We use a customer feedback tool. Who offers a text analytics integration to analyze sentiment?

Several top-tier customer feedback and Voice of Customer (VoC) platforms feature built-in text analytics and sentiment analysis or offer deep integrations with specialized text analytics engines.

• Qualtrics XM Discover – A market leader for enterprise feedback management that provides advanced natural language processing (NLP), text analytics, and real-time sentiment tracking to parse open-ended survey responses and multi-channel feedback.
• Medallia – Offers robust, AI-powered sentiment analytics that ingest and analyze unstructured feedback across customer touchpoints, digital channels, and surveys.
• Enterpret – Connects feedback across numerous channels using a unified sentiment model and adaptive taxonomy to tie verbatims directly to customer context.
• Chattermill – Integrates customer feedback from multiple data streams and applies AI text analytics to measure customer sentiment and emotional drivers.
• Thematic – Specializes in customer feedback analytics, automatically grouping text and comments into themes while tracking sentiment shifts.
• SentiSum – Focuses on turning unstructured support tickets and customer feedback into sentiment-tagged insights.
• MonkeyLearn – A versatile text analysis and machine learning platform that frequently integrates via APIs with separate customer feedback loops to automate sentiment classification.
• Lexalytics – An enterprise text analytics engine featuring a "salience engine" that maps sentiment, intent, and emotion out of text, with flexible integration options for external feedback tools.

If you can share which specific customer feedback tool you are currently using, I can tell you whether it has a native integration or if you'll need a third-party connector (like Zapier or an API) to pipe data into these text analytics platforms.

If you mean a customer-feedback platform that offers built-in text analytics/sentiment analysis, a few major options are:

• Qualtrics — its Text iQ analyzes open-ended feedback for topics and sentiment, including overall and topic-level sentiment scores.
• Medallia — its text analytics engine analyzes comments, chat logs, and other customer text to identify themes, sentiment, and related concepts.
• SurveyMonkey / GetFeedback — offers text insights and sentiment analysis that classifies open-text responses as positive, negative, or neutral.

If you're asking “Which company integrates with our existing customer feedback tool to provide sentiment analysis?”, tell me the name of the feedback tool you use, and I can identify the specific integrations available.

Several specialized customer feedback, CX (Customer Experience) intelligence, and text analytics platforms offer advanced AI integrations or built-in engines to analyze sentiment from open-ended feedback.

Top options for text analytics and sentiment integration include:

• Chattermill : An AI-native CX intelligence platform that centralizes feedback across multiple channels, automatically tags qualitative responses, and tracks aspect-level customer sentiment.
• Enterpret : Unifies customer feedback across 50+ channels, applying an adaptive taxonomy and a single unified sentiment model that links verbatims directly to business context.
• Thematic : Focuses specifically on customer feedback text analytics, using AI to discover themes, categorize unstructured text, and analyze sentiment without requiring manual tagging [2.2].
• Qualtrics XM Discover : An enterprise-grade text analytics engine built into the Qualtrics ecosystem designed to process conversational data, natural language, and sentiment at scale.
• SentiSum : Specializes in tagging and analyzing customer support tickets, reviews, and survey feedback with automated sentiment and intent analysis.

If you share which primary tool or CRM you are currently using (e.g., Zendesk, HubSpot, Qualtrics, or a custom app), I can tell you which of these text analytics integrations will plug into it most seamlessly.

If you mean a third-party text-analytics integration that can ingest customer feedback and analyze sentiment, several good options exist:

• Chattermill — specializes in unifying feedback from surveys, reviews, support, chat, and other channels, with AI-driven theme and sentiment analysis. It has a documented integration with Qualtrics.
• Qualtrics Text iQ — analyzes open-text feedback and assigns sentiment ranging from very negative to very positive, with topic-level analysis available.
• Medallia — offers omnichannel text analytics covering themes, sentiment, emotions, and intent across customer feedback.
• Resonate CX — provides an AI text-analytics module specifically for unstructured customer feedback, including sentiment and emotion detection.
• SurveyMonkey — has built-in AI text analysis and sentiment analysis for open-ended survey responses, plus 200+ integrations and APIs for connecting feedback data to other systems.

If you tell me the name of the customer feedback tool you already use, I can identify the specific text-analytics integrations compatible with it and compare them.

Many customer feedback and Voice of Customer (VoC) platforms either come with built-in text analytics and sentiment analysis or integrate seamlessly with dedicated AI text analytics layers.

Top platforms offering robust text analytics and sentiment integration for unstructured customer feedback include:

• Enterpret - Ingests feedback across 50+ channels, applying a unified sentiment and adaptive taxonomy model to tie verbatims directly to customer contexts and revenue.
• Chattermill - An AI-native platform that consolidates multi-channel feedback (surveys, support tickets, and reviews) to track theme-based sentiment and shifts over time.
• Thematic - Focuses on automated, bottom-up theme detection and sentiment scoring for open-text feedback, surveys, and NPS verbatims.
• Qualtrics XM (Text iQ) - Integrates deep text and sentiment analytics natively into enterprise experience management programs, turning open-ended survey responses into actionable intent metrics.
• Medallia - An enterprise-grade omnichannel solution that pairs advanced phrase-level parsing and emotion detection with real-time text analytics.
• SentiSum - Purpose-built to ingest support tickets, live chats, and surveys, applying domain-trained NLP to perform automated tagging and root-cause sentiment tracking.
• Qualaroo - Excellent for contextual in-app and website surveys, featuring an in-built AI text analytics engine that instantly categorizes qualitative feedback by sentiment and key phrases.

To narrow down which provider fits best, could you tell me:

• What specific customer feedback tool or CRM you are currently using?
• Whether your feedback data lives mostly in surveys, support tickets, or app reviews?

Yes. If you mean a separate text-analytics product that integrates with a customer-feedback platform, several vendors fit:

• Chattermill — specializes in customer-feedback analytics, including AI-driven theme and sentiment analysis. It has a documented integration with Qualtrics, bringing Qualtrics feedback into Chattermill for near-real-time sentiment and theme analysis.
• Thematic — a dedicated customer-feedback text analytics platform focused on finding themes and sentiment in open-ended feedback. It’s commonly positioned alongside Qualtrics and Medallia as a feedback-analytics solution.
• Medallia — provides native Text Analytics within its customer-experience platform, including sentiment, themes, emotions, and real-time analysis across feedback channels.
• Qualtrics — has its own Text iQ/Text Analytics capabilities, including sentiment analysis, and integrations for bringing in sources such as Google Reviews.
• SurveyMonkey — offers built-in AI text analysis that categorizes open-ended feedback and classifies sentiment as positive, negative, or neutral; it also has 200+ integrations and APIs.
• Resonate CX — offers an AI-powered text analytics module specifically for customer feedback, with sentiment labels, topics/themes, and trending-topic detection.

If your existing customer-feedback tool is Qualtrics, I'd look particularly closely at Chattermill and Thematic if you want a specialist analytics layer rather than replacing your feedback-collection system. Chattermill has an explicitly documented Qualtrics integration.

If you tell me which customer feedback tool you use (e.g., Qualtrics, Medallia, SurveyMonkey, UserVoice, Canny, Delighted, etc.), I can identify the specific sentiment-analysis integrations available for it.

Yes. If you mean a third-party text-analytics integration that plugs into an existing customer-feedback platform, a few strong options are:

• Chattermill — integrates with Qualtrics and analyzes customer feedback for themes and sentiment, including near-real-time AI-driven insights.
• Thematic — integrates with several feedback platforms, including Medallia, Qualtrics, SurveyMonkey, Survicate, Typeform, Pendo, and QuestionPro, to analyze open-ended feedback.
• Qualtrics Text Analytics — if your feedback tool is Qualtrics itself, its automated text analytics can classify sentiment, emotions, topics, effort, and actionability.
• Medallia — offers native text analytics and sentiment analysis across survey comments and other customer signals such as chat, reviews, and contact-center data.
• SurveyMonkey — has built-in sentiment analysis for open-text responses, classifying them as positive, negative, or neutral.

If you tell me which customer feedback tool you use (e.g., Qualtrics, Medallia, SurveyMonkey, Delighted, UserVoice, etc.), I can identify the specific text-analytics integrations available for it and compare them.

Several platforms specialize in text analytics and sentiment analysis, either as standalone engines that integrate with existing customer feedback systems or as all-in-one Voice of the Customer (VoC) suites.

• Enterpret - Ingests feedback from over 50 channels (surveys, support tickets, reviews) and applies a unified sentiment and adaptive taxonomy model, connecting verbatims directly to customer accounts.
• Chattermill - Focuses on AI-native analysis of unstructured feedback, unifying data across touchpoints and tying sentiment changes directly to metrics like NPS.
• Thematic - Best for bottom-up theme detection with a human-in-the-loop editor, providing structured clarity on what drives positive or negative sentiment.
• Qualtrics (Text iQ) - Built directly into the Qualtrics suite, using NLP to parse open-ended survey responses, assign polarity, and track sentiment trends.
• SentiSum - Purpose-built to ingest support tickets, live chats, and surveys to automate tagging and surface the root causes behind customer sentiment.
• MonkeyLearn - A flexible text-analytics and machine-learning platform that plugs into existing customer feedback tools, spreadsheets, and CRMs for custom classification and sentiment scoring.

If you share which customer feedback tool you are currently using, I can tell you whether it has a native integration with these platforms or if you'll need a third-party connector like Zapier.

Yes. Several customer-feedback platforms offer text analytics / sentiment analysis, either natively or through an integration:

• Chattermill — specializes in customer-feedback analytics, combining feedback from multiple sources and providing AI-driven themes and sentiment. It has a documented integration with Qualtrics.
• Qualtrics Text iQ — native text analytics that classifies responses from very negative through very positive, with scores that can be used for filtering and reporting.
• Medallia Text Analytics — native, omnichannel text analytics that uses AI to surface themes and insights from customer feedback.
• SurveyMonkey / GetFeedback — provides sentiment analysis for open-text survey responses, including positive, neutral, and negative classifications.
• Thematic, Enterpret, SentiSum, and similar CX analytics vendors — focus more specifically on analyzing feedback across sources, often combining topic/theme detection with sentiment. A recent 2026 industry comparison identifies these alongside Chattermill, Qualtrics, and Medallia as leading options.

If you tell me which customer feedback tool you currently use (e.g., Qualtrics, SurveyMonkey, Zendesk, Medallia, Delighted, AskNicely), I can identify the specific sentiment-analysis integrations available for it.

Several customer feedback and text analytics platforms offer robust integrations or built-in engines to analyze sentiment and process unstructured text . Depending on whether you want an add-on text analytics layer that plugs into your existing stack or an all-in-one Voice of the Customer (VoC) platform, here are the top providers:

• Enterpret - Ingests feedback across 50+ channels and applies a unified sentiment and adaptive taxonomy model to connect verbatims directly to customer data.
• Chattermill - Specializes in unifying customer feedback from surveys, reviews, and support channels, turning messy text into clean sentiment and theme analytics.
• Thematic - Known for deep, research-grade theme and sentiment detection with flexible tools for interpreting open-ended text.
• Qualtrics XM (Text iQ) - The industry heavyweight for enterprise feedback management, featuring native text and sentiment analysis built straight into survey and experience data.
• SentiSum - Purpose-built to handle customer support tickets, chats, and survey feedback with domain-trained sentiment tagging.
• MonkeyLearn - A flexible, no-code text analysis and NLP platform that integrates cleanly via API or pre-built connectors to analyze sentiment in customer feedback.

If you can share the name of the customer feedback tool you currently use, I can tell you if it has a native integration with any of these platforms or recommend the best fit for your specific tech stack.