How to Edit Data in Looker Studio

Your Looker Studio dashboard is pulling in data, but it's not quite right. Maybe you need to create a custom marketing KPI, combine Google Ads cost with Google Analytics conversions, or simply filter out internal traffic to get a clearer picture. Your first instinct might be to go back and manipulate the raw data in your spreadsheet or database, but you can often save time by editing it directly inside Looker Studio. This article covers the essential methods for transforming, refining, and polishing your data without ever leaving your report.

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Why Edit Data Directly in Looker Studio?

While preparing your data at the source (like in Google Sheets or BigQuery) is always a good practice, editing within Looker Studio offers some significant advantages. It’s not about permanently changing your original dataset, rather, it's about reshaping the data for better visualization and more specific analysis.

• Speed and Efficiency: It's much faster to create a custom metric with a formula in Looker Studio than it is to go back to a Google Sheet, add a new column, write a formula, drag it down, and refresh your data source.
• Context-Specific Metrics: You can create metrics that are only needed for one specific report. This keeps your original data source clean and uncluttered. For example, you might create a "Campaign Cost Per Lead" metric just for your Q4 marketing performance dashboard.
• Preserving Original Data: Any edits, calculated fields, or filters you apply in Looker Studio are non-destructive. Your source data remains completely untouched and intact, which is great for data integrity.
• Combining Data: The "blend data" feature is one of Looker Studio's superpowers, allowing you to join datasets from different platforms. You can analyze Google Ads spend alongside Salesforce lead data in a single chart - a process that would otherwise require complex spreadsheet wrangling.

Calculated Fields: Creating Your Own Metrics and Dimensions

Calculated fields are the workhorses of data editing in Looker Studio. They let you apply formulas, functions, and logic to your existing data to create brand new dimensions and metrics. If you’ve ever written a formula in Excel or Google Sheets, you'll feel right at home.

How to Create a Calculated Field

You can add calculated fields either at the data source level (making it available in any report using that source) or at the chart level (making it available only for a specific chart).

Data Source Level (Recommended)

1. In your report, go to Resource > Manage added data sources.
2. Find the data source you want to edit and click the EDIT button.
3. In the top left of the data source editor screen, click the blue (+ ) ADD A FIELD button.
4. This opens the formula editor. Give your new field a name (e.g., "Conversion Rate").
5. Enter your formula in the Formula box. Looker Studio will help by auto-suggesting field names and functions.
6. Once the formula is valid (you'll see a green checkmark), click SAVE. Your new field is now ready to use like any other field.

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Practical Examples of Calculated Fields

Let's look at some common ways to use calculated fields.

1. Basic Mathematical Operations

You can perform simple arithmetic to create new KPIs. For instance, to calculate Ad Cost Per Click (CPC) from spend and clicks:

SUM(Cost) / SUM(Clicks)

Or to find the Average Order Value (AOV) from your e-commerce platform's data:

SUM(Revenue) / COUNT(Orders)

2. Creating Custom Groupings with the CASE Function

The CASE function is incredibly powerful for cleaning up messy data or creating logical groups. Imagine your Google Analytics data shows dozens of campaign names, but you want to group them by channel.

Let's create a "Marketing Channel" dimension:

CASE
  WHEN REGEXP_MATCH(Campaign, ".*(google|bing|cpc|ppc).*") THEN "Paid Search"
  WHEN REGEXP_MATCH(Campaign, ".*(facebook|instagram|social).*") THEN "Paid Social"
  WHEN REGEXP_MATCH(Campaign, ".*(email|newsletter).*") THEN "Email"
  ELSE "Other"
END

This formula scans each campaign name. If it contains words like "google" or "cpc," it gets labeled "Paid Search." If it has "facebook," it's "Paid Social," and so on. Any campaign that doesn't fit a rule is grouped under "Other." Now you can analyze performance by these clean, simple channel groupings.

3. Manipulating Text with CONCAT

Sometimes you need to combine text fields. For a CRM report, you might want a "Full Name" dimension to make tables easier to read. The CONCAT function joins text strings together.

CONCAT(First Name, " ", Last Name)

This formula pulls from your 'First Name' and 'Last Name' fields and adds a space in between to create a complete name.

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Blending Data: How to Join Different Data Sources

What if your data lives in separate places? For example, your ad spend is in Facebook Ads, your website traffic is in Google Analytics, and your sales are in Shopify. Blending allows you to merge these sources into a single chart to see the full customer journey.

Blending works by "joining" two or more data sources using a common dimension, known as a join key. Date is the most common and reliable join key used in marketing analytics.

Step-by-Step Guide to Blending Data

1. First, make sure all the data sources you want to blend are added to your report.
2. Select a chart on your report. In the data panel on the right, under "Data source", click Blend data.
3. The blend editor will pop up. Your current chart's data source will be on the left. Click Join another table to add your second data source (e.g., Google Ads). You can add up to five sources in a blend.
4. Now, you need to configure the join. Select the join keys. These are the dimensions that your data sources have in common. To see ad spend and sessions by day, you would select Date from both data tables as your join key.
5. Next, add the specific metrics and dimensions you want from each source to the blend. From Google Analytics, you might add Sessions. From Google Ads, you might add Cost and Campaign.
6. Click Save. Your chart is now powered by a new, blended data source, and you can visualize website sessions and ad cost on the same timeline.

Pro Tip: The quality of your blended data depends entirely on the join key. Ensure the format is consistent across sources. For example, if you join by "Campaign Name," make sure it's spelled and capitalized identically in both data sources.

Using Filters and Controls to Refine Your View

Sometimes you don't need to create new data, but rather, you just want to narrow your focus. Filters and controls let you and your audience slice and dice the data shown in the report interactively.

Filters

Filters let you set rules to include or exclude specific data. They can be applied to a single chart, a page, or the entire report.

• Chart-Level Filter: Select a chart, scroll down in the data panel, and click Add a filter. You could create a filter to exclude your own brand name from a list of search queries, for example: Exclude -> Query -> Contains -> "Your Brand Name".
• Page-Level Filter: Go to Page > Current page settings, and in the data panel that appears, you can add a filter that affects every chart on that page. This is great for creating pages dedicated to specific regions or product lines.
• Report-Level Filter: Go to File > Report settings to add a filter that applies to the entire report. A common use case here is to exclude internal IP addresses to clean up all of your traffic data.

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Controls

Controls are the interactive widgets that allow report viewers to change the data they're seeing. Instead of creating a static report filtered only for mobile devices, you can add a device control so the viewer can toggle between Desktop, Mobile, and Tablet themselves.

To add one, go to the toolbar and click Add a control. Useful controls include:

• Date range control: The most essential control. It lets users pick the time period for the report.
• Drop-down list: Allows users to filter by a specific dimension, like Country, Campaign Name, or Device Category.
• Input box: A search field lets users find data containing a specific term, which is helpful for digging into campaign performance or search keywords.

Bonus Tip: Adjusting Field Types & Aggregations

Less of an "edit" and more of a "correction," making sure your fields are formatted correctly is critical. Looker Studio usually does a good job of guessing field types, but sometimes it gets them wrong.

In the data source editor (Resource > Manage added data sources > EDIT), you can inspect all your fields.

• Changing Type: Did your transaction IDs import as a number when they should be text? Just click the field's data type (e.g., Number) and change it from the dropdown. This is important because Looker will try to Sum number types by default.
• Changing Aggregation: You can also set a metric’s default aggregation. For example, Price might be better suited to Average instead of Sum as its default. Changing it here ensures it behaves consistently whenever you drag it onto a chart.

Final Thoughts

Looker Studio provides a surprisingly robust set of tools for transforming your data right inside the dashboard interface. By getting comfortable with calculated fields, blending data, and applying strategic filters, you can move beyond simple visualizations and create truly insightful reports that answer specific business questions, all without modifying your source data.

At Graphed, we've focused on making this entire process of data transformation instant and conversational. Instead of building multi-step CASE formulas or manually configuring joins to blend data sources, you can just ask Graphed for what you need in plain language. A prompt like, "Show me an overview comparing my Google Ads spend vs. Shopify revenue by day for this month" automatically builds a chart from a blended data source. We handle all the connections, calculations, and visualizations so you can focus on asking questions and getting answers, not on report setup.