Fields in a report

Prerequisites

To be able to work on the fields of a report, the following points must be observed:

• Have edit access to the report and data source(s)
• Have the correct rights and authentication mode (Owner/Viewer) set up to avoid surprises when editing.
• Have knowledge of the concept of data aggregation

About fields in Looker Studio

Fields represent all the data available for a data source. Each field has a type (metric or dimension), a format (date, URL, text, number, etc.), and an aggregation method in the case of a metric. A field inherits its type, format, and default aggregation from the source, but can be overridden at the report/graph level. There are three different ways to override this information.

Data source

This is the place to standardize: correct types, set default aggregations, define the currency, and create shared calculated fields (e.g., CPC, ROAS, Source/Medium). Everything you would do in each report should live here.

Report

Ideal for contextual adjustments: rename "Cost" to "Cost (EUR)", group campaigns for this report only, choose a specific display format. You keep the source clean while customizing the experience.

Chart

Perfect for quick testing and iteration: a temporary CASE, a format variant, a TO_TEXT() to display an ID. Document these deviations if you keep them: they are not reusable elsewhere.

Simple decision rules

Keep in mind the impact of rights: depending on Owner/Viewer, a user may or may not be able to see certain fields, and above all, may not be able to edit them. Reusable sources limit duplication and discrepancies.

What are the differences between a metric and a dimension?

Dimensions

Definition: these are qualitative, descriptive attributes that allow data to be categorized or segmented. They generally appear in the form of text, dates, or categorical values.

Role: they serve as "keys" for organizing data. They are generally used as rows or columns in a table, or as labels in a graph.

Examples:

• Date
• Country
• Traffic source (Google, Facebook, Email, etc.)
• Campaign name
• Device type (mobile, desktop)
• Age group

Metrics

Definition: these are quantitative, measurable data that can be aggregated (sum, average, rate, etc.). They appear in the form of numbers.

Role: they represent the value being analyzed. They are often used as numerical values in graphs or tables.

Examples:

• Number of clicks
• Impressions
• Conversion rate
• Cost
• Revenue

The interaction between the two types

A dimension segments the information that a metric will deliver. For example, if you want to display clicks by country, the dimension is "Country" and the metric is "Clicks." This interaction transforms raw data into actionable information. It is this dynamic combination of dimensions and metrics that enables flexible and customized performance visualization. In Looker Studio, metrics and dimensions interact with each other in almost all available visualizations.

Different types of formats

Type inference from the connector

The connector sends Looker Studio a schema where each field has a default type. Looker Studio relies primarily on this schema to type the fields in the report.

• Numeric: number, percent, duration
• Text: label, id, campaign name, etc.
• Date and time: date, year, month, week, hour, etc.
• Boolean: true, false
• Geo: country, city, continent, zip code, address, latitude, longitude
• Currency: EUR, USD, GBP, INR, etc.
• URL: URL or image

The list of different field types available: https://developers.google.com/looker-studio/connector/reference#semantictype

1. Time-related formats

In marketing, the concept of time is central. You will often want to analyze your performance by year, month, week, or even hour.

• Year: to track your key indicators on an annual basis.
• Year + quarter: useful for financial analysis or large seasonal campaigns.
• Year + month: ideal for tracking the monthly evolution of your KPIs.
• Year + week: useful for digital marketing, where campaigns are often planned on a weekly basis.
• Specific day: allows you to see the impact of a one-off event such as a campaign launch.
• Day of the week: essential for understanding which day your actions perform best.
• Time: provides an hourly overview, useful for example for sending emails or advertising.
• Duration (in seconds): corresponds to a measure of elapsed time, such as the average session duration on a website.

2. Geographic formats

These formats allow you to view your data according to the location of your audiences or customers.

• Countries and country codes: useful for comparing performance between different international markets.
• Continents and sub-continents: provide a macro view for global strategies.
• Regions and regional codes: allow you to drill down to the state or province level.
• Cities and city codes: relevant for local marketing.
• Latitude and longitude: useful for placing data on a precise map.

3. Numeric formats

These form the basis of your performance indicators.

• Number: used for all raw metrics such as impressions, clicks, or leads.
• Percentage: essential for rates (CTR, conversion rate, open rate).
• Duration: useful for measuring time spent or the duration of an action.
• Currency: useful if you want to highlight monetary data such as the cost of a campaign.

4. Text and logical formats

These are used to describe, categorize, or create filters.

• Text: used to name campaigns, identify traffic sources, or display labels.
• Boolean value (true/false): useful for creating simple filters (e.g., mobile traffic or not).
• URL: allows you to integrate clickable links into your reports.
• Image: allows you to view the image from a link.

Different types of aggregation

Aggregation determines how Looker Studio combines multiple rows when you place a field in a chart or table.

There are several types of aggregation that can be classified into three distinct categories.

1. Numeric aggregations

These functions apply to fields containing numerical values. They are used to calculate statistical indicators.

• SUM: calculates the total sum.
• AVG: calculates the average.
• MAX: returns the highest value.
• MIN: returns the lowest value.

2. Counts

These functions apply to any type of field (text, number, ID, etc.) to count occurrences.

• COUNT: counts the total number of entries, including duplicates.
• COUNT_DISTINCT: counts only unique entries.

3. Special modes

These options control how Looker Studio behaves on fields when no particular aggregation is desired or when the tool must decide automatically.

• NONE: no aggregation is applied, the data is left raw.
• AUTO: Looker Studio automatically chooses the appropriate aggregation, especially in calculated fields.

Conclusion

Mastering fields in Looker Studio is essential for building reliable, readable, and actionable reports. Understanding the difference between dimensions and metrics, knowing where to edit a field (source, report, or graph), and applying the right formats or aggregations not only helps you avoid misinterpretations but also saves valuable time during analysis.

By adopting a clear logic—standardize in sources, contextualize in reports, and experiment in graphs—you create a solid foundation for your visualizations. This ensures consistency in your data, limits duplicates, and promotes smooth collaboration between different users.

With good field management, Looker Studio becomes a powerful tool for transforming raw data into concrete marketing insights, and Catchr further simplifies this step by automating the preparation and formatting of your data, without any technical effort.