live online course

DIGITAL MARKETING ANALYTICS

Kevin Hartman
KEVIN HARTMAN
Director of Analytics / Google
January 19
– February 25
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A LIVE ONLINE COURSE with Director of Analytics at Google
6 weeks
19 Jan 2021 - 25 Feb 2021
Successful marketing requires a delicate blend of art and science. Google’s Director of Analytics, Kevin Hartman, will teach you to address the real problems your company faces through hands-on projects and personalized feedback. Kevin will share the unconventional and creative methods he uses to pull illuminating insights from data.
Growth driver

Dive in deep

Learn how to utilize your analytics and put the right tools to work for your needs, with guidance and support from the Director of Analytics at Google.

Hands-on and interactive

This online course combines live lectures with 4 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.

 
ABOUT THE COURSE
01
The next level in data
Kevin will help you master web analytics for data-driven decision making in marketing programs, media placement, and business strategy. He will show you how to use leading data processing techniques, like performing bulk downloads, tapping APIs, and scraping web pages. You’ll work with Excel, Google Sheets, R, RStudio, Powerpoint, Keynote, Google Slides, and Tableau.
02
Creative and Effective Data Visualization
You’ll learn how to visualize big data, not just for impressive-looking reports, but to understand tendencies and present them in a meaningful and digestible way for the whole team.
03
Personalized feedback

Through live classes and lab work answer your questions and provide you personalize feedback. He’ll work with you to help you apply data analytics.

Instructor
KEVIN
HARTMAN
  • Director of Analytics, 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)
KEVIN HARTMAN
COURSE INTRODUCTION
 
SYLLABUS
01
TUE (1/19) at 8 PM ET
The State of Marketing Analytics Today
  • The ART+SCIENCE mind
  • The early history of analytics
  • The contemporary history of analytics
  • The rise of modern analytics
  • The consumer’s experience today

Assignment: Introduce yourself and share reflections on three roles of the analyst and your current function & skills.

02
THU (1/21) at 8 PM ET
The Channels Of Brand-Consumer Relationships
  • Online video
  • Online search
  • Display media
  • Social media
  • The Consumer Decision Journey

Assignment: Complete a template provided in class details the experience of consumers in their industry (or an industry of their choice) along the steps of McKinsey’s Consumer Decision Journey.

03
TUE (1/26) at 8 PM ET
The Science Of Analytics
  • Digital data infrastructure
  • GDPR and data regulation
  • ITP and technology owners' response to privacy
  • Digital measurement
  • Analytics and dataviz tools
  • Digital marketing maturity

Assignment: Use the provided template to detail output from Bain & Company’s seven-question online assessment of Marketing Maturity for your organization (or the organization of your choice).

04
THU (1/28) at 8 PM ET
Collecting Data: Analytics Tools Lab

Assignment: With the help of digital tools discussed in class (Google Trends for search data, Tweet Reach for Twitter data, and LIWC for sentiment analysis) investigate consumer reaction surrounding the Peloton Holiday Commercial of 2019 and decide if the marketing value created by the commercial and its fallout was positive or negative for the brand.

05
TUE (2/2) at 8 PM ET
The Art Of Analytics, p.1
  • Navigating to your Big Idea
  • Planning for your analytics expedition
  • Getting your story straight

Assignment: After reading the Bellabeat case study, choose one product and provide a brief statement on the marketing objective you think best serves Bellabeat’s needs. Select your marketing objective from the list of probable marketing objectives from "The Six Marketing Objectives" discussed in class.

06
THU (2/4) at 8 PM ET
Planning For Analysis: Bellabeat Case Study Lab

Assignment: Based on the approach demonstrated through the Bellabeat case study, build an analytics project plan for your organization (or an organization of your choice) that will help the company achieve a marketing objective on the selected topic. The plan should include your hypothesis, at least three key questions for analysis, and at least three pieces of data + sources for that data for each key question. Use the Minto "Top-Down" or “Bottom-Up” approach to construct your plan.

07
TUE (2/9) at 8 PM ET
The Art Of Analytics, p.2
  • Collecting data, data everywhere
  • Preparing data for analysis
  • Analyzing for insights

Assignment: Jump into the Python vs R debate. Which tool is better for your organization? Why? Post your thoughts.

08
THU (2/11) at 8 PM ET
Analyzing Data: Netflix Case Study Lab

Assignment: Utilize tools and techniques demonstrated in class to analyze a provided dataset for trends in consumer interest and behaviors that could point Netflix to the next Big Thing in the world of content licensing and distribution.

09
TUE (2/16) at 8 PM ET
Storytelling With Data, p.1
  • Class review for quiz (provide a study guide...encourage students to work in groups and post questions to class Stream)
  • Pictures you see with your brain
  • Evaluation framework for the visual form
  • Sophisticated use of contrast
10
THU (2/18) at 8 PM ET
Storytelling With Data, p.2
  • Ensuring clear meaning
  • Refined execution through visual polish
  • Delivering numbers with impact
  • On your feet and getting your story across

Assignment: A short, multiple choice knowledge check quiz to be taken online

11
TUE (2/23) at 8 PM ET
Expressing Data Visually: Data Visualization Lab

Assignment/Final Project: Using a number of data analysis and visualization tools, including spreadsheet tools, R, and Tableau, mine a provided dataset. After finding important patterns in the data, create a data visualization that effectively demonstrates contrast, critical chart elements, and refined execution to communicate your insights.
This assignment will teach you to mine data for insights using tools that range from simplistic to sophisticated. In addition, you will learn how to create “client-ready” data visualizations.

12
THU (2/25) at 8 PM ET
The Future Of Analytics & The Promise Of Technology
  • Technology’s promise
  • Technology’s dark side
  • The issue of privacy
  • Course Review

Final Test

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