+5 Best Google Maps Reviews Scrapers in 2024 [No Code]
Want to quickly scrape reviews of a Google Maps place, but don't know which scraper to choose?
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.
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.
If it's possible to scrape reviews from Google Maps places, the question arises: why do that?
We've identified 2 main cases:
Let's take a closer look.
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.
Your online respectability is at stake!
That's what one of our German users suggests.
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:
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.
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.
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.
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.
If we go into detail, we need to respect 4 distinct principles:
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.
Make sure that the purpose of scraping meets a legitimate need.
✅ Collect reviews for your establishment ❌ Collect reviews of all French establishments
Only retrieve required data points. That enables you to achieve your goal. No more.
✅ Conserve the text content of a review ❌ Conserve user photo
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
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
Yes, completely!
There are 2 ways to scrape Google Maps Reviews with code.
The official API is interesting, but limited to the last 5 reviews available.
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.
Or use third-party APIs, developed by commercial companies. We recommend the SerpAPI API. It's price-competitive, and runs well.
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.
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.
One star in the Michelin guide, created in 1582 (!), has a dedicated Wikipedia page: we told you, it's a real celebrity.
We'll then judge each no-code scraper on 4 distinct criteria.
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.
The best Google Maps Reviews Scrapers:
And the summary table:
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.
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.
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.
The data scraped is exhaustive. 25 attributes in total, included all the advanced attributes: images, owner response, comment language.
Strong.
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.
0.05 USD / 1000 reviews
✨
230 reviews/minute
Apify is our second choice: the UX is fluid and communicative, and the scraper robust, as Apify is wont to build them.
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.
The tool also offers built-in GDPR functionality, to anonymize user names by default.
It's serious stuff, and it builds trust.
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.
Finally, data structure is very exhaustive. But not always easy to deal with for the average person. With JSON and JSON files everywhere...
0.10 USD / 1000 reviews
🔥
280 reviews / minute
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.
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.
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.
An important point: the speed is simply exceptional. The 2398 reviews are retrieved in 6 minutes 42, that's 350 reviews per minute (!!). Bravo!
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.
0.50 USD / 1000 reviews
🙏
350 reviews/minute 🚀
Outscraper offers a really nice tool: the UX is correct, the data structure exhaustive, and the speed correct.
Beware, it's too expensive.
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.
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.
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.
2 USD / 1000 reviews
💀
150 reviews / minute
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.
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.
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.
1.5 USD / 1000 reviews
110 reviews / minute 🐌
Co-founder @ lobstr.io since 2019. Genuine data avid and lowercase aesthetic observer. Ensure you get the hot data you need.