How will customers act in the future? What will demand for our products and services be? How much inventory should we order for the next season? Beyond simply forecasting what customers will do, marketers need to understand how their actions can shape future behavior. In Developing Forecasting Tools with Excel, learners will develop an understanding of the basic components of a forecasting model, how to build their own forecasting models, and how to evaluate the performance of forecasting models. All of this is done using Microsoft Excel, ensuring that learners can take their skills and apply them to their own business problems.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung 市场分析基础
Forecasting Models for Marketing Decisions
von
Lehrplan - Was Sie in diesem Kurs lernen werden
Woche
12 Stunden zum Abschließen
Basics of Forecasting Models
This module will discuss how to identify the necessary components of a forecasting model based on patterns in the history data. You will also be able to evaluate the performance of a forecasting model using both in-sample and out-of-sample metrics.
4 Videos (Gesamt 33 min), 3 Lektüren, 1 Quiz
4 Videos
Regression - Based Modeling10m
Examining the Residuals6m
Assessing Forecasting Performance4m
3 Lektüren
Simple Forecasting Model Assignment1h
A Predictive Analytics Primer10m
Nowcasting: A Model for the Future of Marketing10m
1 praktische Übung
Module 120m
Woche
25 Stunden zum Abschließen
Customer Analytics: Predicting Individual Customer Behavior
"Meaningful Marketing Insights," This content will be familiar for learners who completed the first course; please think of this portion of the class as a review.
6 Videos (Gesamt 110 min), 5 Lektüren, 1 Quiz
6 Videos
Business Decisions Drive Customer Choices9m
Illustrating Customer Acquisition in Excel11m
Timing Models in Marketing10m
Model for Retention Excel Demonstration29m
Kiwi Bubbles Exercise Excel Demonstration39m
5 Lektüren
Read This First10m
Leveraging Customer Analytics: The Insurance Industry30m
Companies still struggle to unlock customer data analytics insight10m
Retention Exercise Instructions1h
Kiwi Bubbles Instructions1h
1 praktische Übung
Module 220m
Woche
31 Stunde zum Abschließen
Managing Customer Equity: Linking Customer Analytics to Customer Value
This module will discuss managing customer equity, acquisition, retention, & market value, and customer valuation. You will learn how to decompose customer value into its underlying components.
4 Videos (Gesamt 40 min), 2 Lektüren
4 Videos
Acquisition, Retention, & Market Value11m
Customer Valuation8m
Marketing to New & Current Customers9m
2 Lektüren
What You Should Know About Customer Success Technology10m
Online Communities Foster Customer Loyalty10m
Woche
44 Stunden zum Abschließen
Marketing Mix Modeling
A common task in developing forecasting models is to use them to make decisions regarding the marketing mix activity. With a marketing mix model, organizations can assess the efficacy of different marketing actions. Included is a sample of data for a popular frozen food category. In addition to weekly sales and pricing, for the focal brand we have information on whether the product was featured in the store’s advertising (e.g., newspaper circular) and if the product was on display in the store. We also have pricing information from competitors. In this module, we will build a series of regression models to evaluate the impact of the brand’s actions and competitors’ actions.
4 Lektüren, 3 Quiz
4 Lektüren
Marketing Mix Modeling15m
Instructions for Exercise30m
Instructions for Exercise30m
Instructions for Exercise30m
2 praktische Übungen
Conducting Exploratory Analysis Quiz10m
Building a Marketing Mix Model Quiz8m
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Siehe Allgemeine GeschäftsbedingungenDozent
David Schweidel
Associate Professor of MarketingGoizueta Business School
Über 艾莫利大学
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.
Über den Spezialisierung 市场分析基础
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.
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