About this course: With marketers are poised to be the largest users of data within the organization, there is a need to make sense of the variety of consumer data that the organization collects. Surveys, transaction histories and billing records can all provide insight into consumers’ future behavior, provided that they are interpreted correctly. In Introduction to Marketing Analytics, we introduce the tools that learners will need to convert raw data into marketing insights. The included exercises are conducted using Microsoft Excel, ensuring that learners will have the tools they need to extract information from the data available to them. The course provides learners with exposure to essential tools including exploratory data analysis, as well as regression methods that can be used to investigate the impact of marketing activity on aggregate data (e.g., sales) and on individual-level choice data (e.g., brand choices). To successfully complete the assignments in this course, you will require Microsoft Excel. If you do not have Excel, you can download a free 30-day trial here: https://products.office.com/en-us/try
Who is this class for: This course is aimed at those familiar with business and marketing concepts or those currently working in a business analyst or marketing research role.
Taught by: David Schweidel, Associate Professor of Marketing
Goizueta Business School
| Basic Info |
Course 1 of 6 in the
Foundations of Marketing Analytics Specialization.
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| Level | Intermediate |
| Commitment | 5 weeks of study, 2-3 hours/week |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
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|---|---|---|
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| Access to graded materials | Not available | Available |
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Great content. The hands-on approach and the use of actual tools with basic software are just great.
Very interesting course with lots of career pertinent information and learning.
well explained. It would be more good if an entirely new worksheet is given for work at the end of course
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CM
I would have liked more discussion of theory behind what the formulas were and, actually, using slicers for data so that clients couldn't "break" the file unintentionally. Otherwise, it was a good basic course, a little too dependent on showing Excel rather than saying why something worked (IF clauses are a good example here, cutting and pasting formulas is not as helpful to my personal learning style as just explaining the rationale behind them.)