{"id":240803,"date":"2025-08-19T07:28:33","date_gmt":"2025-08-19T07:28:33","guid":{"rendered":"https:\/\/monday.com\/blog\/?p=240803"},"modified":"2026-03-12T06:15:56","modified_gmt":"2026-03-12T11:15:56","slug":"sentiment-analysis-tools","status":"publish","type":"post","link":"https:\/\/monday.com\/blog\/crm-and-sales\/sentiment-analysis-tools\/","title":{"rendered":"Sentiment analysis tools explained + 5 platforms to consider"},"content":{"rendered":"","protected":false},"excerpt":{"rendered":"","protected":false},"author":212,"featured_media":248769,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"pages\/cornerstone-primary.php","format":"standard","meta":{"_acf_changed":false,"_yoast_wpseo_title":"Sentiment Analysis Tools: 5 Top Options To Use In 2026","_yoast_wpseo_metadesc":"Sentiment analysis tools allow teams to detect positive and negative emotions in digital text. Here\u2019s how it works and the best tools to use for your business.","monday_item_id":10045816876,"monday_board_id":0,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[13913],"tags":[],"class_list":["post-240803","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-crm-and-sales"],"acf":{"parse_from_google_doc":false,"content_doc":"

Sentiment analysis tools explained + 5 platforms to use in 2025<\/span><\/h1>\n

Whether or not you notice it, there\u2019s a lot of emotion behind every customer interaction. Sometimes emotions can be hard to detect, and other times it\u2019s clear to see when a client is elated or extremely frustrated. That said, your team likely doesn\u2019t have the time to spend sorting through hundreds or thousands of interactions to detect individual emotions. That\u2019s where sentiment analysis tools come in.<\/span><\/p>\n

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Sentiment analysis tools take the manual guesswork out of tracking customers\u2019 emotions towards your company, product, service, or brand. With sentiment analysis tools, organizations can skip ahead to the underlying emotion in a customer\u2019s communication, helping teams make decisions that impact customer loyalty, satisfaction, and even revenue opportunities.<\/span><\/p>\n

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In this article, we\u2019ll go deeper into what sentiment analysis is and how it works, while also looking at a few of the leading sentiment analysis tools, including how a platform like monday CRM can help teams turn sentiment into actionable insights.<\/span><\/p>\n

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CTA<\/span><\/p>\n

What are sentiment analysis tools, and why are they important?<\/span><\/h2>\n

Sentiment analysis involves using software, algorithms, and AI to analyze digital text and interpret emotions. Tools for sentiment analysis help teams accomplish this automatically so that they can analyze sentiment, tone, emotions, and intention in texts like emails, social media comments, call or chat transcripts, and online reviews.<\/span><\/p>\n

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These tools rely on artificial intelligence and machine learning models to pick up on and categorize natural language based on emotions expressed in text, whether they\u2019re positive, negative, or express joy or frustration.\u00a0<\/span><\/p>\n

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Sentiment analysis tools are becoming indispensable to all kinds of businesses since they help companies get closer to their customers by understanding how they feel about their brand, experience, or products.\u00a0<\/span><\/p>\n

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Armed with sentiment data, organizations can get a complete picture of how audiences really feel, offering a more complete picture when it comes to customer feedback and brand reputation.<\/span><\/p>\n

Understanding the different types of sentiment analysis<\/span><\/h2>\n

Sentiment analysis tools do more than just determine if a text is positive or negative. These tools use smart features to detect specific emotions and intentions, giving teams a clear path on how to intervene or improve certain experiences. Here\u2019s a look at the four core types of sentiment analysis:<\/span><\/p>\n

Fine-grained analysis<\/span><\/h3>\n

Fine-grained analysis involves dividing text into emotions that go beyond \u201cpositive\u201d or \u201cnegative\u201d to get to all the grey zones in between. Generally, this type of analysis rates text sentiment on a wider sliding scale, where different metrics represent whether sentiment was very positive, positive, neutral, negative, or very negative.\u00a0<\/span><\/p>\n

Aspect-based analysis<\/span><\/h3>\n

With aspect-based analysis, tools will focus on pinpointing the sentiment of a product or service\u2019s specific feature. This helps companies hone in on how customers feel about each element individually. For example, a company might use aspect-based analysis to understand how software users feel about a recent update.\u00a0<\/span><\/p>\n

Emotion detection<\/span><\/h3>\n

Aside from determining whether a text is positive or negative, sometimes organizations want to understand more specific emotions and understand the person\u2019s psychological state when they wrote a text. Emotion detection works to identify more complex feelings, such as anger, regret, frustration, joy, or surprise.\u00a0<\/span><\/p>\n

Intent analysis<\/span><\/h3>\n

Intent analysis takes things a step further by determining the sentiment and then attempting to decipher a user\u2019s intent behind what they wrote. For example, if a user wrote an email to a company complaining about the checkout process on their website, an intent analysis tool might pick up on the fact that the user\u2019s goal was to complete a purchase.<\/span><\/p>\n

AI and automations features for deeper insights<\/span><\/h2>\n

Sentiment analysis relies on AI to capture emotions and insights from digital text. There are certain AI and automation features that most sentiment analysis tools offer, and others that you should look for when considering different solutions. Below, we\u2019ll look at some critical features and AI automations to seek out in sentiment analysis software.<\/span><\/p>\n

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