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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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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
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The Seven Questions of Marketing Strategy
Farris, Paul W.; Parry, Mark E.; Borden, Neil H. Jr.; Venkatesan, Rajkumar; Sharpe, Kathryn M.Technical Note DARDEN-M-0779-EMarketingThis simple model of marketing strategy can provide keys to creating a sustainable competitive advantage. Suitable for MBA and executive formats, this technical note demonstrates that individual marketing strategy concepts are interconnected, which renders the strategic process vulnerable to the political machinations of executives. Evolving customer needs and competitors' proactive efforts to steal market share require a dynamic marketing strate...Starting at €8.20
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Cluster Analysis for Segmentation
Venkatesan, RajkumarTechnical Note DARDEN-M-0748-EMarketingThis note is designed for use in an MBA marketing research course. It provides an overview of segmentation using K-means clustering. A simple algorithm for K-means clustering and the process of profiling clusters are provided. The note discusses the need for segmentation in marketing and emphasizes the role of managerial judgment in choosing a segmentation policy. Examples from the insurance industry are used in the note.Starting at €8.20
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Design of Price and Advertising Elasticity Models
Venkatesan, Rajkumar; Farris, Paul W.Technical Note DARDEN-M-0805-EMarketingThe marketing mix that a manager may deploy can affect the sales of a product and can be categorized under the traditional four Ps of marketing (product, price, promotion, and placement). But the perennial question managers face concerns the combination of these different marketing mix variables that will give them maximized sales, highest share, lowest inventory, or maximized margins. Quite often, these questions are answered by historical data:...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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A Resource-Allocation Perspective for Marketing Analytics
Farris, Paul W.; Venkatesan, RajkumarTechnical Note DARDEN-M-0861-EMarketingManagers must understand their marketing efforts as precisely as possible in order to determine how much to spend on each marketing channel. This technical note explores marketing analytics—the process of systematically using empirical data about customers, companies, and industry context to inform strategic marketing decisions and create models that are helpful in understanding consumer behaviors. Resource allocation is the endgame of analytics....Starting at €8.20
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Implementing Marketing Analytics
Farris, Paul W.; Venkatesan, RajkumarTechnical Note DARDEN-M-0869-EMarketingThis note supports cases used in Darden's "Marketing Analytics" course elective. Marketing analytics powered by "big data" holds the promise to transform marketing strategy from a discipline based mostly on intuition to a fact-based decision-making process. Based on interactions with more than 100 executives in conferences, executive education seminars, case study development, and consulting projects, this technical note serves as a road map for ...Starting at €8.20
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Sustainable Competitive Advantage
Venkatesan, RajkumarTechnical Note DARDEN-M-1015-EMarketingThis note discusses the sources of competitive advantage for firms, including scale economies, network economies, counter positioning, switching costs, branding, cornered resources, and process power. It also introduces the features of sustainable competiStarting at €8.20
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Designing Marketing Experiments
Venkatesan, RajkumarTechnical Note DARDEN-M-0839-EMarketingThis technical note is used in Darden's first-year core marketing course as well as in the marketing analytics elective. It could also be used effectively in modules covering the topics of market research, web analytics, or advertising. The note pairs well with the case "Advertising Experiments at the Ohio Art Company" (UVA-M-0752), which includes a student spreadsheet and a teaching note for instructors. Marketing managers must often face the ch...Starting at €8.20