Clauneck is a Ruby-based tool for extracting emails, social media accounts, and other data from websites using Google Search Results. It benefits marketing teams by automating data collection for outreach and lead generation. The tool connects to Google Search and can be integrated into existing data extraction workflows.
git clone https://github.com/serpapi/clauneck.gitClauneck is a Ruby-based tool for extracting emails, social media accounts, and other data from websites using Google Search Results. It benefits marketing teams by automating data collection for outreach and lead generation. The tool connects to Google Search and can be integrated into existing data extraction workflows.
["Install Clauneck: Run `gem install clauneck` in your terminal or add it to your project's Gemfile.","Configure Google Search: Set up a Google Custom Search Engine (CSE) and enable the 'Search the entire web' option. Add your CSE ID and API key to Clauneck's configuration file.","Define Search Queries: Craft search queries targeting your ideal leads. For example, use `\"HR software\" AND \"site:linkedin.com/in\"` to find LinkedIn profiles of HR software professionals.","Run Extraction: Execute Clauneck with your query and export the results to CSV. Example command: `clauneck --query \"HR software\" --output leads.csv`.","Validate and Enrich: Use tools like Hunter.io or Apollo.io to verify email addresses and add missing data (e.g., job titles, company revenue).","Integrate with Outreach Tools: Import the cleaned CSV into your CRM (e.g., HubSpot, Salesforce) or email marketing tool (e.g., Mailchimp, Lemlist) for targeted campaigns."]
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/serpapi/clauneckCopy the install command above and run it in your terminal.
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Use Clauneck to extract email addresses and social media profiles for [TARGET INDUSTRY] companies in [GEOGRAPHIC REGION]. Focus on [SPECIFIC COMPANY SIZE RANGE] businesses. Export the results in CSV format with columns for company name, website URL, email addresses, LinkedIn profiles, and Twitter handles.
Here’s the extracted data for 15 SaaS companies in the Midwest (10-200 employees) specializing in HR software: | Company Name | Website URL | Email Addresses | LinkedIn Profiles | Twitter Handles | |--------------------|---------------------------|-------------------------------------|---------------------------------------|-----------------------| | GreenHire Solutions | https://greenhire.io | sarah@greenhire.io, john@greenhire.io | linkedin.com/company/greenhire-solutions | @GreenHireHR | | PayrollPro Inc | https://payrollpro.com | mike@payrollpro.com, lisa@payrollpro.com | linkedin.com/company/payrollpro-inc | @PayrollProHR | | WorkforceHub | https://workforcehub.com | jane@workforcehub.com, tom@workforcehub.com | linkedin.com/company/workforcehub | @WorkforceHubHR | | ... | ... | ... | ... | ... | **Key Insights:** - 60% of companies listed a generic email format (e.g., info@, contact@). - LinkedIn profiles were found for 93% of companies, while Twitter handles were only present for 40%. - The most common email format was [first initial][last name]@[domain].com (e.g., sarah@greenhire.io). **Next Steps:** 1. Clean the data by removing duplicates and invalid formats. 2. Enrich the dataset with additional details (e.g., job titles, company revenue) using tools like Hunter.io or Apollo.io. 3. Segment the list by company size or funding stage for targeted outreach campaigns. 4. Use the extracted emails to launch a personalized cold email campaign via tools like Lemlist or Mailchimp.
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