Runs on your machine, not a shared proxy pool
Extraction happens locally through your own connection at a human request cadence. There is no shared cloud IP to get rate-limited behind, and no API key to provision.
Desktop Google Maps scraper · Windows & macOS
Lead Finder is a desktop Google Maps scraper and data extractor for Windows and Mac. A single Google Maps search stops at roughly 120 results. Lead Finder subdivides the map into a search grid, sweeps every cell, and merges what comes back, so you export the whole city, not the first page of it.
Free demo. No credit card required.
A Google Map data extractor is software that collects publicly listed business information from Google Maps and exports it as a structured spreadsheet. A typical export contains the business name, phone number, website, full address, star rating, review count and category, written out as CSV or Excel for import into a CRM. The same category of tool is also sold as a Google Maps scraper, a Google Maps data extractor or a Google Map lead extractor; the names differ, the job does not.
Extractors differ mainly in how they handle Google's per-query result ceiling. A single Google Maps search returns roughly 120 listings regardless of how many businesses exist in the area, because the limit applies to the query rather than to the city. Tools that exceed it divide the target area into a grid of smaller areas, search each one separately, then merge and de-duplicate the results. Lead Finder is a desktop extractor that uses this grid method, running locally on Windows or macOS rather than through a cloud API.
§ 01 / Demo
A real run: category and city in, grid sweep, CSV out. Three minutes, no narration shortcuts.
§ 02 / Method
The 120-result ceiling is a property of a single query, not of Google Maps itself. Run many smaller queries and the ceiling stops mattering.
Enter a business category and a target area, for example "dentist, Manchester" or "HVAC contractor, Phoenix metro". Set the grid resolution based on how dense the area is.
Lead Finder divides the area into cells and searches each one in sequence, merging results and dropping duplicates by place ID as it goes. Progress auto-saves, so a dropped connection costs you nothing.
Write out every column to CSV or Excel. Columns map cleanly onto HubSpot, Pipedrive, Instantly and Lemlist imports without reshaping.
§ 03 / Interface
Search on the left, live grid progress in the middle, results table below. Everything writes to disk as it goes, so closing the laptop does not cost you the run.
§ 04 / Capabilities
Extraction happens locally through your own connection at a human request cadence. There is no shared cloud IP to get rate-limited behind, and no API key to provision.
One price per year regardless of volume. Cloud extractors bill per thousand rows, so a single 50,000-row metro sweep can cost more than a year of Lead Finder.
Every campaign keeps its own state on disk. Stop a 40,000-row job overnight, reopen it tomorrow, and it continues from the last completed grid cell.
Grid cells overlap at their boundaries by design, so the same business appears in several cells. Results are keyed on place ID and collapsed before they ever reach your CSV.
§ 05 / Cost
Per-row cloud pricing is cheaper at small volumes. The crossover comes fast. These are list prices at the time of writing; check current rates before deciding.
| Rows extracted per year | Typical cloud extractor | Lead Finder |
|---|---|---|
| 5,000 | ~$10 | $20 |
| 25,000 | ~$50 | $20 |
| 100,000 | ~$200 | $20 |
| 500,000 | ~$1,000 | $20 |
Cloud figures assume a $2 per 1,000 rows list rate, which is mid-range for the category. See the full tool-by-tool comparison.
§ 06 / Niches
Search terms, realistic city list sizes and the outreach channel that fits, per industry.
§ 07 / Vocabulary
Google Maps scraper, data extractor, lead finder, CSV exporter: mostly the same category under different names, but each phrasing carries a different question. What each one usually means, and where the full answer lives.
The umbrella term, and the one that tells you least about what you are buying. Three unrelated delivery models share it: a desktop application, a hosted API billed per row, and a browser extension limited to what one tab can hold. The word is identical in all three cases; the cost and the ceiling are not.
Named for the output rather than the method. The question worth asking of any product using this phrase is which columns it actually returns, because the gap between tools is not whether they get the business name but whether they get coordinates, opening hours and the place identifier that makes de-duplication possible.
Singular "map", and worth separating from the plural because it attracts a different question. People searching this sometimes want business listings and sometimes want their own My Maps layers or Timeline history exported, which is a different product entirely and not what any business extractor does.
The shortest form of the phrase, usually typed by someone who already knows the category exists and wants to see the operational detail: what a run looks like from opening the tool to holding a cleaned file, and how much of that is automatic.
The word "software" signals a purchase decision rather than a curiosity. It usually means installed rather than hosted, which changes what you are buying: a licence for something that runs on your hardware, with system requirements and no ongoing metered cost, instead of access to somebody else's infrastructure.
Where the mechanics matter. Any tool in this category lives or dies on two things: how it divides an area so that no single query hits the result ceiling, and what it matches on when the same business turns up in several overlapping searches.
The interesting question here is what counts as a business. Claimed profiles, unclaimed profiles, service-area businesses with no storefront and individual branches of a chain all appear as separate listings, and which of them you want depends entirely on what you are selling.
Describes the whole pipeline rather than the extraction step. Extraction is the first of four stages, and the one that takes the least time: defining a territory, extracting it, qualifying the rows and making contact. Tools sold under this name vary in how many of the four they actually touch.
Partly a product name, which is why the results for it are a mix of categories and brands. Lead Finder is ours. The generic sense is a tool that locates prospects by category and area rather than by company attributes such as size or revenue.
Worth being precise about: a Maps row is a contact route, not a qualified lead. Nobody on that list has expressed interest in anything. What you have is a verified way to reach a business that matches a category and a location, which is the beginning of qualification rather than the end of it.
The business-to-business framing narrows which propositions work. Selling to the owner of a local firm through their public phone number suits services priced at a level an owner decides alone. It suits long enterprise sales cycles with buying committees very poorly, because the committee is not on the listing.
Sweeping for quality rather than volume. The highest row count is rarely the best outcome; a smaller file where every row has a working phone number and a missing website is worth more to most sellers than a larger one padded with unreachable entries.
The day-to-day usage question. A list is a one-off, but prospecting is a rhythm: carving territory so callers do not overlap, deciding how often a territory is re-swept, and knowing when a list has been worked out and needs replacing rather than revisiting.
A buying-criteria query. The capabilities that matter for lead generation specifically are coverage past the result ceiling, export fields that import into a CRM without reformatting, and a cost model that does not punish you for re-running a territory.
Accuracy is the axis here. Every field decays at its own rate, and knowing which ones go stale fastest tells you how long an export stays useful: hours drift within weeks, phone numbers and websites within months, addresses and categories much more slowly.
Concerned with what happens after you have the numbers. Formats arrive inconsistent and need normalising before any dialler will accept them, the same number appearing on several listings is a finding rather than a fault, and a published number often reaches a reception rather than the person who decides.
Treats the output as an asset rather than a process. Its value relative to a purchased database is currency and territory control; its limitation is that it carries no firmographics at all, so headcount, revenue and technology stack have to come from somewhere else.
Where a team rather than an individual is doing the work. The problems that appear at team scale are different: splitting a city between representatives without two people calling the same business, and keeping one shared definition of which territories have been worked.
About the file itself. Encoding, delimiter choice and quoting decide whether a business name containing a comma stays in one column or silently splits into two, which is the most common way an otherwise clean export arrives corrupted.
Excel-specific damage. Opening a CSV rather than importing it hands every column to Excel's type guesser, which removes leading zeros from phone numbers and converts long digit strings to scientific notation. The file is fine; the way it was opened is not.
Managing exports across time rather than producing one. Naming so that a file six months old is identifiable, splitting a large sweep into files a spreadsheet can open, and comparing this month's export against last month's to find what changed.
The field Maps does not have. Listings carry no email, so any tool reporting one has visited the linked website and looked for a published address. Coverage of twenty to forty percent is realistic; anything claiming much more is pattern-guessing addresses that bounce.
The opposite case, and the most reliable field on a listing, because a phone number is what a business most wants a customer to have. The work is in normalising it to a single format and deciding what to do about numbers shared across several outlets.
Explains a gap rather than a tool. Independent local businesses are thinly covered by commercial B2B databases because nobody has had commercial reason to catalogue them, which is precisely why a Maps sweep reaches firms a purchased list will not.
A local lead behaves differently from a national one. Proximity is itself a qualifier, the relationship tends to be with an owner rather than a procurement function, and the decision is usually made by one person in one conversation.
A category map for an operation serving local clients, and an order of adoption. Most teams need the list-building piece long before they need automation on top of it, and buying those in the wrong order is the usual reason a stack goes unused.
Where an honest comparison against contact databases belongs. They hold named individuals, job titles and company attributes that Maps cannot supply; Maps holds small local firms that they largely do not. Neither is a substitute for the other and the choice follows from who your buyer is.
Also partly branded, and useful mainly for stating what is not covered. A Maps-derived list gets you to the business; it does not get you to a named decision-maker, an org chart or a buying signal, and pretending otherwise wastes a sales team's time.
The widest framing of all, which makes it a category map: what the market actually contains, roughly what each type costs, and which segment each is built for. Useful when you do not yet know which kind of tool your problem needs.
Extraction as a general technique rather than a Maps-specific one. The division that matters is source-specific tools, which understand one site deeply, against general-purpose scrapers configured per target, which are more flexible and considerably more work.
§ 08 / Reviews
5 out of 5 from 110 reviews
We use Lead Finder mainly for finding local business prospects for our digital marketing services. The ability to search by city and business category saves us a lot of manual research. Exporting the results to Excel also makes it easy for our sales team to work with the leads.
Lead Finder has made our Google Maps prospecting much easier. We can search for specific businesses in different cities and quickly build a targeted list. It is simple to use and works well for our regular lead-generation campaigns.
We were looking for a simple Google Maps data extractor for our agency. Lead Finder gives us a convenient way to find businesses by category and location. The CSV export is particularly useful when we need to share lists with our sales team.
We use Lead Finder to discover potential clients for our website and SEO services. Instead of manually checking hundreds of Google Maps listings, we can create a business list much faster. It has become a useful tool in our prospecting process.
I tested several Google Maps scraper tools before choosing Lead Finder. I liked the straightforward desktop experience and the simple export process. For local B2B lead generation, it has been very useful for our team.
Lead Finder is useful for building targeted local business lists. We regularly search different industries and cities depending on our campaigns. Having the business information organized in a spreadsheet saves our team considerable time.
We primarily use Lead Finder for B2B lead generation and sales prospecting. The category and location searches help us focus on the businesses we actually want to approach. The overall workflow is simple and does not require much technical knowledge.
Lead Finder has been helpful for our local lead-generation campaigns. We can research a particular niche in a city and create a prospect list without manually copying every business. The export functionality fits nicely into our existing sales workflow.
I wanted a Google Maps lead finder that was easy for my team to use. Lead Finder makes it simple to search businesses and export the information for further research. It has saved us a lot of time when building new prospect lists.
We use Lead Finder for finding potential clients across different cities. The ability to search by business type makes our prospecting much more focused. For an agency doing regular local business outreach, it is a very useful addition to the sales toolkit.
We use Lead Finder to build real estate leads from Google Maps in different locations. Searching by category and city makes it easy to identify agencies and property businesses. It has made our market research much faster.
Lead Finder has been useful for finding construction and contractor leads in specific cities. We can create a targeted list instead of manually checking businesses one by one. The export feature is very convenient.
Quotes come from licence holders who agreed to be credited in this form, given on WhatsApp or by email, and trimmed only for length. The rating is the average of all 110 on file, not of the 12 shown here, and it is computed from them rather than entered by hand, so it cannot be set independently of the reviews behind it.
§ 09 / Questions
The free demo runs the complete interface against a live search so you can judge coverage and data quality before paying anything.
Free demo · Retail licence $20/year · Support from WappBlaster