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Best Practices

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Writing Effective Queries

Be Specific About What You Need ✅ Good: “Find CTOs at Series B fintech companies in San Francisco with 50-200 employees” ❌ Avoid: “Find some tech people” Combine Multiple Criteria ✅ Good: “Sales directors at SaaS companies that raised funding in the last 90 days and use Salesforce” ❌ Avoid: Making separate searches that could be combined Use Natural Language ✅ Good: “Companies that recently expanded their engineering teams” ❌ Avoid: Trying to write filter syntax manually

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Understanding Entity Types

Vibe Prospecting works with two entity types: Choose “Prospects” when you need:
  • Individual people/contacts
  • Email addresses or phone numbers
  • Specific job titles or roles
  • Decision-makers at companies
Choose “Businesses” when you need:
  • Company information only
  • Firmographics or technographics
  • Market research data
  • Lists of organizations
The AI automatically determines entity type, but mentioning “people,” “contacts,” or “executives” will ensure prospect results.

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Optimizing Credit Usage

1. Start with statistics Before running expensive prospect searches: 
What's the market size of cybersecurity companies with 100-500 employees in the US?
This helps validate your target market without using credits. 2. Review samples before exporting Always check the sample preview to ensure:
  • Results match your expectations
  • Data quality meets your needs
  • Cost is acceptable for your budget
3. Use exclusion lists Prevent duplicate spending: 
Find new prospects, but exclude entities I've already exported
4. Be precise with enrichments Only request enrichments you’ll actually use: 
Enrich with contacts only
vs. 
Enrich with everything available

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Handling Large Datasets

For queries returning 1,000+ results: The system caps at 1,000 results per query. To get more: 
First query: "Find SaaS companies in California with 100-500 employees"
Second query: "Find SaaS companies in New York with 100-500 employees"
Split by geography, industry subcategory, or company size.

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Working with Enrichments

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When to Enrich

Enrichments add detailed information but consume additional credits. Request them when:
  1. You need contact information: Always use enrich-prospects-contacts for emails/phones
  2. You need company details: Use enrich-business-firmographics for basic company info
  3. You need technology insights: Use enrich-business-technographics for full tech stack
  4. You need funding data: Use enrich-business-funding-and-acquisitions for investment history

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Enrichment Examples

Getting Email Addresses 
Find marketing managers at fintech companies, and get their email addresses
AI automatically applies: enrich-prospects-contacts Getting Company Technology Stack 
Show me which technologies are used by top e-commerce companies
AI automatically applies: enrich-business-technographics Multiple Enrichments 
Find CTOs at recently funded companies and get their emails, plus company funding details
AI applies both: enrich-prospects-contacts and enrich-business-funding-and-acquisitions

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Understanding Costs

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Credit System

Vibe Prospecting uses Explorium credits:
  • Base fetch: ~1 credit per entity
  • Enrichments: Additional credits per enrichment type per entity
  • Events: Additional credits when fetching detailed event information

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Cost Estimation

Before any export, you’ll see: 
Export Cost: 450 credits

Sample Preview (5 of 150):
[Table with sample data and cost_in_credits column]

Ready to Export? Get all 150 prospects with full details
👉 Say "export" to download the complete dataset as CSV 👈
Never auto-exports - you always approve costs first.

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