Batch Data Processing in Google Sheets — AI Processing, Enrichment, and More

A common question is how to process each row based on your specific logic (whether it’s web scraping, enrichment, text generation, classification, or anything else). I’ve put together a brief guide for you.


How to Do It

For a practical example, let’s take a list of 50 names in a Google Sheet and create personalized greeting emails using ChatGPT.

Step 1: Add a Status Column

First, we need to add a column to track whether each action has been completed. I’ve labeled this column as “not processed.”


Creating the Scenario

Next, we move on to setting up our scenario in Latenode.

Let’s break down how it works:

  1. Trigger on Run Once: This node triggers the scenario when you click the “Run Once” button.

  2. Find Row: This node is configured to fetch all row numbers where the status is “not processed.” In our example, this status is located in column C, which we specify beforehand.

  1. Iterator: The iterator processes each row individually — exactly what we need. We pass the array of row numbers to it.

  1. Get Cell: The iterator sends each row number to the Get Cell node, allowing us to retrieve the row’s contents.

As you can see, we’ve successfully retrieved the first row.

  1. ChatGPT Node: Open the ChatGPT node and enter your prompt. In our example, we are generating personalized emails that include the user’s name.

At this step, we generate the email text.

  1. Update Cells: Next, we use two nodes to update the cells:
    • The first node writes the email text to the appropriate cell in column B of the corresponding row.

  • The second node updates the status to “processed” in the adjacent column.



Conclusion

And that’s it! This method allows you to process any list efficiently without any hassle.

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