+5 Best Google Maps Reviews Scrapers in 2024 [No Code]

Sasha Bouloudnine
February 22, 2024
12 min read

Want to quickly scrape reviews of a Google Maps place, but don't know which scraper to choose?

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In this article, we're going to review the 5 best Google Maps Reviews Scrapers no-code.

Without having to write a single line of code. Just robust, just no code tools. Let's go.

What is a Google Maps Reviews Scraper?

A Google Maps Reviews Scraper is a tool that will scrape automatically all the reviews of a Google Maps local business.

It is also called automation or an extractor or a web scraper.

As input, you give it the URL of a Google Maps establishment. The robot starts, browses the web, extracts data. And returns it to you in a structured, comprehensive CSV file or Excel file.

If you need a dedicated step-by-step tutorial, check our dedicated article available here.

This saves you a considerable amount of time. And you rely on quality data sets.

google maps reviews scraper before after - image3.png

Why scrape reviews from Google Maps?

If it's possible to scrape reviews from Google Maps places, the question arises: why do that?

We've identified 2 main cases:

  1. Preserve your brand image
  2. Identify opportunities

Let's take a closer look.

Preserving your brand image

The first use case is to preserve your brand image from the impact of disgruntled user reviews.

With web scraping, retrieve user reviews of your local businesses at regular intervals. And identify negative ones.

Once you've identified unflattering reviews, you can respond to them.

google maps review response from the owner - image20.png

Your online respectability is at stake!

That's what one of our German users suggests.

google maps reviews scraper usecase user chat lobstr - image24.png

Identifying opportunities

How can reviews be used to identify opportunities?

Well, it's simple: first collect reviews data, especially negative ones. Then, identify the needs in a given market that are not being met by existing services.

Armed with this information, you can develop a business that meets these needs. And make some dough.

Google Maps data scraping is an advanced bottom-up market research strategy.

Data extraction provides valuable insights, and unlocks real value making opportunities.

That's what @PierreDeWulf, co-founder of scrapingbee, tells us in a tweet of August 13, 2021:

pierre de wulf twitter screenshot how to get a business idea read review - image21.png

Thank you Pierre, if you pass by we salute you warmly.

If you check the Google Maps legal disclaimer, you'll notice that Google isn't too keen on scraping.

The online indexing giant just doesn't like it.

google maps terms of use scraping - image5.png

So do you have the right to retrieve this data with a scraping tool?

Well, yes, entirely. Google Maps reviews are public data, publicly accessible.

As such, they don't belong to Google or anyone else. You can scrape them as often as you like. Period.

This was repeated by the Ninth Circuit on April 18, 2022, in the case pitting LinkedIn against Hiq Labs.

techchrunch scraping legal screenshot - image27.png

What about the GDPR?

Recovering public data, OK. But this is personal data that can be used to identify individuals. Briefly, yes, but still.

And if you live in Europe, you know that you need to treat this data with particular vigilance.

As suggested by the CNIL, the French data protection agency, a username or a photo is considered personal data.

cnil what is personal data - image30.png

Is it legal to scrape and store this data?

Well, yes, absolutely! But only under certain conditions.

To put it simply, you have to inform people that you have their personal data (impossible in this case). And above all delete the data once whatever has been done is finished.

Thanks to ThunderEcho21 for this Reddit thread on ExplainLikeImFive.

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If we go into detail, we need to respect 4 distinct principles:

  1. Purpose principle
  2. Principle of proportionality
  3. Retention limit principle
  4. Security principle

To find out more, feel free to consult the CNIL's dedicated article on the subject.

Let's take a closer look, in the case of someone monitoring his place's negative reviews.

Purpose principle

Make sure that the purpose of scraping meets a legitimate need.

✅ Collect reviews for your establishment ❌ Collect reviews of all French establishments

Principle of proportionality

Only retrieve required data points. That enables you to achieve your goal. No more.

✅ Conserve the text content of a review ❌ Conserve user photo

Retention limit principle

Keep data only for the time you need to achieve your goal.

✅ Keep negative review until response is given ❌ Conserve negative review 6 years after answer is given

Security principle

Limit access to the file. Make sure the file is only accessible to those who need it.

✅ Make the file read-only ❌ Make the file available to everyone

Can I scrape Google Maps Reviews with code?

Yes, completely!

There are 2 ways to scrape Google Maps Reviews with code.

  1. Official Google Maps API
  2. Scraping libraries

The official API is interesting, but limited to the last 5 reviews available.

google reviews from api limited stackoverflow - image7.png

We don't recommend this solution.

You can, however, use scraping libraries, usually written in Python or Javascript.

You can either use an open source library on Github, independently maintained. It costs nothing, but beware, it doesn't always work. For adventurers only.

google maps reviews scraper github open source library - image23.png

Or use third-party APIs, developed by commercial companies. We recommend the SerpAPI API. It's price-competitive, and runs well.

google maps reviews api serpapi - image19.png

However, you need to know how to code. And even with ChatGPT, it's a skill that only a handful of people in the world know how to do.

So in the rest of this article, we'll be looking at the best tool for scraping reviews from Google Maps. At scale. Without a single line of code.

How will the different no-code scrapers be tested?

We're going to subject each scraper to the same standardized test.

Retrieve 2399 reviews of la Tour d'Argent: mythical, world-famous Parisian gourmet restaurant.

la tour d argent total reviews google maps - image36.png

One star in the Michelin guide, created in 1582 (!), has a dedicated Wikipedia page: we told you, it's a real celebrity.

la tour d argent wikipedia page - image28.png

We'll then judge each no-code scraper on 4 distinct criteria.

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Ease of use

Ease of use is the ease with which the user will use the tool.

We'll take into account: the position of buttons, the usefulness of tooltips, the functional display.

Or to put it simply: whether we can get to our goal easily by clicking here and there. We'll take it out of 5.

Speed

How many reviews are collected per minute. A simple, standardized quantitative value.

Price

How much USD for 1000 reviews collected. Again, a simple quantitative value.

Data completeness

How many attributes are collected by each no-code scraper. And how well critical attributes are retrieved.

Here too, we'll take a mark out of 5.

What are the best Google Maps Reviews Scrapers?

The best Google Maps Reviews Scrapers:

  1. Lobstr.io
  2. Apify
  3. Scrape-it
  4. Outscraper
  5. Scrapehero

And the summary table:

best google maps reviews scraper table - image32.png

1. Lobstr.io

Lobstr.io is quite simply the best Google Maps Reviews Scraper on the market.

It's pretty, it works well, it's fast, and the price is ultra-competitive. What the people want.

google maps reviews scraper lobstr io product page - image16.png

Of course, you can say that we're the judge and jury. But on transparent and simple criteria: the scraper is simply the best.

Firstly, the interface is user-friendly, and the UX is clear and intuitive.

Once the scraper is launched, we're not left alone in front of a blank screen as we often are. But with an interface that gives us information about what's going on.

google maps reviews scraper console lobstr - image34.png

The scraper is also one of the fastest. The restaurant's 2398 reviews will be retrieved in 10:35, a solid 230 reviews per minute.

google maps reviews scraper lobstr speed - image26.png

The data scraped is exhaustive. 25 attributes in total, included all the advanced attributes: images, owner response, comment language.

Strong.

google maps reviews scraper lobstr results table - image25.png

Last but not least, the price is the most competitive on the market. First of all, the free plan is extremely generous, with ~3500 reviews per day free every day.

Above all, the first plan at 50 EUR per month gives about 1242K reviews per month. That's a lot of reviews.

And it refers to the extremely competitive price of 0.05 USD per 1000 reviews. Unbeatable.

google maps reviews scraper lobstr pricing - image4.png

Price

0.05 USD / 1000 reviews

Speed

230 reviews/minute

Pros

  1. Communicative and fluid interface
  2. Elegant design
  3. 230 reviews per minute
  4. 0.05 USD per 1000 reviews (!!)
  5. 25+ attributes with advanced attributes
  6. Extremely generous free plan
  7. All languages
  8. Different sorting logics

Cons

  1. Pricing measured in minutes per day not obvious

2. Apify

Apify is our second choice: the UX is fluid and communicative, and the scraper robust, as Apify is wont to build them.

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First of all, the UX is pleasant and communicative.

You know when the scraper is launched, where it is in the collection, and a priori how long it will take to finish.

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The tool also offers built-in GDPR functionality, to anonymize user names by default.

It's serious stuff, and it builds trust.

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The tool is particularly fast. All reviews are retrieved in 8 minutes 27, i.e. 280 reviews/minute.

Above all, it’s 2x more expensive than Lobstr, but the price is really competitive. Exactly 0.25 USD for all reviews, or 0.10 USD per 1000 reviews.

Clear and very competitive.

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Finally, data structure is very exhaustive. But not always easy to deal with for the average person. With JSON and JSON files everywhere...

google maps reviews scraper apify results table - image18.png

Price

0.10 USD / 1000 reviews

🔥

Speed

280 reviews / minute

Pros

  1. Fluid, communicative UX
  2. 280 reviews per minute
  3. 0.10 USD per 1000 reviews (!)
  4. Comprehensive data
  5. Clear pricing displayed directly

Cons

  1. Unclear Excel format
  2. Too much information on the console
  3. JSON format too complex

3. Scrape-it

The Google Maps Reviews Scraper from Scrape-it is really fast, and the price is right! Beware: the data structure is not up to scratch.

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The UX is a little sketchy, but has the merit of being simple and clear.

You know where to put the URL fields, and there aren't too many parameters to adjust.

Beware, however, how to retrieve all reviews of a local place? It’s not clear. And there's a systematic delta of 10 credits that remains unexplained.

google maps reviews scraper scrape it strange ux - image8.png

The price is respectively 10x and 5x more expensive than Lobstr.io and Apify. But it remains pretty competitive. We pay 29 USD for 50,000 reviews, or 0.50 USD per 1,000.

The price is directly in dollars, and the credit system is clear.

scrape it pricing - image29.png

An important point: the speed is simply exceptional. The 2398 reviews are retrieved in 6 minutes 42, that's 350 reviews per minute (!!). Bravo!

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Please note, however, that the data structure is very basic. Essential elements are missing: the complete review text (!), the owner's response and the language of the commentary.

A shame.

Price

0.50 USD / 1000 reviews

🙏

Speed

350 reviews/minute 🚀

Pros

  1. Very fast
  2. Fair price
  3. Free plan with 1000 reviews

Cons

  1. Basic UX
  2. Data structure too incomplete

4. Outscraper

Outscraper offers a really nice tool: the UX is correct, the data structure exhaustive, and the speed correct.

Beware, it's too expensive.

google maps reviews scraper outscraper product page - image33.png

As always with Outscraper, the UX is functional. But it can't be said that it's neither beautiful nor self-explanatory.

There are a lot of fields, and it's not always clear what they're for.

google maps reviews scraper outscraper setup - image17.png

What's more, once you've started scraping, you have no idea what's going on. Number of reviews collected, time remaining, status: it's all a matter of guesswork.

For example, while we know what time we started the scrapbook, we don't know what time it finished.

outscraper console tasks - image11.png

Regarding speed, it's a bit slow. But still decent: the 2398 reviews are retrieved in 15 minutes, or 150 reviews per minute.

But the price is way too high: 2 USD for 1000 reviews, or almost 5 USD for 2400 reviews.

Too much is too much.

google maps reviews scraper outscraper cost - image6.png

Price

2 USD / 1000 reviews

💀

Speed

150 reviews / minute

Pros

  1. Comprehensive data
  2. Advanced collection parameters such as review language
  3. Correct UX

Cons

  1. Slow
  2. Overpriced

5. ScrapeHero

And unfortunately, we need one last one and here it is: ScrapeHero.

The UX is not crazy. Scraping is slow, we're not sure we'll get everything back, and it's quite expensive. Not the sharpest knife in the drawer.

google maps reviews scraper scrapehero product page - image31.png

First of all, the UX isn't crazy.

There are alerts everywhere: maybe we won't get all the reviews, and for hotels, we might need to contact another service. In short, the level of trust isn't great.

google maps reviews scraper scrapehero warning messages console - image14.png

The data structure is OK, but some important attributes are missing, such as the user response, or the list of images.

Scraping is... slow, very slow. We got all 2398 reviews (yes, we got them all!) in... 21 minutes 45. That's 110 reviews per minute. That's tough.

Finally, it costs USD 5 per 3,000 requests, which works out at around USD 1.5 per 1,000 reviews.

It's cheaper than Outscraper, but it's already too much for what it is.

Price

1.5 USD / 1000 reviews

Speed

110 reviews / minute 🐌

Pros

  1. Small 5 USD plan
  2. Correct UX

Cons

  1. Too slow
  2. Too expensive
  3. Too little data
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