A comprehensive toolset for mining social signals, validating personas, and automating customer research workflows to ensure data-driven product development.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install customer-research-dv
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install customer-research-dv using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Customer Research & Validation?
The Customer Research & Validation skill is a critical component of the Openclaw Skills library designed to replace market assumptions with hard data. It enables developers and product managers to perform pre-pipeline validation by extracting real customer signals from subreddits, forums, and review platforms. By automating the discovery of pain points and sentiment, this skill ensures that marketing strategies and product roadmaps are built on high-fidelity user feedback rather than guesswork.
This skill serves as a bridge between raw market data and actionable strategy. It allows teams to automate the extraction of sentiment, identify recurring themes across diverse sources, and generate structured interview guides. Integration into existing Openclaw Skills workflows ensures that findings are piped directly into content creation and product management tools, maintaining a tight feedback loop between the customer and the development team.
Customer Research & Validation Use Cases
- Mining subreddits and forums to extract specific customer pain points and feature requests.
- Validating persona assumptions against real-world user behavior and language patterns.
- Aggregating and analyzing competitor reviews from platforms like G2 and Trustpilot.
- Generating structured customer interview scripts and survey questions based on specific problem statements.
- Monitoring market sentiment for specific product categories or brand mentions.
How Customer Research & Validation Works
- Triggering: The skill is activated when a user requests validation for an idea, persona, or market assumption.
- Data Collection: Specialized scripts fetch raw data from Reddit, niche forums, or review aggregators using provided keywords and parameters.
- Analysis: The system utilizes LLM integration to process text, scoring sentiment and identifying key themes like complexity, cost, or trust.
- Documentation: Findings are compiled into standardized JSON reports stored in the research directory for downstream consumption.
- Integration: Insights are used to update persona databases, inform content pillars, and flag validated needs for the product roadmap.
Customer Research & Validation Setup
To use this component of Openclaw Skills, ensure your environment has jq and curl installed. You will also need OpenClaw LLM access for sentiment analysis tasks.
# Prepare the research directory
mkdir -p data/research
chmod +x scripts/*.sh
# Run a test Reddit mining operation
./scripts/reddit-miner.sh --subreddit "personalfinance" --query "retirement planning" --limit 50 --sentiment
Customer Research & Validation Data Schema & Taxonomy
All research data is stored in data/research/ using a consistent schema to ensure compatibility across the Openclaw Skills ecosystem.
| Object | Description |
|---|---|
meta |
Includes the script name, timestamp, and specific query parameters used. |
findings |
An array containing the source text, sentiment score (0-1), and extracted themes. |
summary |
High-level metrics including total source count, average sentiment, and top recurring themes. |
key_insights |
A list of actionable takeaways derived from the aggregated data. |
Customer Research & Validation Advanced Features
- Multi-source aggregation: Combine data from Reddit, Trustpilot, and G2 into a single analysis pipeline.
- Sentiment confidence thresholds: Only report sentiment scores when a minimum sample size (e.g., 50+ samples) is met.
- Automated theme validation: Requires a theme to appear in at least three independent sources before being flagged as a trend.
- Verbatim quote extraction: Automatically tracks real customer language for use in high-converting marketing copy.
- Integration hooks: Feed validated pain points directly into content strategy workflows for automated pillar creation.
SKILL.md
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