Every organization collects open-ended feedback.
Customers tell you why they love your product. Employees explain what is preventing them from doing their best work. Survey respondents provide context that numbers alone cannot capture.
The challenge has never been collecting feedback. The challenge has always been understanding it at scale.
Reading thousands of comments manually is slow. Traditional text analytics tools often generate generic themes that lack business context. And even when AI helps organize feedback, teams frequently struggle to refine, validate, and operationalize the results.
That’s why we’ve continued to expand TextAI into a complete qualitative intelligence platform – giving teams the speed of AI with the control and flexibility required for enterprise-grade analysis.
Turn Open-Ended Feedback into Structured Insights
TextAI automatically analyzes open-ended responses and organizes them into meaningful themes and sub-themes.
Instead of manually reviewing thousands of comments, teams can quickly understand:
- What customers are talking about
- Which issues occur most frequently
- Emerging opportunities and risks
- The drivers behind satisfaction and dissatisfaction
Whether you’re analyzing customer feedback, employee feedback, market research responses, or Voice of Customer programs, TextAI helps transform unstructured text into actionable insights.
Start with AI or Bring Your Own Framework
Every organization approaches qualitative analysis differently.
Some teams want AI to discover themes automatically. Others already have established coding frameworks and reporting structures.
TextAI supports both approaches.
Organizations can:
- Generate codebooks using QuestionPro AI
- Upload their own codebooks
- Reuse codebooks from existing projects
This allows organizations to standardize classifications across studies and teams, and maintain consistency while still benefiting from AI-powered analysis.
Refine and Improve Results with Theme Configuration
One of the biggest limitations of traditional text analytics platforms is that the output is often fixed.
TextAI takes a different approach.
With Theme Configuration, teams can actively refine how responses are categorized by:
- Creating new themes
- Creating new sub-themes
- Merging similar categories
- Assigning responses manually
- Removing incorrect classifications
- Running recoding workflows
This gives researchers and insight teams complete control over how qualitative data is organized and interpreted.
Go Beyond Analysis with Built-In Sentiment and Insights
Knowing what people are talking about is important.
Understanding how they feel about those themes is even more valuable.
TextAI combines themes modeling with sentiment analysis and AI-generated insights to help teams understand:
- Which themes are driving positive experiences
- Which themes are contributing to dissatisfaction
- Where improvement opportunities exist
- What actions stakeholders should prioritize
The result is faster decision-making and more meaningful reporting.
Compare Audiences with Data Slicers
Customer feedback is rarely uniform.
What matters to new customers may differ from long-term customers. Employee concerns may vary across departments, regions, or roles.
TextAI’s Data Slicers make it easy to compare feedback across different audiences.
Teams can create reusable segments based on survey responses, demographics, customer attributes, or custom criteria and then compare results side-by-side.
This helps uncover differences that would otherwise remain hidden in aggregate data.
Add Confidence with Statistical Testing
Finding differences between groups is useful.
Knowing whether those differences are statistically meaningful is even better.
TextAI includes built-in statistical testing capabilities that help researchers validate findings and identify meaningful variations across audience segments.
This enables teams to move from assumptions to evidence-backed decision-making.
Explore Feedback with Advanced Filters
TextAI provides flexible filtering options that allow teams to focus analysis on the feedback that matters most.
Users can filter results by:
- Date ranges
- Response status
- Survey attributes
- Custom criteria
- Saved filter configurations
This makes it easier to investigate specific populations, campaigns, products, or business initiatives without rebuilding reports.
Analyze Feedback Across Multiple Sources
Organizations collect feedback from many places.
TextAI can analyze data from:
- Surveys
- Customer Experience (CX) programs
- Employee Experience (EX) programs
- External datasets
This allows teams to consolidate qualitative analysis across multiple research and feedback initiatives within a single platform.
Built for Global Teams
As organizations become more global, qualitative analysis must support multilingual environments.
TextAI allows users to select output languages during dashboard creation, helping global teams standardize reporting and collaborate more effectively across regions.
Enterprise-Ready Credit Management
AI-powered analysis requires visibility and governance.
TextAI includes built-in credit management capabilities that allow organizations to:
- Monitor credit consumption
- Review usage logs
- Track processing activity
- Purchase additional credits
- Manage AI usage centrally
This gives administrators greater control over AI investments and usage across teams.
The Future of Qualitative Intelligence
The volume of open-ended feedback continues to grow every year.
Organizations that can quickly understand that feedback gain a significant advantage in customer experience, employee engagement, product development, and market research.
TextAI was built to help teams move beyond manual coding and generic text clustering.
By combining AI-powered themes modeling, sentiment analysis, statistical validation, audience segmentation, configurable codebooks, and human-in-the-loop refinement, TextAI provides a complete qualitative intelligence workflow designed for modern research and experience management teams.
The result is simple: less time organizing feedback and more time acting on it.
