Google vs. Bing SERP Scraping: Wichtige Unterschiede

Why Compare Google and Bing Scraping?

While Google dominates search with over 90% market share globally, Bing holds significant share in specific markets: roughly 9% in the United States, higher among enterprise users, and it powers search results for DuckDuckGo, Yahoo, and Ecosia. For comprehensive SERP monitoring, tracking both search engines gives you a more complete view of your organic visibility.

The technical differences between scraping Google and Bing are substantial. Each search engine has different HTML structures, anti-bot protections, rate limiting, and proxy requirements. This guide breaks down these differences so you can build scrapers that work reliably for both.

For foundational SERP scraping concepts, start with our SERP scraping with proxies guide.

Anti-Bot Protection Comparison

The biggest difference between Google and Bing scraping is how aggressively each search engine detects and blocks automated requests.

Detection Method	Google	Bing
IP rate limiting	Very aggressive — blocks after ~10-20 queries/hour per IP	Moderate — tolerates ~30-50 queries/hour per IP
CAPTCHA challenges	Frequent reCAPTCHA on suspicious IPs	Less frequent, uses simpler challenges
Datacenter IP detection	Actively blocks known datacenter ranges	Less strict — datacenter proxies often work
Browser fingerprinting	Advanced TLS/JS fingerprinting	Basic header and User-Agent checks
Behavioral analysis	Sophisticated pattern detection	Less sophisticated
Cookie enforcement	Tracks and validates cookies	Less reliant on cookie behavior

The key takeaway: Bing is significantly easier to scrape than Google. You can often use datacenter proxies for Bing at moderate volumes, while Google almost always requires residential proxies for reliable results.

HTML Structure Differences

Google and Bing use completely different HTML structures for their search results, requiring separate parsing logic.

Google SERP Structure

# Google organic result selectors
# Container: div#search .g
# Title: h3
# URL: a[href]
# Snippet: .VwiC3b or div[data-snf]
from bs4 import BeautifulSoup
def parse_google(html):
    soup = BeautifulSoup(html, "html.parser")
    results = []
    for g in soup.select("div#search .g"):
        title = g.select_one("h3")
        link = g.select_one("a")
        snippet = g.select_one(".VwiC3b")
        if title and link:
            results.append({
                "title": title.get_text(),
                "url": link["href"],
                "snippet": snippet.get_text() if snippet else "",
            })
    return results

Bing SERP Structure

# Bing organic result selectors
# Container: li.b_algo
# Title: h2 a
# URL: cite
# Snippet: p.b_lineclamp2 or div.b_caption p
def parse_bing(html):
    soup = BeautifulSoup(html, "html.parser")
    results = []
    for item in soup.select("li.b_algo"):
        title_el = item.select_one("h2 a")
        snippet_el = item.select_one("p.b_lineclamp2") or item.select_one("div.b_caption p")
        cite_el = item.select_one("cite")
        if title_el:
            results.append({
                "title": title_el.get_text(),
                "url": title_el["href"],
                "snippet": snippet_el.get_text() if snippet_el else "",
                "display_url": cite_el.get_text() if cite_el else "",
            })
    return results

SERP Feature Comparison

Both search engines display rich SERP features beyond standard blue links, but they differ in format and frequency:

Feature	Google	Bing
Featured snippet	Common — div.xpdopen	Less common — div.b_ans
People Also Ask	Very common — div.related-question-pair	Present as "People also ask" — div.b_rs
Local pack	Map with 3 results — div.VkpGBb	Map with listings — div.b_localA
Knowledge panel	Right sidebar — div.kp-wholepage	Right sidebar — div.b_entityTP
Image carousel	Top or inline — div.ULSxyf	Top — div.imgpt
Video results	Carousel format	Grid format — div.b_vidAns
Related searches	Bottom — div.s75CSd	Bottom and sidebar — div.b_rs

Complete Dual-Engine Scraper

Here is a unified Python scraper that handles both Google and Bing:

import requests
from bs4 import BeautifulSoup
import time
import random
import json
PROXY_URL = "http://USERNAME:PASSWORD@gate.proxyhat.com:8080"
USER_AGENTS = [
    "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36",
    "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36",
]
def scrape_serp(keyword, engine="google", country="us"):
    """Scrape SERP from Google or Bing."""
    proxies = {"http": PROXY_URL, "https": PROXY_URL}
    headers = {
        "User-Agent": random.choice(USER_AGENTS),
        "Accept-Language": "en-US,en;q=0.9",
        "Accept": "text/html,application/xhtml+xml",
    }
    if engine == "google":
        url = "https://www.google.com/search"
        params = {"q": keyword, "num": 10, "hl": "en", "gl": country}
    else:
        url = "https://www.bing.com/search"
        params = {"q": keyword, "count": 10, "cc": country}
    response = requests.get(
        url,
        params=params,
        headers=headers,
        proxies=proxies,
        timeout=15,
    )
    response.raise_for_status()
    soup = BeautifulSoup(response.text, "html.parser")
    if engine == "google":
        return parse_google_results(soup)
    else:
        return parse_bing_results(soup)
def parse_google_results(soup):
    results = []
    for i, g in enumerate(soup.select("div#search .g"), 1):
        title = g.select_one("h3")
        link = g.select_one("a")
        snippet = g.select_one(".VwiC3b")
        if title and link:
            results.append({
                "position": i,
                "title": title.get_text(),
                "url": link["href"],
                "snippet": snippet.get_text() if snippet else "",
            })
    return results
def parse_bing_results(soup):
    results = []
    for i, item in enumerate(soup.select("li.b_algo"), 1):
        title_el = item.select_one("h2 a")
        snippet_el = item.select_one("p.b_lineclamp2") or item.select_one("div.b_caption p")
        if title_el:
            results.append({
                "position": i,
                "title": title_el.get_text(),
                "url": title_el["href"],
                "snippet": snippet_el.get_text() if snippet_el else "",
            })
    return results
# Compare rankings across both engines
keyword = "best web scraping proxies"
google_results = scrape_serp(keyword, "google")
time.sleep(random.uniform(3, 6))
bing_results = scrape_serp(keyword, "bing")
print(f"\n=== Google Results for '{keyword}' ===")
for r in google_results[:5]:
    print(f"  #{r['position']}: {r['title']}")
print(f"\n=== Bing Results for '{keyword}' ===")
for r in bing_results[:5]:
    print(f"  #{r['position']}: {r['title']}")

Node.js Dual-Engine Scraper

const axios = require('axios');
const cheerio = require('cheerio');
const { HttpsProxyAgent } = require('https-proxy-agent');
const agent = new HttpsProxyAgent('http://USERNAME:PASSWORD@gate.proxyhat.com:8080');
async function scrapeSERP(keyword, engine = 'google') {
  const config = engine === 'google'
    ? { url: 'https://www.google.com/search', params: { q: keyword, num: 10, hl: 'en', gl: 'us' } }
    : { url: 'https://www.bing.com/search', params: { q: keyword, count: 10 } };
  const { data } = await axios.get(config.url, {
    params: config.params,
    headers: {
      'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36',
      'Accept-Language': 'en-US,en;q=0.9',
    },
    httpsAgent: agent,
    timeout: 15000,
  });
  const $ = cheerio.load(data);
  if (engine === 'google') {
    return parseGoogle($);
  }
  return parseBing($);
}
function parseGoogle($) {
  const results = [];
  $('div#search .g').each((i, el) => {
    const title = $(el).find('h3').text();
    const url = $(el).find('a').attr('href');
    const snippet = $(el).find('.VwiC3b').text();
    if (title && url) results.push({ position: i + 1, title, url, snippet });
  });
  return results;
}
function parseBing($) {
  const results = [];
  $('li.b_algo').each((i, el) => {
    const titleEl = $(el).find('h2 a');
    const title = titleEl.text();
    const url = titleEl.attr('href');
    const snippet = $(el).find('p.b_lineclamp2').text() || $(el).find('div.b_caption p').text();
    if (title && url) results.push({ position: i + 1, title, url, snippet });
  });
  return results;
}
async function compareEngines(keyword) {
  const [google, bing] = await Promise.all([
    scrapeSERP(keyword, 'google'),
    scrapeSERP(keyword, 'bing'),
  ]);
  console.log(`\nGoogle (${google.length} results):`);
  google.slice(0, 5).forEach(r => console.log(`  #${r.position}: ${r.title}`));
  console.log(`\nBing (${bing.length} results):`);
  bing.slice(0, 5).forEach(r => console.log(`  #${r.position}: ${r.title}`));
}
compareEngines('residential proxy service');

Proxy Requirements Comparison

The proxy strategy for each engine should differ based on their detection levels:

For Google

• Proxy type: Residential proxies required for reliable results
• Rotation: Rotate IP on every request
• Rate: 1-2 requests per minute per IP
• Headers: Full browser-like header set with Sec-Ch-Ua, Sec-Fetch headers
• Geo-targeting: Match proxy location with gl/hl parameters

For Bing

• Proxy type: Datacenter proxies often sufficient; residential for scale
• Rotation: Can reuse IPs for 3-5 requests before rotating
• Rate: 3-5 requests per minute per IP
• Headers: Standard User-Agent and Accept headers usually sufficient
• Geo-targeting: Use cc parameter; IP geo-matching less critical

ProxyHat residential proxies work optimally for both engines. For Bing-only scraping at moderate volume, datacenter proxies may suffice, but residential proxies from ProxyHat provide consistent results across both engines without needing separate infrastructure. Refer to the documentation for setup details.

URL Parameter Comparison

Purpose	Google Parameter	Bing Parameter
Search query	q	q
Results per page	num (10-100)	count (1-50)
Result offset	start	first
Country	gl	cc
Language	hl	setlang
Safe search	safe	safeSearch
Disable personalization	pws=0	N/A (less personalized by default)
Location override	uule	location

When to Track Both Engines

Tracking both Google and Bing is particularly valuable in these scenarios:

• Enterprise markets: Bing has higher market share among corporate users due to Microsoft Edge and Windows integration
• US market focus: Bing holds approximately 9% of US search traffic, representing millions of potential visitors
• Voice search: Bing powers Cortana and some voice assistant results
• Algorithm diversity: Ranking well on Bing often requires different optimization strategies than Google
• DuckDuckGo and Yahoo traffic: Both use Bing's index, so Bing rankings affect these platforms too

Handling Edge Cases

Bing Market-Specific Domains

Unlike Google which uses google.com with gl parameter for all countries, Bing has country-specific domains:

# Bing country-specific URLs
BING_DOMAINS = {
    "us": "https://www.bing.com/search",
    "uk": "https://www.bing.co.uk/search",
    "de": "https://www.bing.de/search",
    "fr": "https://www.bing.fr/search",
    "jp": "https://www.bing.co.jp/search",
}

Different Pagination

# Google pagination: start parameter (0, 10, 20, ...)
google_page_2 = {"q": "query", "start": 10, "num": 10}
# Bing pagination: first parameter (1, 11, 21, ...)
bing_page_2 = {"q": "query", "first": 11, "count": 10}

Building a multi-engine SERP tracker with a unified proxy infrastructure is the most efficient approach. ProxyHat residential proxies handle both Google and Bing with the same connection, simplifying your architecture while ensuring reliable results from both engines.

For more on building robust scraping infrastructure, see our guides on using proxies in Python, using proxies in Node.js, and our best proxies for web scraping overview. Check ProxyHat SERP tracking solutions for tailored configurations.