How to Scrape Emails and Owner Names from Google Business Profiles (3 Methods)

If you are trying to get emails and owner names from Google Business Profiles, the first thing to understand is this:

Google Business Profiles usually do not show email addresses.

The email is normally found on the business website. The owner name might be on the website, in review replies, on BBB, on Facebook, on LinkedIn, or nowhere obvious at all.

So the real workflow is not just "scrape Google Maps."

The real workflow is:

1. Find businesses from Google Business Profiles.
2. Visit their websites.
3. Extract emails from public pages.
4. Verify or at least score those emails.
5. Look for owner, founder, principal, or manager names.
6. Export the data cleanly enough to use in outreach.

The video above walks through the three methods. This article gives you the written version, plus the tradeoffs so you know which one to use.

Quick comparison

Method	Cost	Best for	What you get	Main downside
Manual browser extension	Free or cheap	10 to 50 businesses	Emails you can copy from websites	Slow, no owner names at scale, no verification
LocalProspects	Paid tool	Outreach-ready local lead lists	Emails, owner names, phone type, socials, website text, exports	Not free if you need volume
Apify Google Maps/email actors	Usage-based	Technical scraping workflows	Maps data, websites, phones, emails depending on the actor	More setup, less consistent enrichment

If you only need a few leads, use the free method.

If you need a real prospecting CSV, use LocalProspects.

If you are technical and want to build your own scraping pipeline, use Apify.

Method 1: Free manual lookup with an email extractor extension

This is the simplest way to get started.

Search Google Maps for your niche and location. For example:

• chiropractor near me
• plumber in San Diego
• med spa in Scottsdale
• roofing company in Tampa

Open each Google Business Profile, click through to the business website, and use a browser email extractor extension to detect email addresses on the page.

The basic flow looks like this:

1. Search the niche in Google Maps.
2. Open a business listing.
3. Visit the website from the listing.
4. Let the email extractor extension scan the page.
5. Copy any discovered email into your spreadsheet.
6. Check the Contact, About, Team, and footer pages if the homepage does not show anything.
7. Repeat for every business.

This works better than people expect for some niches. Medical offices, clinics, professional services, and local businesses that want inbound inquiries often publish an email somewhere on the site.

It works worse for businesses that only use forms, booking widgets, or call tracking numbers.

When the free method makes sense

Use this if you are building a tiny list or testing a niche.

For example, if you only need 20 chiropractors in one city, you can probably do it manually without hating your life too much.

The upside is obvious: it is free.

The downside is also obvious: it does not scale.

You still have to:

• open every website
• check multiple pages
• copy data by hand
• find owner names separately
• verify emails somewhere else
• clean the spreadsheet yourself

That is fine for a small test. It is not fine for a weekly lead generation workflow.

Method 2: Use LocalProspects

This is the method I use when I want a usable outreach list instead of a half-finished scrape.

LocalProspects starts with the same idea: search a niche and location from Google Business Profile data.

Then it does the extra work that normally eats your afternoon.

For each business, it can return fields like:

• business name
• website
• Google Business Profile URL
• phone number
• phone type, like mobile, landline, or VoIP when available
• owner or decision-maker name when found
• best email
• all discovered emails
• email verification status
• social profiles
• logo and profile image
• rating and review count
• services and business summary
• website page URLs and text
• CSV export fields for outreach

The important part is that it is not just grabbing an email from one page.

It crawls useful website pages, looks for contact details, tries to verify emails, pulls social links, classifies phone numbers, and keeps website text that you can use for personalization.

That matters because a lead list with only business_name, phone, and email still leaves you doing a lot of work.

A better lead list tells you:

• who you might contact
• whether the email is usable
• whether the phone number is likely a mobile or office line
• what the business actually does
• what their website says
• what you can reference in outreach

Why owner names are harder than emails

Emails are usually found with pattern matching. A scraper can scan page HTML and detect strings that look like email addresses.

Owner names are messier.

The site might say:

• "Founded by Jessica Miller in 2014"
• "Dr. Michael Reyes and his team..."
• "Owned and operated by the Peterson family"
• "Meet our founder, Alyssa Chen"

Or it might not say anything at all.

That is why owner-name extraction usually needs a combination of public sources and AI extraction from website text. It also needs restraint. Guessing an owner name from a domain or email address is worse than leaving the field blank.

For outreach, a blank owner field is annoying.

A wrong owner field is embarrassing.

Why LocalProspects is better for outreach

The biggest difference is that LocalProspects gives you more than contact info.

It gives you context.

For example, if you are doing cold email for a website or SEO offer, you can use the website text to write a better first line:

I noticed you have separate pages for prenatal chiropractic and sports injury care, but I could not find much location-specific content for San Diego.

That is much better than:

Hi, do you need more leads?

The first version requires data from the business website. A raw Google Maps export will not give you that.

Method 3: Use Apify

Apify is the more technical option.

Instead of one fixed lead tool, Apify is a platform with many scraping actors. Some actors scrape Google Maps. Some visit websites and extract contact details. Some can be chained together into a bigger workflow.

The rough process is:

1. Find a Google Maps email extractor or Google Maps scraper actor.
2. Enter your keyword and location.
3. Set a max result count.
4. Run the actor.
5. Export the dataset.
6. Clean the data.
7. Verify emails separately if the actor does not do it.
8. Add owner-name enrichment separately if you need it.

Apify can work well. In the video, the same chiropractor search returns similar basic business data and emails.

The tradeoff is that the output depends on the actor you choose and the settings you use.

In general, expect data like:

• business name
• address
• website
• phone
• rating
• reviews
• social profiles when found
• emails when found

But do not assume every actor will give you:

• owner names
• verified emails
• phone line type
• website page text
• a promoted "best email"
• clean outreach-ready CSV columns

You may be able to build that pipeline yourself. That is the point of Apify. It is flexible.

But if your goal is just "I need a lead list I can use today," flexibility can turn into extra work.

How to choose the right method

Use the manual method when:

• you only need a small list
• you have more time than budget
• you want to test whether a niche publishes emails
• you do not need owner names for every record

Use LocalProspects when:

• you need hundreds or thousands of local leads
• you care about owner names
• you care about email verification
• you want phone type for calling or SMS strategy
• you want social links and website text
• you want a CSV you can actually use for outreach

Use Apify when:

• you are technical
• you want API-driven scraping infrastructure
• you are comfortable testing actors
• you can handle verification, cleanup, and enrichment yourself
• you need a custom workflow instead of a productized lead list

What fields matter most in the final CSV

Do not judge a scraping method by whether it found one email.

Judge it by whether the final CSV can support your outreach workflow.

These are the columns I care about most:

Field	Why it matters
Business name	Needed for dedupe, CRM, and personalization
Website	Source for email, owner name, and context
Google Business Profile URL	Lets you verify the listing and review data
Owner name	Makes outreach feel less generic when accurate
Email	Main cold email field
Email status	Helps avoid bad bounce rates
Phone	Needed for calling and SMS workflows
Phone type	Mobile, landline, and VoIP should be treated differently
Social profiles	Useful for DM outreach and legitimacy checks
Website text	Useful for AI personalization and lead scoring
Rating and reviews	Helps prioritize stronger or weaker prospects

For cold email, the biggest mistake is sending to every scraped address without checking quality.

At minimum, separate:

• verified emails
• unverified emails
• catch-all emails
• role-based emails like info@ or support@
• free-provider emails like Gmail or Yahoo
• invalid emails

You do not need perfect data. You do need to know what kind of data you are sending to.

A simple workflow that works

Here is the practical version I would use:

1. Pick a niche and city.
2. Run a small test first.
3. Check the email fill rate.
4. Check the owner-name fill rate.
5. Inspect 20 random records manually.
6. Remove bad matches, franchises, and irrelevant businesses.
7. Keep only records with enough contact quality for your channel.
8. Use website text to write a specific first line.
9. Export into your CRM or sending tool.
10. Track replies by niche and city so you know what is actually working.

The manual method is good for step one testing.

LocalProspects is good when the test works and you want volume.

Apify is good when you want to build your own pipeline around the scrape.

Final recommendation

If you are doing this once for a tiny list, use a browser email extractor and a spreadsheet.

If you want a real outreach dataset with emails, owner names, phone type, social profiles, and website context, use LocalProspects.

If you want to engineer your own system, use Apify and be ready to handle the missing pieces yourself.

The scrape is not the hard part anymore.

The hard part is getting enough clean context to know who to contact, how to contact them, and what to say.