In this tutorial for beginners, we take a look at the Looker Studio (Formerly Google Data Studio) – one of the most popular services for visualizing data – and show you step-by-step how to use it to build informative, understandable, and more importantly, actionable reports based on data from various sources.
Please note, that Looker Studio is different from another software tool called Looker. Here is a detailed and complete comparison of Lookers by Google.
Note: This post was originally published in August 2020 as the Google Data Studio tutorial and was completely updated in September 2024 for accuracy and comprehensiveness on marketing analytics.
Let's begin with an overview of Looker Studio. It’s an ideal tool for beginners looking to create dynamic and interactive reports. Looker Studio enables you to import data from various platforms, including Google services like Google Ads, BigQuery, Google Analytics 4, Google Sheets, and YouTube Analytics, along with non-Google tools. This platform allows you to visualize your data using charts, tables, and diagrams and to track key performance indicators (KPIs) or other metrics in real-time.
To connect various data sources to Looker Studio, you can use the 'add data' option in the toolbar. Creating reports within Looker Studio is intuitive, similar to early learning experiences with drawing software, where you familiarize yourself with various tools and settings.
Even the free version provides the ability to share reports with colleagues, shareholders or clients. You’re also in the driver’s seat - managing the access rights, giving the editing permissions. In addition, you can make a template of a report so that others can copy and apply their data to your ready-made visuals.
According to Portermetrics, Looker Studio is used by 67% of Fortune 500 companies and has over 3 million users worldwide. We have created a gallery of absolutely free dashboard templates that you can use to build reports with your data.
Looker Studio is an excellent service that allows you to visualize data and get fresh, automatically updated reports, avoiding the limitations of the number of widgets in Google Analytics 4 Dashboards.
Here are some of the other core benefits:
However, Looker Studio is mostly a data visualization tool, which is why you should first collect data using third-party tools to get reports based on non-Google data sources.
Also, the data blending capabilities are too limited, so you'd likely use and external tool for data preparation.
While Looker Studio and Google Sheets both serve as powerful tools for data handling and analysis, they are designed for different purposes and use cases. Looker Studio should not be seen as a direct replacement for Google Sheets. If Google Sheets meets your needs, there might be no reason to switch to Looker Studio.
However, Looker Studio builds on the capabilities of Sheets by offering additional features geared toward more advanced data visualization and reporting.
Below is a comparison of the key differences between Looker Studio and Google Sheets:
In summary, Looker Studio is the better choice if your needs revolve around creating visually rich, interactive reports.
However, Google Sheets remains an excellent tool for day-to-day data entry, simple calculations, and basic analysis.
To start using Looker Studio, log in using a Google account. You can create a free Gmail account if you don’t have one yet.
Once logged in, navigate to the Looker Studio website at lookerstudio.google.com. This is your gateway to exploring Looker Studio.
Let’s explore the Looker Studio starting page and its primary navigation elements:
Left Menu: Offers quick access to create new reports, data sources, or explore features. It also allows you to view reports shared with you, manage your own reports, and access deleted reports in the trash.
Toolbar Menu: This menu includes options to view all your reports, manage your data sources, and explore charts and data without changing existing reports. The data panel helps in managing and organizing various data types such as dimensions and metrics, allowing users to customize charts effectively.
Search Bar: Positioned at the top, it enables you to quickly find reports by searching for their names.
Template Gallery: This panel provides a starting point for new dashboards, offering a choice between starting from scratch or using pre-made templates. More templates can be found by clicking 'Template Gallery” at the top-right corner of this section. The theme and layout panel offers customization options with Theme and Layout tabs to enhance the aesthetic and optimize the appearance of your reports.
Report List: Located below the Template Gallery, this area displays your reports and allows sorting by name, owner, or last opened date, helping you organize and access your work efficiently.
Before you dive into report creation, you need to set up a source of data that you will use in the report. Understanding the distinction between your original data and what Looker Studio uses is key:
In the context of Looker Studio, a data source is a repository or location from which Looker Studio retrieves your data. This repository could be a database management system, a set of spreadsheets, a cloud-based data storage system, or any other system that stores and manages data.
The structure and system of these data sources can vary, but their goal remains consistent: to house data that Looker Studio can analyze.
"A data source in Looker Studio is the foundational rock of data analysis. It's like the library that stocks the books (data) you need for your research (analysis). Without it, data analysis would be like fishing in a pond with no fish."
To link your data source to Looker Studio, you need a data connector. This connector acts as a bridge between a source and a Looker Studio so you can access and use your data.
Data connector as a bridge. It connects Looker Studio to all of the data available from the data sources enabling smooth, automatically updated data flow.
Looker Studio supports over 800 connectors (most of them are paid, but the ones to Google Services are free).
The best part is that setting up a data connector in Looker Studio is as easy as pie. But more on that later.
Once a data connector to a data source is established, you can add a dataset.
A dataset is a collection of related data points. It's a table, or multiple tables, filled with rows and columns of data that have some shared characteristics or themes. In Looker Studio, you can think of a dataset as the raw material for your data analysis.
The quality and organization of your dataset significantly influence the accuracy of your analysis. By working with a well-structured dataset, you can:
The data source keeps the connection credentials and tracks all the datasets involved in that connection.
Looker Studio’s is flexible when working with multiple data sources. So it’s easy to visualize data from multiple sources on separate charts, tables or reports. This functionality proves valuable in collaborative projects, enabling diverse team members to access different data sources within the same report, or just within the same Looker Studio account.
Additionally, data control plays a crucial role in managing how data is filtered and displayed in dashboards, enhancing the customization and usability of reports.
However, the data blending capabilities are pretty low. That is why preparing your datasets carefully before you connect them to Looker Studio is important. Specifically, you need to ensure that your datasets are correctly formatted, cleaned, and structured to display data in reports and widgets effectively. This pre-processing shields against inaccurate data representations, which could lead to misguided decision-making.
Initially, Looker Studio supported only a handful of Google-based data sources. However, the platform has significantly evolved. Now, you can use third-party connectors to access a wide range of non-Google services like LinkedIn, PayPal, Facebook, Twitter, HubSpot, and more through third-party connectors. It's important to note that most of these third-party connectors are not free.
In summary, Looker Studio's ability to integrate with diverse data sources and connectors makes it a great tool for creating detailed and dynamic reports, catering to various data visualization needs.
In Looker Studio, there is a foundation of utilizing two fundamental components: metrics and dimensions. These elements are essential for building the elements for actually transforming raw data into insightful visualizations.
Here's a breakdown of what metrics and dimensions represent in Looker Studio:
Metrics are numerical values used to measure or quantify data. They are derived by applying aggregation functions like COUNT(), SUM(), AVG(), etc., either explicitly or implicitly, to your dataset. Metrics provide quantitative insights into your data and are typically represented as numbers. Examples of metrics include counts, sums, percentages, durations, and currency values.
Dimensions, however, encompass the attributes or characteristics that describe and categorize your data. They provide context to your metrics by offering names, descriptions, or other identifying features of the data you're measuring or counting. Dimensions are used to group and categorize your data in charts and reports. Examples of dimensions include categories like Country, Age, Product ID, Date, or Campaign Name.
In simpler terms, dimensions help organize your data into meaningful groups or categories, while metrics provide the numerical values that quantify aspects of those categories.
Together, metrics and dimensions enable you to create informative and visually appealing dashboards in Looker Studio by effectively summarizing and presenting your data.
Here is a step by step guide on how you can build a report in Looker Studio:
1. Go to the starting page and click on '+ Create” and select ‘Data Source’.
2. Select the desired connector – in our example, Google BigQuery (If you're using OWOX BI, your dataset for reporting is already automatically created in Google BigQuery).
3. Next, give the necessary Google BigQuery permissions to access your data.
4. Select the desired account, project and a dataset.
5. In the top right corner, select the "Connect" button. This will automatically import all the information into Looker Studio.
Use the same procedure, to connect the other data sources.
Once you’ve connected to BigQuery, it’s time to start creating reports in Looker Studio. To initiate a new report, click the Create Blank Report button and choose from built-in templates or start from a blank report to customize your reporting experience.
Looker Studio provides different visual elements:
All visual elements are divided into three groups:
To use these visual elements, you need to:1. Click the "Create Blank Report" button to access the reporting page and start exploring your analytical ideas.
2. Add a visual element. Just indicate which element you want to add and select the area in which you want to add it.
For example, say you’ve selected a pie chart. Here’s what you can do with it:
The first bullet point is intuitive, but the second needs a little explaining. Here’s the list of elements you can work with:
Once you’ve completed all the steps and fine-tuned the settings, you'll have a visual dashboard ready. Below is an example of what such a dashboard might look like:
Your report is ready, you’re satisfied with the outcome, and now it’s time to gather feedback from your colleagues. Go ahead and share it with your team.
There are two ways to do this:
1. In the File menu, choose Share.
2. In the upper right corner, click the Share button.
Choose whichever method you prefer. Then add the emails of your colleagues, click Share and the report is already in their inboxes. You can also schedule report deliver to the emails of the stakeholders or your clients.
Everything you need to know about marketing reporting— from data collection to report templates, dashboards, and the services you need for building them.
Our short Looker Studio tutorial for beginners starts with these 3 simple steps above. But earlier, we've mentioned that Looker Studio has very limited data blending capabilities.
That is why, it's important to note, that if you want to visualize data from multiple sources:
You need to prepare data for your reporting in Looker Studio in advance.
The easiest way to do so is to prepare data for your report in a cloud data warehouse, for example in Google BigQuery in 3 simple steps.
To collect all information from different services automatically and get rid of busy work, use OWOX BI Pipeline. At least you'll need to import Cost data from advertising services, collect website user behavior data with OWOX BI Streaming or setup native GA4 BigQuery export.
NOTE: When directly connecting GA4 to Looker Studio, you can run into limitations of data sampling or quota limitations.
To configure cost data import to Google BigQuery with OWOX BI, everything you need is to provide access to advertising platforms (Facebook, LinkedIn, Bing/Microsoft Ads, Criteo), then provide access to your BigQuery project and all of the data are going to be automatically uploaded (and updated) every day.
In addition, you can use OWOX BI to collect information from CRM/ERP systems, call-tracking, or third-party applications to BigQuery so you'll have the opportunity to compare costs and revenue as well as track important metrics for your business.
Once you've collected all your figures in Google BigQuery, it's time to transform you data.
The data from different data sources is siloed. Different field names, different structures, and formats. BigQuery is a cloud-based data warehouse, perfect for storing raw data, however, it requires SQL knowledge to manipulate the data and blend.
The good news is, that we've already prepared all of the necessary no-code SQL templates that you can apply without any changes in OWOX BI and get your advertising costs merged, GA4 events collected into sessions, attribute paid expenses to sessions, attribution models applied and so much more.
Once you've collected the data and transformed raw data into analytics-ready data, you can prepare your data for reporting - create a dataset with all the necessary information you need for a specific report (or a set of reports).
For example, we've prepared a template for Google Looker Studio with over 50 reports in one for measuring and optimizing all of the main marketing metrics and KPIs.
When you sign up for a free trial of OWOX BI, you'll get access to no-code transformation templates to not only do the basic data manipulations but also to get all of the reports datasets for Google Looker Studio prepared for you.
All with no code. You don't need to hire a data scientist or have SQL coding experience.
Google Looker Studio is a visualization service only. To automatically run more complex calculations and build dashboards based on them, you can use OWOX BI products. For comprehensive guidance on creating dashboards, you can refer to a google looker studio tutorial.
Below are examples of reports built with OWOX BI.
Here you can see how user behavior differs depending on the product category and traffic source:
On the following screen, you’ll be able to see how conversions are distributed based on page type and traffic source. You can also customize the list of sources using a filter:
Want to see more examples? Go to our section with Google Looker Studio dashboard templates by OWOX BI.
If you have any questions concerning marketing problems you want to solve, book a demo, and our specialists will assist you with any questions or issues.
To prepare data for Looker Studio, you typically follow these steps:
- Data Extraction: Gather and extract data from various sources, ensuring it's in a structured format.
- Data Cleaning: Cleanse and preprocess the data by handling missing values, duplicates, and inconsistencies.
- Data Transformation: Transform data as needed, including aggregating, filtering, and joining tables.
- Data Modeling: Create a logical data model that defines relationships between different data sets.
- Data Loading: Load the prepared data into Looker Studio or the connected database.
- Define Metrics and Dimensions: Specify metrics and dimensions to facilitate data analysis.
- Build Reports and Dashboards: Leverage Looker Studio's interface to craft reports and dashboards, facilitating data visualization and analysis.
Looker Studio is primarily used for data visualization and reporting. It enables users to establish connections with a variety of data sources, convert raw data into meaningful visualizations, and construct interactive dashboards and reports. It's commonly used for data analysis, business intelligence, and sharing data-driven insights within organizations, helping users make informed decisions based on data.
You can share your reports and dashboards with others in Google Looker Studio by selecting the "Share" button and choosing the sharing options, such as "Viewer" or "Editor" access.
Yes, you can customize the appearance of your reports and dashboards in Google Looker Studio by downloading custom templates, changing colors, and adding logos or images.
You can connect your data sources to Google Looker Studio by selecting the "Add data" option and then choosing the type of data source, such as Google Analytics, Google Sheets, or a third-party connector.