Marketing Analytics - Wayne L Winston

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Auteur(s) : Wayne L Winston

Editeur : John Wiley & Sons

Langue : Anglais

Parution : 01/01/2014

Format : Moyen, de 350g à 1kg

Nombre de pages : 720

Expédition : 1199

Dimensions : 23.3 x 18.7 x 4.0

ISBN : 111837343X

Résumé :

Powerful techniques for analyzing business data with Excel

Most businesses are awash in data. To make that data work for your business, you need a simple, cost-effective tool ? ideally, one you already know something about. Excel is that tool.

Every example in this book features step-by-step instructions, a downloadable Excel file containing data and solutions, and plenty of screenshots. To sharpen your marketing analytics, you just need this guide and Excel.

This book will help you master many important marketing analytic concepts, including:

• Using Excel charts and functions to summarize marketing data
• Estimating demand curves and using Solver to determine profit-maximizing pricing strategies
• Using cluster analysis for market segmentation
• Developing customized forecasting models that show you how your marketing mix impacts sales
• Measuring the effectiveness of your advertising program
• Understanding the analytics underlying social networks and viral marketing

Companion website

At the companion website, www.wiley.com/go/marketinganalytics, you can download all the Excel files used in this book, find answers to all the exercises at the ends of the chapters, and be advised of any errors discovered.

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Biographie:

Introduction xxiii

I Using Excel to Summarize Marketing Data 1

1 Slicing and Dicing Marketing Data with PivotTables 3

Analyzing Sales at True Colors Hardware 3

Analyzing Sales at La Petit Bakery 14

Analyzing How Demographics Affect Sales 21

Pulling Data from a PivotTable with the GETPIVOTDATA Function 25

Summary 27

Exercises 27

2 Using Excel Charts to Summarize Marketing Data 29

Combination Charts 29

Using a PivotChart to Summarize Market Research Surveys 36

Ensuring Charts Update Automatically When New Data is Added 39

Making Chart Labels Dynamic 40

Summarizing Monthly Sales-Force Rankings 43

Using Check Boxes to Control Data in a Chart 45

Using Sparklines to Summarize Multiple Data Series 48

Using GETPIVOTDATA to Create the End-of-Week Sales Report 52

Summary 55

Exercises 55

3 Using Excel Functions to Summarize Marketing Data 59

Summarizing Data with a Histogram 59

Using Statistical Functions to Summarize Marketing Data 64

Summary 79

Exercises 80

II Pricing 83

4 Estimating Demand Curves and Using Solver to Optimize Price 85

Estimating Linear and Power Demand Curves 85

Using the Excel Solver to Optimize Price 90

Pricing Using Subjectively Estimated Demand Curves 96

Using SolverTable to Price Multiple Products 99

Summary 103

Exercises 104

5 Price Bundling 107

Why Bundle? 107

Using Evolutionary Solver to Find Optimal Bundle Prices 111

Summary 119

Exercises 119

6 Nonlinear Pricing 123

Demand Curves and Willingness to Pay 124

Profit Maximizing with Nonlinear Pricing Strategies 125

Summary 131

Exercises 132

7 Price Skimming and Sales 135

Dropping Prices Over Time 135

Why Have Sales? 138

Summary 142

Exercises 142

8 Revenue Management 143

Estimating Demand for the Bates Motel and Segmenting Customers 144

Handling Uncertainty 150

Markdown Pricing 153

Summary 156

Exercises 156

III Forecasting .159

9 Simple Linear Regression and Correlation 161

Simple Linear Regression 161

Using Correlations to Summarize Linear Relationships 170

Summary 174

Exercises 175

10 Using Multiple Regression to Forecast Sales 177

Introducing Multiple Linear Regression 178

Running a Regression with the Data Analysis Add-In 179

Interpreting the Regression Output 182

Using Qualitative Independent Variables in Regression 186

Modeling Interactions and Nonlinearities 192

Testing Validity of Regression Assumptions 195

Multicollinearity 204

Validation of a Regression 207

Summary 209

Exercises 210

11 Forecasting in the Presence of Special Events 213

Building the Basic Model 213

Summary 222

Exercises 222

12 Modeling Trend and Seasonality 225

Using Moving Averages to Smooth Data and Eliminate Seasonality 225

An Additive Model with Trends and Seasonality 228

A Multiplicative Model with Trend and Seasonality 231

Summary 234

Exercises 234

13 Ratio to Moving Average Forecasting Method 235

Using the Ratio to Moving Average Method 235

Applying the Ratio to Moving Average Method to Monthly Data 238

Summary 238

Exercises 239

14 Winter's Method 241

Pa...

Sommaire:

Wayne L. Winston is John and Esther Reese chaired Professor of Decision Sciences at the Indiana University Kelley School of Business and will be a Visiting Professor at the Bauer College of Business at the University of Houston. He has won more than 45 teaching awards at Indiana University. He has also written numerous journal articles and a dozen books, and has developed two online courses for Harvard Business School.