November 23, 2025

How to Scrape YouTube Search Results: The Complete 2025 Guide (Step-by-Step)

Learn how to scrape YouTube search results in this post.

YouTube is now the world’s second-largest search engine—bigger than Bing, Yahoo, DuckDuckGo, and every AI search portal combined. Every second, users make more than 3,000 searches, creating a massive pool of real-time data.

If you can scrape YouTube search results, you unlock valuable insights:

Trending searches
Keyword opportunities
Competitor intelligence
Influencer targeting
Content gap analysis
Niche validation
Viral content predictions

The YouTube API is limited and restrictive. It doesn’t give you full search-page metadata and has strict rate limits. That’s why most power users—developers, analysts, and SEO teams—turn to web scraping.

In this guide, you’ll learn exactly how to scrape YouTube search results safely, reliably, and at scale.

Table of Contents

Legal, Ethical & Safety Considerations

Before scraping YouTube, here are the ground rules:

Scraping public data is allowed

YouTube’s search results are public information, visible to anyone.

Never scrape private or login-restricted content

No backend panels, private videos, internal dashboards.

Do not overload servers

Use delays, concurrency limits, and respectful scraping.

Rotate IP addresses

YouTube has strict bot detection mechanisms.
Residential proxies significantly reduce blocks.

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs worldwide, ensuring seamless web scraping, automation, and data collection without IP bans or restrictions. Show Less

YouTube Search Results — How They Actually Work

To scrape YouTube effectively, you must understand what you’re scraping.

1. Everything is dynamically rendered

YouTube heavily relies on JavaScript. You won’t get full content with simple HTML requests.

2. Infinite scrolling

Search results load gradually as the user scrolls.

3. Obfuscated HTML structure

YouTube intentionally complicates selectors.

4. Anti-bot systems

Triggered by:

No mouse movement
No scrolling
Too many requests
Same IP requesting videos repeatedly

A standard HTTP request won’t suffice.
You need a browser automation tool.

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

Tools You Will Use

Playwright (Recommended)

Best for scraping modern JS-heavy sites.

Python

Easy to write, maintain, automate.

Residential Proxies

To avoid blocks and bypass rate limits.

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

Data You Can Extract From YouTube Search

Your scraper can collect:

► Primary Video Data

Title
Channel name
Channel URL
Video URL
View count
Upload date
Duration

► Engagement/Metadata

Live badge
Premiere badge
Verified channel status
Thumbnail URL
Description snippet

► Advanced Insights

Keyword match phrases
Related keywords
Trending tags

This makes your scraper powerful for SEO, marketing, and automation.

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

Step-by-Step — Scraping YouTube Search Results with Playwright (Python)

Below is a clean, production-ready script.

📌 Step 1 — Install Requirements

pip install playwright
playwright install
pip install pandas

📌 Step 2 — Python Code for Scraping YouTube Search

import time
import pandas as pd
from playwright.sync_api import sync_playwright

def scrape_youtube_search(query, max_scroll=5):
    with sync_playwright() as p:
        browser = p.chromium.launch(headless=True)
        context = browser.new_context()
        page = context.new_page()

        search_url = f"https://www.youtube.com/results?search_query={query}"
        page.goto(search_url)
        time.sleep(3)

        # Scroll to load more results
        for _ in range(max_scroll):
            page.mouse.wheel(0, 20000)
            time.sleep(2)

        videos = page.query_selector_all("ytd-video-renderer")
        results = []

        for video in videos:
            title = video.query_selector("#video-title")
            channel = video.query_selector("#channel-info a")
            views = video.query_selector("#metadata-line span:nth-child(1)")
            upload_time = video.query_selector("#metadata-line span:nth-child(2)")
            
            results.append({
                "title": title.inner_text().strip() if title else "",
                "video_url": title.get_attribute("href") if title else "",
                "channel_name": channel.inner_text().strip() if channel else "",
                "channel_url": channel.get_attribute("href") if channel else "",
                "views": views.inner_text().strip() if views else "",
                "upload_time": upload_time.inner_text().strip() if upload_time else "",
            })

        browser.close()
        return pd.DataFrame(results)

df = scrape_youtube_search("python tutorial", max_scroll=7)
df.to_csv("youtube_search.csv", index=False)

print(df.head())

How to Avoid YouTube Blocks (IMPORTANT)

YouTube is aggressive with bot detection.

Here are the defenses:

1️⃣ Rotate IP Addresses

Using a different IP address for few requests prevents flags.

👉 This is where residential proxies shine:

Looks like real users
Rarely blocked
Allows massive-scale scraping

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

2️⃣ Randomize Human-Like Behavior

Add 2–5 second delays
Random scroll patterns
Change user agents
Use cookies session rotation

3️⃣ Browser Fingerprinting Protection

Playwright already simulates a real browser.
But you can increase stealth by:

context = browser.new_context(
    user_agent="Mozilla/5.0 ...",
    viewport={"width": 1280, "height": 720}
)

Scaling to Thousands of Keywords

If you want to scrape hundreds or thousands of keywords:

Run multiple threads
Rotate proxy sessions
Save checkpoints
Break large queries into batches of 50
Export to CSV or database

A scalable structure:

keywords = ["python tutorial", "fitness tips", "gadgets 2025"]

all_results = []

for kw in keywords:
    df = scrape_youtube_search(kw, max_scroll=5)
    df["keyword"] = kw
    all_results.append(df)

final = pd.concat(all_results)
final.to_csv("bulk_search_results.csv", index=False)

Advanced YouTube Scraping — Beyond Basics

📌 Extract autocomplete suggestions

Great for keyword research tools.

Track sudden surges in views.

📌 Scrape channel pages for deeper analytics

About page
Social links
Channel creation date

📌 Integrate sentiment analysis on video comments

Use NLP on extracted comments.

Your scraper can grow into a full YouTube intelligence system.

Top Use-Cases Where YouTube Scraping Is a Superpower

1. Keyword & SEO Research

Know what topics are searchable before making videos.

2. Competitor Monitoring

Track uploads, performance, thumbnails, titles.

3. Influencer Discovery

Detect rising creators.

4. Trend Prediction

Use volume patterns + upload recency.

5. Market Research

Identify demand before launching products.

Why Rotating Residential Proxies Are Crucial for YouTube Scraping

Datacenter proxies get blocked almost instantly.

Residential proxies offer:

Real IP addresses from real devices
Higher trust score
Geographic targeting
Low block rate
Stability with JavaScript-heavy sites

When scraping platforms like YouTube, Google, Amazon, Ticketmaster, Airbnb, or Instagram—residential proxies is the only serious option.

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

Final Best Practices

Always use scrolling automation
Always scrape slowly and respectfully
Always rotate IPs
Always save raw HTML for debugging
Always sanitize your output

Frequently Asked Questions about Scraping YouTube Search Results

What tools do I need to scrape YouTube search results in 2025?

To scrape YouTube effectively, you need a combination of tools:

Python for scripting and automation.
Playwright or Selenium to handle JavaScript-heavy pages.
BeautifulSoup for parsing HTML (optional for static pages).
Proxies, preferably residential proxies like Decodo, to prevent blocks.
Pandas to store and manage your scraped data.

Is scraping YouTube search results legal?

Scraping YouTube search results is generally legal if you only collect publicly available data and do not bypass authentication or download private content. It’s essential to comply with YouTube’s Terms of Service and to respect rate limits by using delays and rotating proxies.

How can I avoid getting blocked while scraping YouTube?

To prevent IP bans and bot detection:

Use rotating residential proxies like Decodo.
Randomize user agents.
Introduce delays and scrolling patterns to mimic human behavior.
Limit requests per IP and session.
Utilize browser automation tools, such as Playwright, to simulate real user interactions.

Can I scrape YouTube search results without coding?

Yes, some No-Code platforms and services allow scraping search results, such as Decodo or specialized web scraping APIs. These platforms handle proxies, throttling, and dynamic rendering for you, letting you export results to CSV or JSON without writing scripts.

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

What kind of data can I extract from YouTube search results?

You can extract a wide range of data, including:

Video title and URL
Channel name and URL
Views and upload date
Duration of the video
Badges (live, premiere, verified)
Thumbnail URL and description snippets

This data is useful for SEO, trend analysis, and content research.

How do I scale scraping to hundreds of keywords?

Scaling requires:

Running scraping scripts in batches.
Using rotating proxies and multiple threads or processes.
Storing results in a database or CSV for batch processing.
Automating the workflow with Python loops or job schedulers.

Can I use scraped data for SEO and marketing purposes?

Yes, YouTube search data can help:

Identify trending topics and keywords.
Analyze competitors’ content and strategies.
Discover influencers or emerging channels.
Predict viral content and optimize your SEO campaigns.

Conclusion

Scraping YouTube search results unlocks unmatched insights for SEO, market research, content creation, and automation. With Playwright + rotating residential proxies, you can collect clean, structured, scalable data without getting blocked.

This full guide gives you everything you need to:

build your own scraper
scale to hundreds of keywords
avoid blocks
extract rich metadata
turn YouTube into your research engine

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

INTERESTING POSTS

How to Scrape a Website to Markdown (Complete 2025 Guide)

Resources

Angela Daniel

November 23, 2025

How to Scrape a Website to Markdown (Complete 2025 Guide)

Learn how to scrape any website into Markdown in 2025 using Python, Playwright, BeautifulSoup, and proxies.

Scraping a website and converting it into Markdown (.md) has become a powerful workflow for developers, writers, researchers, archivists, and AI engineers.

Why Markdown?

It’s portable
It’s lightweight
It’s readable by humans and machines
It’s perfect for blogs, GitHub wikis, documentation, AI training datasets, and static site generators

Today, you’ll learn the exact process to scrape any website to Markdown in 2025 — clean, structured, automated, and scalable.

You’ll also get a complete Python script that extracts:

Titles
Subheadings
Paragraphs
Images
Links
Code blocks
Lists
Tables

…and converts all of it into clean Markdown automatically.

Let’s begin.

Table of Contents

Why Scrape Websites to Markdown? (2025 Use Cases)

Markdown extraction is now used across:

1️⃣ Technical Documentation

Developers export website docs into Markdown to host them locally or on GitHub.

2️⃣ Personal Knowledge Bases

Obsidian, Notion, Logseq users import web content to build knowledge graphs.

3️⃣ AI Knowledge Training

Markdown is the preferred format for vector embedding pipelines.

4️⃣ SEO & Content Research

Scraping competitor articles into Markdown for side-by-side analysis.

5️⃣ Static Site Generators

Jekyll, Hugo, Astro, Next.js — all rely on .md content.

6️⃣ Web Archival & Backup

Store entire websites offline, version-controlled, machine-readable.

You’re not just “scraping” — you’re building portable, structured, future-proof knowledge.

Is It Legal to Scrape Websites? (Important)

Website scraping is legal if you follow these rules:

Scrape only publicly accessible content
Respect robots.txt where required
Never bypass logins or paywalls
Do not scrape personal/private user data
Use proxies to avoid accidental blocks
Respect rate limits
Attribute and comply with content licenses

This guide teaches legitimate, ethical scraping only.

Why Proxies Are Necessary for Safe Website Scraping?

Websites have become much stricter:

Cloudflare
Akamai
PerimeterX
DataDome
FingerprintJS

are blocking bots aggressively.

You need rotating IPs to avoid:

429 Too Many Requests
403 Forbidden
CAPTCHA challenges
IP blacklisting

Recommended Proxy Choices for Markdown Scraping

1️⃣ Decodo – Best balance of price + success rate
2️⃣ Oxylabs – Enterprise-level pools
3️⃣ Webshare – Cheapest for small jobs
4️⃣ IPRoyal – Stable residential & mobile proxies
5️⃣ Mars Proxies – Niche eCommerce and social automation

For production workloads, Decodo residential proxies consistently perform well with JavaScript-heavy sites and allow for unlimited scraping volume.

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

How to Scrape Any Website to Markdown: Complete Process Overview

Here’s the high-level pipeline:

1. Fetch the webpage HTML

Using Playwright for JS-rendered sites or requests for simple HTML pages.

2. Parse the content

With BeautifulSoup or the Playwright DOM.

3. Extract text and structure

Headings, paragraphs, lists, images, etc.

4. Convert to Markdown

Using a Markdown converter or your own mapper.

5. Save to .md file

Organized by slug or title.

6. (Optional) Bulk scrape + bulk export

Now let’s dive into the real implementation.

Tools You Need (2025 Stack)

Python 3.10+
Playwright (for dynamic websites)
BeautifulSoup4
markdownify (HTML → Markdown converter)
Proxies (Decodo or others)

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

Install packages:

pip install playwright
pip install beautifulsoup4
pip install markdownify
pip install requests
playwright install

Full Python Script to Scrape a Website to Markdown

(JS-rendered websites supported)

This script handles:

Headless rendering
Proxies
Image downloading
Markdown conversion
Automatic file naming
Cleaning unwanted boilerplate

📌 Python Code

import os
import time
import requests
from bs4 import BeautifulSoup
from markdownify import markdownify as md
from playwright.sync_api import sync_playwright

# -------------------------------------------------------
# 1. CONFIGURATION
# -------------------------------------------------------

PROXY_URL = "http://user:pass@gw.decodo.io:12345"  # Replace with your proxy

SAVE_IMAGES = True
OUTPUT_FOLDER = "markdown_export"

os.makedirs(OUTPUT_FOLDER, exist_ok=True)

# -------------------------------------------------------
# 2. DOWNLOAD IMAGE
# -------------------------------------------------------

def download_image(img_url, folder):
    try:
        if not img_url.startswith("http"):
            return None
        
        filename = img_url.split("/")[-1].split("?")[0]
        path = f"{folder}/{filename}"
        
        img_data = requests.get(img_url, timeout=10).content
        with open(path, "wb") as f:
            f.write(img_data)
        
        return path
    except:
        return None

# -------------------------------------------------------
# 3. SCRAPE WEBSITE USING PLAYWRIGHT
# -------------------------------------------------------

def fetch_html(url):
    with sync_playwright() as p:
        browser = p.firefox.launch(headless=True)
        context = browser.new_context(
            proxy={"server": PROXY_URL}  # proxy integration
        )
        page = context.new_page()

        page.goto(url, timeout=60000)
        time.sleep(5)  # allow JS to render fully
        html = page.content()

        browser.close()
        return html

# -------------------------------------------------------
# 4. CONVERT WEBSITE TO MARKDOWN
# -------------------------------------------------------

def scrape_to_markdown(url):
    html = fetch_html(url)
    soup = BeautifulSoup(html, "html.parser")

    # Remove scripts, ads, navbars, footers
    for tag in soup(["script", "style", "footer", "nav"]):
        tag.decompose()

    # Extract Title
    title = soup.title.string if soup.title else "untitled"
    slug = title.lower().replace(" ", "-").replace("|", "").replace("/", "-")

    # Extract Main Content
    body = soup.find("body")
    content_html = str(body)

    # Convert to markdown
    markdown_text = md(content_html, heading_style="ATX")

    # Save images
    if SAVE_IMAGES:
        img_tags = soup.find_all("img")
        img_folder = f"{OUTPUT_FOLDER}/{slug}_images"
        os.makedirs(img_folder, exist_ok=True)

        for img in img_tags:
            src = img.get("src")
            img_path = download_image(src, img_folder)
            if img_path:
                markdown_text = markdown_text.replace(src, img_path)

    # Save markdown file
    md_path = f"{OUTPUT_FOLDER}/{slug}.md"
    with open(md_path, "w", encoding="utf-8") as f:
        f.write(f"# {title}\n\n")
        f.write(markdown_text)

    return md_path

# -------------------------------------------------------
# USAGE
# -------------------------------------------------------

url = "https://example.com"
file_path = scrape_to_markdown(url)

print("Markdown saved to:", file_path)

How This Script Works (Explained Simply)

1. Playwright loads the page

Even sites protected by JavaScript render normally.

2. HTML is passed to BeautifulSoup

Which strips out unwanted boilerplate (ads, nav, scripts).

3. markdownify converts HTML to Markdown

Keeping structure like:

# H1
## H2
- lists
1. ordered lists
![image](path)

4. Images are downloaded and relinked

Your Markdown becomes fully offline-ready.

5. A clean `.md` file is saved

Handling Sites With Heavy Protection (Cloudflare, Akamai, etc.)

Many modern websites deploy strong bot protection.

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

To bypass these safely and legally, you need:

Human-like browser automation (Playwright)
Strong residential proxies (Decodo, IPRoyal, Oxylabs)
Delay simulation (2–4 seconds)
Random scroll simulation
Dynamic headers

You can add human scrolling:

page.mouse.wheel(0, 5000)
page.wait_for_timeout(1500)

And rotate user agents:

context = browser.new_context(
    user_agent="Mozilla/5.0 ..."
)

Bulk Scraping: Converting Multiple URLs Into Markdown

You can process entire lists:

urls = [
    "https://example.com/docs",
    "https://example.org/article",
    "https://example.net/page",
]

for u in urls:
    print(scrape_to_markdown(u))

This allows:

Full website archiving
One-click conversion of 100+ pages
Competitive research automation
SEO content analysis

AI + Markdown: The Future Workflow

Markdown works perfectly with:

LLM fine-tuning datasets
RAG pipelines
Embedding databases
Vector search
Chatbot knowledge bases

Because Markdown is:

Clean
Structured
Lightweight
Hierarchical
Easy to parse

Increasingly, tech companies are opting for Markdown for AI knowledge ingestion.

When to Use Proxies in Markdown Scraping

Use proxies when a site:

Blocks your country
Has strong rate limits
Needs rotating fingerprints
Uses anti-bot filtering
Bans datacenter IPs

Best Proxy Providers (2025)

1. Decodo

Best for automated scraping + unlimited bandwidth

Strong global residential pool
API key authorization
High success rate on JS websites

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

2. Oxylabs

Premium large-scale option

Enterprise volume
High performance

3. Webshare

Best for budget scraping

Cheap rotating IP
Great for personal projects

4. Mars Proxies

Good for social media & ecommerce tasks

5. IPRoyal

Stable rotating residential & mobile proxies

Recommendation: For most users, Decodo residential proxies are the sweet spot between power, price, and anti-block success rate.

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

Best Practices for Clean Markdown Extraction

1. Remove scripts and styles

2. Strip navigation menus

3. Keep Markdown minimalistic

4. Store images locally

5. Normalize headings (H1 → H6)

6. Avoid duplicate content

7. Keep URLs absolute

Real-World Examples of Markdown Scraping

📌 GitHub Wiki Migration

Convert old HTML docs into Markdown for GitHub wikis.

📌 Knowledge Base Creation

Turn 100+ blog posts into an Obsidian vault.

📌 SEO Competitor Research

Scrape top-ranking articles to analyze structure, keywords, and topical depth.

📌 AI Dataset Creation

Feed Markdown into embedding pipelines for semantic search.

📌 Offline Archival

Save entire websites into Markdown folders for reference.

Frequently Asked Questions About Scraping a Website to Markdown

What does it mean to scrape a website to Markdown?

Scraping a website to Markdown means extracting the content of a website—such as headings, paragraphs, lists, tables, and images—and converting it into Markdown (.md) format. Markdown is a lightweight, readable, and easily usable format for documentation, blogs, AI datasets, and knowledge bases.

What tools do I need to scrape a website and convert it to Markdown in 2025?

The most commonly used tools include Python, Playwright or Selenium for dynamic content, BeautifulSoup for parsing HTML, and markdownify to convert HTML to Markdown. Additionally, proxies like Decodo help you scrape at scale without getting blocked.

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

Can I scrape any website into Markdown?

Technically, most public websites can be scraped into Markdown; however, it is advisable to avoid scraping private content, login-protected pages, and sites with strict terms of service. Always check a website’s robots.txt and scraping policies before extraction.

How do I handle images when scraping to Markdown?

Images can be downloaded locally and referenced in your Markdown file. Using scripts, you can automatically fetch image URLs, save them to a folder, and update the Markdown links so your content is fully offline-ready.

Do I need proxies for scraping websites into Markdown?

Yes, proxies are highly recommended, especially for scraping large websites or sites protected by anti-bot systems. Residential proxies like Decodo or IPRoyal provide real IP addresses that reduce the chance of blocks and CAPTCHAs.

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

Is it legal to scrape a website to Markdown?

Scraping public content for personal, research, or internal use is generally legal. Avoid scraping private data, bypassing logins, or using the scraped content commercially in a manner that violates copyright. Always respect a site’s terms of service and applicable laws.

Can I automate scraping multiple pages into Markdown?

Absolutely. You can create a script that loops through multiple URLs, scrapes each page, and saves them as individual Markdown files. This workflow is ideal for knowledge base migrations, content analysis, or SEO research.

Conclusion

Scraping a website into Markdown unlocks powerful workflows across research, SEO, development, documentation, and AI data pipelines.

With Playwright, Python, BeautifulSoup, and Markdownify — plus rotating residential proxies from providers like Decodo — you can convert any website into clean, portable .md files ready for automation or analysis.

Whether you want to archive pages, study competitors, migrate CMS content, or feed AI systems with structured datasets, scraping to Markdown is one of the most efficient and future-proof methods available today.

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

INTERESTING POSTS

How to Scrape Google Reviews: A Step-by-Step Guide (2025 Edition)

Resources

Angela Daniel

November 23, 2025

How to Scrape Google Reviews: A Step-by-Step Guide (2025 Edition)

Learn how to scrape Google Reviews safely in 2025 using Python, tools, and proxies in this post.

Google Reviews determine customer perception, influence local SEO rankings, and drive real-world sales.

Whether you’re a marketer, brand strategist, developer, or data analyst, scraping Google Reviews gives you access to structured insights such as:

⭐ Customer sentiment
⭐ Hidden complaints
⭐ Feature requests
⭐ Competitor analysis
⭐ Local SEO optimization opportunities
⭐ Data for dashboards and AI models

But Google aggressively blocks scrapers — so you need the right tools, proxies, and safe methods.
This guide walks you through:

✔ How Google Reviews work
✔ Scraping approaches (manual, API, Python, No-Code)
✔ How to avoid IP bans
✔ Best proxies for scraping (Decodo included naturally)
✔ Full Python script to scrape ANY Google Business reviews
✔ Automation workflows

Let’s dive in.

Table of Contents

Understanding Google Reviews Structure

A Google Business Profile page includes:

Business Name
Categories
Address
Coordinates
Average Rating
Number of Reviews
Ratings Breakdown (1–5 stars)
Individual Reviews:
- Reviewer name
- Rating
- Date
- Review text
- Images
- Likes
- Local Guide status

Google does not provide an official free API for reviews.
So scraping becomes necessary when you need:

Bulk reviews
Historical reviews
Multi-location monitoring
Competitor analysis

Is Scraping Google Reviews Legal?

Google’s TOS discourages automated extraction, but scraping public data (reviews without logging in) is generally considered legal IF:

✔ You don’t bypass authentication
✔ You don’t extract private user data
✔ You comply with local laws
✔ You rotate IPs to avoid rate limits

Use the data ethically — not for spam or user identification.

Tools You Can Use to Scrape Google Reviews

A. No-Code Tools (Easiest)

Decodo Web Scraper (Recommended)
Decodo provides high-quality scraping tools + proxy integration.
Their scrapers bypass rate limits automatically and deliver JSON/CSV output. You simply enter a Google Maps URL → you get structured data.
Other No-Code Tools
- Outscraper
- Bright Data Reviews Scraper
- Apify Google Maps Scraper
- Webscraper.io Chrome Extension

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

B. Python-Based Scraping (More Control)

Use libraries such as:

Selenium
Playwright
Requests + parsing
BeautifulSoup
SerpAPI (Paid but simple)

We’ll build a full code example later.

C. API Services

SERP APIs simplify scraping but charge monthly fees.

Examples:

Google Places API
SerpAPI (Google Reviews endpoint)
Zenserp
Scale SERP
Oxylabs Scraper API
Decodo API (lightweight & fast for Maps data)

Why You Must Use Proxies for Google Reviews Scraping

Google blocks repeated requests from:

❌ Datacenter IP ranges
❌ Same IP too many requests
❌ Suspicious scraping patterns
❌ Non-browser user agents

Using proxies ensures:

✔ Continuous scraping
✔ Avoiding throttling
✔ Avoiding CAPTCHA loops
✔ Better geolocation control (useful for local results)

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

Recommended Proxies for Google Reviews Scraping

Provider	Type	Best For	Notes
Decodo Residential Proxies	Residential	Google Maps, Google Search	High success rate, strong rotation
Oxylabs	Residential + Mobile	Large-scale scraping	Enterprise-level
IPRoyal	Residential	Budget workloads	Reliable for small projects
Webshare	Datacenter + ISP	Fast tasks	Cheap and scalable
Mars Proxies	Mobile	Hard targets	Great for antispam evasion

Best option for Google Reviews:
➡️ Residential Proxies – Decodo

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

Step-by-Step: How to Scrape Google Reviews

Let’s break it down from beginner to advanced.

Step 1 — Copy the Google Maps Place URL

Example:

https://www.google.com/maps/place/McDonald's/@40.7614,-73.9828,...

You can get:

Place ID
Coordinates
Raw reviews

Step 2 — Decide Your Method

Method A — No Code (Decodo Scraper)
Quickest option.

Method B — Python (Selenium/Playwright)
Most customizable.

Method C — API (SerpAPI / Decodo / Oxylabs)
Great for speed and reliability.

Step 3 — Install Dependencies (Python)

pip install requests
pip install beautifulsoup4
pip install pandas
pip install fake-useragent

For advanced scraping:

pip install playwright
playwright install

Step 4 — Full Python Script

This script extracts:

✔ Rating
✔ Reviewer
✔ Review Text
✔ Date
✔ Likes

Using Playwright for stability.

from playwright.sync_api import sync_playwright
import pandas as pd
import time

def scrape_google_reviews(url, limit=100):
    data = []

    with sync_playwright() as p:
        browser = p.chromium.launch(headless=True)
        context = browser.new_context(
            user_agent="Mozilla/5.0 (Windows NT 10.0; Win64; x64)",
            locale="en-US"
        )

        page = context.new_page()
        page.goto(url, timeout=100000)

        # Click the reviews button
        page.wait_for_selector("button[jslog*='reviews']")
        page.click("button[jslog*='reviews']")

        time.sleep(3)

        # Scroll reviews container
        scrollable = page.locator("div[aria-label='Reviews']")

        previous_height = 0
        while len(data) < limit:
            scrollable.evaluate("el => el.scrollBy(0, el.scrollHeight)")
            time.sleep(2)

            # Parse reviews
            review_elements = page.locator("div[jscontroller]").all()

            for r in review_elements:
                try:
                    name = r.locator("div[class*='d4r55']").inner_text()
                    rating = r.locator("span[class*='hCC']").get_attribute("aria-label")
                    date = r.locator("span[class*='rsqaWe']").inner_text()
                    text = r.locator("span[class*='wiI7pd']").inner_text()
                except:
                    continue

                data.append({
                    "name": name,
                    "rating": rating,
                    "date": date,
                    "review": text
                })

                if len(data) >= limit:
                    break

        df = pd.DataFrame(data)
        df.to_csv("google_reviews.csv", index=False)
        return df

url = "YOUR_GOOGLE_MAPS_URL_HERE"
df = scrape_google_reviews(url, limit=200)
print(df)

Avoiding Blocks: Best Practices

To scrape without issues:

✔ Rotate proxies every request
✔ Randomize user agents
✔ Insert 1–3 second delays
✔ Use residential proxies for Google
✔ Use headless browsers that mimic real users
✔ Disable images to speed up scraping
✔ Limit to 200–500 reviews per session

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

How to Use Decodo to Scrape Google Reviews (Quick Method)

Decodo gives you:

Maps scraper
Review scraper
Proxy API
Code templates

Steps

Create a Decodo account
Open Google Maps Scraper
Paste the business URL
Choose:
- Output: JSON / CSV
- Limit: Up to thousands
Run
Download your data

This offloads:

✔ Proxy rotation
✔ Browser emulation
✔ Anti-bot bypass
✔ Speed optimization

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

Scraping Multiple Locations

For agencies or SaaS dashboards:

Prepare a CSV of business URLs
Loop through your scraping script
Save each location’s reviews separately
Combine into a master file
Run sentiment analysis (TextBlob, GPT, HuggingFace)

Turning Google Reviews Into Insights

After scraping, you can analyze:

A. Sentiment (Positive / Negative / Neutral)

Useful for product teams and customer service.

B. Topic Clustering (AI)

Using embedding models to detect:

Food quality
Staff complaints
Delivery times
Hygiene concerns

C. Fake Review Detection

Flag patterns such as:

One-word praise
Repeated posting times
Reviewer with no history

D. Competitive Benchmarking

Compare yourself to 3–10 competitors.

Building an Automated Review Monitoring System

Use:

Decodo API
Google Sheets / Notion
Zapier / Make
Playwright scripts on a server

Automatic pipeline:

Run scraper daily
Store reviews in database
Run sentiment model
Trigger alerts for negative reviews
Export weekly reports

Best Proxy Setup for Google Reviews Scraping

For Budget Users

Decodo Proxies
Webshare ISP
IPRoyal Residential

For Medium Scale

Decodo Residential Proxies (best balance of speed + success rate)

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

For Enterprise Scale

Oxylabs Residential + Mobile
Mars Proxies Mobile for extreme anti-bot environments

Rule:
➡️ Avoid datacenter proxies. Google blocks them instantly.

Frequently Asked Questions About Scraping Google Reviews

What is Google Reviews scraping, and why is it useful?

Google Reviews scraping is the process of automatically collecting reviews from Google Business Profiles using scripts, APIs, or scraping tools. It’s useful for businesses, marketers, and analysts to track customer sentiment, perform competitive analysis, monitor brand reputation, and gather data for SEO and AI applications.

Is it legal to scrape Google Reviews?

Scraping public Google Reviews is generally legal if you only access publicly available data, do not bypass logins or paywalls, and comply with Google’s terms of service. Ethical scraping practices, combined with the use of proxies, ensure compliance and reduce the risk of IP bans.

Which tools are best for scraping Google Reviews in 2025?

Top tools include:

Decodo: Easy-to-use scraper with built-in residential proxy rotation.
SerpAPI: Paid API for structured Google Review data.
Playwright or Selenium: For custom Python scraping scripts.
BeautifulSoup: To parse HTML content.

Choosing a tool depends on your scale, technical expertise, and the level of automation required.

Decodo Residential Proxies

Decodo (formerly Smartproxy) Residential Proxies offer a fast, reliable, and affordable solution with 115M+ IPs...Show More

Why do I need proxies when scraping Google Reviews?

Google actively blocks repeated requests from the same IP address, especially those from data center IPs. Using rotating residential proxies (like Decodo, Oxylabs, or IPRoyal) helps avoid blocks, CAPTCHA, and ensures continuous scraping without being flagged as a bot.

Can I scrape multiple locations at once?

Yes. You can create a list of Google Business URLs and loop through them in your scraping script or automation tool. Each location’s reviews can be exported separately or combined into a master dataset for analysis.