AI Text Analysis for Open-Ended Text
Turn text responses into instant insights
Examples of Text Data and the Insights You Can Extract
Amazon reviews:
Surface strengths & weaknesses
App store reviews:
Extract feature requests & complaints
Customer emails:
Identify sentiment & intent
Slack messages:
Track morale & engagement
Exam essays:
Compare argument quality
Support chat logs:
Spot recurring issues & urgent cases
Beta feedback forms:
Compare sentiment across versions
Exit interviews:
Uncover reasons for attrition
Performance reviews:
Pinpoint growth areas
College essays:
Evaluate clarity & structure
Research abstracts:
Distill key findings
Job applications:
Highlight strengths & red flags
Global Insights
What do these text responses mean as a whole?
- Product Reviews: Strengths, weaknesses, and feature requests to guide improvements.
- Support Tickets: Common pain points and recurring issues raised by clients.
- Workplace surveys: Overall job satisfaction and emerging employee concerns.
Ava
Jack
Mia
Noah
Lily
James
Chloe
Henry
We help you discover overarching patterns across your whole data.
Per-response insights
Which text response is unique, and in what way?
- Cover Letters: Highlight strengths and red flags in individual applications.
- Support Tickets: Identify priority level and sentiment for every response.
- Exam Essays: Evaluate depth of understanding and compare quality of arguments.
- Best Applicant
- Critical Ticket
Mia
Noah
We help you discover meaningful outliers from your data.
FAQ
Can I see an example of an AI text analysis report?
How do I analyze survey responses and qualitative feedback with Text Response Hub?
How fast does the AI generate insights from CSV or TXT files?
What types of text data are supported (surveys, reviews, tickets, chat logs)?
Is my uploaded customer feedback data secure and private?
Didn’t find your answer?
Visit our full FAQ