Marketing Analytics: Data-Driven Techniques with Microsoft Excel

Marketing Analytics: Data-Driven Techniques with Microsoft Excel By Wayne L. Winston

Helping tech-savvy marketers and data analysts solve real-world business problems with Excel. Shows you how to perform sophisticated business analyses using the cost-effective and widely available Microsoft Excel instead of expensive, proprietary analytical tools.

Using data-driven business analytics to understand customers and improve results is a great idea in theory, but in today’s busy offices, marketers and analysts need simple, low-cost ways to process and make the most of all that data. This expert book offers the perfect solution. Written by data analysis expert Wayne L. Winston, this practical resource shows you how to tap a simple and cost-effective tool, Microsoft Excel, to solve specific business problems using powerful analytic techniques—and achieve optimum results.

Practical exercises in each chapter help you apply and reinforce techniques as you learn.

Shows you how to perform sophisticated business analyses using the cost-effective and widely available Microsoft Excel instead of expensive, proprietary analytical tools
Reveals how to target and retain profitable customers and avoid high-risk customers
Helps you forecast sales and improve response rates for marketing campaigns
Explores how to optimize price points for products and services, optimize store layouts, and improve online advertising
It Covers social media, viral marketing, and how to exploit both effectively

Marketing Analytics Free PDF Book Download

The book Marketing Analytics: Data-Driven Techniques with Microsoft Excel by Matthew Henry and Sean Grover is a comprehensive guide to data analysis for marketing professionals.

The book is broken down into several chapters that each focus on a different aspect of data analysis for marketing. The first chapter covers basic statistical concepts, such as averages and standard deviation, that are important for understanding how to use data to make better decisions. The second chapter focuses on using these concepts to analyze your business, including looking at customer satisfaction scores and regression analysis to predict sales numbers. The third chapter looks at how you can use advanced statistical techniques in Excel, including exponential smoothing and ARIMA models, which can help you predict future trends based on past data.

The authors explain complex topics in a way that is easy for the average person to understand. Readers can appreciate their work without prior knowledge of statistics or programming languages like R or SAS (used in other books). They also provide examples throughout each chapter that show how one might apply these techniques in their business setting.

Overall this is great.