Data Science for Marketing Analytics: A practical guide to forming a killer marketing strategy through data analysis with Python

Description

Turbocharge your marketing plans by making the leap from simple descriptive statistics in Excel to sophisticated predictive analytics with the Python programming language Key FeaturesUse data analytics and machine learning in a sales and marketing contextGain insights from data to make better business decisionsBuild your experience and confidence with realistic hands-on practiceBook Description Unleash the power of data to reach your marketing goals with this practical guide to data science for business. This book will help you get started on your journey to becoming a master of marketing analytics with Python. You'll work with relevant datasets and build your practical skills by tackling engaging exercises and activities that simulate real-world market analysis projects. You'll learn to think like a data scientist, build your problem-solving skills, and discover how to look at data in new ways to deliver business insights and make intelligent data-driven decisions. As well as learning how to clean, explore, and visualize data, you'll implement machine learning algorithms and build models to make predictions. As you work through the book, you'll use Python tools to analyze sales, visualize advertising data, predict revenue, address customer churn, and implement customer segmentation to understand behavior. By the end of this book, you'll have the knowledge, skills, and confidence to implement data science and machine learning techniques to better understand your marketing data and improve your decision-making. What you will learnLoad, clean, and explore sales and marketing data using pandasForm and test hypotheses using real data sets and analytics toolsVisualize patterns in customer behavior using MatplotlibUse advanced machine learning models like random forest and SVMUse various unsupervised learning algorithms for customer segmentationUse supervised learning techniques for sales predictionEvaluate and compare different models to get the best outcomesOptimize models with hyperparameter tuning and SMOTEWho this book is for This marketing book is for anyone who wants to learn how to use Python for cutting-edge marketing analytics. Whether you're a developer who wants to move into marketing, or a marketing analyst who wants to learn more sophisticated tools and techniques, this book will get you on the right path. Basic prior knowledge of Python and experience working with data will help you access this book more easily.

Get the book

Amazon.com

Search the book

eBay.com

Search the book

Other editions

• 

  Data Science for Marketing Analytics: Achieve your marketing goals with...

  • 2019-03-30
  • 420 pages
  • Ebook
  • Packt Publishing Ltd

Similar books

• 

  Hands-On Data Science for Marketing: Improve your marketing strategies with machine learning using Python and R

  By Yoon Hyup Hwang

  This book will also be beneficial for beginners as it covers basic-to-advanced data science concepts and applications in marketing with real-life examples.

• 

  Marketing Data Science: Modeling Techniques in Predictive Analytics with R and Python

  By Thomas W. Miller

  Houston, B., L. Bruzzese, and S. Weinberg 2002. The Investigative Reporter's Handbook: A Guide to Documents, Databases and Techniques (fourth ed.). Boston: Bedford/St. Martin's. Huber, J. and K. Zwerina 1996. The importance of utility ...

• 

  Creating Value with Data Analytics in Marketing: Mastering Data Science

  By Peter C. Verhoef, Edwin Kooge, Natasha Walk

  This book is a refreshingly practical yet theoretically sound roadmap to leveraging data analytics and data science.

• 

  Marketing Analytics: A Practical Guide to Improving Consumer Insights Using Data Techniques

  By Mike Grigsby

  Complete with downloadable data sets and test bank resources, this book supplies a concrete foundation to optimize marketing analytics for day-to-day business advantage.

• 

  Marketing Analytics: Data-Driven Techniques with Microsoft Excel

  By Wayne L. Winston

  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.

• 

  R for Marketing Research and Analytics

  By Chris Chapman, Elea McDonnell Feit

  Bayesian statistics and marketing. New York: Wiley. Rossini, A., Heiberger, R., Hornik, K., Maechler, M., Sparapani, R., Eglen, S., et al. (2013). ESS – Emacs speaks statistics (13th ed.). Noida: The ESS Developers. Rouder, J. N., Morey ...

• 

  Digital Marketing Analytics: Making Sense of Consumer Data in a Digital World

  By Chuck Hemann, Ken Burbary

  Because you’ve barely begun to use it, that’s why! Good news: neither have your competitors. It’s hard! But digital marketing analytics is 100% doable, it offers colossal opportunities, and all of the data is accessible to you.

• 

  Python for Marketing Research and Analytics

  By Chris Chapman, Jason S. Schwarz, Elea McDonnell Feit

  This book provides an introduction to quantitative marketing with Python. The book presents a hands-on approach to using Python for real marketing questions, organized by key topic areas.

• 

  Marketing Analytics: A practical guide to real marketing science

  By Mike Grigsby

  Online supporting resources for this book include a bank of test questions as well as data sets relating to many of the chapters.

• 

  Cutting-edge Marketing Analytics: Real World Cases and Data Sets for Hands on Learning

  By Paul Farris, Rajkumar Venkatesan, Ronald T. Wilcox

  Paid search advertising is a powerful tool for marketers looking to match their offers with consumers who are ... Marketing Metrics, The Definitive Guide to Measuring Marketing Performance (Upper Saddle River, NJ: FT Press, 2010). 3.