An AI-powered framework for deduplicating, normalizing, and enriching CRM contacts and companies to ensure pristine data hygiene.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install crm-data-cleaner
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 crm-data-cleaner 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 CRM Data Cleaner?
The CRM Data Cleaner is a comprehensive technical framework designed to solve the multi-million dollar problem of poor data quality in sales and marketing operations. By leveraging Openclaw Skills, this tool provides standardized workflows for identifying duplicate records, fixing inconsistent formatting, and filling in missing information. It acts as a bridge between your raw CRM data and high-performing outreach by ensuring every contact and company record is accurate, unique, and enriched with the latest firmographic and technographic data.
This skill is specifically optimized for professional RevOps and DevOps environments where data integrity is paramount. It supports a wide array of platforms including HubSpot, Salesforce, and Pipedrive, allowing teams to maintain a 'Single Source of Truth' without manual data entry. Whether you are dealing with messy CSV imports or scaling a global database, these Openclaw Skills provide the logic needed to automate complex data maintenance tasks.
CRM Data Cleaner Use Cases
- Deduplicating contact lists where users have multiple entries with variations of the same name or email.
- Normalizing international phone numbers and street addresses into a standardized global format.
- Enriching existing lead profiles with missing job titles, company sizes, and industry data using external APIs.
- Auditing CRM health by generating data quality scores based on completeness and accuracy.
- Standardizing company names to remove legal suffixes like Inc or LLC for better personalization in outreach.
How CRM Data Cleaner Works
- Data Assessment: The skill analyzes the current CRM database or CSV export to identify missing fields, duplicates, and formatting errors.
- Normalization: It applies transformation rules to standardize email casing, phone number formats (E.164), and address components.
- Deduplication Logic: Using matching algorithms like Levenshtein Distance and Soundex, it identifies near-duplicate records that simple exact-match filters miss.
- External Enrichment: It interfaces with providers like Clearbit or Apollo to fetch missing data points for identified contacts.
- CRM Synchronization: The cleaned data is pushed back to the CRM platform via API, updating existing records or merging duplicates into a master profile.
CRM Data Cleaner Setup
To begin using these Openclaw Skills for CRM maintenance, you must configure your environment variables with the appropriate API credentials for your CRM and enrichment providers.
# HubSpot Integration
export HUBSPOT_ACCESS_TOKEN='your_hubspot_token'
# Optional Enrichment Keys
export CLEARBIT_API_KEY='your_clearbit_key'
export APOLLO_API_KEY='your_apollo_key'
# Salesforce Integration
export SALESFORCE_ACCESS_TOKEN='your_salesforce_token'
CRM Data Cleaner Data Schema & Taxonomy
The skill organizes data quality tracking using the following taxonomy to ensure high-standard Openclaw Skills implementation:
| Quality Metric | Definition | Target Threshold |
|---|---|---|
| Completeness | Percentage of required fields populated | 95% |
| Accuracy | Validity of email syntax and phone connectivity | 99% |
| Consistency | Adherence to standardized naming and formatting | 95% |
| Uniqueness | Percentage of records that are non-duplicates | <2% duplicate rate |
All enriched data is mapped to specific CRM properties, preserving the original data provenance and timestamping every update.
CRM Data Cleaner Advanced Features
- Fuzzy matching algorithms for advanced duplicate detection across varying name and company spellings.
- Machine learning-based predictive data quality scoring to identify records at risk of decay.
- Bidirectional synchronization logic that resolves conflicts between CRM, marketing automation, and support platforms.
- Automated data routing to manual review queues for high-value enterprise accounts.
- Real-time form submission validation to prevent 'dirty' data from entering the system at the source.
SKILL.md
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