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Forecasting Models for Marketing Decisions

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Forecasting Models for Marketing Decisions

This course is part of Foundations of Marketing Analytics Specialization

Instructor: David Schweidel

19,213 already enrolled

Included with

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4 modules

Gain insight into a topic and learn the fundamentals.

80 reviews

Intermediate level

Some related experience required

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

80 reviews

Intermediate level

Some related experience required

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

Skills you'll gain

Tools you'll learn

Microsoft Excel

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

4 assignments

Taught in English

91%

of learners achieved a positive career outcome

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Build your subject-matter expertise

This course is part of the Foundations of Marketing Analytics Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 4 modules in this course

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.

Module details

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.

What's included

4 videos3 readings1 assignment

4 videosTotal 33 minutes

Approaches to Forecasting12 minutes
Regression - Based Modeling10 minutes
Examining the Residuals7 minutes
Assessing Forecasting Performance4 minutes

3 readingsTotal 80 minutes

Simple Forecasting Model Assignment60 minutes
A Predictive Analytics Primer10 minutes
Nowcasting: A Model for the Future of Marketing10 minutes

1 assignmentTotal 20 minutes

Module 120 minutes

"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.

What's included

6 videos5 readings1 assignment

6 videosTotal 110 minutes

How to Use Customer Centric Analytics10 minutes
Business Decisions Drive Customer Choices9 minutes
Illustrating Customer Acquisition in Excel11 minutes
Timing Models in Marketing10 minutes
Model for Retention Excel Demonstration30 minutes
Kiwi Bubbles Exercise Excel Demonstration39 minutes

5 readingsTotal 170 minutes

Read This First10 minutes
Leveraging Customer Analytics: The Insurance Industry30 minutes
Companies still struggle to unlock customer data analytics insight10 minutes
Retention Exercise Instructions60 minutes
Kiwi Bubbles Instructions60 minutes

1 assignmentTotal 20 minutes

Module 220 minutes

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.

What's included

4 videos2 readings1 discussion prompt

4 videosTotal 40 minutes

Managing Customer Equity11 minutes
Acquisition, Retention, & Market Value11 minutes
Customer Valuation9 minutes
Marketing to New & Current Customers9 minutes

2 readingsTotal 20 minutes

What You Should Know About Customer Success Technology10 minutes
Online Communities Foster Customer Loyalty10 minutes

1 discussion promptTotal 20 minutes

Social Networking and Customer Valuation20 minutes

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.