Digital Product
SignalPRD
Single-page web app that analyzes app store reviews using a map-reduce pipeline powered by GPT-4o-mini. Paste an iOS or Google Play Store link to identify common themes, score them using RICE framework, and generate structured PRDs to prioritize what to build next.
Project Overview
Product teams struggle to manually analyze thousands of app store reviews to identify actionable insights. SignalPRD automates this process using a map-reduce pipeline with GPT-4o-mini, helping teams make data-driven decisions based on real customer feedback.
By combining AI theme extraction with RICE scoring methodology (Reach × Impact × Confidence / Effort), teams can quickly prioritize which features to build based on customer impact and effort estimates. No manual uploads needed—just paste an App Store link.
- • Product managers seeking customer insights
- • Development teams prioritizing features
- • Startup founders validating product direction
- • UX researchers analyzing user feedback
Transform the Voice of Customer (VoC) from scattered reviews into structured, prioritized product requirements that drive real business impact.
How It Works
Paste App Store Link
Simply paste any iOS App Store or Google Play Store URL. No uploads needed—the platform automatically fetches reviews using SerpApi.
AI Analysis
GPT-4o-mini uses a map-reduce pipeline to analyze ~50 reviews, extracting themes and patterns with automatic PII redaction for privacy.
RICE Scoring
Themes are automatically scored using RICE (Reach × Impact × Confidence / Effort) for prioritization.
Generate PRDs
One-click PRD generation for any theme, complete with user stories, evidence, and recommendations.
Key Features
GPT-4o-mini automatically clusters reviews into themes, identifying patterns, pain points, and feature requests.
Automatic RICE scoring (Reach × Impact × Confidence / Effort) with transparent breakdowns for each theme.
Track theme momentum over 4 weeks with visual indicators for trending up, down, or stable.
Auto-generate structured PRDs in Markdown format with user stories, acceptance criteria, and evidence-backed quotes.
Filter by date range, app version, store platform, and minimum RICE score for focused analysis.
Automatic removal of sensitive data like emails, phone numbers, and URLs for privacy protection.
Technical Highlights
Works instantly with examples or real apps
Cost-effective, fast, accurate
Per analysis with deduplication
Technology Stack
Frontend & Backend
AI & Data
Perfect For
Quickly identify what users actually want instead of manually reading thousands of reviews. Use data-driven RICE scores to justify roadmap decisions to stakeholders.
Validate product direction and prioritize features that matter most to users. Save hours of manual analysis and focus on building what customers actually need.
Analyze competitor apps to identify gaps in their offerings and opportunities for differentiation. Understand what their users are complaining about.
Generate ready-to-use PRDs for sprint planning sessions. Each theme comes with evidence, user stories, and RICE-based priority recommendations.
See It In Action
Main Interface
Clean input interface with App Store link input, example apps, and effort selection (S/M/L) for RICE scoring.
Try It Yourself
Analyze any app in seconds. Just paste a link and let AI do the work.
Launch SignalPRD