Web Scraping: How to Automate Product Data Collection

Web Scraping: How to Automate Product Data Collection

Web Scraping: How to Automate Product Data Collection Web Scraping: How to Automate Product Data Collection
Product Strategy & PXM Consultant
Valtech
Matthieu Levallois

21 abril, 2022

In an April 2022 survey of 80 technology leaders, only 16% were using web scraping. The majority of businesses manually collect and enrich data for their products.

Enter: Web scraping, an approach that reduces manual tasks and allows your people to focus on higher value work.

Web Scraping in Three Sentences:

Web scraping is about automatically extracting data from lots of websites and structuring that data in a database. The goal is to improve your database quality through data enrichment, data correction and translation. The end result is that you have in-depth and consistent product data across all of your selling channels, which encourages your customers to buy from you.

The Pitfalls of Manual Data Collection

Whether you have a data expert internally or you are working with someone externally, you’re going to run into similar issues if data is collected and processed manually:

  • Frequent mistakes (such as typos or data pasted in the wrong box). 
  • No established process to route data into a Product Information Management (PIM) team – it’s all ad hoc.  
  • A time-consuming process that isn’t the best use of your people’s time or energy.

Manual data collection costs a lot, is less likely to be accurate, and is not the best use of your team’s time.

Web Scraping: The Process

Step 1: Define data to extract. 

First, there’s some homework to figure out:

  • Which data is needed? 
  • From which web pages? 
  • Which attributes should be included?

Step 2: List all your products. 

Using crawler software, the fastest way to list the product web page URLs of a website is to create an Excel file with all the links.

Step 3: Code.

Python is a language that enables us to extract the data automatically: this enables the actual web scraping (going out and grabbing all that valuable data).

Step 4: Export to Excel.

This is the grand finale where we actually get our hands on our final database. After the Python code has extracted the data from the website, the resulting database is exported as an Excel file, which can be integrated into a PIM.

Making the Business Case for Web Scraping and for a Partner to Guide You

Web scraping is a useful technique that can set your business up for success for all things related to data collection. It can positively impact your bottom line and will give you the most cost-efficient and time-efficient tool for managing your data.

Web scraping is one tool at your disposal. Since product data is such a crucial part of the customer experience that it warrants strategy, planning and innovation.

The Valtech team is here to support your product experience ambitions. From goals to results, we’ll recommend the best tools and change management approaches for revenue growth. Additionally, we have a long history of knowing how best to implement first-party data to deliver new solutions for your brand and your customers. Contact us today to learn more about the opportunities presented through web scrapping.

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