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Marketing Data Science: Modeling Techniques in Predictive Analytics with R and Python (FT Press Analytics)

Amazon.com Price:  $65.16 (as of 12/05/2019 18:30 PST- Details)

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Description

Now , a leader of Northwestern University’s prestigious analytics program presents an absolutely-integrated remedy of both the business and academic elements of marketing applications in predictive analytics. Writing for both managers and students, Thomas W. Miller explains essential concepts, principles, and theory in the context of real-world applications.

 

Building on Miller’s pioneering program, Marketing Data Science thoroughly addresses segmentation, target marketing, brand and product positioning, new product development, choice modeling, recommender systems, pricing research, retail web page selection, demand estimation, sales forecasting, customer retention, and lifetime value analysis.

 

Starting where Miller’s widely-praised Modeling Techniques in Predictive Analytics left off, he integrates the most important information and insights that were prior to now segregated in texts on internet analytics, network science, information technology, and programming. Coverage includes:

  • The role of analytics in delivering effective messages on the web
  • Understanding the internet by understanding its hidden structures
  • Being recognized on the internet – and watching your own competitors
  • Visualizing networks and understanding communities within them
  • Measuring sentiment and making recommendations
  • Leveraging key data science methods: databases/data preparation, classical/Bayesian statistics, regression/classification, machine learning, and text analytics

Six complete case studies address exceptionally relevant issues such as: separating legitimate email from spam; identifying legally-relevant information for lawsuit discovery; gleaning insights from anonymous internet surfing data, and more. This text’s extensive set of internet and network problems draw on wealthy public-domain data sources; many are accompanied by solutions in Python and/or R.


Marketing Data Science will be an invaluable resource for all students, faculty, and professional marketers who wish to use business analytics to beef up marketing performance.


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