How do I scrape Google Maps?

If you are asking how to scrape Google Maps, you almost certainly do not want to scrape Google Maps. What you want is what scraping promises: business data at scale, names and numbers and locations for a whole market, without copying pins by hand. Scraping is just the means that presents itself, usually via ads for tools promising thousands of listings at the click of a button. Before going down that road, it is worth an honest look at where it leads, because the promise and the product are very different things, and a better road exists.

Start with the rules, because they are not ambiguous

The threshold fact: Google's terms of service prohibit scraping and systematic extraction of Maps content. This is not a grey area or a technicality, it is the explicit deal you accept by using the service. The scraping tool ecosystem exists in defiance of those terms, and everything built on such tools inherits that standing. Google actively works against automated extraction, which is why scrapers break constantly, get blocked, and require perpetual cat and mouse maintenance from their developers.

What does that mean for you practically? That any workflow you build on scraping is built on sand. The tool that works this month may return errors next month. Access can be blocked. The vendor may vanish. If lead generation matters to your business, and it does or you would not be reading this, then it deserves a foundation that does not depend on continuously outrunning the platform it extracts from. Business processes need to be boring and reliable, and scraping is neither.

The data is thinner than the row count suggests

Set the rules aside for a moment and inspect the goods. A successful scrape delivers what Maps displays: business name, address, phone number for most listings, a website link for some, review counts. It looks substantial in a spreadsheet, thousands of rows, columns full of text. Now audit it the way you would audit any purchased list.

There are no email addresses, because Maps does not display them. There is no confirmed business identity, no ABN, no way to tell which legal entity stands behind a listing name. Industry is whatever category the listing sat in, which is noisy at best. There is no verification of anything: unclaimed listings, duplicates, and businesses that closed years ago come through the scrape looking identical to healthy, current ones. And critically, coverage is capped by ranking, because a scraper can only harvest what Maps chooses to display, and Maps displays winners of a consumer relevance contest, not complete markets. The invisible businesses stay invisible to the scraper too.

So the honest description of scraped Maps data is this: an unverified, email free, identity free, ranking biased snapshot of the visible layer of a market, decaying from the moment of capture. That is what the impressive row count actually contains.

Count the full cost, not the tool price

Scraping advocates point to price: tools are cheap, some are free, surely that beats paying for data. But price the whole exercise. There is the time cost of learning, running, and babysitting tools that break. The cleanup cost of deduplicating and formatting raw output into something usable. The outreach cost of dialling disconnected numbers and knocking on the doors of closed businesses, because nothing was verified. The opportunity cost of the businesses your scrape never saw, which your better informed competitor is calling. And the compliance dimension: beyond Google's terms, Australian outreach operates under the Spam Act, and data of murky provenance makes your obligations harder to meet, not easier.

Cheap inputs that produce expensive workflows are not cheap. They just move the invoice from your software budget to your calendar, where it is harder to see and larger.

The maintenance treadmill nobody mentions

One more cost deserves its own heading, because it is the one that eventually breaks every scraping based process: maintenance. A scrape is not a system, it is an event, and the output starts ageing immediately. To keep data current you must scrape again, and again, forever, each run subject to the same breakage risks, each output needing the same cleanup, each cycle consuming another evening. Compare that with data infrastructure whose refresh is somebody else's full time job. Rafter Leads updates weekly as a matter of course, newly registered businesses flow in as they appear, and your only maintenance task is running a search. The difference between operating a treadmill and subscribing to a service is the difference between a hobby and a business process, and pipelines deserve to be business processes.

The clean alternative does the job properly

Here is the thing the scraping route obscures: the problem scraping tries to solve is already solved, properly, by data built for the purpose. Rafter Leads exists precisely so that Australian businesses never need to extract anything from anywhere. The platform is grounded in official Australian registry data covering more than 2.6 million actively trading businesses, which means coverage of the actual market, not the ranked slice a scraper can reach. Enrichment and verification happen before you ever see a record.

Every profile that goes live has cleared a strict quality floor: confirmed business name and ABN, working phone number, live website, suburb and postcode, contact email, trusted industry classification, and a written overview of the business. Note the items on that list that no scrape can deliver: the verified identity, the deliverable email, the industry you can trust, the plain English sense of what the business actually does. You search by industry and location and get ranked, complete, working records, sourced cleanly, refreshed weekly, and available the moment you need them rather than after a weekend of tool wrangling.

What to do instead, starting today

So the practical answer to how do I scrape Google Maps is: do not, and do this instead. Define the market you were about to scrape, the industry and the area. Run that exact search on the platform. Review the ranked results, unlock the businesses that fit your ideal customer, and start your outreach this afternoon with complete profiles instead of raw pins. Keep Maps open for what it is good at, eyeballing individual prospects, checking premises, reading reviews, while your actual pipeline runs on data with a foundation.

The desire behind scraping is completely legitimate: you want your market, in usable form, without manual drudgery. The method is what fails, on rules, on quality, and on reliability all at once. Take the desire seriously and route it through infrastructure built to satisfy it. Open a free trial, run your first search, and get the market view the scraper was never going to give you, cleanly, completely, and in about ninety seconds.