Analytics for marketing specialists and digital analysts

This guide is for marketers and data analysts who are already familiar with digital marketing and want to explore how to set up and use Google Analytics, including advanced features and capabilities across different specializations.

Step 1: Begin to collect data

In this section, you will learn to set up a property on your website or app, use events to collect more data, set up conversions for the actions that are valuable to your business, and tag your URLs to attribute conversions properly.

Part 1
Discover how to set up Google Analytics for your website or app by creating a Google Analytics 4 property, adding a data stream, and adding your Google Analytics code.
Part 2
Learn about Google Analytics events including the different types of events, how they are grouped together, and implementation steps.
Part 3
Gain insights into the actions that are most important to your business by marking important actions as conversions and then using that data to improve your marketing efforts.
Part 4
Activate Google signals to get session data from sites and apps that Google associates with users who have signed in to their Google accounts and who have turned on Ads Personalization.
Advanced topic
Send user IDs generated by your business to your Analytics property. The User-ID feature lets you associate your own identifiers with individual users so you can connect their behavior across different sessions and on various devices and platforms.
Advanced topic
Upload data from external sources and join it with your Analytics data. You can export those CSV files from an offline business tool like your CRM or CMS system, or for smaller amounts of data, you can create the files manually in a text editor or spreadsheet.
Advanced topic
Enhance the data in your web and app streams by sending events directly to Google Analytics servers via HTTP requests. Notably, this makes it easy to measure interactions that happen server-to-server and offline.

Step 2: Enhance your advertising

In this section, you will learn how to link your Google Ads account to your Analytics property to see the entire customer cycle, from how users interact with your marketing to how they finally complete the goals you’ve set for them on your site or app.

Part 1
Discover how to link your Google Ad account to a Google Analytics property to see the full customer cycle, from first interaction to goal completion.
Part 2
Discover how to use the URL builder in Google Analytics to add UTM parameters in order to identify the campaigns that refer traffic.
Part 3
Explore how you can use audiences to segment your users in the ways that are important to your business. You can share audiences with the advertising products you use, like Google Ads, so you can market to specific groups of users.

Step 3: Visualize your data

Google Analytics collects data from your websites and apps to create reports that provide insights into your business. In this section, you will learn to see the data you've collected in the available reports, how to customize reports, and how to use more advanced tools to access the data.

Part 1
Explore our reporting guide to understand the basics of reports and see examples of the kinds of data that is collected. You can use reports to monitor traffic, investigate data, and better understand user activity.
Part 2
Explore the touchpoints along a user's path to conversion and how well each of your channels perform.
Part 3
Visualize your Google Analytics data through highly configurable charts and tables, using a subset of the fields available in the Google Analytics Data API, including any custom fields defined for the property.
Advanced topic
Create dimensions and metrics from event parameters and user properties so you can easily access data in reports and explorations.
Advanced topic
Get programmatic access to Google Analytics so you can create reports, build custom dashboards, automate complex reporting tasks, and integrate your data with other business applications.
Advanced topic
Export all of your raw events from Google Analytics (including subproperties and roll-up properties) to BigQuery, and then use an SQL-like syntax to query that data/