If you’re using the People Search Endpoint, understanding how credits are consumed can help you avoid unexpected charges and plan your usage more effectively.
This guide breaks down how usage is calculated, what contributes to the total cost, and how to optimize your requests for better efficiency.
Whether you’re testing results for the first time or scaling enrichment for your team, these tips can help you stay within your budget and get the most value from each call.
How Credit Consumption Works
When using the People Search Endpoint, credits are charged per result returned—typically:
3 credits per returned profile URL
This includes matches from your filtered query, such as job title, location, or employment status.
Example:
If your search returns 100 profiles, it would cost:
3 credits × 100 results = 300 credits
This can add up quickly, especially with high-volume requests or broader queries.
Factors That Impact Credit Use
Several request parameters can affect how many credits are used:
page_size: If not set, it defaults to 100. Combined with the 3-credit-per-result rate, a single call could consume up to 300 credits.
Filtering: Broader filters typically return more results, which increases your credit usage.
✅ How to Reduce Credit Usage
To stay within your budget more effectively:
Set a lower page_size (e.g., 25 or 50)
Use tighter filters to narrow down your search results
Test with smaller values before scaling up to a large dataset
Example:
{
"page_size": 25,
"region": "New York",
"current_role_title": "engineer"
}
📌 Quick Recap
Action | Impact on Credits |
Returned profile URL | 3 credits per result |
page_size not set | Defaults to 100 (can cost 300 credits) |
Broad query filters | May return more results, costing more |
Additional enrichments | May incur extra credit charges |
Still Have Questions?
If you’re not sure how much a request will cost—or want help estimating credit usage—just reach out through the chat icon in the bottom-right corner of the page.
We’re always happy to help!