Data Enrichment
Common patterns for enriching your data with websites, contact information, and company details.Find Company Website
Use Case: You have a company name and need to find their official website.- Knowledge graph results are more reliable than organic search results
- Include location data when available for better accuracy
- Filter out directory sites (Yelp, LinkedIn, etc.) if needed
Get Contact Information
Use Case: Find email and phone number for a person using their LinkedIn profile.- Always prioritize work contact info for B2B outreach
- Provide as much context as possible (name, company) for better results
- Handle missing data gracefully
Find LinkedIn Profile URL
Use Case: Find someone’s LinkedIn profile from their name and company.Enrich LinkedIn Profile Data
Use Case: Get detailed information from a LinkedIn profile.- Full name, headline, current job title
- Location and experience duration
- Work history and education
- Skills and connections count
Find Company LinkedIn URL
Use Case: Find a company’s LinkedIn page from their name or website.Enrich Company Data
Use Case: Get detailed company information from LinkedIn.Parse Address
Use Case: Parse a full address string into structured components.Normalize Website Domain
Use Case: Clean and normalize website URLs to consistent domain format.Get Phone from Knowledge Graph
Use Case: Extract phone number from Google search results.Best Practices
Use Multiple Data Sources
Use Multiple Data Sources
Always have fallback options. Try knowledge graph first, then organic results, then alternative sources.
Filter Directory Sites
Filter Directory Sites
Exclude Yelp, LinkedIn, Facebook, and other directory sites when looking for official websites.
Prioritize Data Quality
Prioritize Data Quality
Work emails are better than personal. Knowledge graph data is more reliable than scraped data.
Handle Missing Data Gracefully
Handle Missing Data Gracefully
Always check if data exists before using it. Return empty strings or null rather than throwing errors.
Normalize Data Consistently
Normalize Data Consistently
Clean and normalize data (URLs, phone numbers, names) to a consistent format.