Places, phones & emails
Google Maps data extractor: every business, emails included.
Hubertino's Google Maps scraper turns a search into one row per business: name, phone, website, rating and review count from the listing, plus the email and socials from its own website.
- No card required
- Pay per result
- XLSX · CSV · API
What is a Google Maps data extractor?
A Google Maps data extractor turns a Google Maps search into a lead list: every business it finds, one row each, that you can qualify by rating and reviews and reach by phone or email. It's also called a Google Maps business extractor or places scraper. Hubertino's finds the email on each business's own website, which the listing doesn't show.
Where the data comes from
- Google Maps
- Their website
- Its reviews
On Google Maps
- Kestry Dental Co
name
- kestrydental.com
website - +1 929 555 0164
phone
On their website
- [email protected]
email
In your sheet
- name
- Kestry Dental Co (from the Google Maps listing)
- phone
- +1 929 555 0164 (from the Google Maps listing)
- [email protected] (from the business's website)
- website
- kestrydental.com (from the Google Maps listing)
- rating
- 4.9 (from the Google Maps listing)
- reviews
- 341 (from the Google Maps listing)
Reviews scraper
A separate job for the reviews themselves: one row per review, at 1 credit per review.
Its reviews, on Google Maps
- Booked online on a Sunday, seen on Tuesday. Gentle with a nervous patient, and no upselling.
text
In a reviews sheet
- place_name
- Kestry Dental Co (from its reviews)
- rating
- 5 (from its reviews)
- text
- Booked online on a Sunday, seen on Tuesday. Gentle… (from its reviews)
- owner_response
- Thank you! See you in six months. (from its reviews)
Plus 32 more columnsCategory, address parts, coordinates, socials, opening hours, booking links and Google's IDs. See all 38, with what each holds, and the paid add-ons' columns.
| Column | ColumnWhat it holds |
|---|---|
| Search and identity | |
| query | queryThe search that found the business: your category and location, as sent to Google Maps. |
| name | nameThe business name as it appears on Google Maps. |
| category | categoryGoogle's categories for the listing, comma-separated, e.g. “Dentist, Cosmetic dentist”. |
| Contact | |
| phone | phoneThe phone number on the listing, as Google shows it. |
emailA contact email from the business's own website: the homepage first, then up to two contact or imprint pages. One address per business, preferring one on its own domain. | |
| website | websiteThe website link on the listing. Sometimes a Facebook, Instagram or booking page rather than a site of the business's own. |
| domain | domainThe website's host without “www.”, for de-duplicating and matching against other lists. |
| Social profiles | |
| company_facebook | company_facebookFacebook page, found on the business's website or its Google business panel. |
| company_instagram | company_instagramInstagram profile, from the same two sources. |
| company_x | company_xX (Twitter) profile, from the same two sources. |
| company_youtube | company_youtubeYouTube channel, from the same two sources. |
| company_linkedin | company_linkedinLinkedIn page, from the same two sources. With the decision-maker add-on, also from the company's professional profile when neither had one. |
| Address | |
| address | addressThe full address on one line, as Google formats it. |
| street | streetStreet and number. |
| city | cityCity or town. |
| state | stateState, province or region, spelled out. |
| state_code | state_codeThe short state or province code where the country uses one, e.g. NY, ON, NSW. |
| postal_code | postal_codeZIP or postcode. |
| country | countryCountry name. |
| country_code | country_codeTwo-letter ISO country code, e.g. US, GB, DE. |
| Coordinates | |
| latitude | latitudeLatitude of the place pin, in decimal degrees. |
| longitude | longitudeLongitude of the place pin, in decimal degrees. |
| plus_code | plus_codeGoogle's Plus Code for the spot, where the listing shows one. |
| Reputation | |
| rating | ratingAverage Google star rating, 1.0 to 5.0. |
| reviews | reviewsNumber of Google reviews. |
| Business details | |
| business_status | business_statusOPERATIONAL, CLOSED_TEMPORARILY or CLOSED_PERMANENTLY. |
| price_range | price_rangeGoogle's “price per person” band, where the listing shows one (mostly restaurants and cafés), e.g. “$20–30”. |
| service_options | service_optionsThe listing's service chips, comma-separated: Dine-in, Takeout, Delivery, In-store shopping and the like. |
| Opening hours | |
| working_hours | working_hoursWeekly opening hours, one entry per day, as JSON. |
| working_hours_csv | working_hours_csvThe same hours flattened into a single text cell. |
| Action links | |
| order_links | order_linksOnline ordering links the listing offers (delivery apps or the business's own), up to three. |
| reservation_links | reservation_linksThe table-booking link on the listing. |
| menu_link | menu_linkThe menu link on the listing. |
| Google references | |
| location_link | location_linkThe place's Google Maps URL. |
| place_id | place_idThe Places API place ID, for joining with Google's own API data. |
| google_id | google_idGoogle Maps' feature ID for the place, in 0x…:0x… form. |
| cid | cidThe listing's CID: the second half of google_id as a decimal number. |
| kgmid | kgmidThe place's Google Knowledge Graph ID, a /g/… or /m/… path. |
| SEO audit (paid add-on) | |
| website_type | website_typeWhat the listing's website really is, in plain English: own website, no website, a social profile, a booking page, a directory listing, unreachable… Free on every place. |
| seo_score | seo_scoreA 0–10 SEO score for each own website we could check. |
| seo_issues | seo_issuesThat site's top three SEO issues, in plain sentences, joined with “ | ”. |
| Decision makers (paid add-on) | |
| company_size | company_sizeThe company's employee band, e.g. “11-50 employees”. |
| contact_1_name | contact_1_nameThe most senior decision maker we found: an owner, founder, CEO or other top executive. |
| contact_1_title | contact_1_titleTheir current job title. |
| contact_1_linkedin | contact_1_linkedinTheir LinkedIn profile. |
| contact_1_email | contact_1_emailA work email when one is known. It's often inferred from the company's email pattern, so verify it before you send. |
| contact_2_name | contact_2_nameA second decision maker, when there is one. |
| contact_2_title | contact_2_titleThe second decision maker's job title. |
| contact_2_linkedin | contact_2_linkedinThe second decision maker's LinkedIn profile. |
| contact_2_email | contact_2_emailThe second decision maker's work email, often inferred too. |
Every export has these columns, in this order; a paid add-on (Website Analysis or Lead Enrichment) adds its own after them. See them filled in the sample XLSX (fictional businesses, decision makers masked).
How it works
From one search to a full sheet
Describe the hunt
Categories and locations, down to postcodes, with a live cost estimate.It runs live on Google Maps
Each category × location is its own search; each website is checked for an email and socials.Export or pull the rows
XLSX, CSV or JSON over the API. Reserved credits a job doesn't use come back.
Revenue plays
Turn the rows into revenue
Each play is a filter on your export and an offer to make. Find yours.
For web designers
Nail salons with no website
- Filter
category= nail salonwebsitenone or social
- Sell
- A website, or a booking page that works.
- Who fits
- 29.7%of nail salons have no site of their own8.9% across all industries
For SEO agencies
Accountants with under 20 reviews
- Filter
category= accountantreviews< 20
- Sell
- Review requests and local SEO.
- Who fits
- 40.9%of accountants have fewer than 20 reviews13.1% across all industries
For reputation agencies
Gyms rated under 4.0
- Filter
category= gymrating< 4.0
- Sell
- Reputation management and review replies.
- Who fits
- 8.8%of gyms are rated under 4.0 stars2.6% across all industries
For suppliers & B2B sales
Coffee shops in your delivery area
- Filter
category= coffee shop- your zip codes
- Sell
- Your beans, machines or software, by email or phone.
- Who fits
- Allthe coffee shops Google Maps lists thereOne search per zip code, not just page one
Review data
Reviews tell you what to pitch
Rating and review count are columns in every places export, at no extra cost, so you can qualify a list before reading a word. The Google Maps reviews scraper goes deeper: each review in full, one row per review, with its stars, date, text and the owner's reply. It's a separate job at 1 credit per review delivered, started from a finished scrape or from pasted Maps links.
- Quote their own customers Open with the complaint their reviews keep repeating, like missed calls.
- Find the silent ones An empty
owner_responsemeans nobody answers reviews: a review-management client. - Read the competition A rival's one- and two-star reviews show what its customers still want.
- Search for your problem Filter the text for what you fix, like “booking”: those businesses are your list.
How we counted
The shares are of the 70,643 businesses in 6,399 lead-list samples (the top Google Maps results for one category in one city, 324 cities) scraped with Hubertino from July 2026 to September 2026. Each card names the industry where its share is highest, among industries with at least 30 listings; the line under it is the share across every industry. “No site of their own” means no website on the listing, or only a social or booking page. The review and rating shares are out of the listings that show a count or a rating. The coffee-shop list is whatever your own search returns. Each sample is the top of one search, so a full sweep of a city can come out differently. A share says how many businesses fit a filter, not what any of them will buy.
Pick a play. Pull the list.
Your first 100 businesses are free, emails included. Or browse live example lists by niche & city.
For developers
The same data over the API
Send categories, locations and maxResults, poll, then page the rows as JSON or download XLSX or CSV: the same 38 columns, on every plan, free included.
Auth, paging and error codes are in the Google Maps scraper API reference.
curl https://hubertino.com/api/v1/scrapes \ -H "Authorization: Bearer $HUBERTINO_API_KEY" \ -H "content-type: application/json" \ -d '{ "categories": ["dentist"], "locations": ["Austin, TX"], "maxResults": 50 }'Python examplestart → poll → download
import os, time, requests API = "https://hubertino.com/api/v1"KEY = os.environ["HUBERTINO_API_KEY"]s = requests.Session()s.headers["Authorization"] = f"Bearer {KEY}" # 1. Start a scrapescrape = s.post(f"{API}/scrapes", json={ "categories": ["dentist"], "locations": ["Austin, TX"], "maxResults": 50,}).json()["scrape"] # 2. Poll until it finisheswhile scrape["status"] not in ("done", "error"): time.sleep(5) scrape = s.get(f"{API}/scrapes/{scrape['id']}").json()["scrape"]if scrape["status"] == "error": raise SystemExit(scrape["error"]) # reserved credits come back # 3. Download the CSVcsv = s.get(f"{API}/scrapes/{scrape['id']}/export?format=csv")csv.raise_for_status()open("leads.csv", "wb").write(csv.content)- POST
/api/v1/scrapesStart a scrape - GET
/api/v1/scrapes/{id}Status and credits - GET
/api/v1/scrapes/{id}/resultsRows as JSON, paged - GET
/api/v1/scrapes/{id}/exportThe finished file, CSV or XLSX?format=csv
Pricing
Start free. Scale when it works.
1 credit per business delivered, emails included. Plan credits roll over 6 months.
- FreeNo cardFree100 credits on signupStart free
- RecommendedStarterFor ongoing prospecting$19/mo50,000 credits / monthSee Starter
- ProFor teams and heavy pipelines$69/mo250,000 credits / monthSee Pro
From $0.276 per 1,000 businesses when a month's credits are used. Full plan details on the pricing page.
FAQ
Questions
Need what customers say, not who they are? See the Google Maps reviews scraper. Only after the emails? See the email extractor. Want to know who runs each business, or how good its website is? See Lead Enrichment and Website Analysis.
What does the Google Maps data extractor export?
One row per business with 38 columns: name, categories, phone, website and domain, a contact email from the business's own site, five social profile columns, the address split into parts, coordinates, rating and review count, business status, price band, service options, opening hours, ordering, booking and menu links, and Google's own IDs (place_id, google_id, CID and kgmid). XLSX or CSV, or JSON over the API.
Does every business come with an email?
No. The email column is filled when a business publishes an address on its own website: in our own samples (67,173 businesses, harvested July 2026) Hubertino found one for 64% of businesses. Businesses with no website, or no address on it, have the field empty. The lookup costs no extra credits.
What can I do with Google Maps review data?
Qualify leads and write the pitch. Rating and review count are columns in every places export, at no extra cost, so you can filter for businesses under 4.0 stars or with few reviews. The Google Maps reviews scraper exports each review in full, one row per review, as a separate job at 1 credit per review delivered. Use it to quote a prospect's own customers, spot reviews nobody answered, read a competitor's weak spots or search the text for the problem you solve.
Is scraping Google Maps legal?
Collecting business details that are publicly listed is generally lawful in the US and EU, but Google's Terms of Service restrict automated collection from Google Maps. What you then do with the data is regulated in its own right: in the UK and EU, GDPR covers keeping any record that identifies a person, and outreach falls under CAN-SPAM in the US, PECR in the UK, § 7 UWG in Germany, CASL in Canada and the Spam Act in Australia. This isn't legal advice; our legal guide goes into more detail.
How is this different from the Google Places API?
The official API is built for showing places inside apps: results are capped per search, there's no email field, and its terms restrict exporting the data. This scraper is built for lead lists — complete coverage via zip-code-level searches, emails dug from business websites, and a plain spreadsheet you own. Weighing other tools? See how Google Maps scrapers compare and the Google Maps browser extensions we checked.
How many businesses can I scrape at once?
As many as your credits cover. A scrape runs every category in every location as its own search, and the location picker splits a city into its zip codes, so a big city isn't cut short at the end of one search's results. A job stops once it has delivered as many businesses as you have credits; a very large hunt splits into several scrapes.
Which countries does it cover?
Do I need to write any code?
No. Describe the hunt in the dashboard and export XLSX or CSV. If you want automation, the same scrapes run over a REST API on every plan, including free.
What does it cost?
1 credit per business delivered, emails and socials included. Signing up gives 100 free credits, no card. Starter is $19 a month for 50,000 credits ($0.38 per 1,000) and Pro $69 for 250,000 ($0.276 per 1,000), when a month's credits are used; plan credits roll over 6 months.
Can I skip businesses I already have?
Yes. Import their Google Place IDs under Settings → Existing contacts, pasted or as a CSV; every Hubertino export has a place_id column. Each scrape, in the dashboard or over the API, checks its results against that list. A place on it is still listed with its Google Maps data and marked Existing, but we skip its website (no email lookup), charge no credit for it and don't count it toward the search's maximum, so you still get up to that many new places. A scrape lists roughly one such match per place it reserves and leaves any further matches out.
Start the hunt
Your customers are on the map
Find them in minutes, emails included. The first 100 are on us.
- No card required
- Pay per result
- Unused reservations refunded