How to Scrape Google Search Result Page (SERP) - 3 Methods

Data is a precious thing and will last longer than the systems themselves.

• , computer scientist and inventor of the World Wide Web

Every day, Google processes searches: These aren't just answers to daily questions; they're a goldmine of insights—market trends, competitor activities, and a wealth of consumer data. Whether you're a salesperson, an expert, or a marketer, you can pull out valuable insights and turn them into actionable business strategies.

Still using the old copy-paste method to gather this data? It's time to say goodbye to it.

In this article, we'll explore what Google SERP is, the valuable data it holds, and we will also introduce you to three methods for using a Google SERP scraper, including the most easy-to-use one, the no-code AI web scraper .

What is Google Search Result Page (SERP)?

(search engine results page) is what you see after typing your search keywords into search engines like , , or . It's the gateway to all traffic, the first stop before you click on any links or pages.

A key feature of SERP is that it's driven by real-time data: updates in algorithms, new SERP features, keyword trends, and changes in website content can all affect search results. Moreover, search engines personalize results based on your search history and location, meaning even at the same time, different people might see different SERPs. As you can imagine, this makes it challenging for non-tech folks to efficiently extract data from these unstructured web pages.

With Google holding over of the global search engine market share, understanding the structure of Google SERP results and how to leverage them is crucial for business success.

What Data Does Google SERP Contain?

Structure of Google SERP

Depending on the nature of the search query, the structure of Google SERP can vary. Generally, it includes three main parts:

• Paid Results: These are search results labeled with "Ad" or "Sponsored." Websites pay Google to appear above or below organic results. Sponsored ads may not appear on every SERP, depending on the user's query. In 2023, Google's ad revenue reached 264.59 billion U.S. dollars, according to .

• Organic Results: These are unpaid search results displayed based on relevance and page ranking. Each result includes a title, meta description, and URL.

• SERP Features: These are features Google incorporates to enhance user experience, and they are constantly evolving. They include featured snippets, AI overviews, People Also Ask boxes (PAA), knowledge panels, local packs (for geographically focused searches), videos, images, and shopping results.

Data Type

Understanding the structure of SERP gives you an idea of the types of information you can extract, including but not limited to:

• Ads
• Title
• URL
• Meta Description
• PAA box
• Shopping Info: price, image
• Email
• Telephone number

What Can You Do with SERP Data

Sales

By using precise search queries, sales teams can efficiently generate leads and discover sales opportunities that others might miss. Google can help extract potential customer information from social platforms, including emails and phone numbers, providing sales teams with valuable contact details. We'll provide a detailed guide on using SERP to extract sales leads from Instagram below.

Market Research

SERP results can assist marketers in working more efficiently. For example, in competitor analysis, by scraping competitors' ads and product information, marketers can understand their strategies and optimize their own advertising and marketing tactics.

SERP is also a predictor of market trends. Analyzing keyword trends in SERP can reveal emerging market opportunities. A sudden increase in search volume for certain keywords might indicate a new market opportunity. For instance, if you run a clothing store and notice a rise in searches for "sustainable fashion," it might be time to add products that align with this trend to your inventory.

SEO Analysis

SERP is the foundation for SEO specialists. By analyzing SERP data, they can adjust keyword strategies and optimize website content to improve search engine rankings.

Let's take PAA as an example. By scraping these related questions and analyzing their changes, you can identify other questions users might be interested in, allowing you to optimize your website content accordingly.

Content Analysis

For journalists, scraping Google News results can help analyze trends and understand public interest topics, guiding content production. You can find detailed information on using a web scraper to extract articles in our guide.

How to Scrape Google Search Result Page

Now that you understand the uses of SERP data, the next question is: how do we collect it?

Manual copy-pasting is an option, but it's not practical for handling large volumes of data. With technological advancements, especially in AI, we can use web scrapers to collect massive data. Here are three automated methods:

Using Thunderbit AI Web Scraper

is a no-code AI web scraper that can help you extract anything you want from a website. You can use our or customize the columns yourself. Let's take a sales use case, Leads Generation, as an example, and provide a step-by-step guide on finding qualified leads using Thunderbit.

• Step 1: Add Thunderbit as a Chrome extension and log in using your Google account or other email.

• Step 2: Insert your search query.

  To narrow your search results, can be useful.

  For example, here's a search query generated by to find emails of people related to gyms in LA on Instagram:

  site:instagram.com ("gym" OR "fitness" OR "trainer") AND ("email" OR "@" OR “@gmail.com“ or ”@yahoo.com“ ) AND ("Los Angeles" OR "LA" OR "California")
  

  Insert the search query in Google and press Enter—now you can see all the information you want in the returned results.

• Step 3: Launch Thunderbit and scrape Use natural language to describe the types of content you want to scrape (you can also click "Add column detailed instruction" to add more descriptions). Choose to export it as a table or directly to Notion, Airtable, or Google Sheets.

  Keep in mind, Thunderbit uses AI to help you scrape. So, even if some emails are blended with other text in the snippet on the Google SERP page, AI can accurately extract the emails for you.

  Click the Scrape button and wait for the results!

Using Traditional Web Scraper

Traditional web scrapers can also help you extract Google SERP data in bulk. Here's how to scrape SERP using WebScraper.io:

• Install the Web Scraper Extension and open Chrome Developer Tools.
• Click “Create new sitemap” and set the start URL to your Google search results page.
• Configure selectors to select specific data.

• Run the scraper and export data.

• After scraping bios, you still have to extract emails from Excel using a regex formula:

  text=REGEXEXTRACT(A2,"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}")
  

  (assuming A2 contains your profile text)

  This will help you extract any email addresses you want to get.

Obviously, the downside of this method is that you need some knowledge of web structure, and if the website changes (which is very likely to happen even within one day), you'll need to reconfigure the selectors.

Using Google Official API or Third-party SERP APIs

Google offers an official API called , which allows you to programmatically access Google's search results page. You need to create and set up your , get an API key, and use Python's requests library to make a request. However, you can only get what they give you, and the amount you can access is strictly limited. If you want personalized customization, this method might not work.

A more common choice is to use third-party SERP scraper APIs (like Zen SERP, SerpApi, ScrapingBee) to handle this. This also involves a complex setup and request process. After installation, you'll need to write code to fetch all related Instagram profile URLs and then extract emails from the bio section. This can be quite complex for business people lacking coding knowledge.

import requests
from bs4 import BeautifulSoup
import re

# SerpApi credentials
SERP_API_KEY = "your_serpapi_key"
SEARCH_QUERY = "marketing consultant site:instagram.com"

# Step 1: Fetch Instagram profile URLs from SerpApi
def get_instagram_profiles(query):
    url = "https://serpapi.com/search"
    params = {
        "engine": "google",
        "q": query,
        "api_key": SERP_API_KEY
    }
    response = requests.get(url, params=params)
    data = response.json()

    profile_urls = []
    for result in data.get("organic_results", []):
        link = result.get("link")
        if "instagram.com" in link:
            profile_urls.append(link)

    return profile_urls

# Step 2: Extract email from Instagram bio section
def extract_email_from_bio(profile_url):
    headers = {"User-Agent": "Mozilla/5.0"}
    response = requests.get(profile_url, headers=headers)
    if response.status_code != 200:
        return None

    soup = BeautifulSoup(response.text, "html.parser")
    bio_section = soup.find("meta", attrs={"name": "description"})

    if bio_section:
        bio_content = bio_section.get("content", "")
        emails = re.findall(r"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}", bio_content)
        return emails if emails else None
    return None

# Example usage
if __name__ == "__main__":
    profiles = get_instagram_profiles(SEARCH_QUERY)
    print("Found Instagram Profiles:", profiles)

    for profile in profiles:
        emails = extract_email_from_bio(profile)
        if emails:
            print(f"Emails found in {profile}: {emails}")
        else:
            print(f"No email found in {profile}")

Comparing the 3 Methods

Need a quick and easy way to get data without a tech background? → Choose

Want full control over data fields and have some HTML/CSS knowledge? → Go with a traditional web scraper

Need to access millions of data points at a lower cost and have a tech expert on hand? → Opt for a third-party SERP API

Is Google Scraper Legal?

When it comes to web scraping, legality is a common concern. ? The short answer is: it depends. The legal status of web scraping varies by jurisdiction, purpose of scraping, terms of service, and the content being scraped. In other words, there's no single answer.

Google's disallow automatic scraping to access any of their services. That said, the general legal framework is that . The purpose of scraping (commercial or non-profit) also significantly impacts its legality.

To ensure your scraping activities are ethical and legal, we recommend thoroughly reading the terms of service, scraping publicly available data, and avoiding using scraped information for illegal purposes. For large-scale scraping, consider seeking advice from legal professionals.

Conclusion

Data is “, and Google SERP is an untapped goldmine. Those who can quickly turn SERP data into actionable strategies will gain a competitive edge in the fast-paced market. Leads generation, market research, and search engine optimization are typical applications of SERP data.

Based on your technical background, budget, data size, and application scenario, we've introduced you to the cutting-edge AI web scraper Thunderbit, traditional web scrapers, and SERP APIs.

If you're a business person looking to scrape all results with one click, Thunderbit is undoubtedly your best choice—what are you waiting for? .

FAQ

1. What types of data can I extract from a Google Search Results Page (SERP)?
You can extract a wide range of data including titles, URLs, meta descriptions, ads, featured snippets, shopping info (like price and images), People Also Ask questions, emails, phone numbers, and more.

2. How is Thunderbit different from traditional web scrapers or SERP APIs?
is a no-code, AI-powered Chrome extension that lets you extract structured data using natural language—no need to configure selectors or write code. Traditional scrapers require technical setup, and APIs involve coding and come with data access limits.

3. Do I need technical knowledge to use Thunderbit for scraping Google search results?
No. Thunderbit is designed for non-technical users. You simply describe the data you want in plain language, and the AI handles the extraction for you.

4. Can I export the scraped data to tools like Google Sheets or Notion?
Yes. Thunderbit allows direct export to Google Sheets, Airtable, Notion, or as a downloadable table—making it easy to use your data right away.

5. What are some practical use cases for scraping Google SERP data?
Common use cases include lead generation, competitor research, SEO analysis, trend spotting, and content planning. For example, sales teams can find contact info, marketers can analyze ad placements, and SEOs can track keyword performance and related queries.

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