You want leads, I want leads.

Everyone wants qualified realtime leads.

That's why we're going to dig down into two powerful Google Maps scraping tools meeting this criteria: Serper.dev and Scrap.io. Let's break it down, shall we?

Table of Contents

Understanding Serper.dev: The Developer's Choice

Let's start with Serper.dev. As its suffix shows, it's a lead generation tool mainly created for developers allowing us to scalably use Google API. I said API. I should rather have said APIs. Actually, you can find the full list of official APIs on console.cloud.google.com and you literally have access to hundreds of them.

Of course, on Serper.dev, they had to make a choice and pick up only the most useful ones. Among them, we can find Google search, images, videos, places, maps, reviews, news, shopping, image search, scholar, patents, autocomplete, and web page.

Why Google Maps for Lead Generation?

So if we want to gather leads, we might use Google search, but it's not the most obvious option we have. Something which is more relevant is Google Maps data scraping because on Google Maps, we can find any small and medium-sized businesses. This is a perfect option to go.

But first things first, let's create a Python project. We call it "serper dev."

Setting Up Your First Query

We have our query meaning we are proceeding the same way as when we are making a normal Google search. For example, if I type "real estate agency New York" here is my query and here is my result. So let's come back to our playground - here is my query and it has been changed the GPS position and zoom level.

That one is a bit more tricky. Every time I move my cursor, every time I'm showing another location, the URL changes a little bit. Have you noticed it? Right, this part has changed. And this is where the coordinates are located, the same as with the zoom level.

We always start with the latitude followed by the longitude. And finally, the zoom level is followed by the letter Z. So here is my new parameter. Let's come back. Here we go. Language, English. Okay. And the number of pages. And we are good to go. Let's click on search.

Data Fields You Get with Serper.dev

And for each and every one of our leads, we have the following data fields: the position, the title, the address, the latitude, the longitude, the rating, the rating count, the type, and the types.

Because on Google Maps, every business is linked to a single main type, but also, and this is optional, with up to nine subtypes. For example, you can be a male or a female. That's your main type. Fortunately, other specificities can define you: your job, location, marital status, which can be considered your subtypes. They are things you can't really see at first glance, but they remain important nonetheless.

The website, the phone numbers, the opening hours, the thumbnail URL, CID, FID, and place ID. If you want to learn more about extracting phone numbers specifically, check out our comprehensive guide on how to scrape phone numbers on Google Maps.

Moving from Playground to Python Script

Now, once we are aware of this that the code is working, maybe we can copy and paste it on a Python script to see if we can scale things up. What about this?

But as I've said, I'm not super comfortable with coding. And by not comfortable, I mean I really suck. Which is why in these cases, what I'm usually doing is using Claude.AI. Generally speaking, Claude does a better job than ChatGPT when it comes to coding.

But first, let's see if that works. I can copy it. Let's install the request model. Of course, pip install request, rerun main and we have our results.

Exporting Your Data

We might want to download it somewhere to store it somewhere. Probably a JSON file will do, but it's not extremely readable for human beings. For this reason, I will go for CSV file.

What I've done is collect the data fields which were already in JSON format and I've pasted the whole result into code along with the following prompt: "Here are the data fields for one item. Make sure to download the result in a CSV file containing all columns."

I come back to my Python script and I paste the updated version. I have to install the model pandas of course. PIP install pandas and the file has been downloaded. Let's check it out now. How many leads do we have? 20 as expected with the following columns which were the same ones as in the JSON file. Okay.

The Scalability Challenge

Now one question remains. How do we make sure to scale our request? For those who don't know what's behind the word scalability, scalability is the idea that we can get 100,000 leads just as easily as getting 100 leads. It's like if I promised you that running a 100-meter race would be just as simple as running a marathon. That's not an obvious statement, is it?

Because we are able to extract results by batch of 20. But we won't get really far with it. So how do we make sure - how do we change our code in order to extract multiple pages at once and we can even go further. How do you make multiple requests at once?

Scaling Variables and Locations

For now we are only focused on real estate lead generation in New York City. Real estate agency is one Google Maps category, one among thousands. In other words, we can scale our lead generation by changing that variable by making it not static but dynamic. If you're specifically targeting real estate professionals, our real estate agency email lists guide provides detailed strategies for this sector.

But that's not all. We can also adjust the location. New York is not the only US city after all. So, we can perfectly set up a dynamic variable for that too.

Wait, slow down. That might not be that simple. Take a closer look at the location. It's actually a mix of different factors. The word "near" never changes. It's followed by a city. Let's make it a dynamic variable followed by the related state and wrapped up with the country.

All that to say that you can make an insane number of combinations. Unfortunately, complexity increases a bit.

Enter Scrap.io: Simplicity at Its Best

But before jumping into it, let's make an introduction regarding Scrap.io. It's not a Google Maps scraping tool created for developers. It's a tool created for everyone to the point that even my cat or my 90-year-old sick grandmother are able to use it.

Unlike many competitors in the market, Scrap.io stands out as a superior alternative. If you're comparing different tools, you might find our OutScraper alternative comparison or our LeadStal vs Scrap.io analysis helpful for making an informed decision.

The User-Friendly Interface

So once I've logged in, you end up with this playground. And this playground is much easier because you don't have any code to write, any code to test. Instead, you have an activity to insert among the 4,000+ we have talked about.

And you have location criteria: country, level one division. If we pick up the case of the US, level one division refers to the states and level two division to the counties. I can also pick up a city.

Something random... Rambling. I hope I do not massacre the name. And the point is that I don't have to specify an activity if I don't need to because if I click on search right now, I will get all activities, meaning all Google Maps categories in Rambling. For a complete guide on extracting all businesses from any location, check out our tutorial on how to extract all businesses from a city on Google Maps.

So, it seems it's not a super huge city, but that's okay because I can change my request in just 30 seconds.

Setting Up Your Search

Let's pick up real estate agency in New York or I can even say New York here, New York county. And in the US, the level one division is required when searching the level two division. So I have to pick up the state related to New York, which I'm not sure what that is. It's New York. Okay, makes sense.

So with that, I'm able to get a database related to a state.

Advanced Filtering Options

You can also filter your results. I only want to get opened businesses with an email address and at least 10 reviews. If I click on filter, well, the filters will be applied.

Now, that's not all. You have something at the top of your screen, which is your exports tab. And as its name suggests, you have access to all the exports you have done so far. So here I've only extracted a sample of 30 data rows from which I can take a look in a CSV or Excel file.

Side-by-Side Comparison: The Results

So now we can make a side-by-side comparison. So this is a file from Serper.dev and this is a file from Scrap.io.

The Data Difference

By the way, you can get up to 70 different columns. So what's best is that if you want to check them all out, you can find a link in the description in which you will find a sample.

But among the most useful columns you can find of course the name, the main type and all types, a website, a phone number, the IDs, the email address, social media links, reviews, review-score related data, additional email addresses, additional contact pages, additional social media links and wraps the whole thing with website technologies and website ad pixels.

Back to Scalability: Serper.dev's Approach

Now let's come back to our previous concern. We were discussing the scalability concerning Serper.dev. We have said we have multiple ways of scaling things up. Among other things, we can create a dynamic variable for the category or for the location.

But before doing all of these things, we can make sure to fetch more pages. So let's see what the code looks like. If I increase the number of pages, I have a new parameter. So I copy that example.

I come back to code and I paste my code alongside the following prompt: "Adjust the code by including the parameter page. Make sure to fetch 10 pages. Let's start slowly for first attempt. For each page, the value increases by one. So stop the loop after 10 repetitions."

And let's verify the script until we reach page 10 out of 10. So we should get 200 results. And we have 200 results. So again that's one way of doing it.

Of course we can also scale it by changing our variables. We have talked about that previously. Actually we have made an entire video about the topic about how to scrape data from Google Maps at scale. For a comprehensive overview of all available methods, check out our complete Google Maps scraping guide.

The Simple vs Easy Dilemma

Now the whole process seems to be simple but simple is not equal to easy. And the point is that everything I have done previously I can do the very same thing using Scrap.io with just a couple of clicks.

Scrap.io's Effortless Scaling

Real estate agencies in the US. I click on search. I have about a lot of results. So, of course, I won't export it right now because it will take quite a lot of time.

So, let's check it out if I've already have a file containing a lot of results, a lot of data rows. And here is something: restaurants in the US with a Facebook account. 200,000 leads. Not bad. Look at this. They're all there.

For businesses looking to automate their lead generation process even further, our complete CRM automation guide shows how to automatically enrich your CRM with Google Maps data, while our Make.com tutorial demonstrates how to build a no-code automated lead generation system.

FAQ: Google Maps Scraping Tools

What is the best tool to scrape data from Google Maps?

The best Google Maps scraper depends on your technical skills and needs. For developers who want full control and customization, Serper.dev offers powerful API access with coding flexibility. For non-technical users who need results quickly, Scrap.io provides an intuitive no-code solution that can extract data from entire countries with just a few clicks. For more tool comparisons, see our detailed Octoparse vs Scrap.io comparison and our comprehensive PhantomBuster alternative guide.

Is scraping Google Maps legal?

Scraping Google Maps is generally legal when you focus on publicly available business information that's accessible to anyone visiting the platform. However, it's important to respect Google's Terms of Service, use reasonable request rates, and focus on public business data rather than personal information. Both Serper.dev and Scrap.io operate within legal frameworks by accessing publicly available data.

How do I scrape data off Google Maps?

There are several methods to extract data from Google Maps:

  1. Developer approach: Use APIs like Serper.dev with Python scripting for maximum customization
  2. No-code approach: Use tools like Scrap.io for instant results without programming
  3. Chrome extensions: Use browser extensions for small-scale extraction - check our top Chrome extensions guide
  4. Official Google Places API: For structured access with usage limits - see our API cost calculator comparison

Which approach is better for beginners: coding or no-code?

For beginners, no-code Google Maps scraping tools like Scrap.io offer the best starting point. You can start generating leads immediately without learning programming languages, setting up development environments, or handling technical complexities. The learning curve is minimal, and you get professional results in minutes rather than hours.

What data can you extract from Google Maps?

Modern Google Maps scraping tools can extract comprehensive business data including:

  • Business names, addresses, and phone numbers
  • Email addresses and website URLs
  • Social media profiles (Facebook, Instagram, LinkedIn, etc.)
  • Customer reviews and ratings
  • Opening hours and business categories
  • Geographic coordinates (latitude/longitude) - learn more in our coordinates extraction guide
  • Photos and business descriptions
  • Website technologies and tracking pixels

How many leads can I generate with these tools?

The scale depends on your chosen tool:

  • Serper.dev: Limited by API quotas and coding complexity, typically hundreds to thousands per session
  • Scrap.io: Can extract data from entire countries (potentially millions of businesses) with advanced filtering options to ensure you only pay for qualified leads. Check our complete filtering guide for optimization tips

The Bottom Line

So, if you want to get your leads without spending 30 minutes on it, you can get your first 100 leads from Scrap.io totally offered.

The choice is yours: spend hours coding and debugging with Serper.dev, or get the same results (and more) with just a few clicks using Scrap.io.

Both lead generation tools have their place, but when it comes to efficiency and ease of use, there's a clear winner for most businesses looking to scale their local business leads generation efforts quickly and effectively.

For those who want to take their lead generation to the next level, consider integrating AI-powered email personalization into your campaigns, or explore our free Maps Connect Chrome extension that shows emails and social media directly on Google Maps.