Objective

Understand what is data scraping, why it's useful in SaaS growth and how to implement a data scraping workflow.

Last Updated

January 2022

Table of Content

Resources

• Facebook - How to format customer lists
• PhantomBuster - LinkedIn automation rate limits
• OpenDataSoft - Contours Géographique des Communes
• La Poste - Base Officielle des Codes Postaux
• Anas El Mhamdi - When, why and how to scrape with proxies ?
• Puppeteer + Extra Stealth + Extra ReCaptcha

<aside> 💡 This guide is meant to provide basic knowledge on a complex topic in the most concise manner. Never take anything as the gospel truth, read from multiple sources before acting.

</aside>

Introduction

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📖 Definition

What is web scraping?

Definition

Web scraping is the process of massively extracting data from online websites (usually without the owner's authorisation).

It is a 5 step process:

1. Load the target website
2. Launch the scraping script
3. Extract the data into a sheet (Google or Excel)
4. Clean the data
5. [Optional] Enrich the data with additional information

Technical details

When using a program for web scraping, it sends a GET request using the HTTP protocol to the target URL you mention. The web server, if it considers your request legitimate, will allow you to read the HTML content of the web page. You'll then store part of this content in your program environment.

Examples

• Obtain the list of all Auchan stores in France with Street Addresses, Phone Numbers and Email Addresses.
• Extract email addresses from Artisans Fleuristes de France

🎯 Objective

Why would you want to scrape data?

In order to run acquisition campaigns (via ads or cold outreach) we need to massively gather specific data on qualified prospects (new potential stores). The most cost & time-effective way to obtain this data is by scraping online repositories.

Process

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