Looker Studio Function : EXTRACT
Category: DATE function
The EXTRACT function in Looker Studio is used to retrieve specific parts of a date or time field—like year, month, day, or hour—for analytical purposes. It simplifies complex datasets and enhances reporting by breaking down time-based dimensions.
Purpose of the EXTRACT Function
1. Data Distribution Analysis :
EXTRACT enables users to analyze data across specific time periods—such as monthly, quarterly, or yearly. This helps identify trends, seasonality, and performance changes over time.
2. Customer Segmentation :
By extracting components like signup year or birth month, you can segment customers into cohorts, enhancing personalized marketing and retention strategies.
3. Decision Making :
EXTRACT provides actionable insights by presenting data in smaller time units. This supports informed business decisions based on hourly sales, daily performance, or monthly customer activity.
Type of Calculation & Practical Use Cases
✅ Performance Benchmarking
EXTRACT enables time-based comparisons by isolating components like month or year, allowing teams to benchmark KPIs over consistent periods such as monthly or yearly.
✅ Customer Segmentation
By extracting date elements like signup month or birth year, EXTRACT allows grouping of users into logical segments for personalized marketing and behavioral analysis.
✅ Time Series Analysis
EXTRACT breaks down dates into recurring intervals (e.g., weeks or days), enabling precise visualization of trends and seasonality in time series data.
EXTRACT(part FROM date_expression)
| Parameter | Type | Description |
|---|---|---|
| part | Text | The portion of the date to extract (e.g., MONTH) |
| date_expression | Date/Time | The actual field or value to extract from |
How Does the EXTRACT Function Work?
The EXTRACT function isolates a specific part of a date—like extracting just the year from a full timestamp. It runs directly on the data source level, ensuring efficiency and accuracy in data transformations.
When Should You Use EXTRACT Function?
Use EXTRACT when your analysis requires breakdowns of time—such as grouping sales by month, identifying peak customer activity periods, or comparing YoY performance. It’s ideal for time-sensitive reporting and segmentation.
Example of EXTRACT with Result
EXTRACT(MONTH FROM Order_Date)
Result :
For Order_Date = “2024-03-12”, result = 3
Example : 1 Basic Usage
Use EXTRACT in calculated fields or charts to group data by extracted time components like year, month, or day. Ideal for dashboards showing trends or segmented reports.
Example 2: Column Usage
You can apply EXTRACT to any column containing valid date formats. This includes order dates, signup times, or any custom timestamp field.
Example 3: Handling Decimals and Scientific Notation
EXTRACT works with date fields only. It doesn’t apply to decimal or scientific values directly. Ensure your input is a valid date field to avoid errors.
Example 4: Combining with Other Functions
You can combine EXTRACT with functions like CASE, DATE_DIFF, or COUNT for powerful data segmentations and filters. For example:
CASE WHEN EXTRACT(MONTH FROM Order_Date) = 12 THEN 'Holiday Sales' ELSE 'Regular' ENDTips and Tricks
Use
EXTRACT(WEEK FROM Date)for weekly trend analysis.Combine with filters to isolate periods like weekends or holidays.
Use with
COUNTorSUMfor aggregating values by extracted time parts.Always ensure your date field is properly formatted in Looker Studio.
You can extract components like YEAR, MONTH, DAY, WEEK, QUARTER, HOUR, and MINUTE. These parts help segment and analyze data based on time intervals for better reporting and trend analysis.
No, EXTRACT only works on valid date or timestamp fields. Applying it to numeric or text data will result in errors, so always ensure the source field is in a proper date format.
EXTRACT lets you pull elements like signup month or birth year to group users into cohorts. This improves targeted marketing, behavioral insights, and personalized customer experiences based on date-related attributes.
EXTRACT is processed at the data source level, making it efficient and lightweight. It doesn’t significantly impact performance and allows faster dashboard rendering when used in calculated fields or filters.
Yes, EXTRACT works well with filters. For example, you can filter sales by a specific month or year by extracting those parts and applying conditions directly in charts or data sources.