AI app for product development · no coding needed
Customer feedback insight and prioritization workspace
Turn scattered feedback into source-grounded, prioritized product insights.
Made for: Product teams collecting user feedback across support, CRM, surveys and review channels
What it does for you
The problem
Feedback arrives in disconnected tools, so recurring signals, churn risk and high-value requests are missed and prioritization is guesswork.
What it gives you
Reviewed, prioritized insight set linked to original sources
What you give it
Widget responsesimported filesCRMsupport recordssurvey answersreview mentions
Build your own version of Feedbase, Feeedback and more
One app with what these 6 AI tools do, yours to keep and change: Feedbase, Feeedback, Propane, Seven24.ai, Duonut, MetaSurvey AI.
Everything these tools do, in one app
- Feedback Collection Widget Embeds a widget on websites to collect user feedback directly.Found in Feedbase, Feeedback
- AI-Powered Analysis Uses AI to analyze feedback and extract insights.Found in Feedbase, Feeedback, Seven24.ai and 2 more
- Centralized Dashboard Consolidates all feedback in one place for easy management.Found in Feedbase, Feeedback, Propane
- Automated Summaries Generates summaries of feedback to save time.Found in Feedbase, Duonut
- Keyword Extraction Identifies key terms from feedback for quick analysis.Found in Feedbase
- Product Improvement Suggestions Suggests product improvements based on customer comments.Found in Feedbase
- Customizable Forms and Templates Provides ready-made templates and customizable forms for feedback collection.Found in Feeedback
- Automatic Testimonial Capture Automatically collects testimonials from sources like Stripe, Senja, and Trustpilot.Found in Feeedback
- Churn Detection Detects potential churn early to engage users and retain them.Found in Feeedback
- Real-Time Analytics Provides real-time analytics on feedback trends.Found in Feeedback
- Project Management Integration Integrates with popular project management tools to align feedback with development.Found in Feeedback
- Signal Aggregation Pulls data from CRM, support, and analytics tools into one location.Found in Propane
- Context Weighting Weights feedback based on account value and user segment to filter noise.Found in Propane
- Shared Canvases Allows multiple users and agents to collaborate in the same workspace.Found in Propane
- Agent Handoffs Sends canonical data sets directly to coding and design agents.Found in Propane
- Source Grounding Grounds every insight in its original source for evidence inspection.Found in Propane
- Clustering Algorithms Groups related feedback across different tools to surface recurring patterns.Found in Propane
- Direct Integrations Integrates with tools like Linear and GitHub to connect development lifecycle.Found in Propane
- Real-Time Feedback Capture Collects feedback at the moment of interaction for timely input.Found in Seven24.ai
- Multi-Format Collection Accepts feedback in text or audio form.Found in Seven24.ai
- Import Existing Feedback Uploads past feedback via CSV files or links for AI analysis.Found in Seven24.ai
- Positivity Booster Identifies positive feedback and encourages users to share reviews on platforms like Trustpilot or Google Maps.Found in Seven24.ai
- Flexible Deployment Creates personalized feedback pages with embed buttons or shareable links for various platforms.Found in Seven24.ai
- AI-Driven Task Prioritization Organizes feedback by importance to focus on high-impact items.Found in Seven24.ai
- Conversational Surveys Engages users with AI-driven, conversational follow-up questions in real time.Found in Duonut
- Automated Question Generation Creates tailored survey questions using website content or internal documentation.Found in Duonut
- Survey Embedding Embeds surveys on websites, product interfaces, or outreach tools.Found in Duonut
- Targeted Feedback Collection Identifies specific user cohorts such as inactive or churned customers for feedback.Found in Duonut
- AI-Assisted Survey Creation Builds surveys from simple prompts using AI.Found in MetaSurvey AI
- Card-Style Survey Format Uses a gamified card-style format to improve respondent engagement.Found in MetaSurvey AI
- Instant Preview Shows changes to surveys in real time.Found in MetaSurvey AI
- Image Integration Integrates images from Unsplash to enhance visual appeal.Found in MetaSurvey AI
How it works, step by step
- Embed feedback widgets and shareable survey links
- Accept text, audio, CSV and link imports
- Generate conversational follow-up questions
- Build surveys from prompts, templates or site content
- Capture testimonials from connected review sources
- Aggregate CRM, support and analytics signals
- Cluster related feedback across tools
- Extract keywords and recurring themes
- Summarize feedback sets automatically
- Weight feedback by account value and segment
- Detect churn risk and flag at-risk accounts
- Suggest product improvements from comments
- Prioritize items by impact and evidence
- Ground every insight in its original source
- Route canonical data sets to coding and design agents
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned reviewed, prioritized insight set linked to original sources with source references and unresolved questions
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 criteria11 KB
- demo/index.htmlThe working demo on sample data199 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
Turn scattered feedback into source-grounded, prioritized product insights. For product teams collecting user feedback across support, CRM, surveys and review channels, convert widget responses, imported files, CRM and support records, survey answers and review mentions into a reviewed, prioritized insight set linked to original sources. The benefit is a testable hypothesis, measured through accepted insights per analyst hour and prioritization decisions traced to source evidence; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect widget responses, imported files, CRM and support records, survey answers and review mentions, then follow this sequence: 1. Embed feedback widgets and shareable survey links. 2. Accept text, audio, CSV and link imports. 3. Generate conversational follow-up questions. 4. Build surveys from prompts, templates or site content. 5. Capture testimonials from connected review sources. 6. Aggregate CRM, support and analytics signals. 7. Cluster related feedback across tools. 8. Extract keywords and recurring themes. 9. Summarize feedback sets automatically. 10. Weight feedback by account value and segment. 11. Detect churn risk and flag at-risk accounts. 12. Suggest product improvements from comments. 13. Prioritize items by impact and evidence. 14. Ground every insight in its original source. 15. Route canonical data sets to coding and design agents. Resolve uncertain cases with qualified reviewers, approve reviewed, prioritized insight set linked to original sources, and measure accepted insights per analyst hour and prioritization 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 three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One fixed feedback taxonomy and approved source set; 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 source attribution, quotation accuracy and usage permissions. Product owners approve substantive prioritization and roadmap scope. One fixed feedback taxonomy and approved source set; 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 fixed feedback taxonomy and approved source set; 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: embed feedback widgets and shareable survey links; accept text, audio, CSV and link imports. Support the third module with operator review: generate conversational follow-up questions. 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
Product-owned feedback sources, authorized CRM and support exports and permitted review platforms. Cloud storage, project management tools, coding and design agents and analytics 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: Collection setup, Insight review board, Prioritized roadmap view. Use a thumbnail gallery for feedback sources, a large central insight canvas, and a right-hand panel for source evidence, account context and comments. Let users compare clusters and versions side by side. Display new, reviewed and prioritized states. Provide a shared client or stakeholder link with comments anchored to the relevant insight. Make the task-specific outcome reviewed, prioritized insight set linked to original sources visible beside its evidence, review state and value baseline.
