Case studies

In 2013, Under Armour had $2.3 billion in sales yet only $500 million came from its women’s apparel, and the company was ready to expand into the female market segment. The “I Will What I Want” global women’s marketing campaign was the largest Under Armour had ever run. Founder Keven Plank and his team launched the campaign on a multichannel platform, with social media at its core. The campaign’s success surpassed what Plank had imagined, and he is left wondering where to take Under Armour’s advertising and marketing next. This case has been used successfully in a marketing course and would be suited for any class with a focus on interactive media, technology, and multichannel marketing.

ThinkAlike, a fictitious marketing consulting firm, was asked by TiVo to segment the market for its new digital video recorder (DVR) product. Students are asked to analyze realistic data and generate segments that will be useful for TiVo s marketing strategy.

Hundreds of thousands of would-be hoteliers have been popping up all around the world, hoping to rent their own homes and apartments to complete strangers through a service called Airbnb. The goal of Airbnb’s aspiring hosts was to use the company’s website to attract guests who were willing to pay the highest rates to stay in their homes for a short time. For Airbnb, the goal was to improve customer review performance so it could, in turn, increase profits. How could the company achieve its goal? Enter text mining, a technique that allowed businesses to scour Internet pages, decipher the meaning of groups of words, and assign the words a sentiment proxy through the use of a software package.

In order for text mining to be useful for Airbnb, its marketing professionals first had to gain access to customer review data on the company’s own website. The team then had to analyze the data to find ways to improve property performance. Was the team going to be able to leverage this large amount of data to determine a strategy going forward?

Two recently graduated MBA students are tasked with developing an ad-serving learning algorithm for a mobile ad-serving company. The case illustrates the way in which hypotheses can be tested in an A/B format or “horse race” in order to establish customer preferences and superior profitability. The case was written for a course elective covering hypothesis testing.

Joe Smith, senior director of merchandise management at Beautiful Bags (BB), was about to place a large order for the upcoming winter season. He had to decide how many pieces he should order of each product. But another big question whether BB should source the product from its domestic manufacturing facility, its Chinese suppliers, or some combination of the two given the timing needs, labor costs, minimum order requirements, and BB's expanding product assortment?

The Global Networks Company (GNC), headquartered in Boston, Massachusetts, made its global footprint in India in 1994 by establishing a presence in Bangalore. Although mainly a sales support office, GNC grew name recognition from its contracts with India’s government to help build nationwide networks. Not quite 20 years later, GNC decided to further invest in India and tapped a manager from the Boston office, Jim Notrika, to establish and then manage GNC’s first global software center in Mumbai. Split between Mumbai and Boston, the project team successfully completed several minor projects, but only months into its first major project, the team was struggling to meet deadlines. Blame was being passed in both directions, and when three talented engineers in Mumbai quit, Notrika makes an emergency trip to Mumbai to better understand the problem.

This case describes three common cross-cultural communication obstacles in teams: a preference for direct versus indirect confrontation of problems; a clash of collectivist versus individualistic cultural values related to reporting bad news or giving negative feedback; and different expectations of team leaders based on power-distance values.

This is the first implementation of Revenue Management System in a major international hotel chain in India. The case describes the history of development, corporate story of overdrive for profit, system integration issues. It describes two components of a revenue management system, forecasting and optimization. It also raises several questions that need to be addressed before implementing a RMS.

In the first case of a two-part series, a strategic finance manager at Wells Fargo with experience installing solar panel systems on bank branches crunches the numbers for a similar project in the Los Angeles area given the uncertain future of a government rebate.

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. It provides students with two real advertising experiments and the challenges involved in executing them. It allows for discussion of the need for advertising experiments, and, at a more general level, the need to measure the return on marketing. Biases surrounding the field experiments provide an opportunity for discussion about the problems with establishing a causal relationship between advertising and sales.