Which brands AI mentions

#BrandMentioned in

Mentioned in · Jul 8 – Oct 15, 2026

ChatGPT SearchChatGPT SearchGoogle AI ModeGoogle AI Mode

Widest split: SentiSum, 22% on ChatGPT Search and 81% on Google AI Mode.

=1ChattermillChatGPT Search 87%Google AI Mode 76%
=1ThematicChatGPT Search 78%Google AI Mode 86%
=1MedalliaChatGPT Search 83%Google AI Mode 57%
=4QualtricsChatGPT Search 78%Google AI Mode 43%
=4SentiSumChatGPT Search 22%Google AI Mode 81%

Questions and answers

ChatGPT SearchOct 6, 2026

Yes. For a large, continuously growing customer-comment dataset, I’d separate the options into two categories: purpose-built CX/brand platforms and cloud NLP APIs.

Best options

Tool	Best for	Why it stands out
Brandwatch	Brand perception + social listening	Excellent when you need to combine customer feedback with social/web conversations. Brandwatch says it processes 500M+ new conversations daily and has extensive historical data.
Qualtrics	Enterprise CX programs	Strong if your comments come from surveys, NPS/CSAT, and other experience programs. Its Text iQ assigns sentiment from very negative through very positive/mixed and provides numerical scores.
Medallia	Omnichannel customer feedback	Particularly suitable for very large enterprises wanting text analytics across multiple CX channels.
Amazon Comprehend	Building your own high-volume pipeline	Best when you have engineers/data infrastructure and want sentiment embedded directly into your data pipeline. It supports synchronous, batch, and asynchronous sentiment jobs, plus targeted sentiment and custom classifiers.
Google Cloud Natural Language	Cloud-native NLP	Good fit if you're already heavily invested in Google Cloud and want an API-based NLP layer rather than a full CX application.
Sprinklr	Social + customer-service ecosystems	Worth considering when social engagement, customer care, and sentiment monitoring need to live in one enterprise platform.
Chattermill / unitQ	AI-native feedback analytics	Good alternatives if your primary goal is turning large quantities of disparate customer feedback into themes, sentiment, and actionable insights.

What I'd choose

If your goal is continuous brand perception:
Brandwatch is probably the strongest starting point because you're not limited to your own customer comments—you can compare owned feedback with the broader online conversation.

If your dataset is primarily surveys/NPS/CSAT:
Go with Qualtrics or Medallia. You're buying a broader CX analytics system rather than just a sentiment API.

If you have millions/billions of comments and a data-engineering team:
I'd lean toward Amazon Comprehend or Google Cloud Natural Language, feeding results into your warehouse/dashboard. Comprehend is especially interesting because you can train custom classifiers around your own categories—e.g. pricing, product quality, shipping, support, competitor mention, churn risk—rather than relying solely on generic positive/negative sentiment.

One important caveat

For brand monitoring, sentiment alone isn't enough. A better pipeline is:

Comments → language detection → sentiment → aspect/topic extraction → emotion → emerging themes → trend/alerting

For example, instead of simply reporting:

62% positive / 24% neutral / 14% negative

you want:

Negative sentiment increased 31% this week, primarily driven by shipping delays and checkout failures among premium customers.

That's much more useful operationally.

If you tell me roughly how many comments you process per day/month, where they come from (surveys, reviews, social, support tickets, etc.), and whether you need an API or a turnkey dashboard, I can narrow this to the 3 best choices and compare expected cost, scalability, languages, customization, and accuracy.

Sources cited in this answer14

ChatGPT SearchOct 15, 2026

If you're looking for customer feedback software with sentiment analysis integrated into text analytics, I'd prioritize platforms that do more than label comments as positive or negative. The strongest options also identify recurring themes, explain what's driving customer satisfaction or dissatisfaction, and integrate with your existing survey, CRM, support, and reporting tools.

Based on current product information, here are the platforms I'd shortlist for 2026.

Top customer feedback software recommendations

1. Chattermill

(Best overall for text analytics)

Chattermill specializes in consolidating unstructured feedback and using AI to identify sentiment, recurring topics, and customer experience issues. It connects with survey platforms, customer support systems, review sites, and tools such as Salesforce, Zendesk, and Intercom.

Best for: Teams analyzing large volumes of feedback from multiple channels.

Official website ·

2. Qualtrics XM

A strong choice for organizations that want a comprehensive voice-of-customer program. You can pair Qualtrics feedback collection with Chattermill for advanced theme and sentiment insights, or investigate Qualtrics' text analytics capabilities for a more consolidated setup.

Best for: Enterprise survey programs, customer experience measurement, and structured feedback workflows.

Official website

3. Thematic

Focuses on turning free-text feedback into meaningful themes and insights, helping teams understand why customer satisfaction scores change rather than simply counting positive and negative comments. It's worth evaluating if text analytics is the primary requirement.

Best for: Research, customer insights, and product teams working with open-ended survey responses.

Official website

4. Medallia Experience Cloud

An enterprise-focused experience management platform for gathering and analyzing customer feedback across interactions and touchpoints. Consider it when sentiment insights need to feed into broader customer experience management and operational processes.

Best for: Large organizations with complex, multichannel customer experience programs.

Official website

5. Enterpret

Worth considering if you want to unify feedback across customer channels and connect themes to product issues, customer segments, and business priorities. It is especially relevant for teams seeking a deeper customer intelligence layer, not just survey reporting.

Best for: Product-led companies and customer insights teams handling feedback at scale.

Official website

Quick comparison

Platform	Sentiment and theme analysis	Integration approach	Ideal use case
Chattermill	AI-driven sentiment and topic insights	Broad, multichannel integrations	Advanced feedback analytics
Qualtrics XM	Text analytics within a wider experience management suite; can integrate with Chattermill	Survey and enterprise workflows	Enterprise feedback programs
Thematic	Theme discovery and feedback analysis	Connect feedback data sources	Survey and research analysis
Medallia	Feedback analytics within an enterprise CX platform	Multichannel experience systems	Large-scale CX management
Enterpret	AI-powered customer intelligence and text analysis	Unified customer feedback sources	Product and customer insights

These are qualitative fit assessments, not a standardized benchmark. Confirm the specific features, connectors, language coverage, and licensing available for your intended deployment.

My recommendation

I'd start with Chattermill if you already collect customer feedback in several systems and need a dedicated sentiment-analysis layer. Its documented integrations include Qualtrics, SurveyMonkey, Zendesk, Salesforce, and Trustpilot.

Before choosing, verify these five capabilities in a demo:

Aspect-based sentiment: Can it distinguish positive and negative opinions about different features within the same comment?
Automated theme detection: Can it identify emerging topics without manually defining every category?
Integration flexibility: Does it support your existing feedback sources through native connectors or APIs?
Actionable reporting: Can you track sentiment over time and connect changes to CSAT or NPS?
Security and cost: What are the data retention, access-control, implementation, and usage-pricing requirements?

One question that would help me narrow this down: Are you looking for a standalone text analytics tool that integrates with your existing feedback software, or an all-in-one customer feedback platform with sentiment analysis built in?

Sources cited in this answer13

Google AI ModeOct 15, 2026

Top-tier customer feedback platforms feature robust built-in text analytics and AI-driven sentiment analysis to parse unstructured customer verbatims, surveys, and reviews.

Qualtrics XM - A leading enterprise feedback management platform that features native Qualtrics Text IQ text analytics. It automatically evaluates open-ended survey responses, tags themes, and scores sentiment as positive, negative, or neutral to pinpoint experience drivers.
Medallia - Known for its enterprise Medallia Text Analytics , this platform processes unstructured feedback from surveys, social media, and digital channels without requiring external integrations. It translates large volumes of verbatims into intuitive, color-coded sentiment reports.
Birdeye - An all-in-one reputation and customer feedback solution featuring Birdeye AI-powered review sentiment analysis . It aggregates and breaks down customer sentiment from online reviews and surveys into location-based and category-specific insights.
Thematic - A specialized feedback analytics platform built around Thematic AI Text Analytics , designed to ingest feedback from multiple sources, automatically discover themes, and track sentiment shifts without manual tagging.
Sprout Social - Ideal if your feedback heavily loops in social channels, reviews, and direct messages, as it includes Sprout Social Sentiment Analysis powered by advanced AI to contextualize customer emotions at scale.

If you can share your primary feedback channels (e.g., website surveys, support tickets, public app store reviews) and your company size , I can help you narrow down which of these platforms best fits your workflow and budget.

Sources cited in this answer1

gartner.comBest Sentiment Analysis Tools Reviews 2026 | Gartner Peer Insights

ChatGPT SearchSep 26, 2026
1Qualtrics
2Medallia
If you mean a customer-feedback/survey platform that can analyze free-text responses for sentiment, two established options are:

Qualtrics — Its Text iQ analyzes open-ended feedback, assigning sentiment such as very negative through very positive, with numeric sentiment scores. It also supports topic-level sentiment and can trigger workflows based on sentiment.

Medallia — Its Text Analytics analyzes customer comments and other unstructured feedback for themes and sentiment, including across multiple channels and languages.

If you tell me which customer feedback tool you currently use (e.g., SurveyMonkey, Typeform, Delighted, AskNicely, UserVoice, etc.), I can identify the specific text-analytics/sentiment integrations that work with it.
Sources cited in this answer6
qualtrics.comText iQ Functionality - Qualtrics
qualtrics.comSentiment Analysis - Qualtrics
qualtrics.comTextFlow - Qualtrics
docs.medallia.comText analysis | Medallia Documentation
medallia.comReal Time Text Analytics Software – Medallia – Medallia
medallia.comMedallia Contact Center Insights – Medallia
Google AI ModeSep 26, 2026
1Enterpret
2Thematic
3Qualtrics
4XM Discover
5SentiSum
6Zendesk
Several platforms specialize in text analytics integrations and native AI engines to analyze sentiment and structure unstructured customer feedback . The leading options on the market depend on how deeply you want to tie sentiment to themes, revenue, or multi-channel data:

Enterpret : Ingests customer feedback text from over 50 channels, utilizing an adaptive taxonomy and a customer context graph to tie sentiment scores directly to customer segments, accounts, and revenue impact.

Chattermilk : Uses deep-learning and aspect-based sentiment analysis (ABSA) via its proprietary Lyra model. It scores sentiment per specific theme within a single comment (rather than flattening a mixed review into one generic label) across support tickets, reviews, and surveys.

Thematic : Focuses on unsupervised AI to discover themes and track sentiment impact without requiring manual pre-labeling, giving analysts transparent control over how feedback themes and sentiment are structured and measured against metrics like NPS.

Qualtrics (Text iQ / XM Discover) : Built natively into the Qualtrics ecosystem, providing built-in machine-learning text analytics, topic detection, and sentiment scoring primarily optimized for survey verbatims and broader CX data.

SentiSum : Integrates deeply with customer support channels (like helpdesks) to tag high-volume ticket text and analyze sentiment in real time using specialized AI engines geared toward support operations and root-cause analysis.

If you're looking to narrow this down, tell me:

What specific customer feedback or support tool (e.g., Zendesk, Intercom, Qualtrics, or a custom database) are you currently using?

Do you need sentiment tied directly to revenue/account data , or strictly focused on support tickets and surveys?

I can help you pinpoint the cleanest integration path for your stack.
Sources cited in this answer6
enterpret.comThe 5 Best Sentiment Analysis Platforms for Customer Feedback
getperspective.aiBest Customer Sentiment Analysis Tools in 2026: 11 Platforms Ranked by Explanatory Power | Blog | Perspective AI
enterpret.comThe 6 Best Customer Text Analytics Tools in 2026
enterpret.comThe 6 Best Voice of Customer Tools That Go Beyond Sentiment Analysis in 2026
chattermill.comSentiSum vs Qualtrics: Which VoC Tool Wins in 2026?
chattermill.comEnterpret vs SentiSum: Which Platform Wins? (2026)

Also asked as

I need a customer feedback platform that integrates with text analytics to help us track sentiment.

Customer feedback sentiment analysis

Which brands AI mentions