AI Text Analysis for Surveys, Reviews & Feedback
Turn text responses into instant insights
Survey feedback, product reviews, and text response analysis insights & examples
Product reviews analysis tool | Amazon reviews
Surface strengths, weaknesses, and recurring themes in customer sentiment.
App store reviews analysis
Extract feature requests & complaints, and usability pain points at a glance.
Customer emails
Identify sentiment and intent; flag urgent issues and standout praise.
Employee feedback | Slack messages
Track morale and engagement; spot shifts and outliers in team sentiment.
Exam essay analysis
Compare argument quality and highlight exemplary responses.
Support chat log analysis
Spot recurring issues & rising problems, and high-priority cases automatically.
Survey feedback analysis | Beta forms
Compare sentiment and themes across versions or cohorts.
Exit interview analysis
Uncover reasons for attrition with grouped themes and per-response insights.
Performance review analysis
Pinpoint growth areas and standout contributions across a review cycle.
College essay analysis
Evaluate clarity and structure; surface top responses and common gaps.
Research abstract analysis
Distill key findings; cluster topics and detect emerging directions.
Job application analysis
Highlight strengths and red flags ;Rank standout cover letters
- Text Response Hub -
- Built for analyzing responses to the same explicit or implicit question
We analyze answers together, not in isolation, to reveal deeper insights. - Dual insights that most tools can only dream of
See both global themes across all responses and unique per-response insights. - Designed for surveys, reviews, feedback, and research data
Purpose-built for surveys, product reviews, essays, and interviews.
Most tools analyze text in isolation. We analyze answers in context.
— what your responses say as a whole
- Product review analysis: Surface strengths, weaknesses, and feature requests to guide improvements.
- Support ticket analysis: Spot recurring pain points and common client issues.
- Workplace survey analysis: Understand overall job satisfaction and uncover emerging employee concerns.
We help you discover overarching patterns across your entire dataset.
— what makes each answer unique
- Cover letter analysis: Highlight strengths and red flags in individual applications.
- Support ticket prioritization: Identify urgency level and sentiment for every response.
- Exam essay evaluation: Assess depth of understanding and compare quality of arguments.
- Best Applicant
- Critical Ticket
We help you pinpoint standout responses, anomalies, and insights in individual entries.
What is Text Response Hub used for?
How is this different from other AI text analysis tools?
Do I need to clean or code my text data before using it?
Can it handle both small and large datasets?
Who is Text Response Hub designed for?
Is my uploaded data secure and private?
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