Digital Marketing 2 from Coursera

Businesses today have access to an increasingly large amount of detailed customer data, and this influx of “big data” is only going to continue. Combined with a detailed history of marketing actions, there is a newfound potential for deriving actionable insights, but you need the tools to do so. Using real-world applications from various industries, this course will help you understand the tools and strategies used to make data-driven decisions that you can put to use in your own company or business.

This valuable data may include in-store and online customer transactions, customer surveys, web analytics, as well as prices and advertising. You’ll also learn how to assess critical managerial problems, develop relevant hypotheses, analyze data and, most importantly, draw inferences to create convincing narratives which yield actionable results. Artificial intelligence and machine learning will be explored as tools to deepen analytical skills and acumen and hone decision-making.

This comprehensive exploration into digital marketing analytics tools and techniques is critical knowledge for marketing influencers, digital marketing analysts, and product and brand decision-makers within small and medium businesses as well as larger organizations with international reach.

What You'll Learn in this Course:

Learn how to leverage leading tools and approaches to digital marketing data analysis. Dive into Search Engine Marketing and Website analytics, online testing, machine learning, and AI/Big Data applications to strengthen your digital marketing efforts and leverage your resources most effectively.

Course Objectives:

This course will cover the fundamentals of digital marketing.

By the end of this course, you will be able to:

1- Analyze and assess the performance of paid search campaigns, diagnose potential problems, and recommend adjustments to the digital marketing campaign.

2- Describe the importance of Search Engine Optimization and Recommendation Systems in digital environments.

3- Evaluate campaign analytics and use online testing to determine how design affects the performance of a digital marketing campaign.

4- Describe the Paradigm shift in machine learning methods.

5- Identify the process of evaluating the performance of machine learning algorithms.

6- Describe the expanding application of big data as they apply to neural networks.

What's inside

Syllabus

SEO, Paid Search, and Web Analytics

Welcome to Week 1 of your course. Each week will have a similar format. The weekly page will first provide an overview of the content we will cover. As you work your way down the page, you will see that the content is divided into sections. Navigate through each lesson on the page to complete the assigned work. Work your way through each item in the lessons to watch videos, read assigned articles, participate in discussions, and complete assignments. You should expect to spend at least 30-minutes in total watching seven short videos. In addition to the videos and readings, you will have practice questions, a few activities, and a scenario at the end of the week. These activities and scenarios are essential to helping you learn and apply the skills you will need to demonstrate and master Digital Marketing Analytics.

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Examines how rich data enhances analytical capacity to make qualitative to quantitative analytical data and machine learning to deep learning AI, resulting in a better understanding of consumer behavior

Introduces big data and artificial intelligence, along with the use of rich data and enhanced analytical capacity to move beyond qualitative to quantitative analytical data

Suitable for marketing influencers, digital marketing analysts, and product and brand decision-makers in small and medium businesses and large organizations

Led by instructors Arifa Garman and Ada Crutchfield

Taught by Arifa Garman and Ada Crutchfield, who are recognized for their work in digital marketing analytics

Leverages a range of real-world applications from multiple industries

Reviews summary

Data-driven digital marketing mastery

According to students, Digital Marketing 2 is a highly valuable course for professionals seeking to enhance their data analytics skills in marketing. Learners praise the program for its practical, real-world applications, particularly in areas like SEO, paid search, and web analytics. Many found the focus on machine learning and AI to be particularly forward-thinking and relevant. While some reviewers noted the pace can be fast or that it assumes some prior knowledge, the overall consensus is that the course provides actionable insights and tools for making data-driven decisions. The instructor's insights and hands-on activities are frequently highlighted as strengths, making it a solid choice for career development.

Instructor provides clear explanations and updates course content.

"The instructor's explanations were clear and concise, making complex topics easier to grasp and apply."

"It's great to see that the course content has been updated, showing the instructor is responsive to feedback and current trends."

"I really valued the instructor's insights and the way they presented the material, making it very engaging."

Provides a broad and fundamental understanding of digital marketing analytics.

"This course covers a wide array of topics from SEO to AI, providing a very comprehensive understanding of the field."

"I feel like I got a really good grasp of the fundamentals across different aspects of digital marketing analytics."

"The structure covering SEO, Paid Search, Web Analytics, ML, and AI was well-thought-out and thorough, covering key areas."

Covers cutting-edge topics like AI, machine learning, and big data.

"The deep dive into machine learning and AI for marketing was exactly what I needed to stay competitive in the industry."

"I appreciated the focus on big data and neural networks; it broadened my understanding significantly."

"The course did a great job of integrating AI/ML concepts into practical digital marketing scenarios, which felt very relevant."

Provides actionable strategies for real-world marketing scenarios.

"I found this course incredibly helpful; it gave me practical tools and strategies I could immediately apply to my marketing campaigns."

"The scenarios and activities were excellent, really helping me understand how to make data-driven decisions in my role."

"This course delivers on its promise of real-world applications. The modules on web analytics were particularly insightful."

Moves quickly and may benefit those with some prior experience.

"The course moved quite fast, and I felt it would be more challenging if you're a complete beginner in marketing analytics."

"While valuable, I think some prior exposure to digital marketing or data concepts would make it easier to follow the content."

"I had to spend extra time on some topics as the pace was brisk, but the material is solid if you push through it."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Digital Marketing 2 with these activities:

Join a Study Group for Digital Marketing Analytics Concepts

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Engaging in peer discussions will foster a better understanding of course concepts and provide diverse perspectives.

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Connect with classmates or join online forums to form a study group.
Establish regular meeting times to discuss assigned readings, assignments, and concepts.
Take turns leading discussions and presenting different perspectives.
Support each other with questions, explanations, and encouragement.

Solve Practice Questions on SEO Fundamentals

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Practicing SEO fundamentals through drills will help you solidify your understanding and prepare you for real-world scenarios.

Browse courses on Search Engine Optimization

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Review the provided materials on SEO basics.
Attempt the practice questions covering topics like keyword research, on-page optimization, and link building.
Check your answers and review the explanations to identify areas for improvement.

Compile a Resource Guide on Digital Marketing Analytics Tools

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Creating a resource guide will help you stay updated on the latest tools and technologies used in digital marketing analytics.

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Research and identify various digital marketing analytics tools available.
Categorize the tools based on their functionalities, such as web analytics, social media analytics, or email marketing analytics.
Compile a list of the tools, including their key features, pricing, and links to their websites.
Share the resource guide with classmates or industry professionals.

Four other activities

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Conduct A/B Testing on Website Elements

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Hands-on A/B testing will provide you with practical experience in optimizing website elements for better performance.

Browse courses on A/B Testing

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Identify a website element to test, such as a headline, call-to-action, or layout.
Create variations of the element with different design or content.
Use a tool or platform to set up the A/B test and collect data.
Analyze the results to determine which variation performs better.
Implement the winning variation on your website.

Complete Online Tutorials on Machine Learning Algorithms

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Following online tutorials on machine learning algorithms will enhance your understanding of their applications and practical implementation.

Browse courses on Machine Learning Algorithms

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Identify reputable online platforms or courses offering tutorials on machine learning algorithms.
Choose tutorials that cover algorithms relevant to digital marketing, such as supervised and unsupervised learning.
Follow the tutorials, experiment with code examples, and take notes on key concepts.
Apply the learned techniques to practical scenarios or projects.

Attend a Workshop on Data Visualization for Digital Marketing

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Attending a workshop on data visualization will enhance your skills in presenting data effectively, which is crucial for digital marketing analytics.

Browse courses on Data Visualization

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Research and identify relevant workshops offered by industry professionals or organizations.
Register and attend the workshop.
Actively participate in the sessions, take notes, and ask questions.
Apply the learned techniques to your own digital marketing projects.

Read 'Digital Marketing Analytics' by Chuck Hemann

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This book provides a comprehensive overview of digital marketing analytics techniques and their applications, which will complement the course content.

View Digital Marketing Analytics: Making Sense of... on Amazon

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Read the assigned chapters on topics like web analytics, paid search, and social media analytics.
Take notes and highlight key concepts.
Complete the chapter exercises to apply your understanding.

Career center

Learners who complete Digital Marketing 2 will develop knowledge and skills that may be useful to these careers:

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Digital Marketing 2

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Reviews summary

Data-driven digital marketing mastery

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