How it works
Describe your ideal prospect
Enter a natural language query describing who you want to find. For example: “Blue-collar business owners in northern Georgia.”
Scouting searches and analyzes
Your query is converted into LinkedIn search filters. Scouting searches profiles, then evaluates each match against your criteria.
Review results
Results appear as a table showing each prospect’s name, current role, education, and criteria match score. Profiles stream in as they are processed.
What you see for each profile
For each match, Scouting shows:- Name and photo — LinkedIn profile name and avatar
- Location — Current city or region
- Headline — LinkedIn headline
- Current role — Job title, company name, and dates
- Education — School name, degree, and years
- Criteria match — A score showing how many of your criteria each profile meets, with detailed reasoning
Import credits
Each book receives a monthly budget of import credits. Importing a prospect uses one credit. Credits reset at the beginning of each month. The credits remaining are shown in the top-right corner of the results page.Search examples
- “Blue-collar business owners in northern Georgia”
- “State employees in the Kansas City metro”
- “University of Texas faculty in their 40s and 50s”
- “Religious couples in Chicago who work in software”
Best practices
- Be specific. Include details like profession, location, and demographics for better results.
- Use natural language. Write the way you would describe your ideal client to a colleague.
- Review criteria matches. Hover over the criteria score to see which criteria each profile meets or does not meet.
- Iterate on searches. Run multiple searches with different criteria to find different types of prospects.