A complete 2026 guide to extracting business phone numbers from Google Maps — manual search, browser extensions, scrapers, APIs — and how to turn a phone number into a qualified sales pipeline with LeadBoba.
LeadBoba's dashboard for discovering business phone numbers and contact data — a screenshot fits well here
Finding business phone numbers used to mean jumping between directories, company websites, social media profiles, and outdated spreadsheets. Google Maps has changed that.
For almost any local business, a Google Maps profile can provide a business name, location, category, website, phone number, opening hours, and reviews. The challenge is that Google Maps is designed for consumers searching for one business at a time — not for sales teams trying to build a database of thousands of prospects.
If you search "roofers in Texas" or "dentists in London," Google Maps doesn't hand you every matching business in one convenient spreadsheet. You might need:
Manually collecting those phone numbers can take hours or days. This guide covers five practical ways to find and extract business phone numbers from Google Maps in 2026, and how to turn that list into an actual sales prospecting workflow.
If you're building a local B2B prospect list, one of the biggest advantages of Google Maps is geographic coverage. Traditional professional databases often focus on companies that meet certain size or revenue criteria — Google Maps is different.
A small family-owned plumbing company can have a Google Business Profile even with no LinkedIn page, no Crunchbase entry, just a basic website and five employees. That makes Google Maps particularly useful for local business lead generation — the businesses that actually operate in your target market, not just the largest companies in it.
Combining fields like category, rating, review count, website, and phone number turns a generic search into a targeted list — for example: roofing companies in Dallas → 4+ Google rating → 50+ reviews → website available → phone number available.
The exact fields available depend on the individual listing, but commonly include:
| Data | Example |
|---|---|
| Business name | ABC Roofing |
| Category | Roofing contractor |
| Phone number | +1 555-123-4567 |
| Website | abcroofing.com |
| Address | Dallas, Texas |
| Rating | 4.7 |
| Review count | 183 |
| Opening hours | Mon–Fri 8AM–6PM |
The phone number is usually one of the most valuable fields for local sales prospecting, and the website — when present — can lead to additional contact information such as emails, contact pages, and social profiles.
Open Google Maps, search a category and location (e.g. "dentists in Leeds"), click each business, copy the phone number into a spreadsheet, and repeat. It works — but it doesn't scale. Even at 20 seconds per business, 1,000 businesses is five-plus hours of repetitive work, assuming every listing has a number and nothing needs verifying. Manual research makes sense for 10–30 businesses; automation becomes attractive well before 1,000.
Make searches more specific — "dentists in London" instead of "businesses in London" — and split large geographic areas into smaller markets (London, Birmingham, Manchester, Leeds…). This produces more manageable datasets, but you still have to repeat the process for every city and category by hand.
A dedicated scraper automates the repetitive part: choose industry → choose location → search → collect businesses → filter results → export leads. The advantage isn't just speed, it's structure — business name, phone, website, and address get organized automatically instead of copy-pasted one field at a time.
Developers can build a custom extraction system with Python, Playwright, Selenium, or Node.js. It offers full control over which fields are collected and how data is stored — but you also own the maintenance: Google Maps changes, selectors break, requests get blocked, and infrastructure needs upkeep. Worthwhile for a specialized internal system, often unnecessary complexity for a salesperson who just wants a list of phone numbers.
Official Google Maps Platform APIs are built for developers who need location or place data programmatically inside an application, returning structured responses instead of requiring automation of a consumer-facing site. But APIs aren't designed around sales prospecting — turning API results into a usable prospect list still needs search expansion, deduplication, enrichment, website crawling, email discovery, and CRM integration on top.
Getting 10,000 phone numbers isn't necessarily useful. Getting 500 highly relevant prospects can be much more valuable. The key is targeting:
For example: roofers in Texas + 4.0+ rating + 30+ reviews + phone number is a significantly more targeted dataset than every business in the state.
| Method | Small Lists | Large Lists | Automation | Technical Skill |
|---|---|---|---|---|
| Manual Google Maps | Excellent | Poor | None | None |
| Browser Extensions | Good | Limited | Basic | Low |
| Dedicated Scraper | Excellent | Excellent | High | Low |
| Custom Python Scraper | Good | Excellent | High | High |
| Google Maps API | Excellent | Depends | High | High |
There isn't one solution for every use case. Manual research is fine for a handful of businesses; a custom scraper suits a highly specialized workflow; an API fits when location data needs to power an application; and a dedicated lead-generation platform suits users who want prospect lists without building the infrastructure themselves.
This is where the difference between business data extraction and lead generation matters. LeadBoba is built around the second problem — turning local businesses into usable sales leads, not just a list of names.
That turns the process from "Google Maps → spreadsheet" into "business discovery → lead qualification → outreach → pipeline" — a fundamentally different workflow.
A screenshot of the CRM pipeline fits well here
A phone number isn't the end of the process — it's the beginning.
A targeted list lets sales teams prioritize outbound calls by industry, location, reviews, and website presence instead of dialing at random.
Web designers, SEO agencies, and marketing companies can search a category (e.g. "restaurants in Manchester"), identify businesses with no website, and use the phone number as a starting point for outreach.
Combining a phone number with an email address supports a multi-channel cadence — for example, email on day 1, a call on day 2, a follow-up email on day 4, and a second call on day 7 — the exact cadence depending on the business, industry, and applicable communication rules.
Public visibility doesn't automatically mean every use of the information is unrestricted. A few things to keep in mind:
Finding one business phone number from Google Maps is easy. Finding hundreds or thousands of relevant businesses and organizing their contact information into a usable sales pipeline is the real challenge. You can do it manually for small lists, use browser extensions for basic extraction, build your own scraper if you have the technical resources, use an API for location-based software, or use a dedicated lead-generation platform when the goal is turning businesses into prospects, not just extracting data.
For businesses that depend on local B2B sales, Google Maps can become the starting point for a repeatable workflow: find businesses → identify contact information → qualify prospects → save leads → contact prospects → manage the pipeline.
Search any industry and location, get phone numbers, emails, and social profiles, organize leads in the built-in CRM, and export to CSV — all in one platform.