Tutorial

How to Compare SEO vs Ads with SERP Data

Use SERP data to decide between SEO and Google Ads for early SaaS. Analyze ad density, organic difficulty, and AI Overview presence per keyword.

Early-stage SaaS founders face a critical decision: invest in SEO for long-term organic traffic or spend on Google Ads for immediate visibility. SERP data makes this decision data-driven instead of guesswork. By analyzing ad density, organic competition strength, AI Overview presence, and featured snippet availability for your target keywords, you can determine which channel offers better ROI. This tutorial shows how to use search API data to compare SEO versus Ads potential for a set of keywords and generate a channel recommendation.

Prerequisites

  • Python 3.8+ installed
  • requests library installed
  • A Scavio API key from scavio.dev
  • A list of target keywords for your SaaS product

Walkthrough

Step 1: Define your target keywords

Set up the keywords you want to analyze for SEO vs Ads potential.

Python
import os, requests, json

API_KEY = os.environ["SCAVIO_API_KEY"]

KEYWORDS = [
    "project management software",
    "team collaboration tool",
    "task management app for startups",
    "best project tracker 2026",
]

Step 2: Analyze SERP composition

For each keyword, check ad presence, organic results, AI Overviews, and SERP features.

Python
def analyze_serp(keyword):
    resp = requests.post("https://api.scavio.dev/api/v1/search",
        headers={"x-api-key": API_KEY},
        json={"platform": "google", "query": keyword})
    data = resp.json()
    organic = data.get("organic_results", [])
    ads = data.get("ads", [])
    return {
        "keyword": keyword,
        "organic_count": len(organic),
        "ad_count": len(ads),
        "has_ai_overview": bool(data.get("ai_overview")),
        "paa_count": len(data.get("people_also_ask", [])),
        "has_featured_snippet": any(r.get("featured_snippet") for r in organic[:3]),
    }

Step 3: Score SEO vs Ads potential

Calculate a score for each channel based on SERP composition.

Python
def score_channels(analysis):
    seo_score = 0
    seo_score += (10 - min(analysis["ad_count"], 10)) * 5
    seo_score += analysis["paa_count"] * 5
    seo_score += 20 if analysis["has_featured_snippet"] else 0
    seo_score -= 15 if analysis["has_ai_overview"] else 0
    ads_score = 0
    ads_score += analysis["ad_count"] * 10
    ads_score += 20 if analysis["has_ai_overview"] else 0
    return {
        **analysis,
        "seo_score": max(seo_score, 0),
        "ads_score": max(ads_score, 0),
        "recommendation": "SEO" if seo_score > ads_score else "Ads",
    }

Step 4: Generate the comparison report

Run the analysis across all keywords and produce a summary recommendation.

Python
def compare_all(keywords):
    results = [score_channels(analyze_serp(kw)) for kw in keywords]
    seo_wins = sum(1 for r in results if r["recommendation"] == "SEO")
    ads_wins = len(results) - seo_wins
    return {
        "total_keywords": len(results),
        "seo_recommended": seo_wins,
        "ads_recommended": ads_wins,
        "overall": "SEO" if seo_wins > ads_wins else "Ads",
        "details": results,
    }

report = compare_all(KEYWORDS)
print(f"Overall: {report['overall']} ({report['seo_recommended']} SEO vs {report['ads_recommended']} Ads)")

Python Example

Python
import os, requests
API_KEY = os.environ["SCAVIO_API_KEY"]
def analyze(keyword):
    resp = requests.post("https://api.scavio.dev/api/v1/search",
        headers={"x-api-key": API_KEY},
        json={"platform": "google", "query": keyword})
    d = resp.json()
    ads = len(d.get("ads", []))
    paa = len(d.get("people_also_ask", []))
    return {"keyword": keyword, "ads": ads, "paa": paa,
            "pick": "Ads" if ads > 3 else "SEO"}

for kw in ["project management software", "task tracker app"]:
    print(analyze(kw))

JavaScript Example

JavaScript
const H = {"x-api-key": process.env.SCAVIO_API_KEY, "Content-Type": "application/json"};
async function analyze(keyword) {
  const r = await fetch("https://api.scavio.dev/api/v1/search", {
    method: "POST", headers: H,
    body: JSON.stringify({platform: "google", query: keyword})
  });
  const d = await r.json();
  const ads = (d.ads||[]).length, paa = (d.people_also_ask||[]).length;
  return {keyword, ads, paa, pick: ads > 3 ? "Ads" : "SEO"};
}
analyze("project management software").then(console.log);

Expected Output

JSON
A keyword-level comparison report showing SEO and Ads scores for each keyword, with an overall channel recommendation based on SERP composition data.

Related Tutorials

Frequently Asked Questions

Most developers complete this tutorial in 15 to 30 minutes. You will need a Scavio API key (free tier works) and a working Python or JavaScript environment.

Python 3.8+ installed. requests library installed. A Scavio API key from scavio.dev. A list of target keywords for your SaaS product. A Scavio API key gives you 250 free credits per month.

Yes. The free tier includes 250 credits per month, which is more than enough to complete this tutorial and prototype a working solution.

Scavio has a native LangChain package (langchain-scavio), an MCP server, and a plain REST API that works with any HTTP client. This tutorial uses the raw REST API, but you can adapt to your framework of choice.

Start Building

Use SERP data to decide between SEO and Google Ads for early SaaS. Analyze ad density, organic difficulty, and AI Overview presence per keyword.