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
Ce cours fait partie de la Spécialisation Foundations of Marketing Analytics
Meaningful Marketing Insights
proposé par
À propos de ce cours
4.4
110 notes
Compétences que vous acquerrez
Basic Descriptive StatisticsData AnalysisMicrosoft ExcelMarketing
Programme du cours : ce que vous apprendrez dans ce cours
Semaine
1Meet Dr. Schweidel & Course Overview
In this module, students will be introduced to the instructor, Dr. David Schweidel and get and overview of the course.
1 vidéos (Total 3 min), 2 lectures
1 vidéos
Meet Dr. Schweidel3 min
2 lectures
Getting Started10 min
A Note About Exercises & Quizzes10 min
Semaine
2Exploring your Data with Visualization and Descriptive Statistics, Part 1
Modules 2 and 3 focus on identifying appropriate descriptive statistics (measures of central tendency and dispersion) for different types of data, as well as recoding data using reference commands to prepare it for analysis. Additionally, you will manipulate and summarize data using pivot tables in Excel, produce visualizations that are appropriate based on the type of data being analyzed, and interpret statistics and visualizations to draw conclusions to address relevant marketing questions.
4 vidéos (Total 43 min), 3 lectures, 1 quiz
4 vidéos
Course Goals & Example 2: Performing Arts Centers8 min
Organizing Data10 min
The Motion Picture Industry12 min
3 lectures
How Companies Learn Your Secrets10 min
Big Data in the Big Apple10 min
Motion Picture Industry Example Data Set10 min
1 exercices pour s'entraîner
Module 2 Quiz25 min
Semaine
3Exploring your Data with Visualization and Descriptive Statistics, Part 2
Modules 2 and 3 focus on identifying appropriate descriptive statistics (measures of central tendency and dispersion) for different types of data, as well as recoding data using reference commands to prepare it for analysis. Additionally, you will manipulate and summarize data using pivot tables in Excel, produce visualizations that are appropriate based on the type of data being analyzed, and interpret statistics and visualizations to draw conclusions to address relevant marketing questions.
5 vidéos (Total 48 min), 3 lectures, 1 quiz
5 vidéos
Displaying Conditional Distributions4 min
Analyzing Qualitative Variables3 min
Steps in Constructing Histograms11 min
Common Descriptive Statistics for Quantitative Data14 min
3 lectures
Giving Viewers What They Want10 min
Why Personalization is Key for Content Marketing5 min
Assignment: Survey Analysis Assignment25 min
1 exercices pour s'entraîner
Module 3 Quiz30 min
Semaine
4Regression Analysis for Marketing Data
In this module, you will be asked to determine the appropriate type of regression for different types of marketing data and will perform regression analysis to assess the impact of marketing actions on outcomes of interest, such as sales, traffic, and brand choices. You will also be asked to interpret regression output to understand overall model performance and importance of different predictors, as well as make predictions using the appropriate regression model.
4 vidéos (Total 41 min), 2 lectures, 1 quiz
4 vidéos
Introduction to Customer Analytics10 min
Customer Choices Drive Business Decisions9 min
Illustrating Customer Analytics in Excel11 min
2 lectures
How to Find Your Most Valuable Customers20 min
Assignment: Customer Acquisition Example25 min
1 exercices pour s'entraîner
Module 4 Quiz25 min
4.4
25 avisMeilleurs avis
par HK•Jan 3rd 2017
Excellent course! Very hands on with right level of theory and application. Prof. Schweidel is obviously an expert in this field.
par JD•Aug 29th 2017
This course went in depth into some excel functions used for analyzing sales and marketing data, really thought it was useful.
Enseignants
David Schweidel
Associate Professor of MarketingGoizueta Business School
À propos de Emory University
Emory University, located in Atlanta, Georgia, is one of the world's leading research universities. Its mission is to create, preserve, teach and apply knowledge in the service of humanity.
À propos de la Spécialisation Foundations of Marketing Analytics
In this specialization you will learn how to:
• Find, extract, organize and describe data to support business decisions
• Identify, quantify and interpret relationships between variables
• Derive customer insights from your data
• Develop spreadsheet models to analyze data, evaluate risk and optimize business decisions
• Present and justify a course of action to management
The capstone project will give you an opportunity to apply what has been covered in the specialization to solve a marketing analytics problem.
Foire Aux Questions
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Une fois que vous êtes inscrit(e) pour un Certificat, vous pouvez accéder à toutes les vidéos de cours, et à tous les quiz et exercices de programmation (le cas échéant). Vous pouvez soumettre des devoirs à examiner par vos pairs et en examiner vous-même uniquement après le début de votre session. Si vous préférez explorer le cours sans l'acheter, vous ne serez peut-être pas en mesure d'accéder à certains devoirs.
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