Nested JSON Fields

Some imports keep related information together inside one block of data. That is a normal way to organize data; you do not need to write code to use it.

Simple Tables detects these details when it imports the data. You can choose the fields later and give them a clear column heading.

What “nested” means

Order Customer details Name or email

Rather than storing every detail side by side, a record can keep customer details in their own group. A path such as user.name tells Simple Tables: open user, then use name from inside it.

Show a detail from inside a group

In this example, user and order are groups. The paths below them point to the individual values you can show as columns.

[
  {
    "user": { "name": "Alice", "email": "alice@example.com" },
    "order": { "id": 123, "total": 99.99 }
  },
  {
    "user": { "name": "Bob", "email": "bob@example.com" },
    "order": { "id": 124, "total": 149.5 }
  }
]

Path	Value
`user.name`	Alice
`user.email`	alice@example.com
`order.id`	123
`order.total`	99.99

Add a nested field

Open the available fields, select the path you need, and check the preview.

Open Add column

Edit the macro, switch to the Columns tab, and select Add column.

Find the path in Columns

Search by field name or path. Nested fields detected during import appear in the list.

Add the field

Select the path you need, such as user.name, then choose Add 1 column. The preview updates immediately.

Rename it if needed

Click the new column and replace the Header in Column details with a reader-friendly label. Save or publish the page when you are done.

A simple example

A CRM team imports customer profiles where contact and account details are grouped together.

Before: Name, email, and account status sit inside the profile blocks. The key details are not visible as individual table fields.
After: The team adds user.name, user.email, and status.level as columns. They can read, sort, and filter the data directly in Confluence.

If nested fields are detected during import, you can add them later from the Columns tab by creating a new column and entering the nested field path.

How it works

Nested fields are referenced using dot-separated paths. For example:

[
  {
    "user": {
      "name": "Alice",
      "email": "alice@example.com"
    },
    "order": {
      "id": 123,
      "total": 99.99
    }
  },
  {
    "user": {
      "name": "Bob",
      "email": "bob@example.com"
    },
    "order": {
      "id": 124,
      "total": 149.5
    }
  }
]

From this structure, you can create columns such as:

user.name
user.email
order.id
order.total

Use case: Customer profile extraction

Customer Insights Team

Shinkansen Systems — CRM Analytics

Context and challenge:
The CRM team works with JSON profile data where useful information such as contact details, status, and account metadata is stored inside nested objects.

Solution:
They add columns using paths like user.name, user.email, and status.level so those values can appear directly in the table.

Impact:
Teams can work with structured JSON data directly in Confluence without flattening the file in advance or writing extra transformation scripts.

Nested field support is especially useful for customer profiles, product catalogs, API responses, and other structured JSON datasets.

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COLUMNS