Case in Looker Studio: Unlocking Advanced Reporting Capabilities

In Looker Studio, you can unlock advanced reporting capabilities to give your team a deeper understanding of your data. This can be achieved by leveraging Looker Studio's built-in features.

One of the key benefits is the ability to create custom dashboards that can be tailored to specific use cases. For example, you can create a dashboard that focuses on sales performance, another on customer engagement, and so on.

By using Looker Studio's data modeling capabilities, you can create a unified view of your data that can be easily accessed by everyone in your organization. This can lead to more informed decision-making and improved collaboration.

Looker Studio's data visualization tools allow you to create interactive and dynamic reports that can be easily shared with others. This can be especially useful for communicating complex data insights to non-technical stakeholders.

Conditional logic is a powerful tool in Looker Studio, allowing you to evaluate complex conditions using OR and AND operators. This enables more in-depth analysis of your data.

You can use the CASE function to concatenate fields conditionally, creating new values by combining text fields. For example, you can build full names from first and last name fields, checking if either name field is NULL and returning the non-NULL value.

The CASE function can also be used to return different values based on specified conditions for multiple dimensions or metrics. It's useful for classifying data based on conditions or transforming notations.

Conditional logic is a powerful tool that helps us make decisions based on specific conditions. A basic starter example of using conditional logic is to categorize stores by sales volume.

We can use the CASE WHEN statement to segment stores into tiers based on their annual sales volume, assigning each store to a tier from 1 to 4 based on sales brackets. This helps us analyze performance trends across segments.

By breaking stores into tiers, we can create a bar chart showing Profit by Store Tier and see if larger stores tend to have higher profit margins. This type of analysis can give us valuable insights into our business.

We can also use the same method to classify customers by purchase frequency, segmenting them into Top, Active, New, and Inactive groups. This allows us to analyze metrics like Average Order Value by Customer Category.

This type of simple numerical classification is recurrent in daily business processes, helping us make informed decisions based on specific conditions.

Evaluating conditions with OR logic is a powerful way to analyze data and make decisions. It allows you to check multiple criteria at once, which can be super helpful in complex data analysis.

You can use the CASE WHEN statement to evaluate complex logical conditions using OR and AND operators. This is especially useful when you need to categorize data based on multiple conditions.

For example, you can use OR to check if a customer is from the APAC or EMEA region, or if they are a wholesale channel. This can help you identify priority customers and assign them a specific label.

The CASE function is a versatile tool that can be used to return different values based on specified conditions for multiple dimensions or metrics. It's perfect for classifying data based on conditions or transforming notations.

Here are some guidelines for when to use the CASE function, IF function, and simple CASE function:

By following these guidelines, you can use the CASE function and its variants to evaluate conditions with OR logic and make informed decisions based on your data.

Conditional field concatenation is a powerful technique in data manipulation. It allows you to combine text fields conditionally to create new values.

This can be achieved using the CASE WHEN function, as seen in an example where a full name is created by combining first and last name fields. The function checks if either name field is NULL, and if so, it returns the non-NULL value. If both are populated, it combines them into a full name.

Records with completely blank values get labeled "Name Unknown". This method can be applied to create full email or postal addresses for example.

You can use CASE WHEN to create custom fields in Looker Studio, which can be used to visualize data in charts. This is a helpful way to get more out of your data.

The CASE WHEN function is also useful for segmenting data, such as classifying customers based on their age groups into “18-24”, “25-30”, and so on.

The CASE function is a powerful tool in Looker Studio that allows you to return different values based on specified conditions for multiple dimensions or metrics.

You can use the CASE function to classify data based on conditions or transform notations.

The recommended usage from official sources is to use the IF function for two options, the simple CASE function for three or more options for one dimension or metric, and the CASE function for multiple dimensions or metrics.

You need to create a calculated field in Looker Studio to use the CASE function, and there are two types of calculated fields: data source calculated fields and chart-specific calculated fields.

The CASE function can be used to categorize data into different groups, such as ranking GA4 pages based on multiple criteria.

Here is an example of how to use the CASE function to rank GA4 pages:

CASE

WHEN average session duration > 120 AND impressions > 10000 THEN "A"

WHEN average session duration > 120 AND impressions > 1000 THEN "B"

WHEN average session duration between 20 and 120 AND impressions > 1000 THEN "C"

ELSE "D"

END

This creates a new dimension called Multi-criteria PageRank.

You can also use the CASE function to divide device types into PC, mobile, tablet, and others, or to combine conditions for device type and OS type to classify into mobile-safari, mobile-chrome, PC-chrome, etc.

Here is a summary of when to use the CASE function:

You can use parameters to filter data dynamically in Looker Studio. For example, you can create a Category parameter that allows users to select multiple categories, and then use CASE WHEN to filter the view based on the parameter selection.

By using parameters, you can easily switch between different views of the same dataset. This can be especially useful for providing 360° views of data, which can help you gain intricate insights from business data.

Here are some ways to display key metrics with parameters:

The possibilities are endless, and the potential of this strategy is limited only by your imagination.

You can use parameters to make your reports interactive. Parameters provide interactivity within reports, allowing users to select specific data to view.

For example, if you have a Category parameter that lets users select multiple categories, you can use CASE WHEN to filter the view dynamically based on the parameter selection.

Here's how it works: the view will display only the selected categories, filtering out any unselected categories by returning NULL. As users update the parameter, the view updates.

You can use parameters to toggle the displayed metric, switching between different metrics in the chart. This is useful for providing different views of the same dataset, such as 360° views of business data.

To create parameters, you need to create them prior to accessing them from your code. This allows you to use them in your reports and make them interactive.

Here's a simple example of how you can use parameters to filter a view:

This approach makes it easy to update the view as users select different categories.

You can rank pages in Looker Studio using multiple criteria to get a more comprehensive view of your data. The CASE function is a useful tool that can transform data and categorize it using multiple conditions.

To use the CASE function, you can define the rank by setting up calculated fields with specific conditions. For example, you can classify pages as A, B, C, or D based on their average session duration and impressions.

Average session duration and impressions are two key metrics that can be used to rank pages. In the example, pages are classified as A if the average session duration is more than 120 seconds and impressions are more than 10,000, and as B if the average session duration is more than 120 seconds and impressions are more than 1,000.

You can also use the CASE function to create a new dimension called Multi-criteria PageRank, which can be used to rank pages based on multiple criteria. This dimension can be used to display the ranked pages in a table or chart.

To create a Multi-criteria PageRank dimension, you can use the CASE function with multiple conditions, such as average session duration, impressions, and views. The dimension can be used to categorize pages into different groups based on their performance metrics.

By using the CASE function and creating a Multi-criteria PageRank dimension, you can get a more detailed view of your data and make informed decisions based on your business's growth metrics.

Grouping your SEO report by pages can be a game-changer for ecommerce sites. You can create a new calculated field using the CASE function to classify pages into different categories.

The CASE function evaluates different conditions and assigns a value according to the page URL. It's like a decision tree that checks each condition one by one until it finds a match.

You can use the REGEX_MATCH function to check if the URL field contains specific terms. For instance, if the page URL is https://example.com/product/, the formula assigns a "Product Pages" value.

Each case is evaluated one after one until the value is found true. If none of the cases is found true, then a default value is assigned to the dimension, which is "Other Pages" in this example.

The formula can be modified to implement your own logic and use it for complex classifications. You can also use it to classify pages into different categories, such as products, categories, and blog posts.

You can use calculated fields to annotate charts by creating a metric that only shows a value of 1 on specific data.

To do this, use the CASE function to assign the value of 1 to the metric only when the date matches a specific date literal.

For example, you can use the DATE literal to specify a date value, like "2023-09-03".

To make it appear as a vertical line on the chart, change the style of the metric to "Bar".

You'll also need to change the Axis to Right and the graph type to Bars for the created series.