DIGITAL MARKETING ANALYTICS
with CHIEF ANALYTICS EVANGELIST at Google
17 MAY 2022 - 23 JUN 2022
Duration:
6 WEEKS
TUESDAYS & THURSDAYS
5 PM PST / 8 PM EST
Dive in deep
Learn how to utilize your data and put the right tools to work for your specific needs, with guidance and support from the Chief Analytics Evangelist at Google.
Hands-on and interactive
This online course combines live lectures with 5 practical labs and direct feedback from Kevin on your projects. Hands-on work helps develop your step-by-step approach to planning, collecting, analyzing, and reporting data.
Through the live classes and the lab work, Kevin will be available to answer your questions and provide personalized feedback on your projects. He’ll help you apply data analytics to the real-world challenges you confront daily. You will join a hand-selected community of data-driven professionals who share ideas, experience, and “peer review” support.
HARTMAN LinkedIn Profile
- Chief Analytics Evangelist at Google
- Over 20 years of experience as a devoted and artistic practitioner of data
- Six-time winner of the Advertising Research Foundation Ogilvy Award
- Oversaw the design of marketing insights and strategies behind campaigns that earned 5 Cannes Lions, 5 Effies, over 50 Tempos, and dozens of other awards.
- Author of Digital Marketing Analytics: In Theory And In Practice (2020)
COURSE INTRODUCTION
Explore the landscape of data analysis today, including key privacy issues at stake.
- The ART+ SCIENCE mindset
- Early history of analytics
- Evolution of modern analytics
- GDPR, ITP, data privacy
Assignment #01: Reflect on three roles of analysts. How do these connect with your current role and skills?
Breakdown the go-to channels seasoned analysts use to empower data collection efforts.
- Owned and operated properties
- Online video and search
- Display media
- Social media
- The Consumer Decision Journey
Assignment #02: Use McKinsey’s Consumer Decision Journey to complete the template provided in class. Outline the consumer experience for your industry or company.
Get familiar with software tools used to find patterns in data – and learn to recognize the signs of a story.
- Digital measurement
- Analytics and data visualization tools
- Digital marketing maturity
Assignment #03: Evaluate the marketing maturity of the company of your choice, using the assessment provided in class. Then, position your company on the BCG maturity model.
Let's get practical! Use publicly available tools to identify new opportunities for an aging consumer packaged goods company.
Case study: What Does the Data Say? Hygieia Brands and Data Analysis Tools
Assignment #04: Investigate consumer reactions surrounding Peloton's controversial 2019 holiday commercial. Use Google Trends, Tweet Reach, LIWC, and Facebook Audience Insights to weigh in: was the commercial ultimately positive or negative for the brand?
Use live Google Analytics data to explore and answer important questions about a real-world online merchant.
Case study: Google Merchandise Store. Creating Business Impact with Google Analytics
Assignment #05: Dig deeper into the Google Merchandise Store’s Google Analytics account dashboard. Use your findings to answer sophisticated questions for the business.
Understand the critical role that planning plays in ensuring an effective, efficient, and bias-free data analytics project.
- Navigating to your Big Idea
- Planning for your analytics expedition
- Getting your story straight
- Identifying your business objective
- Case study: Carter Racing
Assignment #06: Read the Bellabeat case study and choose one product to work with. Which of the six marketing objectives discussed in class best serves Bellabeat’s needs?
Work in small groups to create a data analysis plan that addresses Bellabeat's marketing challenge.
Case study: Where Should We Look? Bellabeat and Planning a Data Analytics Journey
Assignment #07: Use the Minto "top-down" or “bottom-up” approach to build an analytics project plan for your company. Your plan should include your hypothesis, 3+ key analysis questions, and 3+ data sources for each key question.
Dive into how analysis projects are implemented! Learn sophisticated techniques to collect and analyze data.
- Collecting data from everywhere
- Preparing data for analysis
- Analyzing for patterns and insights
Assignment #08: Jump into the Python vs. R debate. Which tool is better for your organization? Why? Post your thoughts.
Learn how to use tools including Google Sheets, SQL, and R to create manageable datasets.
Case study: What's the Next Big Thing? Netflix and Analyzing Data for Insights
Assignment #09: Use the techniques demonstrated in today’s lab to analyze a provided dataset for Netflix (or, alternatively, data from your own company). What trends and opportunities do you see? Make slides breaking down your analysis that help address the identified business challenge.
Discover the science behind good data visualization in order to tell actionable data stories to stakeholders.
- Seeing pictures with your brain
- Evaluation framework for visual presentations
- Clarifying meaning with contrast and common chart elements
- Refined execution and chart polish
Use a sequence of tools – spreadsheets, dataviz software, and presentation software – to transform visually lacking charts. The end result of your work in this lab will be a client-ready, compelling data visualization.
Case study: Sophisticated, Clear, and Polished. Divvy and Data Visualization
Assignment #10: Use techniques and tools to produce a series of client-ready charts from a provided dataset for Divvy (or, alternatively, data from your own company) based on concepts introduced in today’s lab.
Explore the nuanced ethical issues surrounding digital data in marketing today.
- The promise of technology
- Technology’s dark side
- Course review
- Case study: VLBA and the Ethics of Data Science
In this final project, you'll bring the approaches, tools, and open sources of data learned in class to solve a business challenge for a real company.
Your task will be to conduct an end-to-end analysis for an Irish history podcast creator looking to take his product to the US market.
Using additional data sources provided by Kevin, your final deliverable will be data-based recommendations to the podcast team on how to capture a new market across the pond.
What our students say
"Kevin's ability to answer questions and help all students regardless of their company size is what I appreciate the most. We all have a different story as to why we are taking the class yet this class has highlighted our common goals to learn more and be enlightened by an industry leader. It's been an amazing learning experience and I'm happy to be a part of it. Thank you so much!"
"Being able to apply the learnings to real world situations. After the first lessons with Kevin I had moments where I was applying those concepts at work the following day."
"Digital Marketing Analytics is a well-structured course, starting with a more general overview and moving into lessons with concrete advice that can immediately be applied to my real-world job. The highlight of the course is Kevin as an instructor though! He's both approachable and knowledgeable as his enthusiasm for data and teaching shine through. Overall, an excellent experience!"
"It's very informative and easy to follow"
"Very well structured with plenty of opportunities for application"
"Kevin is so great! He makes everyone feel like a part of a team and is receptive to everyone's questions. The information/coursework is also amazing! The lessons, resources, and homework is well thought out and I'm excited to put them to use in my own company!"
"The instructor is very good at understanding our questions and his answers are always spot on. I also like a lot the fact that it is a live class and we can all interact. The content is also very good, I don't come from analytics at all and I find the content advance but accessible."
"I really liked the case studies. It gave me an opportunity to practice what we had learned in class and make sure I was understanding it"