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In this post, we will learn to scrape Google Maps Reviews.

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## Requirements:

Before we begin, we have to install everything we may need in this tutorial to move forward.

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1\. [Node JS](https://nodejs.org/en/)

2\. [Unirest JS](https://www.npmjs.com/package/unirest)

3\. [Cheerio JS](https://www.npmjs.com/package/cheerio)

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So before starting, we have to ensure that we have set up our Node JS project and installed both the packages - Unirest JS and Cheerio JS. You can install both packages from the above link.

We will use Unirest JS for extracting our raw HTML data and Cheerio JS for parsing our extracted HTML data.

## Target:

 ![](https://cdn.hackernoon.com/images/-kya3oii.png)!\[Eiffel Tower Google Maps Results\](./posters/Eiffel Tower Google Maps Result.png)

We will target to scrape the user reviews on Eiffel Tower.

## Process:

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Now, we have set up all the things needed to prepare our scraper. We will use an npm library Unirest JS to make a get request to our target URL so we can get our raw HTML data. Then we will use Cheerio JS for parsing the extracted raw HTML data. We will target this type of URL:

```
https://www.google.com/async/reviewDialog?hl=en_us&async=feature_id:${data_ID},next_page_token:${next_page_token},sort_by:qualityScore,start_index:,associated_topic:,_fmt:pc
```

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Where,

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`data_ID` - It will uniquely identify a place in Google Maps.

`next_page_token` - The next_page_token is used to get the results of a page coming immediately after the first page.

`sort_by` - It is used for sorting and filtering results.

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The various values of sort_by are:

1\. `qualityScore` - the most relevant reviews.

2\. `newestFirst` - the most recent reviews.

3\. `ratingHigh` - the highest rating reviews.

4\. `ratingLow` - the lowest rating reviews.

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Now, how do we get the Data ID of any place?

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 ![](https://cdn.hackernoon.com/images/-g7j3oqf.png)

```
https://www.google.com/maps/place/Eiffel+Tower/@48.8583701,2.2922926,17z/data=!4m7!3m6!1s0x47e66e2964e34e2d:0x8ddca9ee380ef7e0!8m2!3d48.8583701!4d2.2944813!9m1!1b1
```

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You can see in the URL that Data ID is the part after `!4m7!3m6!1s` and before `!8m2!`.

So, our data ID in this case is - `0x47e66e2964e34e2d:0x8ddca9ee380ef7e0` . Our target URL should look like this:

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```
https://www.google.com/async/reviewDialog?hl=en_us&async=feature_id:0x47e66e2964e34e2d:0x8ddca9ee380ef7e0,next_page_token:,sort_by:qualityScore,start_index:,associated_topic:,_fmt:pc
```

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Copy this URL in your browser and press enter. You will see a text file downloading in your browser by entering this URL. Open this file in your respective code editor. Convert it into a `.html` file. After opening the HTML file, we will search for the HTML tags of the elements we want in our response.

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We will first parse the location information of the place, which consists of the location name, address, average rating, and total reviews.

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 ![](https://cdn.hackernoon.com/images/-p3c3o9k.png)

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From the above image, we get the tag for our location name as `.P5Bobd`, tag for our address as `.T6pBCe`, tag for our average rating as `span.Aq14fc` and tag for our total number of reviews as `span.z5jxId`.

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All done for the location information part, we will now move towards parsing Data ID and next_page_token.

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Search for the tag `.lcorif`. In the above image, we can find the class name `.lcorif` in the second line. Under this tag, we have our class name for Data ID  `.loris` and of next_page_token as `.gws-localreviews__general-reviews-block`.

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Now, we will search for the tags which contain data about the user and his review. Search for the tag `.gws-localreviews__google-review`.

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 ![](https://cdn.hackernoon.com/images/-3cd3oah.png)

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This tag contains all information about the user and his reviews. We will parse the extracted HTML for the user's name, link, thumbnail, number of reviews, rating, review description, and the images posted by the user.

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All the above things make our whole code look like this:

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 ![](https://cdn.hackernoon.com/images/-1xe3ofj.png)

You can copy this code by clicking on this link: [Scrape Google Maps Reviews](https://github.com/Darshan972/GoogleScrapingBlogs/blob/main/GoogleMapsReviewsScraper.js)

## Result:

 ![](https://cdn.hackernoon.com/images/-tmg3oe3.png)

Our result should look like this 👆🏻. These are the results of the first ten reviews. If you want to get another 10 put the token, which we have found in our code, in the below URL:

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```
`https://www.google.com/async/reviewDialog?hl=en_us&async=feature_id:0x47e66e2964e34e2d:0x8ddca9ee380ef7e0,next_page_token:tokenFromResponse,sort_by:qualityScore,start_index:,associated_topic:,_fmt:pc`
```

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In this case, we have our token as `CAESBkVnSUlDZw==` . You can find the reviews for every next page using the token we got from their previous pages.

## Result:

 ![](https://cdn.hackernoon.com/images/-wei3orm.png)

## Conclusion:

In this tutorial, we learned how to scrape Google Maps Reviews. Feel free to ask me anything in the comments. Follow me on [Twitter](https://twitter.com/serpdogAPI). Thanks for reading!

## Additional Resources:

[Scrape Google News Results](https://dev.to/darshan0_1/scrape-google-news-results-1je4)

[Scrape Google Images Results](https://hackernoon.com/scrape-google-images-with-node-js)

[Scrape Google Autocomplete Suggestions Results](https://dev.to/darshan0_1/scrape-google-autocomplete-suggestions-1mak)

[Web Scraping Google With Node JS - A Complete Guide](https://serpdog.io/blog/web-scraping-google-with-node-js)

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***Also published [here](https://dev.to/darshan0_1/how-to-scrape-google-maps-reviews-26ob).***

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