📗 Extracting Tables and Repetitive Data

This article applies only to Parsio’s template-based parser.

Extracting tables and repetitive data is useful when you don’t know in advance how many items you need to extract from an email or document. This is common when working with structured, repeating content.

Typical use cases include:

Order confirmation emails with multiple items
Newsletters listing products or blog posts
Invoices containing line items

In this guide, we’ll walk through the table extraction process. Prefer video instructions?

How table extraction works (template-based parser)

Table extraction relies on fixed structure and consistent layout.
It is best suited for machine-generated emails or documents where table rows and columns follow the same pattern.

If your tables vary significantly between documents, consider using an AI-powered or GPT-powered parser instead.

Step-by-step: extracting a table

After creating a mailbox and setting up email auto-forwarding, follow these steps:

1. Open a sample email

2. Select the table

Highlight the entire table and click Add a new table.

3. Review the highlighted table

The table will be highlighted in green. In this example, we’ll extract:

Product name
“Gone in” field
Description

4. Create the first column

Highlight the first product name and click New column. Name the column (for example, Product name).

5. Create additional columns

Repeat the same process for the “Gone in” and Description fields:

Highlight the relevant text
Click New column
Give each column a meaningful name

To improve accuracy in complex tables, highlight additional rows and add them to the existing columns. This helps Parsio better understand the table structure.

Once done, click Save table.