How to Track Events with Google Analytics 4 (Updated in 2022)
This video provides an overview of how to track events with Google Analytics 4. It explains the automatically tracked events, enhanced measurement, recommended events, and how to create custom events. It also covers how to create events from the interface and how to set up event tracking in Google Tag Manager. ▼
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Course Feature
Cost:
Free
Provider:
Youtube
Certificate:
Paid Certification
Language:
English
Start Date:
On-Demand
Course Overview
❗The content presented here is sourced directly from Youtube platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [February 21st, 2023]
This course provides an overview of how to track events with Google Analytics 4 (Updated in 2022). It covers topics such as automatically tracked events in Google Analytics 4, Enhanced Measurement, Recommended events in GA4, Custom events in Google Analytics 4, Create events in GA4 from the interface, and Modify events in Google Analytics 4. Participants will gain an understanding of how to use Google Analytics 4 to track events and gain insights into their website performance. At the end of the course, participants will have the knowledge and skills to create and modify events in Google Analytics 4.
[Applications]
After completing this course, users can apply the knowledge gained to track events with Google Analytics 4. They can use the automatically tracked events, Enhanced Measurement, and Recommended events to gain insights into their website's performance. Additionally, users can create and modify Custom events in Google Analytics 4 to gain a deeper understanding of their website's performance. Finally, users can use the insights gained from tracking events to make informed decisions about their website's performance.
[Career Paths]
Career Paths:
1. Digital Marketing Analyst: Digital marketing analysts use data from Google Analytics 4 to track and analyze user behavior on websites and mobile apps. They use this data to create marketing strategies and campaigns that are tailored to the needs of their target audience. They also use this data to measure the success of their campaigns and make adjustments as needed.
2. Data Scientist: Data scientists use Google Analytics 4 to analyze user behavior and create predictive models. They use this data to identify trends and patterns in user behavior and develop strategies to improve user experience. They also use this data to create reports and insights that can be used to inform business decisions.
3. Web Developer: Web developers use Google Analytics 4 to track user behavior on websites and mobile apps. They use this data to identify areas of improvement and create better user experiences. They also use this data to optimize websites and mobile apps for better performance.
Developing Trends:
1. Machine Learning: Machine learning is becoming increasingly important in digital marketing and data science. Machine learning algorithms can be used to analyze user behavior and create predictive models. This can help marketers and data scientists to better understand user behavior and create more effective strategies.
2. Automation: Automation is becoming increasingly important in web development. Automation tools can be used to automate tasks such as tracking user behavior, creating reports, and optimizing websites and mobile apps. This can help web developers to save time and create better user experiences.
3. AI-Powered Analytics: AI-powered analytics are becoming increasingly important in digital marketing and data science. AI-powered analytics can be used to analyze user behavior and create predictive models. This can help marketers and data scientists to better understand user behavior and create more effective strategies.
[Education Paths]
1. Bachelor's Degree in Computer Science: This degree path provides students with the knowledge and skills to develop, design, and maintain computer systems and networks. It also covers topics such as programming, software engineering, and data structures. With the increasing demand for technology, this degree path is becoming more popular and is expected to continue to grow in the future.
2. Master's Degree in Data Science: This degree path focuses on the analysis and interpretation of data. It covers topics such as machine learning, data mining, and predictive analytics. With the rise of big data, this degree path is becoming increasingly popular and is expected to continue to grow in the future.
3. Bachelor's Degree in Information Technology: This degree path focuses on the development and management of information systems. It covers topics such as database design, network security, and web development. With the increasing demand for technology, this degree path is becoming more popular and is expected to continue to grow in the future.
4. Master's Degree in Business Analytics: This degree path focuses on the analysis and interpretation of business data. It covers topics such as data mining, predictive analytics, and decision-making. With the rise of big data, this degree path is becoming increasingly popular and is expected to continue to grow in the future.
Course Provider
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