Download e-book for iPad: Marketing Data Science: Modeling Techniques in Predictive by Thomas W. Miller

By Thomas W. Miller

Now , a pace-setter of Northwestern University's prestigious analytics application offers a fully-integrated therapy of either the company and educational parts of selling purposes in predictive analytics. Writing for either managers and scholars, Thomas W. Miller explains crucial thoughts, rules, and concept within the context of real-world applications.

 

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

 

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

  • The function of analytics in supplying powerful messages at the web
  • Understanding the internet through realizing its hidden structures
  • Being well-known on the internet – and staring at your individual competitors
  • Visualizing networks and figuring out groups inside of them
  • Measuring sentiment and making recommendations
  • Leveraging key facts technology equipment: databases/data practise, classical/Bayesian information, regression/classification, computer studying, and textual content analytics

Six entire case reviews handle awfully correct concerns equivalent to: setting apart valid e mail from junk mail; picking out legally-relevant info for lawsuit discovery; gleaning insights from nameless net browsing information, and extra. This text's huge set of internet and community difficulties draw on wealthy public-domain facts resources; many are observed by means of recommendations in Python and/or R.


Marketing information Science may be a useful source for all scholars, school, agents who are looking to use enterprise analytics to enhance advertising 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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