İçindekiler
Why Hotels or Other Businesses on Google Maps?
Every hotel with millions of potential customers benefits from listing its business on Google Maps. A significant part of hotel data comes from the owners or managers of the hotels. Another part is supplied by enthusiastic customers. This makes Google Places the best source of truth for hotels and other categories (e.g., restaurants, bars, shopping malls, etc.).
Ok, Google Does Have It, but How Can I Get the Data?
Kazımanın ne olduğunu anlayanlar için akla gelen ilk şey verileri kazımaktır. Google Maps scraping, harvesting, or extracting is a process of getting all the information about places (name, address, coordinates, site, phone, working hours, etc.) from the Google Maps site. It automates the manual exporting of data and saves a lot of time for marketing teams.
4 Ways to Scrape Google Places
There are several ways to get the data into a CSV or Excel file:
- kendi senaryonuzu yazın;
- use the official Google Places API;
- hire a freelancer;
- gibi mevcut sıyırıcıları kullanın Google Haritalar Veri Kazıyıcı.
İlk seçenek, kazıma alanında birkaç yıllık deneyiminiz ve kazıyıcıyı oluşturmak ve sürdürmek için kaynaklarınız varsa işe yarayacaktır. Google korumasını tarayıcı emülatörleri/proxy'ler/reCaptcha çözücüler vb. ile idare etmeye hazır olun.
Resmi belgeyi kullanarak Google Places API will be a good option but might be costly for small teams. Moreover, the fields are limited, but fortunately, you can still get some main data like names, coordinates, addresses, etc.
Hiring a freelancer can work, although you must maintain a relationship with them. Make sure the freelancer doesn’t disappear after Google updates its security and you want to fix the program.
Aşağıdaki gibi mevcut bir bulut kazıyıcı kullanarak Google Haritalar Veri Kazıyıcı will be the ultimate option, as it will not require any developer’s skills and the prices are much lower than using the Official API. You can get the results in a CSV/XLSX file. The results contain a variety of fields, including phone numbers, emails, social links, etc.
The Challenge of Scraping the Hotels From the Entire Country
Eğer şöyle bir sorgu açarsanız “hotels near NYC, NY, USA,” you will see only about 500 places for your search. Since Google Maps limits the number of results to a single search query, you will only see some hotels (unless it’s a city with fewer than 500 hotels).
Bu nedenle, bir ülkeden tüm sonuçları elde etmenin zorluğu, bazı sınırlı alanlarda belirli yerleri arayacak bir sorgu listesi oluşturmaktır.
What Queries Do You Need to Scrape Hotels From the US?
Çözüm, farklı kategorilerin (Otel, Aile Oteli, Lüks Otel, vb.) yanı sıra örneğin küçük alanlara (mahalleler, ilçeler, vb.) bölünmüş konumların bir kombinasyonu olacaktır:
- McDonald’s, Albany, New York, United States
- McDonald’s, Amherst, New York, United States
Ayrıca, kesin sorgular oluşturmak için posta kodlarını kullanabilirsiniz. Bu yaklaşımı kullanmak, örneğin yalnızca bir işletme kategorisi kullanmanıza olanak tanıyacaktır:
- Oteller, 04781, CA, ABD
- Oteller, 04783, CA, ABD
- Oteller, 04785, CA, ABD
- Oteller, 04786, CA, ABD
Kategoriler
The entire list of all the categories in Google Places can be found Burada. Bu örnekte, aşağıdakileri kullanıyoruz Google Haritalar Veri Kazıyıcı, so we don’t need to combine the categories with locations now. Moreover, as we are going to use postal codes, it will be enough to use only one main category, “hotel”:
Konumlar
İdeal konum, bir şehir ve ülke adıyla birlikte bir posta kodu olacaktır. Küçük şehirler veya mahalleler kullanmak da harika sonuç verecektir. Eğer kullanıyorsanız İletişimposta kodlarını veya şehir listesini bulmaya gerek yoktur. Açılır menüden gerekli bölgeleri seçmeniz yeterlidir. Ayrıca şunları da kullanabilirsiniz bu dosya tüm konumları almak ve başka bir uygulama içinde kullanmak için:
To specify the locations manually, use the “custom locations” checkbox and insert the data from any table you have. Make sure you have a country name inside each location. This will help the scraper find the places regardless of the IP address it’s using:
Gelişmiş Parametreler
Kullanırken Google Haritalar Veri Kazıyıcı you can select the language, the total number of places limit, and whether to extract additional data from places’ websites or not. Consider selecting the region to eliminate any other countries that might appear from cities with ambiguous names.
You also might want to use “Drop duplicates” so you will ignore duplicate items within a single task (the same places from different queries):
Starting the Scraping Task
Once everything looks right, click the “Scrape data” button and validate a few queries by opening them on Google Maps. Make sure the queries are working on Google Maps, and you can see the locations.
Eğer ilk ekstraksiyonu çalıştırıyorsanız, sizden hesabı doğrulamanızı isteyecektir. Açılan sayfadaki talimatları izleyin ve "I’ve performed the actions” once you have verified the account. When your task is running, you can open the Arama Sonuçları ilerlemeyi izlemek için:
Sonuçlar
Once your task is finished, you will receive an email with a link to the data. The file will be available for 30 days to download. You can also download the results from the tasks page.
The results file contains the following fields:
- name – name of the place on Google Maps.
- site – website of the place.
- type - altında bulunduğu yerin türü (alt türlerden herhangi bir öğe olabilir).
- alt tipler – all types of the place.
- category - yerin ana türü (bazen yerel dilde olabilir).
- phone – place phone number.
- full_address – full address of the place location.
- borough – borough of the place location.
- street – street of the place location.
- city – city of the place location.
- postal_code – postal code of the place location.
- state – state of the place location.
- us_state – state of the place location (will be removed in future versions).
- country – country of the place location.
- country_code – country code of the place location.
- latitude – latitude of the place location.
- longitude – longitude of the place location.
- time_zone – timezone of the place location.
- plus_code – location plus code or open location code (works only for individual search, e.g., query: “Hotel Colombo Berat,” “0x3e49a63f6b05fe3b:0xc73d6b1f31b2ccc8”).
- rating – rating of the place.
- reviews – number of reviews
- reviews_link – link to the place’s reviews.
- reviews_per_score – JSON object with reviews per score.
- photos_count – number of photos from the place.
- photo – image link of the place.
- street_view – image link of the place street view.
- working_hours – JSON object with working hours of the place.
- working_hours_old_format – working hours of the place.
- popular_times – popular time of the place (works only for individual search, e.g., query: “Hotel Colombo Berat,” “0x3e49a63f6b05fe3b:0xc73d6b1f31b2ccc8”).
- business_status – current status of the business.
- about - Yer hakkında ekstra bilgiler (örneğin, kadınlara ait, LGBTQ + dostu olarak tanımlanır).
- description – place description.
- range – price range of the place.
- posts – JSON object with posts from the place (works only for some places).
- verified – indicates if the place was claimed.
- owner_id – unique identifier of the place owner.
- owner_title – title of the owner’s profile page.
- owner_link – link to owner profile on Google Maps.
- reservation_links – link to make a reservation.
- booking_appointment_link – link to book an appointment.
- menu_link – link to the menu.
- order_links – link to place an order.
- location_link – link to the place on Google Maps.
- place_id – unique identifier of the place (Google might update it a couple of times per year).
- google_id - Özellik Kimliği olarak da bilinen yerin benzersiz tanımlayıcısı (Google bunu yılda birkaç kez güncelleyebilir).
- cid – multi-platform ID of a listing in the Google ecosystem.
- reviews_id – unique identifier of the places’ reviews.
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SIKÇA SORULAN SORULAR
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