Lookup Tables

Amplitude's Lookup Table integration lets you import your own data and map it to ingested properties to have an enhanced set of properties.

You can also create and manage lookup tables through an API. See Lookup Table API for more information.

Setup

Prerequisites

To set up this integration, you need the following:

• An event property or user property to create a mapping from.

• A CSV that has the data you want to map to:

  • The first row must contain column names/headers.
  • The first column must correspond to the mapping property value and must contain unique values. Lookup Tables search for exact matches, and are case-sensitive.
  • Columns must be separated by commas.
  • Rows must be separated by line breaks.
  • If a field value contains commas or quotes, wrap the contents with double quotation marks ("). The first double quote signifies the beginning of the column data, and the last double quote marks the end. If a string contains double quotes, replace them with single quotes.

Amplitude setup

1. In Amplitude Data, click Catalog and select the Sources tab.
2. In the Lookup Tables section, click CSV.
3. Select a column in the CSV to be the key column.
4. Map your property.
5. When you're done mapping, click Finish.

Update a lookup table

If you want to create a new lookup property or that mapped property is wrong, you can update the lookup table.

1. In Amplitude, navigate to Data Sources, then find the lookup table in the Sources table.
2. Make your changes. You can change the mapping, or replace the CSV by uploading a new one.
3. When finished, click Save Changes.

Delete the lookup table and its properties

When you no longer need a lookup table, you can delete it.

1. In Amplitude, navigate to Data Sources, then find the lookup table in the Sources table.
2. Click the trash icon.
3. Follow the on-screen instructions.

Lookup table use cases

With Amplitude's Lookup Table feature, you can import your own data and map it to ingested properties to create an enhanced set of event and user properties. With them, you can:

• Enrich data using ingested property values. You've captured an event called Purchased with an event property named SKU. The SKU value itself doesn't inherently hold a lot of meaning. But with your list of all the SKUs and their corresponding product names, you can use this feature to create a new property called Product Name and have it automatically populate based on that list.
• Bulk update property values. You've captured a user property called Language Code and passed in language codes (en_US, fr_FR, de_DE, etc.). This is difficult to read, so you want a Language property that maps to friendlier values like English, French, and German. Use this feature to create a new property called Language that maps the language codes to the language names.
• Bulk filter long lists. You want to see user behavior for a specific region and you have a list of all the customers and their regions. Use this to map each customer to a region, creating a new "Region" property. Now you can filter specifically to each region in a chart.

CSV example

The following CSV creates a new property called Language that maps to the SKU property. This CSV is an example implementation of the Bulk update property values use case from the previous section.