Social Listening
& Monitoring

Social listening and monitoring is the backbone of social intelligence. It enables you to track and analyse online conversations about your brand, products and other relevant trends and topics.

Highlights

In 2025, this goes far beyond just text in social media mentions. With innovations in audio transcription and detection and image recognition, these tools now help practitioners access richer, more context-aware signals. Tools in this category offer features including sentiment analysis, reporting and alerts which helps your whole organisation stay informed.

This category includes:

Social Listening

Social Media Monitoring

Image Intelligence

Social Audio Intelligence

Social Video Intelligence

Review Analysis & Management

Search Intelligence

Hashtag Tracking

Media Monitoring

Social Listening

Social Listening tools help you to monitor, analyse and draw insights from social media conversations and mentions about your brand, product, competitors or the wider industry. These tools do more than social media monitoring as the advanced analytics, sentiment analysis and data visualisation features help you understand the broader impact of online conversations. With this, you can learn more about your target audience and competitors, and you’ll be able to track emerging trends more easily.

Brand health monitoring: Track social media mentions about your brand, products or services to gauge overall brand sentiment and spot potential crises before they happen. This is also helpful to measure the impact of your marketing and PR efforts.

Competitor analysis: Monitor and analyse social media conversations and sentiment related to competitors, their products and any of their marketing campaigns. This gives you a benchmark to measure your performance against and helps you keep an eye on potential threats or opportunities.

Audience insights: Analyse social media data to understand your target audience better to create more targeted and personalised marketing campaigns and improve the customer experience.

Trend identification: Identify emerging trends, topics and conversations relevant to your industry or target audience by analysing social media data over time. This helps you stay ahead of the curve and adapt your strategy to make sure what you’re sharing with your audience - either content or a new product - is relevant.

Influencer and KOL mapping: Find influencers or brand advocates that can help you amplify your message to new audiences based on their social media presence, reach, thought-leadership, engagement and relevance.

Use Cases >

Featured Tools

Social listening is considered a foundational element of social intelligence. It enables brands to quickly gather and analyse social data at scale to understand a whole range of consumer behaviours that can help you make more strategic decisions. Whilst social listening technology has been around for a while, it’s developing rapidly and we’re starting to see some exciting developments in this space, particularly as AI continues to be integrated. We caught up with omniOsocial, a multimodal AI social listening platform that helps brands understand and engage with their audiences better, to learn how they see this technology evolving.

What types of thinking or decisions do social listening tools make possible that wouldn’t happen without them?

“Social listening tools with advanced AI for audience insight and trend detection help uncover real-time sentiment, emerging topics, content trends, and hidden audience dynamics. This enables smarter decisions across brand positioning, influencer selection, campaign timing, and content strategy. For example, one of the most critical needs in marketing, especially in B2B, is identifying and reaching the right audience because decision-makers are often harder to access. Traditional methods focus on surface-level metrics, such as mention volumes or sentiment scores. Now, teams can go deeper by understanding who is engaging, what roles they hold, which industries they represent, and how they respond to specific content.

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On LinkedIn, this supports more targeted and effective campaigns that reflect real audience behavior and intent. As digital interactions become increasingly fragmented and visual-first, analyzing both structured and unstructured data, including video, images, and platform-specific behavior, is essential for maintaining marketing relevance and performance.”

What’s a moment where you saw a client truly realise the strategic value of social data and what changed for them after that?

“Recently, one of our clients – a global pharmaceutical company – was relying on traditional social listening tools that focused primarily on mentions and sentiment, with limited visibility into audience insights or visual content. This restricted their ability to uncover deeper behavioral patterns. Their perspective shifted when we introduced our AI-powered social intelligence platform, delivering rich vision insights and audience-level intelligence, including demographic insights (location, age-groups, etc), engagement behaviors, and platform-specific trends. On LinkedIn, they discovered high-value audience segments based on profession and seniority. This unlocked more tailored, high-impact marketing campaigns, stronger audience engagement, and transformed their approach from surface-level monitoring to strategic, data-driven execution.”

What’s the most common blind spot in how organisations approach social data and what does it cost them?

“Over 70% of today’s social content is visual, including videos, images, and rich media, yet many organizations still rely on legacy text-based tools. This creates a critical blind spot, as these tools overlook visual signals, video engagement trends, and platform-specific audience behaviors. Visual content is no longer limited to platforms like YouTube or TikTok. LinkedIn now features a growing volume of video and image-led posts that drive meaningful engagement among professional audiences. One of our recent clients uncovered a surge in engagement from senior professionals on LinkedIn video posts. This insight led them to realign their messaging and focus targeting efforts on high-value decision-makers. Without vision insights or historical, context-rich data, brands are left making reactive and incomplete decisions. This blind spot ultimately weakens campaign performance, limits innovation, and leads to missed opportunities in competitive digital environments.”

What future capability in social listening do you think will feel obvious in 5 years but is misunderstood today?

“In five years, intelligent, brand-aware AI agents (human-like assistants) will be essential to social listening, acting not as tools but as adaptive collaborators. Most current systems rely on generic GPT-like chat interfaces, which lack personalization, brand context, and privacy safeguards for sensitive data. What’s misunderstood is the shift toward agents that learn from internal signals, align with business goals, and autonomously surface insights across visual and text data. These agents will interpret audience behavior, anticipate shifts, and trigger responses in real time. A privacy-first architecture and brand-level customization will no longer be differentiators, they’ll be expected foundations for trusted social intelligence.”

these tools overlook visual signals, video engagement trends, and platform-specific audience behaviors. Visual content is no longer limited to platforms like YouTube or TikTok. LinkedIn now features a growing volume of video and image-led posts that drive meaningful engagement among professional audiences. One of our recent clients uncovered a surge in engagement from senior professionals on LinkedIn video posts. This insight led them to realign their messaging and focus targeting efforts on high-value decision-makers. Without vision insights or historical, context-rich data, brands are left making reactive and incomplete decisions. This blind spot ultimately weakens campaign performance, limits innovation, and leads to missed opportunities in competitive digital environments.”

What future capability in social listening do you think will feel obvious in 5 years but is misunderstood today?

What problem are you building toward solving that most people in the industry still don’t see clearly?

“We’re building toward a secure, privacy-first AI future powered by human-like personal AI assistants (cognitive AI agents) designed to help organizations derive deep social insights without compromising data control or regulatory compliance. Most current solutions depend on public AI models like ChatGPT, which pose significant security risks, particularly for regulated industries such as pharma, finance, and government. Our focus is on secured and personal AI agents that operate safely within client environments, combining internal data with external social signals to deliver contextual, real-time intelligence. As privacy, trust, and customization become central to enterprise AI adoption, we’re addressing a critical gap the industry is only beginning to recognize: the need for secure, personal brand-aligned AI assistants.”

Raj Muppala

CEO & Founder

omniOsocial

What problem are you building toward solving that most people in the industry still don’t see clearly?

Raj Muppala

CEO & Founder

omniOsocial

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YouScan is an AI-powered social listening platform that helps marketers, researchers and PR professionals understand consumers better by providing insights into what they say and do. They see social listening and monitoring as a way to help analysts move from anecdotal observations to structured, data-based insights. That includes anything from tracking sentiment and brand health over time and across different audience segments to spotting emerging trends before they show up in traditional research or media.

According to Alex Orap, Founder & Chief Growth Officer of YouScan, “social listening gives social intelligence professionals a faster, deeper, and more nuanced understanding of their audience, and the market.” Compared to other business intelligence tools, social listening technology can process noisy and unstructured data - such as data from online customer review platforms - more easily. Advanced tools in this category go further, extracting signals from the noise to help reveal actionable insights.

YouScan work with many clients in this area. American fast food chain, White Castle, used social listening when developing their new app to track customer response and quickly identify any problems. They monitored sentiment changes before and after the update to identify trends in how customers felt about the new experience which could be passed on to the app development team. They were also quickly able to identify glitches and their relevant impact to be able to prioritise them efficiently. These insights were shared across teams via a dedicated dashboard that monitored app reviews.

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Visual listening: An opportunity to seize

Whilst text-based social listening is very common for tracking customer opinions - as this example shows - there’s an opportunity that many are missing. Visual listening. This approach helps uncover massive volumes of brand mentions in social media images where the brand logo appears, even without text. With advanced AI image analysis, brands can also see how their consumers are interacting with their products in real life. This also gives them a deeper understanding of their customers’ needs and pain points. According to Alex, by ignoring this, “A lot of brands still leave value on the table when it comes to how they use social listening.”

And when it comes to developments within the Review Analysis & Management subcategory, the increased integration of AI - specifically GenAI - in recent years has made it easier for non-experts in data analysis, such as those working in customer experience, to get more out of social data, according to Alex. For example, YouScan’s Insight’s Copilot is a conversational AI agent that allows users to ask questions of the data using natural language. The aim of this is to make generating insights more accessible.

The trend towards increased AI-powered and AI-native technology is clear in this year’s SITech market landscape. YouScan are also exploring this area more deeply too, as their customers increasingly demand new features and ways to integrate it into

There’s a lot of value to be extracted from by analysing customer reviews. The growing focus on AI-powered listening across this category, particularly across different media types, should help social intelligence professionals get more from the data that’s available, enabling them to generate more impactful insights to their business.

their workflows. They plan to continue developing AI-powered features, focusing on making it easier for teams to work together better and faster. For example, better collaboration tools and more customisable dashboards. They’re also looking at how to make it easier for users to combine different data types, incorporating reviews with other social data sources, to generate even more valuable insights.

Alex Orap

Founder & Chief Growth Officer

YouScan

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Social Media Monitoring

With Social Media Monitoring technology, you can track and analyse - in real time - conversations and mentions of your brand, products or relevant keywords across social media. These tools are the first step for understanding what people are saying about your brand or a specific topic.

Brand mention tracking: Monitor social media platforms for mentions of your brand, products or team members to quickly identify and respond to customer questions or complaints.

Keyword monitoring: Track specific keywords or phrases about your industry, competitors or marketing campaigns to stay up-to-date with relevant conversations and trends. This will help you join conversations with your target audience more naturally.

Social media engagement: Find opportunities to connect and share useful info with your customers, prospects or influencers by monitoring social media conversations and mentions. This can help create a community-feeling around your products or services.

Crisis detection: Monitor social media channels to spot potential crises that could impact your reputation and get real-time alerts to enable you to respond quickly. This can help you maintain trust and credibility.

Basic reporting: Create reports and dashboards that summarise key social media metrics so that you can track your social media presence, show the impact of engagement campaigns and improve your long-term marketing strategy.

Use Cases >

Featured Tools

Image Intelligence

These tools use machine learning (ML) techniques to analyse images from different online sources and find insights about the objects, scenes and emotions they contain. This information can help you understand how your brand’s visual content is perceived by your audience and how they engage with it. Image analytics is usually done alongside text-based content analytics, adding an extra dimension to help you understand your brand’s online presence better. In 2025, the shift towards multimodal AI (technology that analyses both text and visuals simultaneously) is driving innovation in this space. Tools are improving emotion detection, visual sentiment scoring and the ability to distinguish AI-generated imagery - a growing concern for trust and authenticity.

Visual brand monitoring: Track how visual elements of your brand - logos, products, packaging etc - are being used in user-generated content (UGC) across the internet to monitor brand consistency and find out when people are using your brand imagery without permission.

Synthetic content detection: Flag content that may have been generated by AI, which is increasingly important for brands working to build trust and transparency.

Visual trend detection: Discover emerging visual trends, such as popular image styles or filters, so that you can stay ahead of the curve and create visually appealing content that taps into what’s trending with your audience.

Emotion analysis: Analyse facial expressions or body language in images and videos to understand how audiences connect with visual content. This can help you create more emotionally engaging content.

Object and scene detection: Identify objects, scenes and actions shown in images and videos, such as products, locations or events to get a better understanding of how your products or services are being used or experienced by customers.

Use Cases >

Featured Tools

Social Video Intelligence

Like Social Video Analytics tools, Social Video Intelligence technology helps you understand how your audience consumes video content. However, these tools go further by using advanced analytics and ML techniques to extract insights by analysing visual and audio elements (including keyword mentions) and metadata. With this information, you can identify relevant trends and find opportunities to create more engaging video content tailored to your audience. You can also measure how this content impacts brand perception and consumer behaviour.

In 2025, more tools in this category benefit from deeper integrations with transcription technology, AI-native summarisation and tools that can detect patterns in video.

Video content analysis: Analyse the visual and audio components of video content that you share on social media, such as product demos or customer testimonials, to get an idea of how people are engaging with it.

Video trend detection: Discover emerging trends and topics in video content shared online, such as new video formats, popular themes or viral clips, to stay ahead of the curve and create video content that resonates with your audience.

Video influencer identification: Find influential video creators on social media based on factors like reach, engagement, and sentiment. This helps you understand the impact of influencer campaigns and manage influencer relationships better.

Video competitive analysis: Analyse video content shared by your competitors to benchmark your performance against them. With this info you can identify gaps and develop strategies to stand out and gain a competitive edge.

Audio-visual narrative tracking: Detect themes or topics that spread via video content and track their evolution, especially where voice plays a key role.

Use Cases >

Featured Tools

ViralMoment is an AI-powered, machine learning-driven social intelligence platform that helps brands extract insights from social video platforms like TikTok. The technology allows users to analyse content within videos, helping brands to understand what’s influencing an audience's beliefs, behaviours and purchasing decisions. This can help build a fuller picture of their customer needs and wants. As Elizabeth Arnold, Head of Growth at ViralMoment explains, “it's really important to be able to call out where your brand is showing up organically and authentically within the communities that truly resonate…being able to look inside of the video is the only way that you can do that.”

HUNTER, a user of ViralMoment, agrees that the benefits of social video analysis are huge. They used it to monitor, in real-time, a brand crisis for one of their clients, and report on the potential impact on their reputation.

Michael Lamp, Chief Digital & Social Officer at HUNTER explains, using a social video analysis tool like ViralMoment, “allowed us to share a different type of analysis every day. We weren’t just saying, ‘here’s an updated chart with numbers,’ we were able to instead say, ‘here’s how the conversation is shifting from the initial thing we were concerned about to reveal the larger, more long-lasting brand threats, illustrating the real story behind the data. We were able to give our clients a much richer understanding of their consumers' thought processes and motivations.”

In this case, the client saw negative sentiment around their brand after a high-profile influencer created TikTok videos sharing a bad experience she’d had with the brand: after returning an item in one of their stores, she felt the service she received was very poor and decided to tell her followers about it.

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service she received was very poor and decided to tell her followers about it.

More than reporting, you get insights

Rather than engage with the influencer publicly, the brand monitored how the online conversation developed while also working to rectify the situation privately. HUNTER used ViralMoment, in particular the ChatterScore feature, to see how the conversations were evolving. This allowed them to track the velocity of the conversation in each video, giving them deeper insights into which content or themes were taking off, and which were stagnating. From this, they were able to share several insights with the client.

Firstly, by tracking conversations around the influencer’s content and those referencing the brand, they could see which posts had the most impact and which themes were resonating. This helped the brand understand where most damage could potentially be done, and where they should focus their communication efforts.

Secondly, after the videos from the influencer went viral, several people started creating copycat content, i.e. pretending that the incident had happened to them. This meant awareness of the brand and the issue spread to a whole new audience. Whilst these copycat creators were simply trying to ride the wave of the success of the original post, it highlights how disinformation can easily cause a crisis to escalate and spread further.

Finally, through ViralMoment, the team were able to see how the story spread to different social media platforms. As the original post went viral, other key personalities and news sites within the luxury and beauty spaces began reporting on the incident on their own channels on TikTok, YouTube and Instagram etc. By tracking the evolution of the story, the brand could understand the pace at which it was growing and where it was having the most impact. This enabled them to take action if it escalated too far.

team were able to see how the story spread to different social media platforms. As the original post went viral, other key personalities and news sites within the luxury and beauty spaces began reporting on the incident on their own channels on TikTok, YouTube and Instagram etc. By tracking the evolution of the story, the brand could understand the pace at which it was growing and where it was having the most impact. This enabled them to take action if it escalated too far.

Knowing where to look is half the battle

Ultimately, the brand decided not to engage publicly with any of the online content about the incident. By tracking the evolution of the story, they were confidently able to stay out of the conversations knowing they could join if necessary. Monitoring the entire lifecycle of the event - and the ChatterScore - to know when conversations were starting to recede, also helped them decide when to switch on other marketing campaigns without risk of a backlash. With the information they gathered through the crisis monitoring project, they were able to successfully launch their new products a few weeks later without any residual impact.

To be able to monitor these conversations and ensure you’re covering every aspect of a crisis and the themes that emerge, you need to know how to look for it. There are so many conversations happening across social video, it can be like looking for a needle in a haystack. It’s important to understand what you want to find out from the data.

Michael’s advice is, “You need to be specific with your objectives to be able to hone AI to the right data. It helps to know where to listen, so spend time on the front end. It will pay you back when you need it most.”

Elizabeth Arnold

Head of Growth

ViralMoment

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Social Audio Intelligence

A new category of tools has emerged to help researchers analyse what’s being said in audio content and how it’s resonating. Social Audio Intelligence tools enable you to monitor, search and extract insights from audio- and video-based content, especially when paired with transcript-based analysis. These tools analyse transcribed audio from sources such as podcasts, video audio tracks (inc. from video platforms like YouTube), broadcasts or live streams. With this technology, you can identify brand mentions, keyword frequency, sentiment shifts and emerging narrative all from formats that were previously difficult to monitor at scale.The rise of this category reflects a growing recognition that audio holds untapped potential for brand intelligence, cultural insight and reputation tracking.

Podcast and livestream monitoring: Track brand mentions, competitor references, or industry keywords within long-form audio content, including podcasts, YouTube audio transcripts or livestream platforms. This enables retrospective reputation monitoring in audio and video-first spaces.

Narrative trend detection: Identify emerging topics, ideas or language patterns (e.g., memes, slang) from regularly occurring audio segments (e.g., weekly shows, interviews, broadcasts) to spot shifts in how themes are discussed over time. This is perfect for cultural insight, media framing or issue tracking.

Campaign evaluation through earned audio: Analyse how marketing campaigns, product launches, or sponsorships are referenced in audio content, whether organically discussed by content creators or raised in interviews. Useful for measuring earned media in audio and video environments and YouTube commentary.

Mis-/Disinformation or narrative monitoring: Detect and trace the spread of problematic narratives or brand-related mis-/disinformation that may appear in audio commentary, especially in unmoderated or fast-moving formats. This helps with reputational risk management.

Use Cases >

Featured Tools

Review Analysis & Management

Review Analysis & Management tools can help you manage your brand’s online reputation and improve customer service. With this technology you can monitor, analyse and respond to customer reviews across platforms including Google, Yelp, TripAdvisor and industry-specific review sites, and prevent potential problems from escalating publicly.

Tools in this space are increasingly linking structured review data with unstructured social data, creating a more complete picture of customer sentiment. Some platforms now offer GenAI-powered auto-replies, while others feed insights into product development pipelines.

Review monitoring: Track customer reviews and ratings on one dashboard so that you can monitor your online reputation and quickly address any issues without having to manually check each review platform.

Review analysis: Use sentiment analysis and natural language processing (NLP) techniques to analyse customer reviews, find common themes and trends, and learn more about your customers’ experiences. This can help you develop better products, services and marketing strategies.

Review response management: Respond quicker to reviews with customisable response templates, workflows and collaboration tools to show how committed you are to customer satisfaction. These tools also help you keep your brand voice across review platforms.

Review generation: Encourage satisfied customers to leave reviews by sending automated follow-up comms with direct links to review platforms so that you can build a strong online reputation and attract more customers.

Reporting and insights: Create reports and dashboards that summarise key social media metrics to help you track the impact of your reputation management efforts and identify areas for improvement.

Use Cases >

Featured Tools

Yogi is a social intelligence platform that transforms raw feedback from sources such as product reviews, support tickets, surveys and social media into real-time, actionable intelligence. By going beyond the top-of-funnel buzz, brand mentions and cultural moments that general social listening captures, they help brands get product-level feedback and insights. This can be used across the business - from marketing to customer service to innovation teams - to create better products and services for consumers.

Brands use Yogi to help centralise and structure feedback, deliver specific product performance analysis, filter out noise and quantify shifting sentiment and emerging themes. Olly, a leading global health and wellness brand that is B-Corp certified and known for its gummy supplements, have been using the platform to improve their knowledge of consumer sentiment to continue innovating to meet customer needs.

The challenge: Unifying review data into a single source

One of their main challenges was that reviews and feedback were scattered across platforms and buried in unstructured formats, making it nearly impossible to extract reliable insights quickly. As Jennifer Peters, Director of DTC, MarTech and Digital Compliance at Olly explains, “We had data, but no real way to pull it together into something that helped us make decisions quickly. It lived in too many places.” They needed to connect the dots between consumer sentiment and product performance to improve decision making across the business.

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the business.

Their objectives when starting to use review analysis software were to:

Unify consumer feedback data from multiple sources
Make consumer insights accessible to different business teams
Increase speed to insight from days or weeks of manual research to real-time understanding
Validate product development and marketing decisions
Increase cross-function collaboration by democratising access to customer feedback

By customising the way they used Yogi to access feedback, each team was able to access the insights that they needed. For example, brand teams could focus on messaging cues while product teams could extract feedback about flavour and texture.

Quick, evidenced-based decision making

With these real-time insights, the team was able to quickly react to customer complaints and requests. For example, Olly started noticing scattered feedback about texture issues with their gummies. Several people reported that the gummies had melted into a single solid mass, usually when the weather was hot. By looking at reviews and feedback as a whole, they saw a consistent pattern around “melting” and “clumping”. This was also reflected in Customer Care feedback too, suggesting the issue was with the product itself,

rather than with a particular supplier. As a result, the team decided to reformulate the product. This was a major strategic decision, however being able to gather the data in real-time enabled them to make it confidently and quickly.

Overall, using a review analytics and management tool enabled Olly to:

Save time. As Sara Ellefson, Marketing Analytics Manager explained “Requests would come in last-minute and I’d have to manually pull review data from multiple sources. It took hours, sometimes days.” With the software, it can be reduced to minutes.
Make faster decisions with better outcomes by spotting consumer concerns earlier in the launch process
Improve confidence and alignment across teams by creating a single source of truth grounded on data
Gain a competitive edge by understanding features consumers like about other brands
Increased flexibility to respond to problems faster

Opportunities beyond customer sentiment

As Olly have experienced, review analysis platforms are great for helping with new product development and validation to identify taste and texture preferences or opinions about packaging; for highlighting language used by consumers that can be incorporated into product messaging; for tracking competitors and benchmarking

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sentiment around brand and products; and for monitoring performance, in particular around product quality and customer satisfaction. According to Sara, “there have been instances where we were able to leverage Yogi data to prevent us from going forward with something that might have been a costly mistake.”

However, there are several use cases where this type of technology is underutilised. For example, tracking consumer feedback can reveal new trends before they take off, such as emerging ingredients or new flavour combinations. It can also be used to alert you to potential product or service problems allowing you to take action before they escalate into a brand crisis, as Olly did with the melting gummies. Finally, it can encourage the whole organisation to take a consumer-first approach to their work by democratising access to review data. As Jennifer highlights, “We don’t have a huge insights team. We needed a tool that made every department feel empowered to go look for answers. Yogi made that possible.”

In today’s SITech stack, review intelligence is becoming a must-have. Unlike social media chatter, reviews reflect a specific moment of purchase or product usage, so brings additional context, intent and emotion linked to that experience. For consumer goods brands, this data is one of the most powerful and actionable sources of insight available.

Gautam Kanumuru

CEO & Co-Founder

Yogi

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Search Intelligence

Search Intelligence tools can help you refine social listening queries and track conversations by identifying keywords and phrases that are most relevant to your audience. This is done by providing insights into what topics people search for and the type of content they’re directed to. It can also show whether search trends match what people share publicly online. On top of this, you can use Search Intelligence technology to analyse search query data to improve your brand’s SEO and SEM strategies. These can increase visibility and website traffic.

Keyword research: Find the most relevant and high-traffic keywords related to your products, services or industry to create targeted content that ranks well in search engine results pages (SERPs) and attracts qualified traffic.

SERP monitoring: Track your search engine rankings for target keywords and competitors over time to measure how effective your SEO strategy is and find ways to stay ahead of the competition.

On-site search analysis: Analyse the search queries and behaviours of users on your website to understand what they’re looking for so that you can optimise your website's structure, content and navigation to improve usability and conversion rates.

Backlink analysis: Track the quantity and quality of backlinks pointing to your website from other domains to measure the effectiveness of your link-building strategies, find high-value link opportunities and spot potentially harmful or spammy links.

Search traffic analysis: Analyse search traffic to your website to understand who is coming from search and why, so that you can optimise your landing pages for a better user experience (UX).

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Featured Tools

Hashtag Tracking

Hashtag Tracking tools help you monitor and analyse how specific hashtags are used across social media platforms, and how they perform. With this technology you can track volume, reach, engagement and sentiment for each hashtag, which offer you an insight into audience perception of a particular topic or marketing campaign. Hashtag Tracking is a core feature of all Social Listening and Social Media Monitoring technology, but there are also standalone tools too.

In 2025, with the fragmentation of platforms, hashtag usage is diversifying. The best tools now offer cross-platform tracking, predictive virality scoring and AI-aided theme detection based on hashtag co-occurence.

Campaign monitoring: Track how branded or campaign-specific hashtags (e.g., from product launches, events or promotions) perform so that you can measure the success of these campaigns on brand awareness and sentiment and discover influencers.

Trend identification: Monitor relevant trending hashtags to discover new topics and find opportunities to engage with your audience in a more authentic way.

Competitor analysis: Analyse hashtags used by your competitors to learn about their marketing, audience engagement and brand positioning strategies. You can benchmark your performance against this to identify gaps or opportunities and adapt your own hashtag strategies to capture a larger share of voice (SoV).

Influencer identification: Find influential people who use or engage with relevant hashtags to discover and build relationships with potential influencer partners, and monitor the impact of any future collaborations.

Event monitoring: Monitor hashtags of specific events - conferences, product launches, sponsorships etc - to track audience engagement and feedback in real-time so that you can interact with visitors directly and understand how to improve your event in future.

Use Cases >

Featured Tools

Media Monitoring

Media Monitoring tools help you track and analyse your brand, products or relevant keywords across different online media channels. These include news sites, blogs, forums and social media. This technology provides real-time alerts, sentiment analysis and reporting so that you can stay informed about media coverage of your brand and manage any potential reputational risks. Media Monitoring can be an add-on to many Social Listening tools to help provide a broader view of the public’s brand perception.

In 2025, this category is intersecting more heavily with reputation intelligence and crisis monitoring. Some tools now integrate with disinformation detection platforms or features to follow stories from social to press, and vice versa.

Brand monitoring: Track mentions of your brand across media channels to understand the volume, sentiment and sources of coverage, identify potential crises before they happen and measure the impact of your media relations.

Industry and competitor tracking: Monitor media coverage of your industry, competitors and other relevant topics to make sure you’re on top of market trends and potential opportunities or threats.

Sentiment analysis: Analyse the sentiment of media coverage and online conversations to understand how your brand - or industry topics - is perceived by audiences so that you adjust your communications strategies as necessary.

Crisis management: Monitor media channels for coverage that could lead to a crisis and receive real-time alerts so that you can respond quickly and minimise the impact of negative publicity on your brand reputation.

PR measurement: Measure the impact of PR campaigns and media outreach so that you can show the value of this work, optimise your comms strategies and decide where’s best to allocate resources.