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Suitable for both MBA- and undergraduate-level courses such as integrated marketing communications, this case traces a product from idea to established, successful brand. A spirits industry executive perceives a gap between the under-$10 and the $25-and-up "prestige" vodkas. In this case he explores whether he could quantify the financial value of the awards his product has won. Would that be a good basis for the design of future campaigns: Decisions on pricing, target, distribution, branding, and promotion are considered in the A case (UVA-M-0774). The B case (UVA-M-0775) presents the results, which include the important benchmark of one million case sales by 2006. It also presents the founder's assessment of which initial decisions were most critical and explores the new choices he faces, including changes to the distribution channels and additions to the product line.

The 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: for example, past sales or market share for different levels of expenditures on these marketing mix variables. In this note, we consider the design of models that allow managers to obtain robust price and advertising elasticity estimates.

In the follow-up to the A case of the same name, this case reveals post-launch results for Tata's $2,500 car. Students learn about Tata's promotion, price, place, segment, targeting, and positioning for marketing "the world's cheapest car." This case series is effective for MBA, undergraduate, and executive learners studying market segmentation, pricing, cannibalization risk, pricing, and break-even sales in the face of different price and cost scenarios. Did Tata choose the right marketing strategy? Did the Nano represent an evolution or a revolution in automobile marketing?

In this, the second of a two-part case series, the SVEDKA founder assesses which initial decisions were most critical in the launch of his now-successful product. He also explores the new choices he faces, including changes to the distribution channels and additions to the product line. Suitable for both MBA- and undergraduate-level courses such as integrated marketing communications, the case presents opportunities to discuss pricing, target, distribution, branding, and promotion. See also "SVEDKA Vodka (A)," (UV4284).

Suitable for both MBA- and undergraduate-level courses such as integrated marketing communications, this case traces a product from idea to established, successful brand. A spirits industry executive perceives a gap between the under-$10 and the $25-and-up "prestige" vodkas. Could a midpriced vodka capture some volume from each of those markets? Decisions on pricing, target, distribution, branding, and promotion are considered in the A case. The B case (UV4285) presents the results, which include the important benchmark of one million case sales by 2006. It also presents the founder's assessment of which initial decisions were most critical and explores the new choices he faces, including changes to the distribution channels and additions to the product line.

This 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 strategy.

Students identify promotion, price, place, segment, targeting, and positioning for marketing "the world's cheapest car." This case is effective for MBA, undergraduate, and executive learners studying market segmentation, pricing, cannibalization risk, pricing, and break-even sales in the face of different price and cost scenarios. Has Tata chosen the right marketing strategy? Does the Nano represent an evolution or a revolution in automobile marketing?

Spreadsheet for UV2965

This case is intended to be part of a first-year MBA marketing course, or a second-year elective in advertising, integrated marketing communications, market research, or marketing analytics. The case provides students with examples of two real advertising experiments and the challenges involved in executing the experiments. It allows for a discussion of the need for advertising experiments, and also, at a more general level, the need to measure the return on marketing. Biases surrounding the field experiments allow for a discussion of the problems with establishing a causal relationship between advertising and sales.

This 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.

Despite an abundance of data, most companies do a poor job of predicting the behavior of their customers. In fact, the authors' research suggests that even companies that take the greatest trouble over their predictions about whether a particular customer will buy a particular product are correct only around 55% of the time--a result that hardly justifies the costs of having a customer relationship management (CRM) system in the first place. Businesses usually conclude from studies like this that it's impossible to use the past to predict the future, so they revert to the timeworn marketing practice of inundating their customers with offers. But as the authors explain, the reason for the poor predictions is not any basic limitation of CRM systems or the predictive power of past behavior, but rather of the mathematical methods that companies use to interpret the data. The authors have developed a new way of predicting customer behavior, based on the work of the Nobel Prize-winning economist Daniel McFadden, that delivers vastly improved results. Indeed, the methodology increases the odds of successfully predicting a specific purchase by a specific customer at a specific time to about 85%, a number that will have a major impact on any company's marketing ROI. What's more, using this methodology, companies can increase revenues while reducing their frequency of customer contact--evidence that overcommunication with customers may actually damage a company's sales.