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Logistic Regression
Venkatesan, Rajkumar; Gibbs, SheaTechnical Note DARDEN-M-0859-EMarketingThis technical note presents the reason for using a binomial logic regression in marketing applications. It is used in Darden's "Big Data in Marketing" course elective. The issues surrounding the use of a linear regression model when the dependent variable is a dummy variable are identified. A consumer-utility-based behavioral rationale is presented for the applicability of the binomial logistic regression for modeling dummy variables. Simulated ...Starting at €8.20
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Multiple Regression and Marketing-Mix Models
Venkatesan, Rajkumar; Gibbs, SheaTechnical Note DARDEN-M-0855-EMarketingIn this technical note, the concept of regression using a single independent variable is first introduced and then some of the practical challenges associated with it, including multiple independent variables in a regression, are discussed. Particular attention is paid to bias in the regression coefficients in the presence of omitted variables. The concept of the economic significance of a model is introduced and is contrasted with statistical s...Starting at €8.20
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Paid Search Advertising
Venkatesan, Rajkumar; Gibbs, SheaTechnical Note DARDEN-M-0860-EMarketingThis note provides a primer on paid search advertising, which is an important component of digital marketing. The mechanics of paid search is explained using the Google search engine platform. The note covers metrics for evaluating the performance of paid search, the strategic objective of paid search, the relationship between customer lifetime value and search ads, how to overcome sparse data problems using keyword clouds, and the nature of Goog...Starting at €8.20
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Highly Recommended: Collaborative Filtering Gives Customers What They Want
Venkatesan, Rajkumar; Gibbs, SheaTechnical Note DARDEN-M-0974-EMarketingNetflix Top Picks, Amazon recommendations, the iTunes Genius button. They all have one thing in common: they are driven by clever algorithms that use a technique known as collaborative filtering. Often used in machine learning operations, collaborative filtering is the process by which a firm like Netflix generates predictions about a single user’s preferences using data taken from a large number of users. This technical note offers an overview o...Starting at €8.20
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Text Analytics: Turning Words into Data
Venkatesan, Rajkumar; Gibbs, SheaTechnical Note DARDEN-M-0986-EMarketingThe searchable internet contains almost 2 billion websites. And new, text-rich sites are being added at a rapid pace: more than 700 million popped up from 2016 to 2017, according to the International Real Time Statistics Project. A lot of this web-based text is relevant to marketers: online product reviews, information about purchasing behavior, customer-to-customer interactions, and transcribed tele-sales calls. Marketers now have more informati...Starting at €8.20