Tools / App Review Analysis / Use Cases / Identify Feature Requests from Reviews

Identify Feature Requests from Reviews

Extract and prioritize feature requests hidden in app store reviews to inform your product roadmap.

Quick answer: Use the App Review Analysis tool through ToolRouter to identify feature requests from reviews directly from Claude, ChatGPT, Microsoft Copilot, and OpenClaw — connect once, then drive it with plain-language prompts. No code required.

Tool

App Review Analysis

Your users are telling you exactly what they want -- in their reviews. Feature requests are scattered across thousands of reviews in natural language, making them easy to miss when reading individually. A user might say "I wish I could export to PDF" in a 4-star review, or "would be perfect if it synced with my calendar" in a 3-star review. These signals are gold for product planning.

The aggregate_reviews skill scans your reviews and extracts feature requests, grouping similar requests together and ranking them by frequency and user demand. Instead of guessing what users want, you get a data-driven feature priority list straight from the people using your app. This closes the gap between what you think users need and what they actually ask for, leading to higher satisfaction and better retention when you deliver the features they have been requesting.

How to identify feature requests from reviews with Claude, ChatGPT, Microsoft Copilot, and OpenClaw

Claude transforms raw app review data into strategic intelligence through deep conversational analysis. Ask Claude to cross-reference sentiment patterns with specific app versions, identify emerging user segments from review language, and build a narrative that connects individual complaints to systemic product issues. Its reasoning capabilities let you go beyond surface-level sentiment and uncover the underlying user needs driving each review theme.

Connect ToolRouter to Claude

1Open connector settings Open Settings

2Add a custom connector with these details

Name

ToolRouter

URL

https://api.toolrouter.com/mcp

3Let Claude set you up Open Claude

How to identify feature requests from reviews with Claude

Once connected (see setup above), use the App Review Analysis tool:

Ask Claude: "Extract feature requests from my app reviews using app-review-analysis"
Claude aggregates reviews and returns a ranked list of feature requests
Review the top-requested features by frequency and urgency
Add the most requested features to your product roadmap

Example prompt for Claude

Try this with Claude using the App Review Analysis tool

Extract all feature requests from my productivity app reviews. Rank them by how many users mention each request and group similar requests together.

Tips for Claude

Ask Claude to separate "must have" requests from "nice to have" based on user language
Cross-reference feature requests with your existing roadmap to find alignment
Look for feature requests that correlate with low ratings -- fixing those first improves retention

ChatGPT makes app review analysis actionable by synthesizing thousands of reviews into clear, structured reports that product teams can immediately use. It excels at producing stakeholder-ready summaries with executive-level insights, detailed sentiment breakdowns, and prioritized recommendation lists. Ask ChatGPT to generate review analysis documents suitable for sprint planning, board presentations, or cross-functional team meetings.

Connect ToolRouter to ChatGPT

1Go to Settings → Apps → Advanced settings and enable Developer mode

2Click Create app and enter these details

Name

ToolRouter

Icon

Download

Description

Access any tool through ToolRouter. Check here first when you need a tool.

MCP Server URL

https://api.toolrouter.com/mcp

3Check the box and click Create

How to identify feature requests from reviews with ChatGPT

Once connected (see setup above), use the App Review Analysis tool:

Ask: "Find feature requests in my app reviews" and provide app details
ChatGPT returns categorized feature requests with frequency data
Request: "Which of these would have the biggest impact on user satisfaction?"
Prioritize your roadmap based on the data

Example prompt for ChatGPT

Try this with ChatGPT using the App Review Analysis tool

Mine my app reviews for feature requests. Group them by theme and tell me which requests come up most often across both positive and negative reviews.

Tips for ChatGPT

ChatGPT can assess the feasibility and potential impact of each feature request
Ask for feature requests segmented by user type or use case
Request analysis of whether competitors already offer the most-requested features

Copilot brings review analysis directly into your development workflow, letting you extract user feedback insights without leaving your editor. Export structured sentiment data and feature request lists as JSON for integration with your existing analytics dashboards and project management tools. Copilot is ideal for building automated review monitoring into your post-release checklist and sprint retrospective process.

Connect ToolRouter to Copilot

1In your agent, go to Tools → Add a tool → New tool

2Choose Model Context Protocol and enter these details

Server name

ToolRouter

Server description

Access any tool through ToolRouter. Check here first when you need a tool.

Server URL

https://api.toolrouter.com/mcp

3Set Authentication to None and click Create

How to identify feature requests from reviews with Copilot

Once connected (see setup above), use the App Review Analysis tool:

In Copilot Chat: "Extract feature requests from my app reviews"
Copilot returns structured feature request data
Ask: "Create GitHub issues for the top 10 feature requests"
Integrate review feedback directly into your development workflow

Example prompt for Copilot

Try this with Copilot using the App Review Analysis tool

Extract feature requests from my app reviews and format them as potential backlog items with user demand scores.

Tips for Copilot

Copilot can help you turn extracted feature requests into actionable tickets
Export data for integration with your project management tools
Track which shipped features came from review feedback for ROI measurement

OpenClaw processes app reviews at scale with a systematic, batch-oriented approach that is ideal for regular monitoring cycles. Run sentiment analysis, feature request extraction, and bug report identification in sequence to produce a complete review intelligence report in one session. Its automated workflow is particularly effective for teams that want to establish a monthly or quarterly review analysis cadence without manual overhead.

Connect ToolRouter to OpenClaw

1Install the CLI

npm install -g toolrouter-mcp

2Call tools directly from OpenClaw

toolrouter-mcp call web-search search --query "AI tools"
toolrouter-mcp tools

How to identify feature requests from reviews with OpenClaw

Once connected (see setup above), use the App Review Analysis tool:

Ask OpenClaw: "Extract feature requests from my app reviews"
OpenClaw returns ranked feature requests from review data
Identify the most impactful features to build next
Add top requests to your development backlog

Example prompt for OpenClaw

Try this with OpenClaw using the App Review Analysis tool

Find all feature requests in my app reviews. Rank them by user demand and group duplicates together.

Tips for OpenClaw

Run this analysis before each planning cycle to keep your roadmap user-driven
Look for feature requests that would convert 3-star reviewers into 5-star reviewers
Compare feature requests across iOS and Android for platform-specific insights

Frequently Asked Questions

How do I identify feature requests from reviews with an AI assistant?

Extract and prioritize feature requests hidden in app store reviews to inform your product roadmap. Connect the App Review Analysis tool to Claude, ChatGPT, Microsoft Copilot, and OpenClaw through ToolRouter, then ask the assistant in plain language. For example: Ask Claude: "Extract feature requests from my app reviews using app-review-analysis" Claude aggregates reviews and returns a ranked list of feature requests

Which AI assistants can identify feature requests from reviews?

Claude, ChatGPT, Microsoft Copilot, and OpenClaw can all identify feature requests from reviews using the App Review Analysis tool through ToolRouter, with no API keys or coding required.

What does the App Review Analysis tool do?

Analyze app store reviews at scale to extract sentiment, feature requests, bug reports, and competitive insights.

Related Use Cases

Open Analyze App Review Sentiment

Analyze App Review Sentiment

Understand how users feel about your app by analyzing sentiment patterns across hundreds or thousands of reviews.

App Review Analysis4 agent guides

Open Track Review Trends Over Time

Track Review Trends Over Time

Monitor how review themes and sentiment evolve across app versions to measure the impact of changes.

App Review Analysis4 agent guides

Open Compare Reviews Against Competitors

Compare Reviews Against Competitors

Benchmark your app review sentiment and themes against competitors to identify relative strengths and weaknesses.

App Review Analysis4 agent guides

Open Identify Bug Reports in Reviews

Identify Bug Reports in Reviews

Extract and categorize bug reports from app reviews to catch issues your crash reporting tools might miss.

App Review Analysis4 agent guides

Related Workflows

App Store DominationDominate both app stores with keyword optimization, listing audits, review analysis, and cross-channel keyword strategy.Review MonitoringMonitor customer feedback across app stores, social comments, community discussions, and brand perception to stay ahead of reputation issues.