Digital Marketing Analytics in Practice (Coursera)

Digital Marketing Analytics in Practice (Coursera)

Successfully marketing brands today requires a well-balanced blend of art and science. This course introduces students to the science of web analytics while casting a keen eye toward the artful use of numbers found in the digital space. The goal is to provide the foundation needed to apply data analytics to real-world challenges marketers confront daily. Students will learn to identify the web analytic tool right for their specific needs; understand valid and reliable ways to collect, analyze, and visualize data from the web; and utilize data in decision making for agencies, organizations or clients.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

Digital Analytics for Marketing Professionals: Marketing Analytics in Practice is the second in a two-part series of complementary courses and focuses on the skills and practical abilities analysts need to be successful in today's digital business world.
Course 3 of 7 in the Digital Marketing Specialization.

What You Will Learn

  • Gain hands-on, working knowledge of a step-by-step approach to planning, collecting, analyzing, and reporting data
  • Learn to evaluate and choose appropriate web analytics tools and techniques
  • Utilize tools to collect data using today’s most important online techniques: performing bulk downloads, tapping APIs, and scraping webpages
  • Understand approaches to visualizing data effectively

Syllabus

WEEK 1
Course Overview and The Art of Analytics
In the orientation, you will become familiar with the course, your instructor, your classmates, and our learning environment. The orientation also helps you obtain the technical skills required for the course. Every analyst dreams of coming up with the “big idea” – the game-changing and previously unseen insight or approach that gives their organization a competitive advantage and their career a huge boost. But dreaming won’t get you there. It requires a thoughtful and disciplined approach to analysis projects. In this part of the course, I detail the four elements of the Marketing Analytics Process (MAP): plan, collect, analyze, report. Module 1 also explains the role of the analyst, the six mutually exclusive and collectively exhaustive (“MECE”) marketing objectives of analytics, how to find context and patterns in collected data, and how to avoid the pitfalls of bias.

WEEK 2
Storytelling with Data
In Module 2, we dive headlong into the most important aspect of digital marketing analytics: transforming the data the analyst compiled into a comprehensive, coherent, and meaningful report. I outline the key characteristics of good visuals and the minutiae of chart design and provide a five-step process for analysts to follow when they’re on their feet and presenting to an audience. The goal is to equip analysts with the tools they need to tell a compelling and memorable story that “cuts through the noise” of the overwhelming amount of information audiences experience every day.

WEEK 3
Bellabeat Case Study
Module 3 brings to life the concepts, theories, techniques, and tools discussed in the course in a business case written about Bellabeat, a high-tech design and manufacturing company that produced health-focused smart devices for women. Students will see each step in the MAP illustrated through the case.

WEEK 4
The Future of Analytics
Data’s road from crude maps to gigabytes of multidimensional information has been a long and winding one. But it is far from over. If anything, the industry finds itself at a critical crossroads that will determine its future for decades to come. Module 4 explores this predicament while casting an eye toward what comes next for digital marketing analytics.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Practical Time Series Analysis (Coursera) Coursera
The State University of New York

Practical Time Series Analysis (Coursera)

Many of us are "accidental" data analysts. We trained in the sciences, business, or engineering and then found ourselves confronted with data for which we have no formal analytic training. This course is designed for people with some technical competencies who would like more than a "cookbook" approach, but who still need to concentrate on the routine sorts of presentation and analysis that deepen the understanding of our professional topics.

Nov 2nd 2026
5-12 Weeks
Marketing Verde (Coursera) Coursera
Universidad de los Andes

Marketing Verde (Coursera)

Al finalizar este curso serás capaz de diseñar y ejecutar campañas para productos, servicios o iniciativas relacionadas con algún tema ambiental, así como también de crear propuestas de valor para cualquier producto o servicio con criterios de sostenibilidad ambiental, es decir, generando el mayor valor para la marca y el menor impacto posible en el entorno.

Oct 26th 2026
5-12 Weeks
Publicidad Digital con Google AdWords (Coursera) Coursera
Universidad Austral

Publicidad Digital con Google AdWords (Coursera)

En este curso de Google Adwords, aprenderás sobre los conceptos fundamentales y técnicas avanzadas de la publicidad en Google. Con estos, serás capaz de crear, publicar y optimizar correctamente campañas para promocionar las marcas, productos o servicios que desee en una de las herramientas publicitarias más poderosas del mundo. El curso profundiza tanto en la red de Búsqueda como la red de Display, detallando sus aspectos teóricos y prácticos desde la propia herramienta.

Nov 2nd 2026
4 Weeks
Population Health: Predictive Analytics (Coursera) Coursera
Leiden University

Population Health: Predictive Analytics (Coursera)

Predictive analytics has a longstanding tradition in medicine. Developing better prediction models is a critical step in the pursuit of improved health care: we need these tools to guide our decision-making on preventive measures, and individualized treatments. In order to effectively use and develop these models, we must understand them better. In this course, you will learn how to make accurate prediction tools, and how to assess their validity. First, we will discuss the role of predictive analytics for prevention, diagnosis, and effectiveness. Then, we look at key concepts such as study design, sample size and overfitting.

Oct 26th 2026
4 Weeks
Supply Chain Analytics Essentials (Coursera) Coursera
Rutgers University

Supply Chain Analytics Essentials (Coursera)

In this introductory course to Supply Chain Analytics, I will take you on a journey to this fascinating area where supply chain management meets data analytics. You will learn real life examples on how analytics can be applied to various domains of a supply chain, from selling, to logistics, production and sourcing, to generate a significant social / economic impact.

Nov 2nd 2026
4 Weeks
Data science perspectives on pandemic management (Coursera) Coursera
Politecnico di Milano

Data science perspectives on pandemic management (Coursera)

The COVID-19 pandemic is one of the first world-wide scenarios where data made a difference in capturing and analyzing the diffusion and impact of the disease. We offer an introductory course for decision makers, policy makers, public bodies, NGOs, and private organizations about methods, tools, and experiences on the use of data for managing current and future pandemic scenarios.

Nov 2nd 2026
5-12 Weeks
Marketing estratégico: claves para competir con éxito (Coursera) Coursera
IESE Business School

Marketing estratégico: claves para competir con éxito (Coursera)

El papel del marketing difiere entre empresas y sectores. Además, la visión que los profesionales tienen del mismo depende del nivel jerárquico dentro de la organización, así como del bagaje profesional de cada uno. Quizá por ello, a menudo es mal entendido y reducido a un nivel táctico exclusivamente de comunicación.

Nov 2nd 2026
4 Weeks
From Excel to Power BI (Coursera) Coursera
Knowledge Accelerators

From Excel to Power BI (Coursera)

Are you using Excel to manage, analyze, and visualize your data? Would you like to do more? Perhaps you've considered Power BI as an alternative, but have been intimidated by the idea of working in an advanced environment. The fact is, many of the same tools and mechanisms exist across both these Microsoft products. This means Excel users are actually uniquely positioned to transition to data modeling and visualization in Power BI! Using methods that will feel familiar, you can learn to use Power BI to make data-driven business decisions using large volumes of data.

Nov 2nd 2026
1 Week
Functional Programming in Scala Capstone (Coursera) Coursera
École Polytechnique Fédérale de Lausanne

Functional Programming in Scala Capstone (Coursera)

In the final capstone project you will apply the skills you learned by building a large data-intensive application using real-world data. You will implement a complete application processing several gigabytes of data. This application will show interactive visualizations of the evolution of temperatures over time all over the world.

Nov 2nd 2026
5-12 Weeks
HI-FIVE: Health Informatics For Innovation, Value & Enrichment (Administrative/IT Perspective) (Coursera) Coursera
Columbia University

HI-FIVE: Health Informatics For Innovation, Value & Enrichment (Administrative/IT Perspective) (Coursera)

HI-FIVE (Health Informatics For Innovation, Value & Enrichment) Training is an approximately 10-hour online course designed by Columbia University in 2016, with sponsorship from the Office of the National Coordinator for Health Information Technology (ONC). The training is role-based and uses case scenarios. No additional hardware or software are required for this course. Our nation’s healthcare system is changing at a rapid pace.

Oct 26th 2026
4 Weeks