Stanford Continuing Studies course "Data-Driven Marketing" by Angel Evan — Customer Insights and Analytics Consultant, January 16 - March 2, 2018 (7 weeks)
BUS 139 is a course for those interested in developing a set of foundational skills in the use of marketing-related data. It is expressly designed for students without math,quantitative or statistical backgrounds and requires no expensive third-party software of hardware—only a Mac or PC version of Microsoft Excel 2013 or later. Each session deals with a core data concept and is supplemented with “how-to” videos and exercises on a variety of tasks marketers commonly perform.
Tableau Public is an incredibly powerful business intelligence tool used extensively in analytics. In fact, it's what Angel Evan uses at his agency.
Week 1: Introduction and Goal Setting
- Cursory overview of the class and its goals
- Examining the delta between the promise of data and marketers’ ability to act
- Overview of various marketing data types and how they differ
- Three simple rules for dealing with data
- Qualitative vs. quantitative data, including when to use each
- Examples of how data can be used to make better business decisions
- Setting Goals – determining what a real goal is and what’s important to track
Week 2: Collection and Preparation
- The four inputs – a review of the various sources of data and how they can be gathered
- Determining the best sources of data – which data is trustworthy
- Customer attributes – determining which truly matter to your business, e.g.,demographics, psychographics, purchasing behavior
- What to do if your data isn’t perfect, e.g., dealing with missing values and how to deal with noisy data
Week 3: Analysis and Interpretation
- Using summary statistics to create immediate insights
- Creating simple formulas that lead to big insights
- Seeing through the lies in data
- Identifying trends, e.g., seasonal trends and customer lifecycle trends
- Segmentation and correlation (positive and negative)
- Sorting, ranking, binning, and filtering
- Using visualization techniques to improve understanding
- Co-mingling data from different sources, e.g., website and social media
Week 4: Decision
- Using data to measure the success of marketing outcomes
- The anatomy of a marketing strategy
- Making data ladder up to real business objectives
- Separating decisions from outcomes
- Placing bets – determining which marketing tactics and channels to invest in
Week 5: Visualization
- Overview of visualization basics
- Examples of good and bad data visualization
- Determining the best format for visualizing your information
- Seven basic types of charts
- Charts vs. infographics vs. data visualization
- Deciding which patterns are worth highlighting and what to emphasize
Week 6: Presentation
- Determining what story you want your data to tell and how best to bring it to life
- The power of narrative
- Three types of presentations for delivering a forceful argument
Week 7: Prediction and Forecasting
- Overview of various predictive analytics and forecasting methodologies
- Forecasting vs. predicting
- Linear vs. logistic regression
- Introduction to basic Artificial Intelligence (AI) models and machine learning
- The basics of predictive algorithms and how they can be used in marketing