AI app for product development · no coding needed
Customer feedback insight and prioritization workspace
Reduce the time from raw feedback to a prioritized, evidence-backed product decision.
Made for: Product managers and product teams turning customer feedback and research into prioritized product insights
What it does for you
The problem
Feedback arrives across email, social media, surveys, support tickets and calls, and teams cannot consistently turn it into prioritized, evidence-backed product decisions.
What it gives you
Reviewed, source-linked product insights and prioritized action items
What you give it
Multi-channel feedbackinterview transcriptssurvey responsessupport tickets
Build your own version of Iterato, AI Insights 2.0 by Zeda.io and more
One app with what these 10 AI tools do, yours to keep and change: Iterato, AI Insights 2.0 by Zeda.io, Lancey (YC S22), Visionari, ManyPI, Monterey AI 2.0, Feedback Navigator, AI Consultant, BetterFeedback, Listen Labs.
Everything these tools do, in one app
- Multi-channel feedback collection Gathers customer feedback automatically from channels such as email, social media, surveys, support tickets, and calls.Found in Lancey (YC S22), Feedback Navigator, Monterey AI 2.0
- Conversational feedback collection Interacts with users through human-like conversations to collect feedback.Found in Iterato, BetterFeedback
- Automated customer interviews Conducts customer interviews automatically without manual intervention.Found in Listen Labs
- Embedded AI surveys Provides AI-powered surveys that can be embedded anywhere to quickly launch and manage feedback collection.Found in Monterey AI 2.0
- Adaptive follow-up questions Asks follow-up questions based on user responses to uncover deeper insights.Found in BetterFeedback
- Sentiment and emotion analysis Analyzes the emotional tone and sentiment behind feedback to understand customer opinions.Found in Iterato, Monterey AI 2.0, Feedback Navigator
- Context analysis Interprets the underlying context and issues behind feedback.Found in Iterato
- Automated feedback categorization Automatically sorts and categorizes feedback from multiple sources.Found in Lancey (YC S22)
- AI-driven summarization Summarizes feedback and interviews into clear, actionable reports.Found in Iterato, Listen Labs, BetterFeedback
- Prioritization of action items Highlights and prioritizes feedback based on urgency and impact.Found in Iterato, Lancey (YC S22), Monterey AI 2.0
- AI-generated reports Generates reports that highlight priorities, customer issues, and growth opportunities.Found in Iterato, AI Insights 2.0 by Zeda.io, Listen Labs
- Revenue impact tracking Tracks how customer signals influence revenue to support strategic planning.Found in AI Insights 2.0 by Zeda.io
- Post-launch impact analysis Measures how new features are received and used by customers after launch.Found in Lancey (YC S22)
- Automatic ticket generation Creates tickets and issues automatically based on prioritized feedback.Found in Lancey (YC S22)
- Natural language querying Allows users to query customer feedback in plain English and receive detailed reports.Found in Monterey AI 2.0
- Real-time dashboards Provides customizable dashboards with real-time data visualization to track feedback trends.Found in Feedback Navigator
- Team collaboration Enables teams to assign feedback items and track resolution progress.Found in Feedback Navigator
- Integration with business tools Connects with popular platforms like Slack, Intercom, Zendesk, Salesforce, Jira, and Asana for seamless data aggregation.Found in AI Insights 2.0 by Zeda.io, Monterey AI 2.0, Feedback Navigator
How it works, step by step
- Collect feedback from email, social media, surveys, support tickets and calls
- Run conversational feedback collection with users
- Conduct automated customer interviews
- Deploy embedded AI surveys
- Ask adaptive follow-up questions based on responses
- Analyze sentiment and emotion behind feedback
- Interpret underlying context and issues
- Categorize feedback automatically across sources
- Summarize feedback and interviews into reports
- Prioritize action items by urgency and impact
- Generate reports on priorities, issues and growth opportunities
- Track how customer signals influence revenue
- Measure post-launch feature reception and usage
- Create tickets and issues from prioritized feedback
- Query feedback in natural language
- Display real-time dashboards of feedback trends
- Assign feedback items and track resolution progress
- Connect Slack, Intercom, Zendesk, Salesforce, Jira and Asana
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Customer feedback insight and prioritization workspace with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Customer feedback insight and prioritization workspace with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links5 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare25 KB
- prompt-vps.mdThe same build on your own server (Docker)25 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria12 KB
- demo/index.htmlThe working demo on sample data201 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
Reduce the time from raw feedback to a prioritized, evidence-backed product decision. For product managers and product teams turning customer feedback and research into prioritized product insights, convert multi-channel feedback, interview transcripts, survey responses and support tickets into reviewed, source-linked product insights and prioritized action items. The benefit is a testable hypothesis, measured through accepted insights per analyst hour and decisions traced to source evidence; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect multi-channel feedback, interview transcripts, survey responses and support tickets, then follow this sequence: 1. Collect feedback from email, social media, surveys, support tickets and calls. 2. Run conversational feedback collection with users. 3. Conduct automated customer interviews. 4. Deploy embedded AI surveys. 5. Ask adaptive follow-up questions based on responses. 6. Analyze sentiment and emotion behind feedback. 7. Interpret underlying context and issues. 8. Categorize feedback automatically across sources. 9. Summarize feedback and interviews into reports. 10. Prioritize action items by urgency and impact. 11. Generate reports on priorities, issues and growth opportunities. 12. Track how customer signals influence revenue. 13. Measure post-launch feature reception and usage. 14. Create tickets and issues from prioritized feedback. 15. Query feedback in natural language. 16. Display real-time dashboards of feedback trends. 17. Assign feedback items and track resolution progress. 18. Connect Slack, Intercom, Zendesk, Salesforce, Jira and Asana. Resolve uncertain cases with qualified reviewers, approve reviewed, source-linked product insights and prioritized action items, and measure accepted insights per analyst hour and decisions traced to source evidence against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. Final prioritization and product decisions remain with the product team. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve customer voice, source attribution, quotation accuracy and usage permissions. Product teams approve substantive changes and publication scope. One approved feedback source set and one product area; final prioritization and product decisions remain with the product team. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.
What to build first
Pilot scope: One approved feedback source set and one product area; final prioritization and product decisions remain with the product team. Implement one approved input format, a bounded representative case set and the first two task modules: collect feedback from email, social media, surveys, support tickets and calls; run conversational feedback collection with users. Support the remaining modules with operator review. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.
What it can connect to
Slack, Intercom, Zendesk, Salesforce, Jira and Asana. Cloud asset storage, design-file import/export and publishing destinations. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
The screens in detail
Primary screens: Feedback intake and sources, Insight review and prioritization, Client report and delivery. Use a thumbnail gallery for feedback sources, a large central review canvas, and a right-hand panel for evidence, constraints and comments. Let users compare insight versions side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant feedback item. Make the task-specific outcome reviewed, source-linked product insights and prioritized action items visible beside its evidence, review state and value baseline.
