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Google SERP Scraper – Scrape Google SERP from Any Website

RealdataAPI / google-search-scraper

The Google SERP Scraper allows you to scrape Google search results from any location, providing real-time data for SEO analysis, competitor tracking, and keyword research. With the Real Data API, you can extract search rankings, organic results, paid ads, featured snippets, and more. Our advanced tool enables businesses to scrape Google search results without any coding, making data collection easy and efficient. Get accurate insights from multiple countries, including Australia, Canada, Germany, France, Singapore, USA, UK, UAE, and India. Enhance your SEO strategy with the best Google SERP Scraper today! Automate data extraction and gain competitive advantages with real-time search insights.

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What is Google SERP Scraper, and How does it Work?

A Google SERP Scraper is a tool that extracts search engine results data, including organic rankings, paid ads, featured snippets, and related searches. It helps businesses analyze competitors, track keyword performance, and improve SEO strategies. Using a Google SERP Scraper, you can scrape Google search results automatically. The process involves sending a query to Google, retrieving search results, and structuring the data for analysis. Advanced tools allow users to scrape Google search results without any coding, making it accessible for marketers, researchers, and businesses.

Why extract data from Google SERP?

Extracting data from Google SERP Scraper is crucial for businesses, marketers, and SEO professionals to gain real-time insights into search trends, rankings, and competitor strategies. A Google Search Results Scraper helps collect structured data for analysis and decision-making.

Key Benefits:
  • SEO Performance Tracking : Scrape Google Search Results to monitor keyword rankings, featured snippets, and organic search positions.
  • Competitor Research : Use a Google Search Scraper to analyze competitor websites, backlinks, and paid ads.
  • Market & Trend Analysis : Extract search trends, user queries, and content opportunities.
  • Automation & Accuracy : Scrape Google Search Results Without Any Coding, ensuring efficiency and precision.

Is it legal to extract Google SERP restaurant data?

Extracting restaurant data from Google SERP Scraper falls into a legal gray area and depends on how the data is collected and used. Scraping Google Search Results for public information is generally allowed, but violating Google’s Terms of Service by excessive automated requests may lead to restrictions.

Key Legal Considerations:
  • Publicly Available Data : If the information is publicly accessible, using a Google Search Results Scraper for analysis is generally acceptable.
  • Terms of Service Compliance : Google prohibits automated scraping in its policies, so ensure your methods follow ethical guidelines.
  • Fair Use & Ethical Practices : Always respect website rules, avoid excessive requests, and use data responsibly.

How can I extract data from Google SERP?

Extracting data from Google SERP Scraper allows businesses to track search rankings, analyze competitors, and optimize SEO strategies. Follow this step-by-step guide to scrape Google search results efficiently.

Step 1: Choose a Google SERP Scraper

Select a Google Search Results Scraper with advanced features like automated data extraction, keyword tracking, and real-time updates. Ensure it supports multiple formats like CSV, JSON, and API integration for easy analysis.

Step 2: Define Search Queries

Identify the target keywords, domain names, or specific search parameters you want to extract. This helps filter relevant data, making it easier to track rankings, competitor performance, and user intent.

Step 3: Set Target Locations & Filters

Use geolocation filters to extract region-specific Google search scraper data. Set parameters such as country, language, and device type to get precise search results from different global markets for better insights.

Step 4: Execute the Scraping Process

Run the Google SERP Scraper to extract organic rankings, paid ads, featured snippets, and related searches. The scraper automates data collection, eliminating manual effort while ensuring accuracy and speed in gathering insights.

Step 5: Process & Clean the Data

Once extracted, clean the data by filtering duplicates, removing irrelevant entries, and structuring it into a readable format. Well-processed data enhances analysis and improves decision-making for marketing and SEO strategies.

Step 6: Store & Analyze Results

Save extracted data in structured formats such as CSV, JSON, or databases. Integrate it with analytics tools like Google Data Studio or Power BI for deeper insights and performance tracking.

Input Options

A Google SERP Scraper offers multiple input options to customize search queries and extract precise data. These input methods help businesses scrape Google search results effectively for SEO tracking, competitor analysis, and market research.

1. Keyword-Based Input

Users can enter specific keywords to extract relevant search results. This option is useful for tracking Google search scraper rankings, featured snippets, and organic or paid ad placements.

2. Domain or URL-Based Input

Input a domain or website URL to analyze its ranking across various keywords. This is ideal for businesses tracking their own performance or monitoring competitors’ Google search results scraper data.

3. Location-Based Input

Scrape search results from different geographical locations by specifying country, city, or ZIP code. This is beneficial for localized SEO strategies, competitor research, and market expansion analysis.

4. Device-Specific Input

Extract search results based on device types like desktop, mobile, or tablet. This helps in understanding how rankings vary across different devices for better SEO optimization.

5. Date and Time-Based Input

Use time-based parameters to monitor historical search trends or track ranking fluctuations over time. This helps in analyzing seasonality and campaign effectiveness.

Sample Result of Google SERP Data Scraper

A Google SERP Scraper extracts search engine data, providing structured insights for SEO analysis, competitor tracking, and market research. Below is a sample output of scrape Google search results data.

Here’s a sample JSON output for a Google SERP Scraper, structured in a machine-readable format: 

{
    "search_query": "Best smartphones",
    "location": "USA",
    "device": "Mobile",
    "date": 2025-03-05,
    "results":[
    {
    "rank": 1
    "url": https://www.example.com
    "title": Best Smartphones 2025
    "meta_description": Find the latest smartphones ranked
    "type": Organic
    "ads_or_organic": Organic
    },
    {
    "rank": 2
    "url": https://www.example2.com
    "title": Top 10 Smartphones This Year
    "meta_description": Compare features and prices
    "type": Organic
    "ads_or_organic": Organic
    },
    {
    "rank": "3"
    "url": https://www.ads-example.com
    "title": Buy New Smartphones Online
    "meta_description": Huge discounts on new arrivals
    "type": Paid Ad
    "ads_or_organic": Paid
    }
    ]
    }

Key Features of This Output:

  • Structured Data : JSON format makes it easy to integrate with analytics tools.
  • Rank & Type Differentiation : Distinguishes between organic results and paid ads.
  • Multi-Device & Location Support : Includes data based on location and device type.

Integrations with Google SERP Data Scraper

A Google SERP Scraper can integrate with various tools and platforms to enhance SEO tracking, competitor analysis, and market research. These integrations help businesses scrape Google search results efficiently and use the extracted data for data-driven decision-making.

1. SEO & Rank Tracking Tools

Integrate with tools like SEMrush, Ahrefs, Moz, and Google Search Console to track keyword rankings, analyze backlinks, and monitor search engine visibility. This helps businesses optimize their SEO strategies based on real-time search data.

2. Business Intelligence & Analytics Platforms

Connect with Google Data Studio, Power BI, Tableau, or Looker to visualize and analyze Google Search Results Scraper data. This allows businesses to track trends, measure performance, and gain deeper insights from search rankings.

3. Marketing & CRM Systems

Sync with HubSpot, Salesforce, Marketo, and other CRM tools to leverage Google SERP Scraper data for targeted marketing campaigns, customer segmentation, and lead generation.

4. Cloud & Database Storage

Store extracted search data in Google BigQuery, AWS, Firebase, or MongoDB for easy access, scalability, and real-time data processing.

Executing Google SERP Data Scraping with Real Data API Google SERP Scraper

A Google SERP Scraper powered by Real Data API enables businesses to extract search engine data efficiently for SEO tracking, competitor analysis, and digital marketing. Follow these steps to scrape Google search results seamlessly.

Step 1: Set Up API Access

Register for Real Data API and obtain API credentials. This ensures secure and authenticated access to extract Google Search Results Scraper data.

Step 2: Define Search Parameters

Specify keywords, target locations, device types (mobile, desktop, tablet), language, and filters to refine the search query and obtain relevant results.

Step 3: Execute API Request

Send a GET or POST request using the Google SERP Scraper API, and it will fetch structured search result data in JSON or CSV format.

Step 4: Process & Store Data

Parse the retrieved Google search scraper data, filter duplicate results, and store it in databases like MySQL, MongoDB, or cloud storage.

Step 5: Analyze & Integrate Data

Use BI tools like Google Data Studio or Power BI to visualize rankings, analyze trends, and enhance SEO strategies.

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You should have a Real Data API account to execute the program examples. Replace < YOUR_API_TOKEN > in the program using the token of your actor. Read about the live APIs with Real Data API docs for more explanation. 

import { RealdataAPIClient } from 'RealdataAPI-client';

// Initialize the RealdataAPIClient with API token
const client = new RealdataAPIClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare actor input
const input = {
    "queries": "Food in NYC",
    "maxPagesPerQuery": 1,
    "resultsPerPage": 100,
    "countryCode": "",
    "customDataFunction": async ({ input, $, request, response, html }) => {
      return {
        pageTitle: $('title').text(),
      };
    }
};

(async () => {
    // Run the actor and wait for it to finish
    const run = await client.actor("RealdataAPI/google-search-scraper").call(input);

    // Fetch and print actor results from the run's dataset (if any)
    console.log('Results from dataset');
    const { items } = await client.dataset(run.defaultDatasetId).listItems();
    items.forEach((item) => {
        console.dir(item);
    });
})();

from RealdataAPI_client import RealdataAPIClient

# Initialize the RealdataAPIClient with your API token
client = RealdataAPIClient("<YOUR_API_TOKEN>")

# Prepare the actor input
run_input = {
    "queries": "Food in NYC",
    "maxPagesPerQuery": 1,
    "resultsPerPage": 100,
    "countryCode": "",
    "customDataFunction": """async ({ input, $, request, response, html }) => {
  return {
    pageTitle: $('title').text(),
  };
};""",
}

# Run the actor and wait for it to finish
run = client.actor("RealdataAPI/google-search-scraper").call(run_input=run_input)

# Fetch and print actor results from the run's dataset (if there are any)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# Set API token
API_TOKEN=<YOUR_API_TOKEN>

# Prepare actor input
cat > input.json <<'EOF'
{
  "queries": "Food in NYC",
  "maxPagesPerQuery": 1,
  "resultsPerPage": 100,
  "countryCode": "",
  "customDataFunction": "async ({ input, $, request, response, html }) => {/n  return {/n    pageTitle: $('title').text(),/n  };/n};"
}
EOF

# Run the actor
curl "https://api.RealdataAPI.com/v2/acts/RealdataAPI~google-search-scraper/runs?token=$API_TOKEN" /
  -X POST /
  -d @input.json /
  -H 'Content-Type: application/json'

URLs or Search Queries

queries Required String

It is an input parameter for the Google search query field. For example, you can search for clothes in NYC. It also allows searching using the URL like https://www.google.com/search?q=clothes+NYC.

The input parameter allows you to submit a single item in a line.

Maximum Pages for each URL or Search Query

maxPagesPerQuery Optional Integer

After crawling for a specific URL or search query, you can put the maximum count for Google SERP. Remember that the source platform restricts the maximum search result pages count between three hundred to four hundred.

Results Per Google Page

resultsPerPage Optional Integer

Google search option shows ten options on each page. For this input field, you need to set the search result count for every page of Google results. It means you need to set these values in multiples of 10. As our trial plan offers a hundred proxies for SERP results, each request needs one proxy, regardless of the result count per page.

Due to this, you should set this input parameter to the hundred as a maximum value.

Mobile Results

mobileResults Optional Boolean

After checking, the tool will show Google search results in a mobile version. By default, you will see the desktop version output.

CSV Friendly Data Output

csvFriendlyOutput Optional Boolean

This parameter permits you to customize data output in CSV Friendly format. After checking, the tool will not include a few SERP features, like people also asking, prices, reviews, and related queries in the dataset. It will only show paid and organic results

Important Note: Remember that paid results depend heavily on browsing history and location.

Country

countryCode Optional Enum

Here, the scraper uses the United States as a default country. The IP address of proxy servers depends on the country.

Options:

ai string, ad string, aq string, au string, us string, uk string, ee string , de string, fr string , nz string, in string

Language

languageCode Optional Enum

It is about the language of the Google search results, which the tool passes to Google search as a parameter of URL term. There is no need always to use the language parameter. Only use this parameter when you use a non-default language for selected countries.

Options:

en string, da string, hi string, cs string, eu string, et string, fr string, it string, ro string, ro string, uk string, uz string, zu string

Google UULE Parameter for Exact Location

locationUule Optional String

It is to program for the exact Google search location. The SERP API passes the string to the UULE parameter for the link term.

Max concurrency

maxConcurrency Optional Integer

The scraper will crawl the maximum pages parallelly. You will get quick results for higher page counts. But the tool will consume more proxies quickly.

Store HTML to Dataset

saveHtml Optional Boolean

After checking, the tool will save Google SERP output in the default HTML format. If you want to process the HTML further, it is helpful. However, it will decrease performance and increase the dataset size.

Locate HTML data in Key-Value Store

saveHtmlToKeyValueStore Optional Boolean

After checking, the scraper will save the HTML file of scraped results into the key-value store and connect to the saved data files under htmlSnapshotUrl. Use it effectively to debug the data since you can browse and observe pages seamlessly. But, it may reduce the performance of the process and tool.

Include Unfiltered Results

includeUnfilteredResults Optional Boolean

After checking, the scraper will include results with fewer quality outputs after filtering them. It typically contains 100 additional outputs.

Custom Data Function

customDataFunction Optional String

It is a customized function with Javascript programming to scrape extra HTML attributes of the SERP. It accepts parameters like handlePageFunction. The scraper will store the return value to the output as a customData property. 

{
  "queries": "Food in NYC",
  "maxPagesPerQuery": 1,
  "resultsPerPage": 100,
  "mobileResults": false,
  "csvFriendlyOutput": false,
  "languageCode": "",
  "maxConcurrency": 10,
  "saveHtml": false,
  "saveHtmlToKeyValueStore": false,
  "includeUnfilteredResults": false,
  "customDataFunction": "async ({ input, $, request, response, html }) => {/n  return {/n    pageTitle: $('title').text(),/n  };/n};"
}

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