Looker Studio Function : REGEXP_EXTRACT
REGEXP_EXTRACT Function in Looker Studio – Practical Regex Extraction Guide
Category: Text Function
The REGEXP_EXTRACT function in Looker Studio is used to extract a specific part of a text value based on a regular expression pattern. Unlike REGEXP_CONTAINS, which only checks for the presence of a pattern, REGEXP_EXTRACT actually returns the matched value. This makes it extremely useful when working with structured text like URLs, campaign names, product codes, tracking parameters, or system-generated IDs.
In real-world dashboards, data often comes as a single combined string instead of neatly separated columns. For example, UTM parameters embedded in URLs or multiple details stored in one field. REGEXP_EXTRACT allows analysts to pull out exactly the required portion without changing the source data.
From a BI point of view, this function helps reduce dependency on data engineering for small transformations. It is commonly used to create new calculated dimensions, simplify reporting logic, and improve dashboard clarity. Since it works at row level, REGEXP_EXTRACT scales well for large datasets, provided regex patterns are written efficiently.
Overall, REGEXP_EXTRACT is a must-have function for advanced text manipulation in Looker Studio.
Purpose of REGEXP_EXTRACT Function
1. Extract Specific Values
Helps extract meaningful values like IDs, codes, or parameters from text.
2. Parse Structured Text
Used to break down structured strings such as URLs or campaign names.
3. Create New Dimensions
Allows creation of new calculated dimensions from existing text fields.
4. Reduce Data Dependency
Minimizes the need for source-level data transformations.
Type of Calculation & Practical Use Cases
1. Text Extraction
Returns extracted text based on regex match.
2. Calculated Dimensions
Most commonly used in calculated dimensions.
3. Data Preparation
Acts as an in-report data preparation step.
4. Reporting Accuracy
Ensures only relevant parts of text are used in analysis.
REGEXP_EXTRACT(text, regular_expression)
REGEXP_EXTRACT Function – Parameters Table
| Parameter | Type | Description |
|---|---|---|
| text | Text | The text value to extract data from |
| regular_expression | Text | Regex pattern with a capture group |
How Does the REGEXP_EXTRACT Function Work?
REGEXP_EXTRACT scans the given text value and applies the provided regular expression. The function looks for a capture group (defined using parentheses () in the regex). If a match is found, the value inside the capture group is returned as text.
If no match is found, the function returns NULL. The function is case-sensitive by default, so patterns must be written carefully. Since it processes each row independently, it works efficiently across large datasets when used correctly.
When Should You Use REGEXP_EXTRACT Function?
When you need to extract part of a text field
When working with URLs, UTM parameters, or IDs
When text follows a predictable pattern
When simple text functions are not enough
When creating clean calculated dimensions
Examples of REGEXP_EXTRACT Function
Example 1: Extract UTM Source from URL
REGEXP_EXTRACT(Page_URL, "utm_source=([^&]+)")
Extracts the UTM source value.
Example 2: Extract Product Code
REGEXP_EXTRACT(Product_Name, "([A-Z]{2}[0-9]{3})")
Extracts codes like AB123.
Example 3: Extract Year from Order ID
REGEXP_EXTRACT(Order_ID, "(20[0-9]{2})")
Extracts year value.
Tips & Best Practices
Always use capture groups
()for extractionKeep regex patterns simple and readable
Test regex patterns on sample data
Use REGEXP_CONTAINS when extraction is not required
Document complex regex logic for future reference
Yes, it is case-sensitive by default.
The function returns NULL.
No, it extracts only the first matched capture group.
It is mainly used in calculated dimensions.
Basic regex understanding is enough for most use cases.