SpiderPeople

v2.17.0 Feature - SpiderPeople is available as of December 2025.

Overview

SpiderPeople is SpiderIQ’s intelligent layer for finding the right people behind companies. When you’ve identified companies that match your Ideal Customer Profile (ICP), SpiderPeople helps you find the decision makers—CEOs, CTOs, VPs, and other key roles—at those companies.

The ICP Problem

Every ICP defines two critical dimensions for targeting:

Role: Who makes decisions? (CEO, CTO, VP Sales, Marketing Director)
Location: Where are they? (Tel Aviv, San Francisco, London)

SpiderPeople solves this by searching across the web, finding LinkedIn profiles that match your criteria, and extracting the data you need. Example: Find all CTOs at tech companies in Israel:

CTO tech Israel

How It Works

Search: SpiderPeople searches Google using your natural language query
Discover: Finds LinkedIn profiles matching your criteria
Extract: Pulls profile data (name, title, company, experience)
Enrich: Optionally generates AI-powered insights and research reports

Three Modes

Search Mode

Find decision makers by role, industry, and location

Profile Mode

Get full profile data from a LinkedIn URL

Research Mode

Generate AI research reports on key people

Search Mode

The primary mode for ICP-based prospecting. Use natural language to find decision makers.

Query Examples

Query	What It Finds
`CEO tech Israel`	CEOs at tech companies in Israel
`VP Sales SaaS San Francisco`	VP Sales at SaaS companies in SF
`CTO fintech London`	CTOs at fintech companies in London
`Marketing Director healthcare`	Marketing directors in healthcare
`5 AI engineers at Google`	AI engineers at Google (limits to 5)

Example Request

curl -X POST https://spideriq.di-atomic.com/api/v1/jobs/spiderPeople/submit \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer <your_token>" \
  -d '{
    "payload": {
      "mode": "search",
      "search_query": "CTO fintech Tel Aviv",
      "search_limit": 10
    }
  }'

What You Get

{
  "data": {
    "mode": "search",
    "query": "CTO fintech Tel Aviv",
    "results_count": 10,
    "profiles": [
      {
        "linkedin_url": "https://linkedin.com/in/johndoe",
        "linkedin_id": "johndoe",
        "name": "John Doe",
        "headline": "CTO at FinTech Startup",
        "location": "Tel Aviv, Israel"
      }
    ]
  }
}

Pro Tip: Start broad, then narrow down. Search CTO Israel first, then filter by industry or city in your application.

Profile Mode

Get complete LinkedIn profile data when you have a specific URL.

When to Use

Enrich existing lead records with LinkedIn data
Get detailed work history and education
Extract profile pictures and connection counts
Verify information about known prospects

Example Request

curl -X POST https://spideriq.di-atomic.com/api/v1/jobs/spiderPeople/submit \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer <your_token>" \
  -d '{
    "payload": {
      "mode": "profile",
      "linkedin_url": "https://linkedin.com/in/example-person"
    }
  }'

Profile Data Fields

Field	Description
`full_name`	Person’s full name
`headline`	Current professional headline
`about`	Profile summary/bio
`location`	Geographic location
`current_company`	Current employer
`experience`	Work history (company, title, duration)
`education`	Educational background
`connections`	Connection count
`followers`	Follower count
`profile_pic_url`	Profile photo URL

Caching: Profile data is cached for 7 days. Subsequent requests for the same profile return instantly.

Research Mode

Generate comprehensive AI research reports for key prospects.

When to Use

Deep dive on high-value prospects
Prepare for important meetings
Competitive intelligence on key people
Due diligence research

Example Request

curl -X POST https://spideriq.di-atomic.com/api/v1/jobs/spiderPeople/submit \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer <your_token>" \
  -d '{
    "payload": {
      "mode": "research",
      "linkedin_url": "https://linkedin.com/in/target-executive"
    }
  }'

Research Report Contents

The AI-generated report includes:

Executive Summary: Key facts about the person
Career Overview: Professional trajectory and highlights
Current Role: Deep dive on current position
Notable Achievements: Accomplishments and milestones
Public Presence: Media mentions, speaking engagements
Sources: Links to information sources

Research mode takes 10-30 seconds as it involves AI analysis. Use profile mode for quick lookups.

ICP Workflow: Search → Profile

A typical workflow for ICP-based prospecting:

Step 1: Search for Decision Makers

import requests
import time

headers = {"Authorization": "Bearer <your_token>", "Content-Type": "application/json"}

# Search for CTOs in Israeli fintech
search_response = requests.post(
    "https://spideriq.di-atomic.com/api/v1/jobs/spiderPeople/submit",
    headers=headers,
    json={
        "payload": {
            "mode": "search",
            "search_query": "CTO fintech Israel",
            "search_limit": 20
        }
    }
)

search_job_id = search_response.json()["job_id"]

Step 2: Poll for Results

# Wait for search to complete
while True:
    status = requests.get(
        f"https://spideriq.di-atomic.com/api/v1/jobs/{search_job_id}/status",
        headers=headers
    ).json()

    if status["status"] == "completed":
        break
    time.sleep(2)

# Get search results
results = requests.get(
    f"https://spideriq.di-atomic.com/api/v1/jobs/{search_job_id}/results",
    headers=headers
).json()

profiles = results["data"]["profiles"]
print(f"Found {len(profiles)} decision makers")

Step 3: Enrich Top Prospects

# Get full profile for best matches
for profile in profiles[:5]:  # Top 5
    profile_response = requests.post(
        "https://spideriq.di-atomic.com/api/v1/jobs/spiderPeople/submit",
        headers=headers,
        json={
            "payload": {
                "mode": "profile",
                "linkedin_url": profile["linkedin_url"]
            }
        }
    )
    # Poll for results...

CHAMP Lead Scoring

Score profiles against your ICP for qualification:

{
  "payload": {
    "mode": "profile",
    "linkedin_url": "https://linkedin.com/in/example",
    "product_description": "AI-powered sales automation platform",
    "icp_description": "VP Sales at B2B SaaS companies, 50-200 employees"
  }
}

This generates a CHAMP score indicating how well the person matches your ICP.

Common Use Cases

ICP Targeting

Find decision makers matching role + location criteria

Lead Enrichment

Add LinkedIn data to existing CRM records

Talent Sourcing

Find candidates matching specific criteria

Sales Intelligence

Research prospects before outreach

Best Practices

Writing Effective Search Queries

Include role: CEO, CTO, VP Sales, Director of Marketing
Add location: City, country, or region
Specify industry: fintech, SaaS, healthcare, AI
Limit results: Use search_limit to control volume
Be specific: “VP Engineering AI startup Tel Aviv” > “engineer Israel”

Handling Private Profiles

Some LinkedIn profiles are private. When you encounter one:

The job completes but returns limited data
Check for error field in response
Use search mode to find alternative contacts

Rate Limiting

Standard rate limits apply (100/min)
Research mode uses more resources
Use profile mode for bulk lookups
Implement exponential backoff for retries

Processing Times

Mode	Typical Time	Notes
Search	5-15s	Depends on result count
Profile	3-10s	Faster if cached
Research	10-30s	AI analysis required

Guides

Overview

The ICP Problem

How It Works

Three Modes

Search Mode

Profile Mode

Research Mode

Search Mode

Query Examples

Example Request

What You Get

Profile Mode

When to Use

Example Request

Profile Data Fields

Research Mode

When to Use

Example Request

Research Report Contents

ICP Workflow: Search → Profile

Step 1: Search for Decision Makers

Step 2: Poll for Results

Step 3: Enrich Top Prospects

CHAMP Lead Scoring

Common Use Cases

ICP Targeting

Lead Enrichment

Talent Sourcing

Sales Intelligence

Best Practices

Processing Times

Next Steps

API Reference

Error Handling

Guides

​Overview

​The ICP Problem

​How It Works

​Three Modes

Search Mode

Profile Mode

Research Mode

​Search Mode

​Query Examples

​Example Request

​What You Get

​Profile Mode

​When to Use

​Example Request

​Profile Data Fields

​Research Mode

​When to Use

​Example Request

​Research Report Contents

​ICP Workflow: Search → Profile

​Step 1: Search for Decision Makers

​Step 2: Poll for Results

​Step 3: Enrich Top Prospects

​CHAMP Lead Scoring

​Common Use Cases

ICP Targeting

Lead Enrichment

Talent Sourcing

Sales Intelligence

​Best Practices

​Processing Times

​Next Steps

API Reference

Error Handling

Overview

The ICP Problem

How It Works

Three Modes

Search Mode

Query Examples

Example Request

What You Get

Profile Mode

When to Use

Example Request

Profile Data Fields

Research Mode

When to Use

Example Request

Research Report Contents

ICP Workflow: Search → Profile

Step 1: Search for Decision Makers

Step 2: Poll for Results

Step 3: Enrich Top Prospects

CHAMP Lead Scoring

Common Use Cases

Best Practices

Processing Times

Next Steps