Ad Intelligence API for Paid Search Monitoring

What the API returns for paid-search-adjacent monitoring

The current OrbitScraper public response is best used for commercial-query monitoring rather than direct ad-copy extraction. Teams use detected_intent, organic_results, related_searches, and search_information to understand who owns high-intent queries and how the query landscape changes over time.

curl -X POST "https://api.orbitscraper.com/v1/search" \
  -H "x-api-key: ORS_your_key" \
  -H "Content-Type: application/json" \
  -d '{
    "q": "crm software for startups",
    "engine": "google",
    "gl": "us",
    "num": 10
  }'

{
  "detected_intent": "commercial",
  "organic_results": [
    {
      "position": 1,
      "title": "CRM Built for Startups",
      "link": "https://competitor.com/crm",
      "displayed_link": "competitor.com",
      "snippet": "Close more deals with less effort."
    }
  ],
  "related_searches": [
    { "query": "best crm for startup sales teams" }
  ]
}

Use cases for commercial query data

• Competitor landing-page monitoring: track how often the same competitor domain shows up on high-intent keywords.
• Keyword intent classification: use detected_intent to separate informational research terms from commercial or product terms.
• Multi-engine coverage: run the same query across Google, Bing, Brave, and DuckDuckGo to see where competitors are strongest.
• Trademark query monitoring: keep an eye on brand-plus-category searches that matter to your paid and organic programs.
• Share of voice: count how often a competitor appears in top positions across a target keyword set over time.

Code example — competitor commercial query monitoring

import json
import requests

API_KEY = "ORS_your_key"
KEYWORDS = ["crm software", "crm for startups", "best crm 2026"]
COMPETITOR_DOMAIN = "competitor.com"

for keyword in KEYWORDS:
    response = requests.post(
        "https://api.orbitscraper.com/v1/search",
        headers={"x-api-key": API_KEY, "Content-Type": "application/json"},
        json={"q": keyword, "engine": "google", "gl": "us", "num": 10},
        timeout=30,
    )
    response.raise_for_status()
    payload = response.json()
    print(json.dumps({"keyword": keyword, "jobId": payload["jobId"]}, indent=2))

Key parameters for ad intelligence

• engine: run the same query across multiple engines to see where competitors prioritize search visibility.
• gl: compare country-by-country differences in commercial query composition.
• device: mobile and desktop often show different landing-page competition and query layouts.
• detected_intent: use as a routing signal for growth and paid-search workflows.

Who uses this

• PPC agencies monitoring competitor visibility on client keyword sets.
• In-house growth teams tracking which landing pages keep winning commercial queries.
• Competitive intelligence teams comparing bottom-of-funnel query coverage across markets.
• Brands watching trademark or brand-plus-category searches over time.