Acerca de este curso: 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
Para quién es esta clase: This course is aimed at those familiar with business and marketing concepts or those currently working in a business analyst or marketing research role.
Enseñado por: David Schweidel, Associate Professor of Marketing
Goizueta Business School
| Información básica | Curso 1 de 6 en Foundations of Marketing Analytics Specialization |
| Nivel | Intermediate |
| Compromiso | 5 weeks of study, 2-3 hours/week |
| Idioma | English |
| Cómo aprobar | Aprueba todas las tareas calificadas para completar el curso. |
| Calificaciones del usuario |
- Vídeo: Meet Dr. Schweidel
- Reading: Getting Started
- Reading: A Note About Exercises & Quizzes
- Discussion Prompt: Introduce Yourself
- Vídeo: Course Objectives & Example 1: Political Advertising Expenditures
- Vídeo: Course Goals & Example 2: Performing Arts Centers
- Vídeo: Organizing Data
- Vídeo: The Motion Picture Industry
- Reading: How Companies Learn Your Secrets
- Reading: Big Data in the Big Apple
- Discussion Prompt: Categorical Variables in the Motion Picture Industry
- Reading: Motion Picture Industry Example Data Set
- Vídeo: Excel Analysis of Motion Picture Industry Data
- Vídeo: Displaying Conditional Distributions
- Vídeo: Analyzing Qualitative Variables
- Vídeo: Steps in Constructing Histograms
- Vídeo: Common Descriptive Statistics for Quantitative Data
- Reading: Giving Viewers What They Want
- Reading: Why Personalization is Key for Content Marketing
- Reading: Assignment: Survey Analysis Assignment
- Discussion Prompt: Visualizing Data: Technique Review
- Vídeo: Regression-Based Modeling
- Vídeo: Introduction to Customer Analytics
- Vídeo: Customer Choices Drive Business Decisions
- Vídeo: Illustrating Customer Analytics in Excel
- Reading: How to Find Your Most Valuable Customers
- Reading: Assignment: Customer Acquisition Example
- Discussion Prompt: Logit v. Probit Models
- Vídeo: Customer Valuation Excel Demonstration
- Vídeo: Inventory Management Excel Demonstration
- Reading: Encouraging TV Binge Watching May Backfire On Advertisers
- Reading: Use Big Data to Create Value for Customers, Not Just Target Them
- Reading: Assignment: Using Regression for Inventory Management
- Discussion Prompt: Course Reflection
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| Comprar curso | |
|---|---|
| Accede a los materiales del curso | Disponible |
| Accede a los materiales con calificación | Disponible |
| Recibe una calificación final | Disponible |
| Obtén un Certificado de curso para compartir | Disponible |
This course went in depth into some excel functions used for analyzing sales and marketing data, really thought it was useful.
This course provided practical hands-on approach to understanding basics of marketing forecasting.
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.)
The last 2 video lectures: Customer Valuation Excel Demonstration and Inventory Management Excel Demonstrationm were very well explained and taught me something new and useful.