How to Master Customer Insights Using Google Maps Review Scraping Guide
Table of Contents
Introduction to Google Maps Reviews Scraper
As a business owner, have you ever wondered how some businesses seem to know exactly what their customers want, even before they walk through any business or establishment? It’s intriguing indeed, but here’s a clue: They’re not guessing; they’re listening to what people are saying online. Where do they go to get this information? The answer is simple: Google Maps reviews.
Scrape all the reviews from Google Maps into a CSV/Excel/JSON file. Only 6 minutes to get started.
With Google Maps, every time someone leaves a review, they’re sharing firsthand insights about what works, what doesn’t, and what keeps them coming back to the business. For savvy business or business owners, these reviews aren’t just feedback-they’re a roadmap to growth. By tapping Google Maps review data, companies can track customer preferences, spot emerging trends, and fine-tune their services. But with these data, it will lead to the big question: how exactly can they access and analyze this data at scale?
In this Google Maps Reviews Scraper guide, we will dive deeper and explore whether it’s possible to gather this information efficiently, the legal and ethical considerations involved, and the best tools and techniques available.
Did you know that Google Maps accounts for 59% of all online reviews, surpassing dominant social media platform Facebook, directory site Yelp, and TripAdvisor combined? Google Maps boasts over 1 billion active users, making it the primary source for local business information.
One of the biggest challenges businesses face with Google Maps reviews is accessing this wealth of data in a way that is both efficient and compliant with legal guidelines. Google Maps reviews are loaded with valuable insights and real opinions from customer’s experiences, but manually gathering, sorting, and analyzing this information is time-consuming and impractical.
Moreover, Google’s Strict Terms of Service create a barrier for automated data extraction methods, often limiting scraping and the risks of being banned or having legal repercussions. This is challenging for companies who want to expand and top into Google Maps reviews responsively and effectively. We will discuss how to solve this problem and the other challenges with Google Maps review scraping.
Google Maps Reviews Statistics 2024
- Google Maps surpassed 2 billion monthly active users according to the announcement made by Google CEO Sundar Pichai in Alphabet’s Q3 2024 earnings.
- Google Maps has more than 150 million local reviews and ratings. (Source: Worldmetrics.org)
- Google Maps was the third most downloaded Google app worldwide with 11.9 million downloads as of July 2024. (Source: Statista)
- 93% of consumers say reviews play a role in their purchasing decisions (Source: Podium)
- The average consumer reads 10 reviews before trusting a business (Source: BrightLocal)
- Businesses with more than 40 reviews generate 12x more leads than those with no reviews (Source: ReviewTrackers)
- Positive reviews encourage customers to spend 31% more (Source: EmbedSocial)
- 89% of users read online reviews before buying the product (Source: RankoMedia)
Scrape all the reviews from Google Maps into a CSV/Excel/JSON file. Only 6 minutes to get started.
Can you Scrape Google Maps Reviews?
The answer is Yes, scraping Google Maps reviews is technically possible, but realistically speaking, it raises both curiosity and caution. For businesses, data analysts, and developers, these reviews are more than just feedback—they’re a strategic asset, offering a glimpse into customer sentiment, market trends, and competitive insights that traditional data sources often miss.
Having access to real, unfiltered opinions on everything from product quality to customer service is very important for all businesses and business owners. This can mean spotting gaps in service, understanding customer pain points, and adapting strategies based on authentic and real-time feedback. For data analysts and developers, Google Maps reviews provide a unique dataset that can power predictive models, sentiment analysis, and user behavior insights, transforming how a business understands and interacts with its customers.
Despite all the benefits of scraping Google Maps reviews, many wonder why scraping is worth the risk or effort. Gathering reviews manually and analyzing such vast amounts of data can be overwhelming and prone to error. This is where Google Maps scraping shines, there are many available service providers for this one, but Outscraper’s Google Maps Review scraper is one of the most recommended tools in the market today.
Google Maps reviews scraper by Outscraper allows you to collect, organize, and analyze review data at scale—faster and more precisely than ever. While legal and ethical considerations must guide the process, the benefits of efficiently gathered, richly detailed data are hard to ignore for those aiming to stay ahead of the competition.
Best Tools for Scraping Google Maps Reviews
There are many tools available online if you prefer scraping tools that simplify the process, these platforms specialize in Google Maps reviews but let us dig deeper into their capabilities.
- Outscraper: Outscraper’s Google Maps Scraper tool is a user-friendly web scraper that is specifically designed for estraxting review data from Google Maps and other popular review websites. It offers a streamlined way to gather information like review ratings, text, and timestamps, making it easy for non-technical users to access reviews. One of their strength is their capability to handle IP-blocking because their servers are hosted in the cloud. Outscraper also offers API for review scraping if you have some background in coding.
- Apify: Apify offers flexible and customizable scraping options, allowing users to create tailored workflows for collecting reviews. With prebuilt Google Maps integrations, Apify is well-suited for users looking to integrate data collection seamlessly into other systems.
- ParseHub: ParseHub is a no-code tool with a point-and-click setup, perfect for beginners. It allows you to select and extract review data from Google Maps visually, enabling non-coders to gather data efficiently.
Scraping Google Maps Reviews with Python
For those comfortable with coding, Python provides a versatile option to scrape Google Maps reviews. By using the Google Places API or libraries like BeautifulSoup and Selenium, developers can automate the data collection process. You can read our comprehensive guide on how to Scrape Google Maps data using Selenium to understand the process better.
API Docs
Use the data from your app. Check out the API Docs to see code examples.
Scrape all the reviews from Google Maps into a CSV/Excel/JSON file. Only 6 minutes to get started.
How to Use Outscraper’s Google Maps Reviews Scraper
- Sign up or log in with your Outscraper account to use one of Outscraper’s most popular scraping tools, Google Maps Review Scraper.
- Go to your Outscraper’s account dashboard, click the Services Tab, and next select “By Brand,” followed by “Google,” and “Google Maps Reviews Scraper.” You can also proceed by clicking this link directly.
- If you select the Categories or brand search you need to specify the Locations by selecting the Country and State or City. For Plain queries search the location should be included in your search query (category + city or zip + country), URLs, Google or Places IDs. You can use anything that will work on Google Maps.
- After selecting the location, you will proceed to Sorting, there are four different sorting parameters you can use to get the results you want. The sorting options include “Most relevant, Newest, Highest rating, and Lowest rating.”
- There is also an option in the Sorting section wherein you can tick the checkmark and the date option will appear. You can select the date of your choice from when the reviews were made and if you check the Relative option, the estimated number of days or months will appear. You will have an option also to tick the “To” option and select the latest or newest date when the reviews were taken.
- In checking the limits, there are parameters you should consider, Reviews Limit per place, and Places per one query search. The Reviews limit per one place specifies the limit of reviews to extract per one place. You should put a number because “0” means unlimited. In the Places per One query search option, you can use “1” to find a specific place (e.g. Central Park, NY, US). However, when you’re searching for `restaurants, NY, USA` you might want to extract all the places from your search and use `500`.
- For the Advanced Parameters, you can select the language to use. There’s an additional option for the Reviews query search for a specific keyword such as “Amazing or great.” An option to Ignore reviews without text can be selected as well. The other parameters include the result extension to use such as CSV, XLSX, JSON, or PARQUET. The task tags should be added also for your reference.
- You can also select enrichment options or the columns to return if you want a specific column such as query, name, google id, place id, location link, reviews link, and other parameters. If you want to return all, leave it empty.
- Run the task by clicking the Export Reviews button and confirm your task and a pop-up will appear for the estimated number of hours for the task to be done and the rough estimate of usage as well as the rough cost of the task. Just click the Confirm button and let Outscraper do the rest. You can then proceed to the Task options and download the reviews once the task is completed.
Reviews Data Dictionary
Columns names and descriptions for Google Reviews.
- name – name of the place on Google Maps.
- google_id – unique identifier of the place.
- location_link – link to the place.
- reviews_link – link to the place reviews.
- reviews_per_score – JSON object with scores and the number of reviews per each score.
- rating – rating of the review.
- review_id – unique identifier of the review.
- author_link – link to author’s profile on Google Maps.
- author_title – title of the author’s profile page.
- author_id – unique identifier of the author.
- author_image – image link from the author’s profile page.
- author_reviews_count – number of total reviews left by the author.
- author_ratings_count – author’s ratings.
- review_text – text of the review (if exists).
- review_img_url – image link from the review (if exists).
- owner_answer – text of the owner replay (if exists).
- owner_answer_timestamp – timestamp value when owner replied (if exists).
- owner_answer_timestamp_datetime_utc – datetime value when owner replied (if exists).
- review_link – link to the review.
- review_rating – rating of the review.
- review_timestamp – timestamp value when review created.
- review_datetime_utc – datetime value when review created.
- review_likes – amount of the review’s likes.
- reviews_id – unique identifier of the place’s reviews.
Conclusion
Google Maps reviews are valuable resources for businesses, offering insights into customer satisfaction and service quality. By analyzing these reviews, businesses can identify what’s working, spot areas for improvement, and adjust their business strategies to meet customer expectations and get real feedback. However, collecting this data manually is challenging, especially with Google’s restrictions on automated scraping.
Outscraper, with its advanced technology and cloud-based scraping methods, bypasses these limitations, making it one of the most reliable tools for gathering Google Maps review data at scale. Simply input the location’s URL, and Outscraper’s systems handle the rest, gathering data such as review text, star ratings, reviewer names, and response timestamps quickly and accurately. The cloud infrastructure also helps avoid IP blocks and maintains uninterrupted access to the reviews.
Additionally, Outscraper allows users to sort reviews by relevance, rating, or date and offers flexible formats like CSV and Excel for easy data analysis. With Outscraper’s capabilities, businesses can access crucial review insights efficiently and stay ahead of competitors by basing decisions on real customer feedback—all without worrying about Google’s scraping restrictions.
Video Tutorial
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FAQ
Most frequent questions and answers
Google Maps reviews scraping, harvesting, or extracting is a process of getting business reviews from the Google Maps site. It automates manual exporting of the reviews.
Scraping and extracting of public data is protected by the First Amendment of the United States Constitution.
Yes. You can scrape all the reviews from Google Maps by using Google Maps reviews scraper.
- Login to Google Maps reviews scraper.
- Insert the link to Google Maps place that you want to extract reviews from.
- Select language and check other advanced parameters.
- Click “Scrape reviews”.
You can use google-services-api package to scrape the reviews in your python code.
No. All scraping activities occur on Outscraper servers, ensuring that your IP address is not utilized for data scraping. It also means your computer can be turned off when extraction tasks are running.