Web scraping is a powerful technique that can be used to collect data from the web quickly and efficiently. In the below instructions, we will see how to scrape a Shopify store into an Airtable.
This page has illustrated easy steps to help users scrape data from a Shopify store and export it into an Airtable using a robust Shopify Store Scraper tool developed by Byteline. Similarly, you can export products from Shopify stores to Google Sheets or other CMS. For a better understanding, we will scrape products from three Shopify stores.
For simplicity, we have divided this blog into two parts, as follows:
In this section, you will learn the steps to create a flow, set a scheduler, and extract data using the new Shopify Store Scraper node by Byteline.
Let’s start by configuring the scheduler node first and then move to the Shopify Store Scraper node.
Step 1: Click on the add button next to the FLOWS tab in the left sidebar of the Byteline console to create a new flow.
Step 2: Assign a name to the flow. Here we have assigned this flow with the name - ‘Scrape Shopify Stores.’
Step 3: Select the Scheduler node to run the task (data scraping) at regular intervals to identify the new entries, if any.
Step 4: Click on the Edit button to configure the scheduler settings.
Step 5: Select the time interval at which you want the scraper to run automatically. Here, we have configured the node to run every week.
Step 6: Click on the Data tab to configure the data that you want to use for scraping the stores.
Step 7: Enter the spreadsheet ID from the Google Sheet.
Step 8: Click on the Save button to save the scheduler settings.
Once you have configured the scheduler node successfully, you need to configure the Shopify Store Scraper node. Let’s see the steps for the configuration.
Step 1: Click on the ‘+’ button to add the next node.
Step 2: Select the Shopify Store Scraper node to extract data from a Shopify store.
Step 3: Click on the Edit button to configure the node.
Step 4: To configure the URL, click on the selector tool to select the Shopify store URL you want to scrape.
Step 5: Select the number of products you want to scrape from each URL. Here we have selected 10.
Step 6: Click on the Save button to save the new configurations.
Step 7: Before configuring the final node, make sure to test run the flow to check the status of the flow.
Step 8: Once you see the Success message, click on the ‘i’ button to see the output.
Step 9: The success dialog window will show all the data that you’ve scraped.
In this section, you will learn the steps to configure the Airtable - Update Records node to export data into the Airtable.
Step 1: Click on the ‘+’ button to add the next node.
Step 2: Select the Airtable - Update Records node.
Step 3: Click on the Edit button to configure the node.
Step 2: By clicking on the Here button as shown below, you will be redirected to your Airtable account, from where you can get your Airtable Base ID.
Step 3: Click on the base you are using. Here we are using BI_base.
Step 4: Copy the Airtable base ID.
Step 5: Paste the copied Airtable ID in the Airtable base ID field.
Step 6: Now, enter the table name where you want to export the data. Make sure you enter the exact table name as Airtable.
Note: Once you write the table name, the node will automatically complete all the columns from the base. However, to automatically fetch the details, make sure you have at least one row in the table.
Step 7: Next, tick the loop over the checkbox because we are going to insert multiple records into an Airtable based on the data fetched from the Shopify scraper.
Step 8: Select the corresponding flow from which you are fetching the data. Here we are using the flow - Scrape Shopify stores.
Step 9: You need to configure the mapping for the column by selecting the variable name that corresponds to the selected field name by clicking on the Selector button.
Step 10: Click on the Save button to save the configurations for the task node.
Step 11: Run the task node.
Step 12: Once you see the success status, click on the ‘i’ button to check the output.
Step 13: You will see the below success window, and the Airtable will be exported with all the data that is fetched by the Shopify Scraper node.
Here are some important notes you should consider while exporting data from Shopify Store to Airtable.
Note 1: You can see the store from which the data is fetched by clicking on the ‘i’ button on the scheduler node and checking the success window. In this case, the store used to fetch the product’s data is the first store mentioned in Google doc.
Note 2: If you see the runs of this flow, you will observe multiple runs, one run for each record in the Google Sheet.
Now, you can see the updated record in the Airtable.
Note 3: In Airtable - Update Records node, when you run the flow every week, make sure that when the next run happens, it overwrites the existing records. For this, you need to click on the overwrite radio button in the advanced menu.
With these easy steps, you can simply extract products from a Shopify product scraper and put them into an Airtable using Byteline's Shopify Store Scraper node. The no-code Shopify Store Scraper node makes it simple to extract data without having to know how to program in high-level languages.
It’s amazing, right? So, don’t forget to let us know how you have liked this new node in the comment section below.