How to scrape @mails of Restaurants in Paris on TripAdvisor?

Sasha Bouloudnine
July 4, 2022
3 min read

tl;dr

Let’s collect 100 Paris restaurants data — included mails — on TripAdvisor. With no code. For free.

In 2 minutes:

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Overview

TripAdvisor is a fantastic source of data. In Paris only, of course world city of gastronomy and “fromage” exposure — s/o ratatouille we love ya — the website gathers more than 17,839 restaurants:

Such a tower, isn’t it?

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On top of providing a large pool of exceptionally qualitative restaurants, the website provide high-quality datapoints. You’ll find of course all usual items — name, address, reviews — advanced items related to restaurants industry — food type, price, michelin stars (!!) — and highly-qualified contact datapoints — phones, and valid mails you’ll be able to leverage you lead acquisition and high-scale growth:

https://www.tripadvisor.fr/Restaurant_Review-g187147-d7621672-Reviews-Bustronome_Paris-Paris_Ile_de_France.html

OK now let’s do quick math. Let’s say you copy past 1 mail every 10 seconds i.e. 6 mails every minute, you’ll need approx. 3000 minutes to collect all of it, or 50h. With totally no interruption. Copy-pasting like a bot. Day and night. Collecting only mail. Terrible.

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How can we scrape all these Restaurants in Paris — with all datapoints — without copy-pasting like a mad machine? The answer is: using a web scraper. But wait! TripAdvisor uses a bot detection service called DataDome to prevent web scrapers from extracting data. Worried again? We got you covered.

In this tutorial, we will see how to scrape all datapoints, of all restaurants in Paris on TripAdvisor, at scale while bypassing DataDome. Without any line of code. In 2 minutes of setup. For free!

Target

First of all, let’s go on TripAdvisor, and let’s choose the Paris target, with all restaurants. Then, let’s symply copy-paste the URL which is in the browser:

Here we go!

Let’s keep it preciously — we’ll need it later on: https://www.tripadvisor.fr/Restaurants-g187147-Paris_Ile_de_France.html

Setup

Now, let's go to the TripAdvisor crawler available right here: https://lobstr.io/store/f781435f026b36b19ef74d591a077cb7/tripadvisor-iter-restaurants

And we’ll simply click on ‘Start Now’:

If you click on the cool arrow beside ‘Output’, you can download a sample for free! Just click. It’s totally free.

Here, simply paste the previously saved URL (1). Beside, for the purpose of the demonstration, let’s set ‘Max Results’ at 100 (2) i.e. we’ll collect only 100 results max. Let’s not be too greedy to start with.

Endly, let’s click on ‘Save’ (3) :

Finally, here we want to launch the crawler only once, manually - and not at regular frequency at a given time.

So we will choose 'Manually' (1) and click on 'Save & Extract' (2):

That’s simple and… that’s it!

Launch

A final modal is raised

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Let’s press yes!

A run is automatically triggered:

Time to wait relax while the machines are at work

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Enjoy

The run has been successfully completed! Just click on the line that represents the run:

We get a detailed overview of what happened:

  1. 4 minutes of collection
  2. exactly 100 gorgeous results

Finally, you can directly press the 'Download' button, and get the associated .csv. Once opened in Numbers, you get a superb data set, structured and exhaustive, that you will be able to fully leverage:

In total, we collected 100 establishments in 5 minutes i.e. 20 establishments per minute, including 100 phones and 82 @mail addresses (!!!). Awesome!

With a 20 EUR per month plan, you get 1 hour per day of collection - that's 1200 establishments per day, and 36000 establishments per month.

Conclusion

TripAdvisor is an exceptional source of data, with exhaustive and accurate datapoints. On top, it provides exceptional contact elements, such as mail and phone. Ideal for creating a list of highly qualified, comprehensive and quickly usable prospects.

With lobstr, we collected 100 establishments in 5 minutes, or 20 establishments per minute. Including 82 mails addresses. No painful copy and paste. No coding. In a matter of seconds.

Happy scraping!

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Sasha Bouloudnine

Co-founder @ lobstr.io since 2019. Genuine data avid and lowercase aesthetic observer. Ensure you get the hot data you need.