Best Google Maps Extractors in 2026

Key Takeaways:

• A Google Maps extractor turns the map into structured rows — business name, rating, place link, and (depending on the tool) phone, address, and website — for lead generation, local SEO, and market research.
• The hard part is that Maps is a JavaScript app behind active anti-bot defenses. Results load into a scrollable feed only after the page renders, so a raw HTTP request returns nothing useful. The tools that work either run a real browser or run a managed extraction service.
• Scrapeless ranks first for developers who want to render Google Maps in a real cloud browser and write their own extraction, with residential egress and a free tier to start.
• The right pick depends on who you are. Developers want an API or browser they control; non-technical teams want a no-code desktop app; high-volume buyers want pay-per-record datasets.
• Pricing models differ more than prices. Some tools charge per result, some per monthly subscription, some per dataset record — match the model to your run shape before comparing sticker numbers.
• Free to start. New Scrapeless accounts include free Scraping Browser runtime — sign up at app.scrapeless.com.

TL;DR: Best Google Maps Extractors at a Glance

What Is a Google Maps Extractor?

A Google Maps extractor is a tool that collects business data from Google Maps search results and place pages, and returns it as structured records instead of a screen you have to read by hand. A single query like "coffee shops in Austin" can yield dozens of listings, each with a name, rating, category, place URL, and — on the detail panel — phone number, address, website, and hours.

Teams use that data for lead generation (building call lists by category and city), local SEO and reputation tracking (monitoring ratings and review counts), and market research (mapping competitor density in an area). The extractor is what turns a manual, page-by-page copy job into a repeatable dataset.

How Do Google Maps Extractors Work?

Google Maps is a client-rendered application. When you search, the results don't arrive as HTML in the initial response — the page loads, then JavaScript fetches and paints listings into a scrollable feed on the left. So an extractor has to do three things a plain HTTP request can't:

1. Render the app so the listings actually exist in the DOM.
2. Scroll the feed to load listings beyond the first screen, since Maps paginates by lazy-loading as you scroll.
3. Read structured fields from each card and, for deeper data, open each place panel.

Tools split into two camps. Some run a real (often cloud) browser and let you script the render-scroll-extract loop yourself. Others run a managed service that does the whole job behind an API or a no-code UI and hands back rows. The first gives you control; the second trades control for convenience.

How We Evaluated These Tools

Each tool was assessed on five things that matter for Maps specifically: whether it can render and reach Maps reliably, the data fields it returns, the interface (API/browser vs. no-code), the pricing model, and whether there's a free tier to test with. Pricing is described by model (per-result, subscription, per-record) rather than a single sticker number, because the right cost depends entirely on run shape — and every pricing claim here was checked on each vendor's own live page.

The Best Google Maps Extractors: Ranked

1. Scrapeless — Best for developers rendering Maps in a real cloud browser

Scrapeless Scraping Browser is a customizable, anti-detection cloud browser designed for web crawlers and AI agents. For Google Maps, that's the key capability: because scraper.google.maps-style HTTP actors are limited, the reliable route is to render google.com/maps in a real browser and extract the feed — which is exactly what the Scraping Browser is for. It connects over standard Puppeteer, supplies residential egress, and runs the JavaScript that builds the listing feed.

Why it ranks first: you get a real Chromium render plus US residential egress and a standard Puppeteer connection, so the render-scroll-extract loop is plain browser code you control — not a black-box actor. It has a free tier to start.

Install (the docs cover the full SDK and CLI surface):

npm install @scrapeless-ai/sdk puppeteer-core

export SCRAPELESS_API_KEY="your_api_token_here"

How you actually use it: prompt your agent. With the Scrapeless skill loaded, you can drive the extraction in natural language — "search Google Maps for coffee shops in Austin and return each place's name, rating, and link" — and let the agent run the loop below. The code is the under-the-hood reference.

Worked example (run live — search → render → extract the feed):

import { Puppeteer } from '@scrapeless-ai/sdk';

const browser = await Puppeteer.connect({
  apiKey: process.env.SCRAPELESS_API_KEY,
  sessionName: 'maps-extractor',
  proxyCountry: 'US',
  sessionTTL: 300,
});

const page = await browser.newPage();
await page.goto('https://www.google.com/maps/search/coffee+shops+in+Austin/', {
  waitUntil: 'domcontentloaded',
  timeout: 60000,
});
await new Promise((r) => setTimeout(r, 5000)); // let the feed paint

const places = await page.evaluate(() => {
  const abs = (u) => { try { return new URL(u, location.href).href; } catch { return null; } };
  return [...document.querySelectorAll('div[role="feed"] > div > div[jsaction]')]
    .map((card) => ({
      name: card.querySelector('[class*="fontHeadlineSmall"]')?.innerText?.trim() || null,
      link: abs(card.querySelector('a[href*="/maps/place/"]')?.getAttribute('href')),
      rating: card.querySelector('span[role="img"][aria-label*="star"]')?.getAttribute('aria-label') || null,
    }))
    .filter((p) => p.name);
});

console.log(await page.title(), '—', places.length, 'places');
console.log(places[0]);
// coffee shops in Austin - Google Maps — 7 places
// { name: 'Terrible Love', link: 'https://www.google.com/maps/place/Terrible+Love/...', rating: '4.9 stars' }

60-second smoke test: run the snippet above with your API key. If it prints a place count and a first record with a /maps/place/ link, your render-and-extract loop works; scroll the feed in a loop to load more than the first screen.

Get your API key on the free plan: app.scrapeless.com

2. Apify (Google Maps Scraper) — Best for pay-per-result runs without infrastructure

Apify hosts a Google Maps Scraper actor you call by API or run from its console. It does the render-scroll-extract job server-side and returns place records, so you don't manage a browser. Pricing is pay-per-result, and there's a free monthly usage allowance to test with. It's a good fit when you want results without running anything yourself and are comfortable paying by the row.

3. Outscraper — Best for quick pay-as-you-go pulls

Outscraper offers Google Maps data through a web app and an API on a pay-as-you-go model, with a free tier to start. It leans toward fast, ad-hoc extractions — enter a query, get rows — and suits users who want occasional pulls without a subscription commitment.

4. Octoparse — Best for non-technical, no-code extraction

Octoparse is a no-code desktop and cloud scraping app with point-and-click templates, including ones aimed at Google Maps. It targets users who don't want to write code: you configure the extraction visually rather than scripting it. It has a free plan plus paid subscription tiers. The trade-off versus a browser/API tool is less programmatic control.

5. Bright Data — Best for high-volume dataset buyers

Bright Data sells Google Maps data through managed scrapers and pre-collected datasets on a pay-per-record model, with a trial available. It's oriented toward buyers who need large volumes delivered as a dataset rather than developers scripting their own runs, and prices by the record.

Side-by-Side Comparison

How Do You Pick the Right Tool?

• You're a developer who wants control — render Maps yourself and write the extraction. Scrapeless gives you the cloud browser and residential egress to do it as plain Puppeteer code.
• You want rows without running anything — a hosted actor (Apify) or pay-as-you-go API (Outscraper) returns records for a per-result fee.
• You don't write code — a no-code app (Octoparse) lets you configure extraction visually.
• You're buying volume — a pay-per-record dataset provider (Bright Data) delivers large pulls as a dataset.

Match the pricing model to your run shape first: per-result is cheap for small ad-hoc jobs and expensive at scale; a subscription flips that; per-record datasets suit bulk one-offs.

Common Use Cases for Google Maps Data

• Lead generation — build call or email lists by category and city from business listings.
• Local SEO and reputation — track ratings, review counts, and category placement over time.
• Market and competitor research — map how many competitors operate in an area and how they're rated.
• Data enrichment — match existing records to Maps listings for phone, address, and website fields.

Why Is Google Maps Hard to Scrape?

Two reasons. First, it's a fully client-rendered app: the listing feed is painted by JavaScript after the page loads and paginates by lazy-loading as you scroll, so there's no static HTML page of results to request. Second, it carries active anti-bot defenses that key on IP reputation and browser fingerprint, so requests from a datacenter IP or a headless browser that reads as automation get challenged. Clearing both is why the tools that work either run a real (cloud) browser with residential egress, or run a managed service that handles rendering and access for you.

FAQ

Q: Is scraping Google Maps legal?
Collecting publicly visible business listings is generally permissible, but Google's Terms of Service and local law govern how you store and use the data — and personal data carries extra obligations. Access only public data, respect the ToS, and consult counsel for your use case.

Q: Do I need a proxy to extract Google Maps?
Yes. Maps keys on IP reputation, so a consistent residential egress (pin a country) is what keeps the feed loading like a normal visitor. Tools like Scrapeless supply residential egress built in.

Q: Why does a plain HTTP request return no listings?
Because Maps renders results with JavaScript after the page loads. A raw request gets the app shell, not the feed — you need a real browser render (or a managed service that does the render) to see the listings.

Q: How do I get more than the first screen of results?
Scroll the results feed in a loop until it stops growing — Maps lazy-loads additional listings as you scroll, so the first render only contains the top few.

Q: Which tool is cheapest?
It depends entirely on run shape. Pay-per-result is cheapest for small ad-hoc jobs; a subscription wins for steady high-frequency use; per-record datasets suit bulk one-offs. Compare the model, not just the sticker number.

Q: Can I extract phone numbers and websites, not just names?
Yes, but those live on each place's detail panel, not the results card. Open each /maps/place/ link (or use a tool that does) to read phone, address, website, and hours.

Conclusion

A Google Maps extractor is only as good as its ability to render the app, scroll the feed, and clear anti-bot defenses — everything downstream is field selection. For developers who want to own that loop, Scrapeless ranks first: a real cloud browser with residential egress and a free tier, where extraction is plain Puppeteer code you control. Hosted actors and no-code apps trade that control for convenience, and dataset providers trade it for volume. Pick by who you are and how often you run, render in a real browser, and treat the place panel as a second step. See the Scraping Browser product page, a worked Google Maps lead-generation pipeline, and pricing to start.

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