---
title: "How to use lookups with custom fields"
slug: "how-to-use-lookups-with-custom-fields"
description: "Transform your data with lookups to enhance clarity and consistency in reports from platforms like Facebook Ads and Google Ads."
updated: 2026-04-22T08:31:23Z
published: 2026-04-22T08:31:23Z
---

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.supermetrics.com/llms.txt
> Use this file to discover all available pages before exploring further.

# How to use lookups with custom fields

Lookups allows you to match values across different tables before you transform them. They enable you to modify and improve the legibility and usefulness of your data from platforms like Facebook Ads and Google Ads. By replacing existing values in your data with new ones defined by you, lookups are essential for recategorizing or renaming values in large datasets.

Lookup transformations are especially useful for large data sets that don't change often. They streamline your data analysis and ensure consistency across your reports.

Some popular use cases include:

- **Renaming categories**: If you have ad campaigns labeled with numeric IDs in your Google Ads data, you could use a lookup transformation to replace these IDs with more understandable campaign names, making your analysis more straightforward.
- **Recategorizing values**: Perhaps you've segmented your Facebook Ads by age groups, and the platform provides data in granular 1-year increments. Using a lookup, you can recategorize these into broader age brackets (such as 18-24, 25-34) for more high-level analysis.

Lookups can also be [combined with additional transformation steps to perform more complex sequences](/v1/docs/how-to-add-multiple-transformation-steps-to-custom-fields).

## Instructions

1. On the [Supermetrics Hub](https://hub.supermetrics.com/), go to **Custom fields** under **Manage**.
2. Click **New custom field**.
3. Select either dimension or metric and click **Next**. This selection is based on the aspect of the data you aim to manipulate.
4. Select the data source you want to apply a transformation to and click **Next**.
5. Select **Lookup** as your transformation type. This selection allows you to map existing values in your data to new values defined by you.
6. Select the field you want to transform.
7. Define the lookup rule. You can select between "equals", "equals (ignore case)", "contains", and "contains (ignore case)".
8. Depending on the rule, your lookup transformation will match the original values in your data to your defined new values.
9. Build your lookup table. Here, you define pairs of **Lookup value** (existing value) and **Return value** (new value). You can create individual rows for each pair or upload in bulk using a CSV format.
10. Once your lookup table is set up, click **Next**.
11. Give your custom field a name.
12. Click **Create custom field**.

You can now [use your new custom field in your reporting](/v1/docs/how-to-use-custom-fields-in-your-reporting).

## More resources

- [How to use functions with custom fields](/v1/docs/how-to-use-functions-with-custom-fields)
- [How to use conditions with custom fields](/v1/docs/how-to-use-conditions-with-custom-fields)
- [How to add multiple transformation steps to custom fields](/v1/docs/how-to-add-multiple-transformation-steps-to-custom-fields)
- [How to use AI features with custom fields](/v1/docs/how-to-use-ai-features-with-custom-fields)