10 Best Sentiment Analysis Tools in 2025 (By Use Case)
Sentiment analysis is the process of analyzing natural language to interpret how individuals feel about a brand, product, or service.
Companies can choose to analyze sentiment in many different ways, including via customer interactions, surveys, reviews, and social media posts.
However, how you do so will vary depending on the kinds of data you need. For instance, call centers generally need to analyze customer interactions to understand how customers feel about their brand and products, identify recurring pain points, and uncover opportunities to improve service quality and agent performance.
Meanwhile, marketing teams require a tool with social listening capabilities to analyze what people are saying about their brand across social platforms, forums, or review sites.
In this guide, we explore the 10 best sentiment analysis tools for use cases in customer service and marketing. We begin with our own solution, Level AI, which analyzes customer interactions to identify sentiment, intent, and recurring issues, and improves the customer experience for QA and customer service teams.
Table of Contents
- What to Look For in a Sentiment Analysis Tool
- Top Sentiment Analysis Tools for Customer Service
- Top Sentiment Analysis Tools for Sales & Marketing
What to Look for in a Sentiment Analysis Tool
Choosing the right sentiment analysis tool means knowing which capabilities actually make a difference. Some solutions offer only surface-level insights, while others deliver a deeper understanding of customer emotions and intent.
Look for a sentiment analysis tool that:
Uses AI to Interpret Meaning Instead of Keyword-Matching Rules
Basic sentiment analysis tools rely on rule-based algorithms to detect keywords, such as flagging words or phrases like “unhappy” or “don’t like” as negative sentiments. While this works for surface-level analysis, it often misses the full picture.
These tools can’t interpret context, tone, or sarcasm, so they frequently misclassify how a customer is actually feeling.
On the other hand, AI-powered conversation analytics software uses natural language understanding (NLU) and generative AI to understand the meaning and context of what's being said during a conversation.
When you use a basic tool that relies on keyword matching, you’ll need to manually enter a long list of specific words and phrases you want the system to catch. But even if you're willing to enter hundreds (or thousands) of keywords, these tools can still miss nuanced customer emotions like sarcasm, confusion, or passive frustration.
An AI-based system recognizes tone, intent, and linguistic patterns. They can detect a subtle sentiment shift in a single sentence, changes in emotion throughout a conversation, and the overall mood of an interaction.
This ability to accurately gauge how customers are feeling allows businesses to spot problems early, respond with more empathy, and take proactive steps before a negative experience turns into churn.
Captures Both Sentiment Direction and Underlying Emotion
Most basic sentiment tools only detect sentiment direction, like whether a feeling is positive, negative, or neutral. Some might also detect intensity (e.g., mildly negative vs. very negative), but that’s still a superficial view.
What they miss is the underlying emotional state driving that sentiment reading.
Advanced artificial intelligence systems go beyond polarity and intensity to detect specific emotions like confusion, frustration, excitement, disappointment, or relief. This emotional depth provides more accurate and actionable insight into how a customer is really feeling.
For example, a statement like “I finally got it to work” might appear positive. But a more advanced tool may recognize relief as well, and the underlying frustration preceding it.
By capturing both what’s being said and how a customer feels, these tools help teams respond more appropriately, tailor their messaging, and proactively fix issues to improve both call center efficiency and customer experiences.
Tracks Sentiment Across Various Channels
For sentiment analysis to be effective, it must reflect the entire customer experience rather than just isolated moments. That’s why it’s critical to include all relevant channels in your call center tracking system software.
For customer service teams, this means analyzing sentiment in:
- Phone calls and transcripts
- AI agent interactions
- Live chat interactions
- Emails
- Helpdesk and support tickets
- Agent notes or CRM entries
Since customers often interact with brands using multiple touchpoints, observing how sentiment changes across channels provides a more comprehensive picture of satisfaction, frustration, or urgency. It also helps prevent escalations or recurring issues before they happen.
For marketing teams, multi-channel coverage includes:
- Social media platforms (X, Facebook, LinkedIn, TikTok, etc.)
- Customer reviews and public comments
- Online forums and Reddit threads
- News sites and blog mentions
This enables teams to track how people talk about their brand naturally, spot emerging trends, and act quickly if sentiment shifts in the market.
Top Sentiment Analysis Tools for Customer Service
Solutions in customer support allow faster issue resolution and personalized support, and are designed to track emotions across interactions, identify at-risk customers, and guide agent coaching:
1. Level AI
Level AI uses natural language understanding, semantic intelligence, and generative AI to analyze 100% of customer interactions across all channels to accurately detect emotion and intent in real time.
Unlike standard sentiment tools that rely on limited keyword matching or survey-based CSAT scores, our platform delivers actionable sentiment insights without needing post-call surveys or manual scoring for individual interactions.
Level AI provides:
- Accurate sentiment detection that goes beyond simple labels to identify nuanced emotions like disappointment, admiration, frustration, and gratitude.
- Sentiment tracking and emotion tagging for every interaction (also in real time), allowing managers to see how customer mood evolves throughout a call.
- Customizable dashboards and contact center automation tools to track sentiment trends, recurring emotional patterns, and agent performance across all support channels.
- AI-powered evaluation tools that use sentiment insights to pinpoint coachable moments and guide agent development.
Level AI’s ability to analyze emotion starts with automatic speech recognition (ASR), which transcribes voice interactions into structured text, using models trained on real-world customer conversations, not generic voice data.
The software uses ASR and NLU to detect intent with near-human accuracy and determine what a customer actually wants or is feeling.
Our platform also integrates such features in its AI Virtual Agent, which uses underlying conversational intelligence software by Level AI to handle routine customer inquiries with empathy, precision, and contextual awareness.
Below, we’ll show you how our software detects call drivers and helps support teams act faster, reduce escalations, and improve the overall experience.
Detecting What Customers Want
Level AI’s Scenario Engine identifies what a customer or agent wants to know or accomplish when they express certain words and classifies these as scenarios.
For example, a customer might say, “My card was declined,” or “The subscription is too expensive,” and the system classifies these as a Billing Issue.
Level AI includes a library of predefined scenarios (such as “Connection Issues” or “Delivery Problems”) and also allows teams to create custom tags tailored to their specific business needs.
You can also create your own custom scenarios that are relevant to your business:
Every scenario is automatically tagged within conversations via conversation tags, searchable and filterable for matching conversations where a certain intent was expressed. Users can also link tags together with other performance metrics, like CSAT, resolution time, and agent handling quality for deeper analysis.
This level of intent detection turns thousands of unstructured conversations into actionable data. Support leaders can quickly spot patterns and take steps to fix product gaps, retrain agents, or escalate engineering fixes.
Accurately Gauging Sentiment to Know How Customers Feel
Level AI detects the broadest range of emotions of any software in its category, including:
- Anger
- Annoyance
- Disapproval
- Disappointment/Sadness
- Worry
- Happiness
- Admiration
- Gratitude/Appreciation
The system also marks moments throughout conversations where sentiments occur with sentiment tags. These tags serve as a useful reporting tool, as they can be searched on to locate specific interactions where certain emotions were expressed.
Beyond simply detecting emotions or identifying those moments within a conversation, our software also assigns an overall Sentiment Score that reflects the emotional tone and intensity of an interaction, ranging from 0 to 10, where 0 signifies a highly negative sentiment and 10 indicates a highly positive one.
Each score is calculated by weighting emotions detected throughout the conversation, placing greater emphasis on sentiments expressed at the end. These are considered to more accurately reflect a customer’s lasting impression of the resolution provided and their overall feelings towards the brand.
Using both Sentiment Score and sentiment tags, organizations can instantly analyze and come to conclusions about customer sentiment based on customer interactions. This also provides a more complete view of the customer experience that standard CSAT surveys might miss.
Uncovering Coachable Moments
Customer service teams typically rely on random sampling to manually review 1–2% of recorded calls to identify coaching opportunities.
While this might catch the occasional agent mistake, it sometimes overlooks broader behavioral patterns, recurring issues, or subtle moments where customer experience might have been improved.
Level AI’s broad and automatic analysis of customer interactions instantly surfaces coachable moments for you, without you having to manually comb through recorded conversations for clues.
This advanced sentiment analysis pinpoints specific moments where customer frustration spikes or satisfaction dips, directly revealing where an agent's behavior or communication style could be improved.
As we’ve already discussed, sentiment tags indicate emotional shifts in conversations, making it easy to spot where an agent did well or may need improvement. But beyond highlighting emotional cues, our software also provides direct performance assessments with InstaScore, a system powered by agent rubrics and metric tags. These represent specific agent behaviors and customer interaction outcomes, such as:
- How quickly an agent responds once a ticket is triggered.
- Periods of silence that suggest the agent is avoiding the call.
- Average agent talk speed or agent overtalk.
- Whether an agent demonstrated a strong understanding of the customer’s issue.
Each conversation receives an overall InstaScore (expressed as a percentage value) displayed next to the Sentiment Score in the call center analytics dashboard, providing supervisors with an immediate snapshot of agent performance and customer sentiment for every interaction. This allows them to quickly determine if follow-up coaching is necessary without having to listen to full calls unless the data indicates a deeper issue.
Level AI also offers InstaReview, which automatically flags conversations for review based on specific criteria, including a high number of requested assists, longer-than-usual call durations, or low satisfaction scores.
See our most recent article on how to improve quality assurance in a call center.
These features are typical for post-call analysis, but our system also offers live features. With Real-Time Manager Assist, you can monitor calls in progress with live sentiment score, InstaScore, and Coachable Insights, and take immediate action, as shown in the dashboard below:
See our latest article on how to monitor call center performance.
Find Recurring Issues and New Sentiment Trends with Voice of the Customer (VoC)
As mentioned already, traditional sentiment analysis (like post-call surveys or generic CSAT forms) often misses the mark because they feature low participation rates, response bias, and limited emotional insight. As a result, businesses are left with an incomplete view of how customers truly feel and why.
Level AI analyzes VoC signals straight from actual interactions — calls, chats, emails, and tickets. There’s no need to wait for a customer to fill out a survey or log a complaint.
Our system detects trends relating to a variety of customer analytics use cases. For example, our system might indicate a spike in negative sentiment tied to a newly released feature, or recurring complaints in conversations about slow response times.
Level AI’s Voice of Customer Insights shows such trends for you to take the next steps to potentially improve the customer experience. All of this data is visualized in Level AI’s intuitive VoC dashboards:
Also, our reporting and analytics dashboards allow users to filter sentiment trends by topic, time period, or support channel, or break down negative sentiment by agent, team, or queue to pinpoint where improvements are most needed.
Level AI's Inferred Customer Satisfaction (iCSAT) provides a holistic, inferred measure of customer satisfaction across an entire interaction and ranges from 1 (very dissatisfied) to 5 (very satisfied); it’s derived from three components:
- Sentiment Score: Evaluates the emotional tone, including signals such as frustration, relief, or gratitude.
- Resolution Score: Measures the extent to which the customer’s issue was fully resolved during the interaction.
- Customer Effort Score: Identifies moments when customers were forced to repeat themselves, explain context again, or follow confusing steps.
You can use both iCSAT and our voice of customer tools to spot and address systemic process issues that frustrate customers. Additionally, teams can identify agents who may need targeted coaching before these impact satisfaction scores, or connect sentiment trends to key metrics such as revenue or churn.
Ready to optimize your organization's sentiment analysis capabilities? Schedule a demo today to see how Level AI automates the entire workflow.
2. Medallia
Medallia is an enterprise customer experience platform that captures and analyzes experience signals across every touchpoint to understand customer sentiment at scale.
It combines structured and unstructured feedback, behavioral cues, and real-time signals into a unified view of customer emotion.
Medallia's key features include:
- Speech and text analytics combined, with real-time transcription layered with emotion and intent scoring.
- Behavioral signal intelligence, detecting frustration, confusion, and satisfaction from how something is said, not just what’s said.
- Custom topic and theme detection, helping teams track sentiment trends around product issues, policy changes, or agent behavior.
- Actionable alerts, triggered when negative sentiment or emotion thresholds are crossed, allowing for timely intervention.
Medallia is built for large organizations that require custom plans. Pricing is not available publicly.
3. Qualtrics XM Discover
Qualtrics XM Discover is an unstructured data analysis engine that uses natural language processing and machine learning to interpret sentiment, emotion, and intent from customer support conversations.
It brings advanced voice analytics into the CX workflow, helping organizations improve service quality and loyalty.
Notable Qualtrics features include:
- Omnichannel sentiment analysis, including speech-to-text processing for call center conversations.
- Emotion and effort scoring, capturing not just what’s said but how it’s said.Topic detection and driver analysis to uncover what’s truly impacting satisfaction.
- End-to-end CX integration, allowing sentiment data to feed into broader experience management initiatives.
Qualtrics offers custom pricing only for the XM Discover platform.
4. InMoment
InMoment is a customer experience platform that offers various tools for digital listening, customer feedback, and conversational intelligence.
The XI (Experience Improvement) Platform helps businesses link emotional signals directly to customer satisfaction, churn, and revenue impact.
Top InMoment features include:
- Integrated voice and text analytics, enabling sentiment analysis across call transcripts, tickets, and open-ended survey responses.
- Multilingual sentiment modeling, trained on native language data rather than translations for higher accuracy.
- Case routing and escalation, so emotionally charged conversations automatically trigger follow-up workflows.
InMoment offers custom pricing plans only for enterprise teams.
5. Thematic
Thematic is a feedback analytics tool that specializes in analyzing open-ended responses (like surveys, tickets, and chat transcripts) to extract actionable themes and sentiment patterns without the need for manual coding or tagging.
It’s built for CX and support teams looking to turn qualitative feedback into quantitative insight.
Key features for customer service teams include:
- AI-powered sentiment analysis that detects subtle emotional cues and tone.
- Dynamic theme discovery using unsupervised learning, uncovering patterns you didn’t know to look for.
- Custom taxonomies and tagging, tailored to your business language and needs.
- Easy-to-use dashboards for tracking trends over time and drilling into specific issues.
Thematic pricing starts at $25,000 per year with custom plans for enterprise teams.
Top Sentiment Analysis Tools for Sales & Marketing
Sentiment analysis helps teams gauge audience reactions to campaigns, content, and brand messaging across channels. These tools surface trends in customer opinions, flag emerging risks, and show valuable insights that drive more effective campaigns.
1. Brand24
Brand24 is an AI-powered social listening and media monitoring platform that offers real-time sentiment analysis. It helps businesses track and understand customer opinions across more than 25 million online sources.
It's a great tool for marketers who want to better gauge brand perception, identify influential voices, and quickly respond to customer feedback.
Key Brand24 features include:
- Brand monitoring across millions of online sources, including social media, blogs, forums, and news sites
- Real-time alerts for significant shifts in mention volume or sentiment
- Advanced reporting to track changes in sentiment, the emotional context of brand mentions, and other key metrics
Brand24 offers a 14-day free trial, with pricing starting at $149/month (billed annually). Enterprise plans are also available for $999/month (billed annually).
2. Brandwatch
Brandwatch is a consumer intelligence platform that uses AI and NLP to provide in-depth sentiment analysis across social media and online conversations.
The platform offers access to over 1.4 trillion posts, and regularly updates with approximately 496 million new posts added every day.
Beyond extensive coverage, the platform also provides:
- AI-powered sentiment analysis with emotion and intent categorization
- Deep audience segmentation by location, interests, profession, and online behavior
- Trend tracking tools to uncover emerging topics and viral moments in real time
- Social media monitoring and management capabilities
- Image insights to match photos associated with your brand
- Custom dashboards and reporting to visualize sentiment shifts over time
Brandwatch offers custom pricing based on your data needs, number of user seats, and required enterprise features.
3. Meltwater
Meltwater is a media intelligence and PR software that combines media monitoring with sentiment analysis and competitive insights.
It’s built for marketing and comms teams who need both media coverage tracking and customer sentiment data. Additionally, it offers various tools for sales intelligence, social media management, and influencer marketing.
Key Meltwater features include:
- Sentiment analysis across 242 languages, covering social media, news, blogs, and even broadcast media, with spam filtering for reliable data.
- Automated sentiment tagging for brand mentions and earned media.
- Competitive benchmarking and share-of-voice tracking.
- Custom reports and alerts to keep teams aligned on brand health.
No pricing options are listed publicly. Meltwater offers custom enterprise plans only.
4. Talkwalker
Talkwalker is an enterprise social listening and analytics platform that helps brands track and understand what consumers are saying online.
It helps marketing teams monitor online conversations across 150 million data sources, including social media, blogs, forums, and news sites.
Top Talkwalker features include:
- Real-time social listening and monitoring across multiple online channels
- Visual and text-based analysis, including logo detection and aspect-based sentiment analysis
- Social benchmarking to compare your social media performance against your competitors
Talkwalker pricing is not available online. Interested users need to request a demo because they currently only offer customized pricing plans.
5. Mention
Mention is a real-time media monitoring tool that helps brands track online conversations and analyze sentiment across web and social channels.
It’s designed for marketers, PR teams, and agencies looking to monitor brand reputation and respond quickly to audience feedback.
Key Mention features include:
- Real-time monitoring of over 1 billion sources, including Facebook, Twitter, Instagram, TikTok, Reddit, and millions of blogs and news sites.
- Competitive benchmarking to compare your share of voice, sentiment, and engagement metrics against industry rivals.
- Collaboration tools, including the ability to assign mentions, create tasks, and export reports across teams.
Mention offers a 14-day free trial, with paid plans starting at $49/month. Higher-tier plans include historical data, API access, and advanced export and reporting features tailored for agencies and enterprise teams.
Uncover How Customers Actually Feel with AI-Powered Sentiment Analysis
Level AI goes beyond simple keyword matching and post-call surveys to reveal the true emotions behind every customer interaction. Identify recurring customer trends, changes in sentiment, and how customers perceive your brand across various channels.
Book a demo today to see how Level AI helps you understand your customers with deeper insights.
