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The case deals with marketing research study undertaken to introduce a new product in the market. The company was planning to introduce Cerenity, a toilet seat sanitizer for women who frequently use shared restrooms. The case discusses the conclusive study undertaken involving quantitative marketing research. The research team carried out quantitative survey and collected the data. It applied various quantitative research methods such as factor analysis, multiple regression, cluster analysis and conjoint analysis for analysis the collected and drawing managerial inferences.

In 2013, ‘Fashion Destination’, a well-established clothing retailer considered setting up a clothing and accessories rental service. They hired a market research agency ‘Wright & Company’ to conduct a research on the sustainability and profitability of such a business model. The consultants collected primary data and did an extensive analysis for Fashion Destination. Based on the secondary research, expert interviews, extensive qualitative and quantitative research the consultants recommended the management to start a clothes and accessories rental service but suggested that the product offering be limited to formal clothes only and offer accessories. Vishal had doubts despite of the go-ahead signal from consultancy. He wondered what recommendations should he accept and which needed further verification.

Narayana, the head of Market Dynamic's (MD) Telecom vertical was working on the data analysis plan for the research on the telecom project that they had done for CWP. CWP was a well known consultant and had conducted a research with MD to generate consumer insights in the telecom space. These would help bring credibility for CWP and help in business development. CWP had requested for an early delivery and Narayana was planning to work on the analysis plan himself as his chief analyst was on leave. This case highlights the importance of an analysis plan in research. Specifically, it illustrate the role of different tools in data analysis and familiarizes participants with various tools and their applications. This case would be useful for students in Business Research and Market Research courses.

‘Fashion Destination’ was a prominent one-stop shop of clothing retail in Ahmedabad which has faced business slowdown in the last 5 years. Vishal, who had recently taken over the management wondered, would renting of premium clothing be a good business model to get back to the business. While pondering over the issue Vishal did some secondary research had found that the Indian retail industry is growing at a fast rate and that the online rental service is an upcoming trend in Indian market. Vishal hired an external market research agency ‘Wright & Company’, before changing the business model, to clarify certain doubts regarding renting clothes as a social stigma, willingness of people to rent clothes, requirement of physical store, about target consumers and product assortment.

Since the concept of rental clothing business was new for Indian market and very few players were dealing in it, ‘Wright & Company’ consulting did an exploratory research to understand the model. Through two expert interviews and extensive survey of the business model of existing players across countries, they developed better understanding of kinds of business models, range of products offered, customer expectations and concerns regarding such service and business challenges. The research showed the purchase intention but further detailed primary research was required to validate the findings. To conduct the quantitative survey they designed a questionnaire but was not sure of the appropriateness of the questionnaire and thus wanted to pre-test it and construct a final detailed questionnaire. Vishal also wondered if he needed to do more extensive in-depth qualitative research.

Fruitzone India Limited was the Indian subsidiary of the multinational company Gypsy Inc., the global leader in the beverages industry. The company was contemplating the launch of a new flavour of fruit juice and decided to conduct a feasibility study. It hired an external market research agency, India Monitor International (IMI) to conduct the market research. This case discusses the exploratory phase of the research conducted by IMI. This case is useful for participants in the Business Research Methods, Market Research and Qualitative Research courses.

The case study is based on field research and also on secondary data. A primary survey is included in the case study. Simple frequency and factor analysis as statistical tools have been used.

Family businesses, like that of Kiran Rai’s, owning a local Mom and Pop store in an emerging city were faced with a serious problem of sustaining their businesses. These family businesses countered immense competition from: their own types, i.e. from other local Mom and Pop stores within the same cities; online stores; and the organised stores.The choice of the customers to buy goods from the neighbourhood shops has remained largely as an age-old tradition in the households. With the millennials and the Generation Z (Gen Z) exposed to an array of brands, can they become the first choice of young customers for shopping for all kinds of products and varieties? Can the local Mom and Pop stores spread their wings across the young generations, particularly the Millennials and Gen Z through inexpensive social media channels? What are their growth options? How can the social media serve this purpose? The case uses the social cognition theory and the use gratification theory to throw light on the new concept of Social Shopping.

The case is meant to be discussed in courses like Fundamentals of Marketing, Digital Marketing and Retail Marketing in a 90-min session in the Post Graduate as well as in the Working Executives’ Management programmes. The case analysis will expose the students to the use of social media and its benefits to the small businesses. The students will also be able to analyse and understand the different types of Online Consumers’ Shopping Personalities. This would enable them to strategize for different stages in the decision-making processes.

This compact case provides a relatively large data set that students explore using visualization and a Tableau dynamic dashboard that they create. Students were asked to describe what the data set contained in relation to employee attrition experience of Baca Beverage Distributors (BBD). The application and managerial questions are set in human resources and a company that is facing high attrition during the pandemic.

BBD shared their data and problem scenario for this compact case. The protagonist, Morgan Matthews, was the authors’ contact and provided significant clarification and guidance about the data. Both the company and the protagonist have been disguised. Some of the job positions have been rephrased. All names of employees, supervisors and managers have been replaced with codes.

During the 2020–2022 pandemic years, BBD experienced, like many companies, a higher than usual employee turnover rate and Morgan Matthews, Director of People, was concerned. Not only was it time-consuming, expensive and disruptive but the company had prided itself on being a good place to work. Were they hiring the right people, people that fit the company culture and people that fit the positions for which they were hired? The company had been using the Predictive Index [1] when on-boarding employees. In addition, there were results from self-reviews and manager reviews that could be used. Morgan wondered if data visualization and visual analytics would be useful in describing their employees and whether it would reveal any opportunities to improve the turnover rate. Before seeking a solution for the high turnover, it was important to step back and learn what the data said about who was leaving and the reasons they gave for leaving.

This compact case can be used in courses that include visualization using Tableau and dashboards. As it is a compact case, it requires less preparation time from the students and less class time for discussion. The case is for students who have been recently introduced to business analytics, specifically visualization and data storytelling with Tableau. For this reason, significant guidance has been provided in the case assignment. The level of the case can be adjusted by the amount of guidance provided in the case assignment. Courses include introduction to business analytics, descriptive analytics and visualization, communication through data storytelling. The case can be used for all modalities – in person, hybrid, online. The authors use it here for visualization and dynamic dashboards but using the same data set and compact case description, exploratory data analysis could be assigned.

Supplementary material for this article can be found online.

The case deals with the application of marketing research for launching a new product in the market place. The company was planning to enter the Fast Moving Consumer Goods (FMCG) market in India with its new product Cerenity. Cerenity was a toilet seat sanitizer for women who frequently use public restrooms. The case describes the exploratory study conducted by the research team. The team used different qualitative marketing research tools such as focus groups, in-depth Interviews and participant observations.

The case is designed to be used with the digital business model framework developed by Peter Weill and Stephanie Woerner of Massachusetts Institute of Technology (MIT) (Weill and Woerner, 2015) and is referred to as the W & W framework. This approach provides a useful structure for thinking through the strategic options facing environments ripe for digital transformation.

Research for this case was conducted through face-to-face interviews with the protagonist, as well as through a review of their business planning documents and other data and documentation provided by the founder. Some of the market and industry data were obtained using secondary research and industry reports. Interviews were digitally recorded and transcribed to ensure accuracy.

The case follows the story of Kurt Waltenbaugh, a Minnesota entrepreneur who shared the dream of using data analytics to reduce costs within the US health-care system. In early 2014, Waltenbaugh and a physician colleague founded Carrot Health to bring together their personal experience and expertise in both consumer data analytics and health care. From the beginning, they focused on how to use data analytics to help identify high-risk/high-cost patients who had not yet sought medical treatment. They believed that they could use these insights to encourage early medical interventions and, as a result, lower the long-term cost of care.

Carrot’s initial success found them in a consultative role, working on behalf of insurance companies. Through this work, they honed their capabilities by helping their clients combine existing claims data with external consumer behavioral data to identify new potential customers. These initial consulting contracts gave Carrot the opportunity to develop its analytic tools, business model and, importantly, to earn some much-needed cash flow during the start-up phase. However, they also learned that, while insurance companies were willing to purchase data insights for one-off market expansion projects, it was much more difficult to motivate them to use data proactively to eliminate costs on an ongoing basis. Waltenbaugh believed that Carrot’s greatest potential lay in their ability to develop predictive models of health outcomes, and this case explores Carrot’s journey through strategic decisions and company transformation.

This case is intended for either an undergraduate or graduate course on entrepreneurial strategy. It provides an effective introduction to the unique structure and constraints which apply to an innovative start-up within the health-care industry. The case also serves as a platform to explore the critical criteria to be considered when developing a digital transformation strategy and exposing students to the digital business model developed by Weill and Woerner (2015) at MIT (referred to in this instructor’s manual as the W&W framework). The case was written to be used in an advanced strategy Master of Business Administration (MBA) class, an undergraduate specialty health-care course or as part of a health-care concentration in a regular MBA, Master of Health Care Administration (MHA) or Master of Public Health (MPH). It may be taught toward the end of a course on business strategy when students are building on generic strategy frameworks and adapting their strategic thinking to the characteristics of specific industries or sectors. However, the case can also be taught as part of a course on health-care innovation in which case it also serves well as an introduction to the health-care payments and insurance system in the USA. Finally, the case can be used in a specialized course on digital transformation strategy in which case it serves as an introduction to the MIT W&W framework.

The case is particularly well-suited to students who are familiar with traditional frameworks for business strategy and business models. The analysis builds on this knowledge and introduces students interested in learning about the opportunities and challenges of digital strategy. Equally, the case works well for students with clinical backgrounds, who are interested in how business strategy can influence changes within the health-care sphere. Finally, an important aspect of the case design was to develop students’ analytical confidence by encouraging them to “get their hands dirty” and to carry out some basic exploratory data analytics themselves. As such, the case requires students to combine and correlate data and to experience the potentially powerful combination of clinical and consumer data. Instructors should find that the insights from these activities give students unique insights into the potential for of data analytics to move health care from a reactive/treatment ethos to a proactive/intervention ethos. This experience can be particularly revealing for students with clinical backgrounds who may initially be resistant to the use of clinical data by commercial organizations.