Data Mining

Marketing Data Science: Modeling Techniques in Predictive by Thomas W. Miller PDF

By Thomas W. Miller

ISBN-10: 0133886557

ISBN-13: 9780133886559

Now , a pace-setter of Northwestern University's prestigious analytics software provides a fully-integrated therapy of either the company and educational components of promoting functions in predictive analytics. Writing for either managers and scholars, Thomas W. Miller explains crucial strategies, rules, and conception within the context of real-world applications.

 

Building on Miller's pioneering software, Marketing information Science completely addresses segmentation, objective advertising, model and product positioning, new product improvement, selection modeling, recommender platforms, pricing learn, retail website choice, call for estimation, revenues forecasting, buyer retention, and lifelong worth analysis.

 

Starting the place Miller's widely-praised Modeling ideas in Predictive Analytics left off, he integrates the most important info and insights that have been formerly segregated in texts on net analytics, community technological know-how, info expertise, and programming. assurance includes:

  • The position of analytics in providing powerful messages at the web
  • Understanding the internet by way of figuring out its hidden structures
  • Being famous on the net – and staring at your personal competitors
  • Visualizing networks and realizing groups inside of them
  • Measuring sentiment and making recommendations
  • Leveraging key information technological know-how equipment: databases/data education, classical/Bayesian facts, regression/classification, laptop studying, and textual content analytics

Six entire case stories deal with tremendously correct matters akin to: isolating valid electronic mail from junk mail; picking legally-relevant info for lawsuit discovery; gleaning insights from nameless internet browsing facts, and extra. This text's wide set of internet and community difficulties draw on wealthy public-domain information assets; many are followed via ideas in Python and/or R.


Marketing facts Science could be a useful source for all scholars, school, agents who are looking to use enterprise analytics to enhance advertising and marketing performance.

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Marketing Data Science: Modeling Techniques in Predictive Analytics with R and Python (FT Press Analytics) by Thomas W. Miller


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