Tools / Social Media Comments / Use Cases / Find Product Feedback in Social Comments

Find Product Feedback in Social Comments

Extract actionable product feedback from YouTube, Reddit, and TikTok comments about your product or competitors.

Quick answer: Use the Social Media Comments tool through ToolRouter to find product feedback in social comments directly from Claude, ChatGPT, Microsoft Copilot, and OpenClaw — connect once, then drive it with plain-language prompts. No code required.

Tool

Social Media Comments

The most honest product feedback lives in social media comments, not in survey responses. When someone comments on a YouTube review that the battery dies after two hours, or a Reddit user explains why they switched to a competitor, or a TikTok commenter describes exactly how they use your product in an unexpected way -- that is unfiltered, unsolicited truth about your product.

Collecting comments from product-related posts across YouTube, Reddit, and TikTok surfaces feedback that never makes it into formal channels. Reddit threads are especially valuable because users provide detailed, technical feedback in discussions. YouTube review comments often contain real usage experiences. TikTok comments capture immediate emotional reactions to products.

How to find product feedback in social comments with Claude, ChatGPT, Microsoft Copilot, and OpenClaw

Claude turns product feedback mining into a targeted terminal investigation. Pull comments from product-related posts and Claude extracts actionable feedback, grouping it by category -- bugs, feature requests, praise, confusion. Ask follow-up questions like "what features are users asking for most?" or "how does competitor product feedback differ from ours?" for deep product intelligence.

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 find product feedback in social comments with Claude

Once connected (see setup above), use the Social Media Comments tool:

Ask Claude: "Pull comments from this YouTube product review and this Reddit discussion thread"
Claude collects comments and extracts product-specific feedback, complaints, and feature requests
Ask: "What are the top five product issues mentioned? Any feature requests?"

Example prompt for Claude

Try this with Claude using the Social Media Comments tool

Collect comments from this YouTube review of our product and the top Reddit threads discussing it. Extract all product feedback -- complaints, praise, feature requests, and usage patterns.

Tips for Claude

Include competitor product posts to understand what users wish your product had
Ask Claude to categorize feedback into themes aligned with your product roadmap

ChatGPT extracts product feedback from social comments and generates a product insights report organized by theme. It categorizes feedback into bugs, feature requests, and user experience observations, then ranks them by frequency and severity. The output includes a product improvement roadmap suggestion based on what users are actually saying.

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 find product feedback in social comments with ChatGPT

Once connected (see setup above), use the Social Media Comments tool:

Ask: "Pull comments from this Reddit thread about our product and extract feedback"
ChatGPT collects comments and categorizes the feedback by type
Request: "Rank feedback items by frequency and suggest product improvements"

Example prompt for ChatGPT

Try this with ChatGPT using the Social Media Comments tool

Collect comments from this Reddit discussion about our app. Extract all user feedback, categorize it as bugs, feature requests, or praise, and rank by frequency.

Tips for ChatGPT

ChatGPT can suggest concrete product improvements based on the feedback patterns
Ask for both direct feedback and implied pain points from how users describe their workflows

Copilot pulls product feedback from social comments directly into your IDE, bridging the gap between customer voice and engineering backlog. Fetch comments and Copilot helps format feature requests as user stories, bug reports as issue descriptions, and integration points that route social feedback into your product management workflow.

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 find product feedback in social comments with Copilot

Once connected (see setup above), use the Social Media Comments tool:

In Copilot Chat: "Pull Reddit comments about our product and extract bug reports"
Copilot collects comments and identifies technical feedback
Ask: "Format feature requests as user stories for our backlog"

Example prompt for Copilot

Try this with Copilot using the Social Media Comments tool

Collect comments from this Reddit thread and this YouTube review about our developer tool. Extract feature requests and format them as user stories.

Tips for Copilot

Turn comment-sourced feature requests directly into backlog items
Combine with competitor product comments to identify gaps in your offering

OpenClaw automates product feedback extraction by batch-pulling comments from product-related posts across platforms and categorizing every piece of feedback. Output includes structured feedback inventories with category labels, frequency scores, and source attribution. Import directly into product management tools for data-driven roadmap planning.

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 find product feedback in social comments with OpenClaw

Once connected (see setup above), use the Social Media Comments tool:

Ask OpenClaw: "Pull comments from this YouTube review and extract product feedback"
OpenClaw fetches comments and highlights actionable feedback
Ask: "What patterns emerge? What do users want most?"

Example prompt for OpenClaw

Try this with OpenClaw using the Social Media Comments tool

Collect comments from this YouTube product review and this TikTok video. Extract all product feedback and identify the most requested improvements.

Tips for OpenClaw

Look at both your product posts and competitor product posts for a complete picture
Ask for feedback grouped by product area to route to the right team

Frequently Asked Questions

How do I find product feedback in social comments with an AI assistant?

Extract actionable product feedback from YouTube, Reddit, and TikTok comments about your product or competitors. Connect the Social Media Comments tool to Claude, ChatGPT, Microsoft Copilot, and OpenClaw through ToolRouter, then ask the assistant in plain language. For example: Ask Claude: "Pull comments from this YouTube product review and this Reddit discussion thread" Claude collects comments and extracts product-specific feedback, complaints, and feature requests

Which AI assistants can find product feedback in social comments?

Claude, ChatGPT, Microsoft Copilot, and OpenClaw can all find product feedback in social comments using the Social Media Comments tool through ToolRouter, with no API keys or coding required.

What does the Social Media Comments tool do?

Collect and analyze comments from TikTok, YouTube, Instagram, and Reddit. Extract audience sentiment, questions, and feedback at scale.

Related Use Cases

Open Analyze Comment Sentiment Across Platforms

Analyze Comment Sentiment Across Platforms

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Open Monitor Customer Issues in Social Comments

Monitor Customer Issues in Social Comments

Detect customer complaints, bug reports, and support requests hiding in social media comment threads.

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Open Research Campaign Reactions from Comments

Research Campaign Reactions from Comments

Measure how your marketing campaigns land by analyzing audience comments across TikTok, YouTube, and Instagram.

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Open Identify Common Questions from Comments

Identify Common Questions from Comments

Discover the questions your audience keeps asking by analyzing comment threads across YouTube, Reddit, and Instagram.

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Related Workflows

Influencer DiscoveryDiscover and vet potential influencer partners by profiling their audience, searching niche creators, evaluating engagement quality, and finding contacts.Review MonitoringMonitor customer feedback across app stores, social comments, community discussions, and brand perception to stay ahead of reputation issues.Crisis MonitoringMonitor for brand reputation crises by scanning news, social media, and comment sentiment to detect and assess threats early.Customer Research PipelineBuild customer personas from real social data by mining social media conversations, analyzing comments, generating personas, and validating with market research.