended to outperform campaigns focused solely on sponsorship visibility.

Learn how to turn global cultural moments into marketing opportunities. See Meltwater in Action

Who Won World Cup Marketing Before Kickoff?

Social media is one of the most powerful tools in any marketers arsenal. It helps you connect with your audience in a more casual way than through an email or ad, and offers innumerable options for content types — from videos to quizzes, tutorials to behind-the-scenes. But to know how this content is actually performing and serving your goals, you need social media analytics. 

Getting the most out of your social media efforts is easier when you choose the right social media analytics tools. 

Benefits of using a social media analytics tool

What to look for in a social media analytics tool

Social analytics tools are softwares, plugins, or native analytics that allow you to see engagement metrics for your channels, as well as your competitors channels. 

Many social platforms offer a built-in, easy-to-use analytics dashboard, so you could start there, but note that they do have their limitations if you're looking for omnichannel marketing insights.

For example, Twitter / X Analytics can tell you at a glance your followers growth, impressions, profile visits, and mentions. Facebook Insights delivers post-related data, such as audience reach, clicks, and reactions. LinkedIn offers analytics that measure engagement and supply information about your followers’ demographics.

Outside of native analytics channels, you can use third-party social media analytics tools, which provide a holistic view of the effectiveness of your social media strategy. These platforms save you time from switching between the different social media networks and offer customizable dashboards so that you can easily compare your performance across networks.

Tip: Learn how to measure social media campaign success.

There are many benefits to social media analytics tools. Namely, they provide context, data, and insights that help you and your social media team understand which posts are resonating the most with you audience, and on which platforms. 

Social media analytics tools often offer more in-depth insights than native tools, and allow you to easily compare performance over different date ranges.

Here are some of the top platforms for social media analytics software:

Meltwater transforms social, traditional media, and AI signals into actionable intelligence that helps organizations understand audiences, measure performance, identify emerging trends, and make faster, more confident decisions. By combining social listening, consumer intelligence, AI-powered analysis, and executive-ready reporting in one unified platform, Meltwater helps brands see the full picture behind social performance.

Unified intelligence platform: Analyze social conversations, news coverage, reviews, forums, and AI-generated narratives in one connected view

Social listening and analytics: Monitor audience sentiment, engagement trends, brand perception, and emerging conversations across global social channels

Advanced AI for speed to insight: Automatically identify themes, anomalies, sentiment shifts, and trend opportunities using AI-powered analysis

Executive-ready reporting: Transform social performance data into stakeholder-ready dashboards, reports, and actionable insights

Unmatched global data coverage: Access consumer conversations across millions of sources, 240+ languages, and major global and regional social platforms

Best for: Mid-sized to enterprise brands that need social media analytics, consumer intelligence, social listening, and executive reporting in a single platform

Meltwater also allows you to find top-performing posts by topic tags, to improve your understanding of the content that resonates with your audience. Your analytics can be easily summarized in reports and shareable dashboards to send to key stakeholders.

Sprout Social is a popular social media analytics software option for marketers, particularly at the enterprise level. They help brands see a cross-channel view, providing qualitative analysis and insights into your top-performing content. 

Cross-platform analytics: Measure engagement, audience growth, and content performance across social channels

Social listening: Monitor conversations, trends, and audience sentiment related to your brand

Competitive benchmarking: Compare social performance against competitors and industry benchmarks

Profile performance reporting: Track account-level growth and engagement metrics

AI-powered insights: Surface trends and recommendations to improve social strategy

Best for: Mid-sized to enterprise social teams managing analytics and engagement across multiple networks

Sprout Social also provides social listening capabilities and a unified inbox to help you reply to all DMs from one place. A unique feature of Sprout Social is their employee advocacy tool, which helps you amplify your messages using employees, thereby improving engagement.

With Sprout Social's social media analytics software, you can analyze various topics and hashtags to understand the best social content for getting engagement from your audience.

Tip: Take a look at Sprout Social alternatives.

While not solely designed for social media analytics, Google Analytics does provide some great insights into how your social content is performing.

Traffic attribution: Measure how social media contributes to website traffic and conversions

User journey analysis: Understand how social visitors interact with your website

Conversion tracking: Connect social campaigns to business outcomes and revenue

Audience insights: Analyze demographics and behaviors of social traffic sources

Custom reporting: Build dashboards that combine social and website performance metrics

Best for: Marketing teams focused on connecting social activity to website performance and conversions

Social Listening

Who Won World Cup Marketing Before Kickoff?

Best Social Media Analytics Tools & Software 2025

Grok Brand Monitoring: A Step-by-Step Guide to Tracking Brand Mentions

Why 2026 Is the Year of “Maxxing”

Top 10 YouTube Monitoring and Analytics Tools

Best Twitter Monitoring Tools for Tracking Brand Mentions

10 Most Effective Hashtag Tracking Tools

The Ultimate Guide to X (Twitter) Social Listening for Influencer & Social Teams

How Popular Is TikTok Shop? Data Insights & Trends 2026

Platform Deep Dive: 7 Trends Defining Beauty Reddit Right Now

How to Measure Share of Voice to Improve Brand Visibility

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

Social Listening

Who Won World Cup Marketing Before Kickoff?

Best Social Media Analytics Tools & Software 2025

Grok Brand Monitoring: A Step-by-Step Guide to Tracking Brand Mentions

Why 2026 Is the Year of “Maxxing”

Top 10 YouTube Monitoring and Analytics Tools

Best Twitter Monitoring Tools for Tracking Brand Mentions

10 Most Effective Hashtag Tracking Tools

The Ultimate Guide to X (Twitter) Social Listening for Influencer & Social Teams

How Popular Is TikTok Shop? Data Insights & Trends 2026

Platform Deep Dive: 7 Trends Defining Beauty Reddit Right Now

How to Measure Share of Voice to Improve Brand Visibility

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

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