Название: Marketing Analytics: Optimize Your Business with Data Science in R, Python, and SQL Автор: Dave Jacobs
Издательство: Dave Jacobs
Год: 2016
Страниц: 164
Язык: английский
Формат: pdf
Размер: 14.5 MB
Is the term “marketing analytics” unclear to you? Do you want to discover methodologies that will help maximize your marketing efforts? Are you familiar with marketing analytics methodologies but don’t know R, Python, or SQL? If so, then this book is for you. This book will help you to go from zero knowledge of any of these three languages to having a solid grasp of each.
If you do not have a good understanding of marketing analytics methodologies, after reading this book you will know how to do the following:
•Segment customers in a scientific way using pivot tables and statistical measures of significance
•Build predictive models to identify customers or prospects that are most likely to take an action
•Determine optimal channel, offer and message
•Identify customers or prospects that are most likely to be influenced by marketing
•Create databases
•Set up test and control groups to be used in experimental design
•Measure the effectiveness of your campaigns
•Visualize results with impressive graphs
•Forecast sales and other KPIs
•Understand customer sentiment through text analytics
Technical books often give examples that are overly complex and academic, with scenarios that are not easily translatable to real world situations. This book teaches fundamental concepts about marketing analytics by using real world examples that are faced by many businesses today. By following the examples in this book, you will quickly gain a solid grasp of marketing analytics and understand what it can do to better your business. The best part is that you don’t need to buy expensive statistical software to learn this. Excel is relatively inexpensive, and the programs we will be using for R, Python, and SQL are totally free!
Michelangelo once said, “Every block of stone has a statue inside it and it is the task of the sculptor to discover it.” I believe that just like a sculptor, a good data scientist is able to look at a mass of data and see the meaning inside. Learning these languages and methodologies will give you the tools to do just that.
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