How to Scrape Restaurants Data from Google | Google Map Restaurants Data Scraping

Launched in 2005, Google Maps has progressed a lot and gets different usages besides how to reach from point X to point Y. Its most general offerings include satellite imagery, real-time traffic maps, aerial photographs, as well as route planning through bikes, cars, public transport, etc. Although, it is heavily utilized to get local restaurants as well as find more regarding them. Scraping Google Maps data helps restaurants scrape food data.

Let’s assume that you have shifted to a new city and want to find a good restaurant nearby. The most general thing to do is typing the keyword “restaurants” in Google Maps as well as get the ones, which are within your budget as well as have maximum reviews. Google Maps also allow people to get the timing when a restaurant might be open as well as even allows one to edit data for any changes. All the data points together with valued customer reviews could prove to be extremely helpful in case, one can gather data properly as well as store that in usable formats.

Google Maps is created from data size of over 20 Petabytes and a huge part of that is made from millions of smaller businesses across cities and towns. As nearly 13% of all the Google searches are associated with its maps, this huge dataset is surprising. This huge user-base and dataset together assisted in capturing nearly 67% of the navigation apps market (till 2018). Data scraping Google Maps assists in extracting data resources from Google.

List of Data Fields to Be Scraped from Google Maps

If you are looking for food or a restaurant service then you should scrape the following data fields:

How to Take Benefits from Local Restaurant Data from Google Maps?

Local restaurant data proves to be extremely important if utilized correctly. It could answer the questions, which can be solved through data only:

Market Research

Scraping restaurant data can assist businesses in getting solutions to various problems with market research. For instance, a fast-food company could utilize local restaurant data for finding areas of a city that have additional fast-food joints. The data would specify that these areas are very popular amongst the foodies. In contrast, one can use local restaurant data for finding which areas are having lesser food joints as well as open new restaurants there.

Data Aggregation

Data aggregating can offer an extensive picture while looked like the whole. The similar goes with restaurant data as data aggregation and harvesting of certain restaurant types can assist in decoding fundamental problems, points that are getting missed, the possibility of newer restaurant entries, etc. Aggregated data from various restaurants on Google Maps could open the doors, which information from one restaurant can’t.

Maintaining Brand Image and Sentiment Analysis

Today, different public perceptions about the restaurant are as vital as products that sell. You could keep a track of the brand images of all restaurants by tracking the newest reviews on various platforms. Scraping restaurant data from Google Maps has thousands of reviews of millions of restaurants. The data offers a great data-set to perform sentiment analysis as well as also assists restaurants in analyzing what they get right as well as where they missed the mark. Scraping Google Maps data helps to extract the necessary data fields.

Competitive Analysis

Getting insights into your competitors is as vital as getting your house in good shape. That’s the reason why businesses want to scrape data from different restaurants parallel to theirs. This data could be easily available using Google Maps. Then, the data can be utilized to get insights into price strategies, opening as well as closing the timings, customer perception, add-on services, and more. This data can be utilized to find the space for improvement and make data-supported restaurant decisions.

How to Scrape Food & Restaurant Data?

Many ways are there through which you can scrape data related to domestic restaurants and food from Google Maps. Let’s discuss a few ways:

Google Maps API

Google offers different APIs, which can be utilized to scrape data related to different places on the maps. These APIs could be used if a user monitors certain guidelines, which have been put down. Else, you will need to pay certain money per 1000 calls to every API. Whereas the costs might not look so much, they might add up because you try and fetch more data across different locations or when you try and refresh the data frequently.

Writing Codes

Writing codes to extract a site like Google Maps could prove to be extremely challenging. That’s because a user interface becomes updated frequently as well as different kinds of restaurants are having their listings in various formats, usually sporting various data points as well as features. There are also risks of being blacklisted if you result in hitting different maps pages from similar IPs in a shorter period. Making a data scraping solution, which might read the data associated with local restaurants at various locations as well as an update in real-time might not be difficult as well as expensive to make but also come up with additional overhead of maintenance and infrastructure setup.

Paid & Unpaid Software Solutions

The majority of these software solutions are utilized by the companies where a restaurant team (that has no coding knowledge), handles data scraping requirements. Whereas they could be utilized with training, you are guaranteed to run in the roadblocks for lacking different features. In addition, re-learning for the new employees and handling the configuration and infrastructure changes constantly and would eat up in the key priority of a restaurant team.

DaaS Solutions

DaaS solution providers are data-based end-to-end service providers, which generally handles the majority of stages in data workflow, providing you 2 things:

Generally, the prices are based on the total data amount, which is required to be extracted, and therefore, you should only pay for data points as well as the number of restaurants, which you need data for. In a long time, you will only pay for the data points, which have got updated–to drive the cost down.

Why Foodspark?

Our enterprise-grade, well-managed, and end-to-end solutions can assist you in having all data points needed from restaurants in all locations around the world. Any type of customized requirements like filters for some kinds of restaurants could also get implemented if needed.

At Foodspark, we offer a lower latency food and restaurant data scraping solution that revives data in real-time. Our well-managed food data scraping services take care of the maintenance and infrastructure setup. Our complete cloud-based solutions consider various integration requirements, which customers might have. Therefore, we offer data in different formats like JSON, CSV, or XML through the means of REST APIs, S3, or DropBox. Your journey of scraping data from Google Maps as well as integrating it in the restaurant workflow could be a continuous upgrade using our DaaS solutions.

For all your food and restaurant data scraping service requirements, contact Foodspark or ask for a free quote!