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

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, 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.

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

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

A decade ago, book publishers relied heavily on bestseller lists, critic reviews, and prime bookstore placement to encourage sales and identify emerging trends. Today, many of publishing's biggest success stories begin somewhere else entirely: TikTok.

What started as a niche reading community has evolved into one of the most influential book discovery and promotion ecosystems in the world. BookTok regularly drives sales spikes, resurrects old titles, influences adaptations, and shapes reading trends across entire genres.

To understand how the conversation is evolving, Meltwater analyzed approximately 1.3 million BookTok-related mentions and 1.7 billion engagements between January 1 and June 21, 2026. 

The findings reveal an ecosystem that has matured but continues to grow rapidly. It is also increasingly defined by romance content, title-specific fandoms, and cultural influence that extends well beyond social media.

BookTok weekly mentions grew 60% in under six months, but earning attention is getting harder

Romance has become BookTok's dominant genre

Viral books often have a stronger impact than viral creators

Adaptations are creating powerful BookTok feedback loops

BookTok is inspiring a new era for physical bookstores

How Meltwater helps brands spot growing trends and tap into cultural moments

<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;"><a href="https://www.meltwater.com/en/products/explore-plus">Meltwater Explore+</a></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;">Jan. 1 – Jun. 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;">
        TikTok, Reddit, YouTube, Pinterest, Instagram, X, Facebook, 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;">BookTok</td>
    </tr>
    <tr>
      <td style="padding:12px; border:1px solid #ccc; font-weight:bold; vertical-align:top;">Key term definitions</td>
      <td style="padding:12px; border:1px solid #ccc;">
        <p><strong>Engagement</strong>: the number of shares, comments, likes, retweets, replies, direct messages, etc.</p>
        <p><strong>Mentions</strong>: the number of instances when key words and phrases appeared within a piece or collection of content</p>
        <p><strong>Share of Engagement (SOE)</strong>: the percentage, or share, of total engagement actions attributed to a particular brand, market, or entity</p>
        <p><strong>Subreddit</strong>: a user-created community on Reddit dedicated to a particular interest or topic</p>
      </td>
    </tr>
  </tbody>
</table>

Download a one-page pdf summarizing the findings of this analysis

BookTok — the community of readers that began on TikTok and quickly garnered somewhat surprising popularity is still growing and expanding since its inception, but engagement is not as consistent.

Across the near six month analysis period, weekly mention volume increased from roughly 46,000 mentions to more than 74,000 mentions, representing approximately 60% growth. Rather than being driven by a single viral event, the increase was gradual and sustained, suggesting more structural audience expansion.

Engagement, however, is not following the same trajectory.

While engagement peaked during mid-May, average engagement per mention fell by roughly 38% throughout the analysis period. Leading to the conclusion that more people are participating in the conversation, but individual posts are competing for a smaller share of audience attention.

This pattern is common for maturing digital ecosystems. As participation grows, visibility becomes harder to earn and creators must compete within increasingly crowded feeds within the community itself.

BookTok is no longer an emerging trend, nor should it be viewed as one. The story is no longer that “people still read” but rather, people are using BookTok as a primary and established discovery channel, where competition for attention is intensifying. For brands and publishers, success depends less on simply participating and more on understanding which conversations, genres, and titles are gaining momentum.

BookTok as a general descriptor for the reader community may have now expanded across YouTube, Pinterest, Instagram, Reddit, and X, but TikTok remains the primary engine driving attention.

TikTok accounted for 44.1% of total mentions in the dataset and generated 80.7% of all engagement. No other platform came close to matching its ability to amplify book conversations at scale.

By comparison, YouTube generated more than 20% of mentions but only 4.3% of engagement, and Reddit contributed just 2% of mentions despite playing an outsized role in deeper discussion and recommendation culture.

This suggests that each platform fills a particular role when it comes to the popularity of BookTok: TikTok drives reach and virality, YouTube supports longer-form discovery, Pinterest fuels aspirational book content, and Reddit serves as the conversation's discussion floor.

For publishers and marketers, platform strategy matters as much as content strategy. TikTok remains the primary channel for generating visibility, while other platforms help deepen engagement and sustain discussion.

44.1% — Share of BookTok mentions occurring on TikTok

80.7% — Share of total engagement generated on TikTok

20.5% — Share of mentions occurring on YouTube

~2% — Share of mentions occurring on Reddit

A burgeoning BookTok phenomenon is the popularity of work that falls under the romance genre umbrella. So much so that the “BookTok” hashtag is becoming synonymous with content not specifically to do with books or series. For example it is used on posts like this viral TikTok reacting to the TV series adaptation of Off-Campus, driving much of the engagement spike in May.

I absolutely died at this scene 😮‍💨 #offcampus #ellekennedy #garrettgraham #booktok #fyp 

The share of romance-related content rose significantly throughout the six month analysis period, growing from roughly 7% of sampled posts in January to May’s peak of 22.5%. Across both volume and engagement metrics, romance outperformed every other genre category. 

And the trend extends well beyond TikTok itself.

Reddit community analysis from the top-30 subreddit sample (13K mentions), reveals that romance-focused communities account for roughly three times the discussion volume of fantasy-focused communities among major BookTok-related subreddits.

Related subgenres such as r/fantasyromance, r/RomanceBooks, and r/DarkRomance have become some of the most active genre communities connected to BookTok culture, generating significant engagement despite differing audience sizes.

Ignoring BookTok’s strongest audience signal could mean missing out on key marketing opportunities. Romance has become the ecosystem's primary engagement engine, influencing everything from bestseller momentum to adaptation interest and retail merchandising.

22.5% — Peak share of romance-related posts during May 2026

~22% — Share of major Reddit discussion driven by romance-focused communities

6.6% — Share of engagement driven by the Off-Campus series in top-performing content

One of the clearest findings is that BookTok is increasingly title-driven rather than creator-driven.

The strongest example comes from the Off-Campus series by Elle Kennedy. During the analysis period, Off-Campus accounted for roughly 4.1% of sampled posts and approximately 6.6% of engagement across top-performing content.

No individual creator or author came close to generating comparable influence. The most-named author (Elle Kennedy) garnered under 1% of engagement, while no creator got above 1%.

Instead, audiences organized around specific series, books, characters, and fandoms. Readers shared reactions, edits, reviews, adaptation discussions, and recommendations centered on titles rather than personalities.

*Engagement share = share of total engagement across the top 2,000 sampled posts

This pattern appeared across multiple breakout books, including Off-Campus, Fourth Wing, A Court of Thorns and Roses, Heated Rivalry, and Haunting Adeline.

For publishers and marketers, tracking breakout titles may be more valuable than tracking individual influencers. A rapidly emerging book conversation often signals future audience demand long before sales rankings or bestseller lists fully reflect the trend.

BookTok is increasingly behaving similarly to entertainment fandoms.

The clearest example was the May conversation surge surrounding Off-Campus following Prime Video's adaptation launch. Discussion expanded beyond traditional book content into reaction videos, fan edits, sports crossovers, and adaptation commentary, reflecting a broader pattern.

Books generate BookTok buzz and successful titles attract film and television adaption interest. Adaptations then introduce the story to new audiences who return to social platforms, creating a second wave of discussion and discovery.

Another top title, The Housemaid, gained engagement share largely due to casting announcements and promotion for an upcoming film adaptation.

she's on a whole other level  #thehousemaid #ninawinchester #amandaseyfried #booktok #movie

As streaming platforms continue investing in romance and fantasy adaptations, this feedback loop is likely to accelerate.

Publishers, studios, and marketers should view BookTok as both a discovery channel and an audience validation tool. Monitoring adaptation-related discussion can provide early indicators of sustained cultural momentum.

One of the more endearing and surprising trends to come out of the current stage of BookTok is one that extends beyond social media entirely.

As BookTok communities continue growing online, bookstores are increasingly adapting their retail strategies to match audience demand.

Reporting from People, PBS, and more points to a rise in BookTok-inspired merchandising, dedicated romance store sections, and even genre-specific bookstores reacting to the Romance trend.

Specialized romance bookstores are opening across the United States, while independent booksellers increasingly describe their stores as community spaces where readers discover titles that first gained momentum on TikTok.

What began as a digital recommendation engine is now influencing physical shelf space and purchasing behavior in a powerful way.

BookTok's influence can no longer be measured solely through social metrics. The conversation is increasingly translating into real-world consumer behavior, making it a valuable signal for retailers, publishers, and entertainment brands alike.

Growing number of romance-focused bookstores nationwide

Increased bookstore merchandising built around BookTok recommendations

Stronger connections between online reading communities and in-store discovery

Continued investment by major booksellers in younger, social-first audiences

The BookTok community is evolving into a broad and diverse ecosystem. It continues to reshape how audiences discover and engage with books across both digital and physical spaces. 

What begins as a niche conversation can quickly influence what becomes a bestseller, accelerate adaptation pipelines, inspire genre popularity, and even translate into innovative in-store retail strategies. As social discussion, fandom culture, and consumer behavior become increasingly interconnected, understanding these shifts requires a broader, cross-channel perspective.

Meltwater helps brand and marketing teams track these dynamics holistically, uncovering what’s driving engagement across platforms, and inspiring more informed decisions as trends emerge and evolve.

Use Case 1: Spot emerging titles before they break out into the mainstream

By the time a book appears on bestseller lists, much of its momentum has already been built through social conversation.

Monitor BookTok conversations across TikTok, Reddit, Instagram, YouTube, and other social channels in one platform

Track emerging titles, authors, genres, and keywords gaining momentum over time

Identify unusual spikes in conversation volume before they become mainstream trends

From 1.3 million BookTok mentions and 1.7 billion engagements Meltwater analysis uncovers where reader attention is growing, which genres dominate, and what's coming next.

The Future of BookTok: What 1.7 Billion Engagements Reveal

TikTok has evolved from a short-form video platform into a primary search engine and cultural powerhouse. For brands in 2026, the ability to parse through millions of hours of footage to find relevant mentions, emerging trends, and competitor movements is a competitive necessity. This guide provides a detailed evaluation of the top tools designed to optimize your TikTok strategy through robust data monitoring.

The growing necessity of TikTok monitoring for modern brands

How we evaluated the best TikTok monitoring tools

Common metrics to monitor for TikTok success

Get started with Meltwater's TikTok monitoring capabilities

Brands that monitor TikTok effectively can strategize more proactively by identifying customer pain points mentioned in "storytime" videos, capitalizing on user-generated content (UGC) for ad creative, and mitigating reputational risks before a negative video reaches millions of views. Furthermore, because TikTok is increasingly used for product discovery, monitoring provides direct insights into the consumer path to purchase.

TikTok monitoring tracks, analyzes, and provides insights on data generated through the TikTok platform. It typically encompasses two primary functions: owned analytics (tracking your brand's account performance) and earned social listening (tracking what others are saying about your brand, competitors, or industry). Unlike traditional platforms, TikTok monitoring also requires tracking specific audio clips, hashtags, and visual effects that drive the platform’s unique algorithm.

To ensure these recommendations meet professional standards, we assessed each platform based on five rigorous criteria.

We prioritized tools that offer near-instant data updates. In the fast-moving TikTok ecosystem, data that is 24 hours old is often obsolete. Accuracy in reporting views, shares, and engagement rates is the baseline for any professional audit.

A tool must allow you to place your performance side-by-side with your competitors. We looked for features that enable share of voice (SOV) analysis and the ability to track competitor posting frequencies and top-performing content formats.

Social listening and trend identification

We evaluated how well tools identify "rising" hashtags and sounds. Monitoring isn't just about what happened; it’s about what is about to happen. Tools that offer early-stage trend detection received higher rankings.

Data is only useful if it is accessible. We analyzed the complexity of the dashboards and the ability to integrate TikTok data into broader business intelligence (BI) stacks or CRM systems.

Professional tools range from free native dashboards to five-figure enterprise contracts. We assessed whether the feature set justifies the price point for different business scales.

<table class="table-primary alternate-color">
  <thead>
    <tr>
      <th>Tool</th>
      <th>Best For</th>
      <th>Social Listening</th>
      <th>Hashtag Tracking</th>
      <th>Competitor Analysis</th>
      <th>Trend Discovery</th>
      <th>Reporting</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>Meltwater</td>
      <td>Enterprise TikTok monitoring and consumer intelligence</td>
      <td>✓</td>
      <td>✓</td>
      <td>✓</td>
      <td>✓</td>
      <td>Advanced</td>
    </tr>
    <tr>
      <td>Brandwatch</td>
      <td>Enterprise social listening</td>
      <td>✓</td>
      <td>✓</td>
      <td>✓</td>
      <td>✓</td>
      <td>Advanced</td>
    </tr>
    <tr>
      <td>Sprout Social</td>
      <td>Social media management and analytics</td>
      <td>✓</td>
      <td>Limited</td>
      <td>✓</td>
      <td>Moderate</td>
      <td>Advanced</td>
    </tr>
    <tr>
      <td>Pentos</td>
      <td>TikTok-specific trend tracking</td>
      <td>Limited</td>
      <td>✓</td>
      <td>✓</td>
      <td>✓</td>
      <td>Moderate</td>
    </tr>
    <tr>
      <td>Keyhole</td>
      <td>Campaign and hashtag tracking</td>
      <td>✓</td>
      <td>✓</td>
      <td>✓</td>
      <td>Moderate</td>
      <td>Advanced</td>
    </tr>
    <tr>
      <td>Exolyt</td>
      <td>Creator and influencer analysis</td>
      <td>Limited</td>
      <td>✓</td>
      <td>✓</td>
      <td>Moderate</td>
      <td>Moderate</td>
    </tr>
    <tr>
      <td>Analisa.io</td>
      <td>AI-powered profile analytics</td>
      <td>Limited</td>
      <td>✓</td>
      <td>Moderate</td>
      <td>Moderate</td>
      <td>Moderate</td>
    </tr>
    <tr>
      <td>Iconosquare</td>
      <td>Reporting and scheduling</td>
      <td>No</td>
      <td>Limited</td>
      <td>No</td>
      <td>Limited</td>
      <td>Moderate</td>
    </tr>
    <tr>
      <td>Rival IQ</td>
      <td>Competitive benchmarking</td>
      <td>Limited</td>
      <td>No</td>
      <td>✓</td>
      <td>Moderate</td>
      <td>Advanced</td>
    </tr>
    <tr>
      <td>TikTok Creative Center</td>
      <td>Native trend discovery</td>
      <td>No</td>
      <td>✓</td>
      <td>No</td>
      <td>✓</td>
      <td>Basic</td>
    </tr>
  </tbody>
</table>

Meltwater stands out as a leader for brands that seek to connect TikTok monitoring data to their broader media ecosystem. The Meltwater platform is designed for large-scale organizations that require a unified view of trends and conversations occurring across all social media, news, and more. On TikTok, brands can monitor mentions, track hashtags, measure engagement, and understand audience sentiment.

Unified dashboard: View TikTok metrics alongside Instagram, LinkedIn, and even offline news mentions.

Trend detection and performance insights: Identify emerging content trends, track brand mentions and campaign hashtags, and analyze TikTok conversations to understand what's resonating with audiences.

Sentiment analysis: Use AI-driven natural language processing to categorize mentions as positive, negative, or neutral.

Best for: Comprehensive media intelligence and global social listening

TikTok trends can emerge and disappear in a matter of days, often making it difficult for brands to keep up with audience conversations, creator activity, and competitor movements. 

Meltwater helps organizations transform conversations and trends happening on TikTok into actionable intelligence by combining social listening, consumer intelligence, AI-powered analysis, and executive-ready reporting in one unified platform.

Meltwater offers customized enterprise pricing based on organizational needs, monitoring requirements, and platform capabilities. 

Contact the Meltwater team for a personalized demo and pricing consultation.

Brandwatch is a powerhouse in data science and consumer research. It is specifically built for analysts who want to dive deep into the "why" behind consumer behavior on TikTok.

Consumer research suite: Access a massive historical archive of TikTok data to identify long-term shifts in consumer interests.

AI-driven alerts: Receive automated notifications when your brand experiences an unusual spike in TikTok mentions.

Influencer identification: Advanced filtering to find creators who actually align with your brand’s audience demographics.

Best for: Enterprise-level social listening

Brandwatch has become one of the most widely used consumer intelligence platforms among global brands because of its ability to process large volumes of social data and surface meaningful audience insights. 

For organizations looking to understand not just what is happening on TikTok but why it is happening, Brandwatch provides robust listening and analytics capabilities.

Pricing is bespoke and tiered based on the number of mentions tracked and the specific modules selected.

If your goal is to manage your TikTok presence alongside your publishing calendar, Sprout Social provides the most seamless experience for mid-to-large marketing teams.

Smart Inbox: Consolidate TikTok comments and mentions into a single stream for rapid community management.

Automated reporting: Generate presentation-ready PDF reports that highlight TikTok growth and engagement trends.

Listening queries: Set up specific keyword listeners to monitor industry conversations.

Best for: Comprehensive social media management

Sprout Social is popular among marketing teams that want to combine publishing, engagement, and analytics in a single platform. Its TikTok analytics capabilities are especially useful for brands managing multiple social channels and looking to connect content performance with broader social strategies.

Plans typically start around $199 per user/month, with higher tiers for advanced listening and premium analytics.

Pentos is one of the few tools built from the ground up specifically for TikTok. It focuses heavily on the "viral mechanics" of the platform.

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TikTok Blog

The Future of BookTok: What 1.7 Billion Engagements Reveal

10 Best TikTok Monitoring Tools for 2026

Influencer Marketing Costs 2025: Influencer Rates per Channel

The Top Branded Influencer Posts of Coachella 2026

Social Media News: The 5 Biggest Stories of the Week

The Best TikTok Hashtags For More Views

45 TikTok Stats You Need To Know [2026]

What's Trending? The Top TikTok Trends for 2026

How to Schedule TikTok Posts for Maximum Engagement

How to Make Money on TikTok: A Comprehensive Guide

TikTok Advertising Guide: 9 Steps To Creating TikTok Ads

When is the Best Time to Post on TikTok in 2025?

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