This course, offered by Meta, provides a deep dive into Meta Marketing Analytics Tools. Participants will learn to create ads using Meta Ads Manager, conduct A/B testing, and analyze campaign results. Additionally, they will explore running experiments, such as brand lift and conversion lift tests, and optimizing marketing mix modeling and attribution. The course equips learners with the skills to evaluate and optimize sales funnels, plan and forecast marketing efforts across various channels, and implement a full analysis process from hypothesis to presenting results.
Key learning points include:
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Get Started / More InfoThe course modules cover fundamentals of Facebook Ads Manager, analyzing campaign results, running Facebook experiments, optimizing marketing mix, and putting marketing analytics into action.
This module introduces learners to the fundamentals of Facebook Ads Manager, covering topics such as the ad auction, campaign structure, planning and scheduling ads, audience selection, and more. Participants will gain insights into the key components and strategies for successful ad management.
Participants will explore the process of analyzing campaign results, focusing on ads manager reporting, customizing reports, and evaluating results against campaign goals. They will also learn about the attribution setting and utilizing the Facebook pixel for effective analysis.
This module delves into running Facebook experiments, including conversion lift tests, brand lift tests, and the evaluation of test results. Participants will gain an understanding of the Facebook Conversion API and best practices for conducting successful experiments.
Learners will delve into optimizing marketing mix through A/B testing, marketing mix modeling, and the latest developments in this area. They will explore the process of setting up and evaluating A/B tests, as well as utilizing marketing mix modeling to achieve desired outcomes.
In this module, participants will put marketing analytics into action by assessing goals and key performance indicators, formulating hypotheses, recommending measurement solutions, performing analysis, and presenting data-driven recommendations. The module also covers communication strategies for effective presentation of results.
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