Domain authority is not a single metric you can look up -- it is a composite signal derived from how often a domain ranks, where it ranks, and what SERP features it owns. Third-party DA scores from Moz or Ahrefs are proprietary estimates that lag behind reality. A SERP-based approach queries multiple relevant keywords, counts how often a target domain appears in the top 10, tracks its average position, and checks for featured snippet or AI Overview citations. This tutorial builds that pipeline using the Scavio API, producing a domain strength report based on live SERP data rather than stale crawl indices.
Prerequisites
- Python 3.8 or higher installed
- requests library installed
- A Scavio API key from scavio.dev
- A list of industry keywords relevant to the target domain
Walkthrough
Step 1: Define the target domain and keyword set
Choose the domain you want to evaluate and a set of keywords that represent its competitive landscape. More keywords produce a more accurate picture.
Python
TARGET_DOMAIN = "example.com"
KEYWORDS = [
"best project management tool",
"project management software 2026",
"team collaboration platform",
"agile project tracking",
"free project management app"
]Step 2: Query SERPs and extract ranking data
For each keyword, fetch the SERP and check if the target domain appears in organic results. Record its position and any SERP features it owns.
Python
import os
import requests
API_KEY = os.environ.get("SCAVIO_API_KEY", "your_scavio_api_key")
ENDPOINT = "https://api.scavio.dev/api/v1/search"
def analyze_serp(query: str, domain: str) -> dict:
r = requests.post(
ENDPOINT,
headers={"x-api-key": API_KEY},
json={"query": query, "country_code": "us"}
)
data = r.json()
result = {"query": query, "position": None, "featured_snippet": False, "ai_overview": False}
for item in data.get("organic_results", []):
if domain in item.get("link", ""):
result["position"] = item["position"]
break
snippet = data.get("featured_snippet", {})
if domain in snippet.get("link", ""):
result["featured_snippet"] = True
for src in data.get("ai_overview", {}).get("sources", []):
if domain in src.get("domain", ""):
result["ai_overview"] = True
return resultStep 3: Aggregate metrics into a domain score
Calculate visibility rate, average position, and SERP feature ownership across all queried keywords.
Python
def compute_metrics(results: list[dict]) -> dict:
total = len(results)
ranked = [r for r in results if r["position"] is not None]
positions = [r["position"] for r in ranked]
snippets = sum(1 for r in results if r["featured_snippet"])
ai_cites = sum(1 for r in results if r["ai_overview"])
return {
"keywords_checked": total,
"keywords_ranked": len(ranked),
"visibility_rate": round(len(ranked) / total * 100, 1) if total else 0,
"avg_position": round(sum(positions) / len(positions), 1) if positions else None,
"featured_snippets": snippets,
"ai_overview_citations": ai_cites
}Python Example
Python
import os
import json
import requests
API_KEY = os.environ.get("SCAVIO_API_KEY", "your_scavio_api_key")
ENDPOINT = "https://api.scavio.dev/api/v1/search"
def analyze_serp(query: str, domain: str) -> dict:
r = requests.post(
ENDPOINT,
headers={"x-api-key": API_KEY},
json={"query": query, "country_code": "us"}
)
r.raise_for_status()
data = r.json()
result = {"query": query, "position": None, "featured_snippet": False, "ai_overview": False}
for item in data.get("organic_results", []):
if domain in item.get("link", ""):
result["position"] = item["position"]
break
snippet = data.get("featured_snippet", {})
if domain in snippet.get("link", ""):
result["featured_snippet"] = True
for src in data.get("ai_overview", {}).get("sources", []):
if domain in src.get("domain", ""):
result["ai_overview"] = True
return result
def domain_metrics(domain: str, keywords: list[str]) -> dict:
results = [analyze_serp(kw, domain) for kw in keywords]
ranked = [r for r in results if r["position"] is not None]
positions = [r["position"] for r in ranked]
return {
"domain": domain,
"keywords_checked": len(keywords),
"keywords_ranked": len(ranked),
"visibility_pct": round(len(ranked) / len(keywords) * 100, 1),
"avg_position": round(sum(positions) / len(positions), 1) if positions else None,
"featured_snippets": sum(1 for r in results if r["featured_snippet"]),
"ai_overview_citations": sum(1 for r in results if r["ai_overview"]),
"details": results
}
if __name__ == "__main__":
keywords = ["best project management tool", "project management software 2026", "team collaboration platform"]
report = domain_metrics("example.com", keywords)
print(json.dumps(report, indent=2))JavaScript Example
JavaScript
const API_KEY = process.env.SCAVIO_API_KEY || "your_scavio_api_key";
const ENDPOINT = "https://api.scavio.dev/api/v1/search";
async function analyzeSerp(query, domain) {
const res = await fetch(ENDPOINT, {
method: "POST",
headers: { "x-api-key": API_KEY, "Content-Type": "application/json" },
body: JSON.stringify({ query, country_code: "us" })
});
const data = await res.json();
const result = { query, position: null, featuredSnippet: false, aiOverview: false };
for (const item of data.organic_results || []) {
if ((item.link || "").includes(domain)) { result.position = item.position; break; }
}
if ((data.featured_snippet?.link || "").includes(domain)) result.featuredSnippet = true;
for (const src of data.ai_overview?.sources || []) {
if ((src.domain || "").includes(domain)) result.aiOverview = true;
}
return result;
}
async function domainMetrics(domain, keywords) {
const results = [];
for (const kw of keywords) results.push(await analyzeSerp(kw, domain));
const ranked = results.filter(r => r.position !== null);
const positions = ranked.map(r => r.position);
console.log(`${domain}: ${ranked.length}/${keywords.length} keywords ranked`);
if (positions.length) console.log(`Avg position: ${(positions.reduce((a,b) => a+b, 0) / positions.length).toFixed(1)}`);
console.log(`Featured snippets: ${results.filter(r => r.featuredSnippet).length}`);
console.log(`AI Overview citations: ${results.filter(r => r.aiOverview).length}`);
}
domainMetrics("example.com", ["best project management tool", "project management software 2026"]).catch(console.error);Expected Output
JSON
{
"domain": "example.com",
"keywords_checked": 5,
"keywords_ranked": 3,
"visibility_pct": 60.0,
"avg_position": 4.7,
"featured_snippets": 1,
"ai_overview_citations": 1,
"details": [
{ "query": "best project management tool", "position": 3, "featured_snippet": true, "ai_overview": false },
{ "query": "project management software 2026", "position": 5, "featured_snippet": false, "ai_overview": true },
{ "query": "team collaboration platform", "position": 6, "featured_snippet": false, "ai_overview": false }
]
}