How to scrape Walmart product data with Google Sheets? [2024 tutorial]

Author: Alan Trébuquet
Published: February 28, 2024

Walmart, as one of the world’s largest marketplace, holds valuable data that businesses and retailers can analyze to achieve success. Analyzing this data enables businesses to make informed decisions regarding pricing strategies, product placement, inventory management, etc.

However, accessing this data in a structured and efficient manner can be a hard task if not too time-consuming.

3 usual methods to extract Walmart product data

When it comes to extract data from Walmart, businesses and researchers have explored various options:

  • Manual Extraction: The traditional approach involves manually copying and pasting data, a time-consuming and error-prone process that becomes increasingly impractical as the scale of data grows.
  • Home-made solutions: Some opt to rely on tech teams or developers to create custom data extraction solutions. While effective, this approach can be resource-intensive and may require ongoing technical support.
  • Data Extraction Tools: Alternatively, there are data extraction tools available that promise efficiency and ease of use. However, some of these tools may have limitations such as complex interfaces.

These existing solutions offer different paths to data extraction, each with its own advantages and drawbacks. This is why, we’d like to introduce an original but efficient solution for Walmart data extraction: Google Sheets combined with the add-on ImportFromWeb.

With ImportFromWeb, Walmart data are directly extracted with a simple Google Sheets formula and ready to be manipulated and analyzed since they’re presented in a table.

The benefits of extracting data from Walmart to Google Sheets

Extracting data from Walmart and importing it into Google Sheets offers numerous benefits for businesses, aiming to streamline their operations and gain valuable insights. Here are some key advantages:

  1. Centralized Data Management: By transferring Walmart data to Google Sheets, businesses can consolidate information from multiple sources into one centralized platform. This facilitates easier access, organization, and analysis of data, eliminating the need to switch between various tools and platforms.
  2. Real-time Updates: With a web scraping tool, data extraction from Walmart can be automated to provide real-time updates on product prices, availability, and other relevant metrics. This ensures that businesses have access to the most current information, enabling them to make timely decisions and stay ahead of the competition.
  3. Customizable Analysis: Google Sheets offers robust features for data analysis and visualization. By importing Walmart data into Sheets, analysts can manipulate the data, create custom reports, and generate visualizations to uncover trends, patterns, and insights for informed decision-making.
  4. Collaboration and Sharing: Google Sheets enables collaborative work, allowing multiple users to access, edit, and share data simultaneously. This fosters teamwork and facilitates knowledge sharing among team members, promoting better collaboration.
  5. Cost-effectiveness and Scalability: Leveraging Google Sheets for data extraction and analysis is cost-effective compared to investing in complex data management systems. Moreover, Google Sheets scales effortlessly with the growing needs of businesses, accommodating increased data volume and user requirements without additional infrastructure costs.

Step by step tutorial to scrape Walmart product data in Google Sheets

As mentioned above, we’ll use ImportFromWeb as a part of our process to extract Walmart Product data. So please make sure first to install ImportFromWeb from the Google Workspace Marketplace and activate it in a new Google Sheets (from the Extension menu).

ImportFromWeb is a Google Sheets add-on that enables to easily extract real-time data from any Walmart listings. The process relies on a simple Google sheets function – named =IMPORTFROMWEB() – that requires 2 parameters: the URL of the Walmart listing and one or a list of selectors specifying the data points to be extracted. Executing the function outputs the data points requested in a simple table.

Step 1: Input the Walmart product URLs

First of all, let’s copy/paste your list of URLs in the first column of your spreadsheet.

Step 2: Write the headers specifying the data points to be collected

Let’s say for our use case that we want to scrape the titles, prices, ratings and number of reviews for each of our product.

From the list of Walmart selectors available on this page, we understand that the =IMPORTFROMWEB() function needs the following selectors: title, price, ratings and reviews_count.

Let’s write them in the first row:

Step 3: Enter the =IMPORTFROMWEB() function

Now you can enter the IMPORTFROMWEB formula in B2:


Pressing enter and executing the function will output the data. In the background, a robot is sent to the page, crawls it all, analyses its source code and extract the data requested.

Last step is as easy as manipulating a classic spreadsheet formula: adding “$” around the data selectors, you can drag the formula down to your last row and process the data extraction on all the listings!


Step 4: Regularly update the data

Oneshot analysis is of course not enough, since prices or ratings on Walmart are not be set in stone, and you will need to review them regularly.

The benefit of using ImportFromWeb is that your spreadsheets are somehow synced with Walmart real-time data. So every time you execute the =IMPORTFROMWEB() formulas, your dashboard is updated with Walmart live data.

Thus, we advise you to run regularly the function using the ImportFromWeb sidebar (make sure to select all the cells that contain the formulas):

Our Free Google Sheets Template to extract Walmart product data

To help you get started right away, we’ve prepared a ready-to-use Google Sheets template that incorporates ImportFromWeb, making it even easier to extract Walmart product data in bulk. Simply click on the link below to access the Walmart product scraper page that contains the template: