How to run a platform to match 4 million writers of stories to 75 million readers? Use data science. Make money by doing deals with television and film makers and book publishers. The case describes the challenges of matching readers to stories, and of helping writers to produce better stories by supplying feedback on their chapters as they write, all by processing a billion data points daily. But it's hard to acquire new customer groups when algorithms have a bias to replicate the tastes on which they are trained.
DataXu served marketers by buying digital advertising for brands using its demand-side platform. It sought a way to build a more predictable revenue stream in the very transactional media marketplace, and hoped that two new marketing analytics products would give it a more predictable revenue stream. But sales were behind forecast. DataXu's large brand and advertising agency clients found the new products interesting, but evidence suggested that their buying processes might be incompatible with the recurring sales model DataXu wanted to implement. Will DataXu need to change its sales organization, pricing approach, or hiring criteria to sell the new products?
Legendary, the Hollywood studio responsible for such hits as Jurassic World and The Dark Knight, decides to take the marketing of its films in-house, and to market them fan-by-fan. Owner Thomas Tull acquires the big-data-in-sports firm started by Matt Marolda and appoints him to run marketing analytics for Legendary. The methods perform well in the motion picture market. Other Hollywood studios want to lease its services, and firms outside of entertainment express interest. Marolda and Tull consider setting up Legendary Analytics as an independent consulting business. At that point Dalian Wanda, China's largest entertainment and real estate conglomerate, buys Legendary. Should Marolda focus on China or the diversified U.S. market?
Acxiom built the market for personal data, yet sales have been flat for a decade during which marketing's appetite for data has exploded. Will the acquisition of a digital data onboarder, LiveRamp, give marketers what they want from a data broker?
Instacart is testing an Uber-style solution to the challenge of building a home-delivered grocery business. It is backed by $220 million of venture funding. Will this model succeed where businesses like Webvan failed? What are the questions that this exploratory venture needs to answer?
The marketing and operations managers for Olympic Rent-A-Car meet to decide how to respond to changes in the loyalty rewards program at the market-leading competitor. The competitor's program gives awards based on dollars spent instead of days rented and eliminates blackout dates. Olympic expects the program to capture more of the valuable business traveler segment, which rents cars more frequently and generally pays higher premiums than the leisure traveler segment. At the meeting, the team reviews the financial performance of the firm and the firm's reward program, called Olympic Medalist. They consider whether they can afford to match the competitor's loyalty program terms as they have done in the past and also consider how the competitor's actions will affect the entire car rental industry. Ultimately, they must respond with a truly distinctive strategy. Students must perform a quantitative analysis of each possible response and consider the value of customers in loyalty programs.
What is the value of Bluefin Labs's social listening data to Twitter? Acquired by Twitter in 2013, Bluefin had built a system that gathered millions of online comments in an effort to develop new metrics for TV programs and brand advertising. With data from Twitter and other social sites, expressions, not just impressions, could now be aggregated, measured, and used to calibrate brand performance and to sell media time. A second objective of the case is to understand the implications of social TV viewing, the audience engagement that results when people watch television with a smartphone or tablet in hand, participating in a virtual community of real-time TV watchers.
Four businesses had, by 2012, grown to dominate the infrastructure that all firms rely on to reach online customers. Will the balance of power among the four persist, will one take command at the expense of the other three, or are all four more vulnerable than they seem to outside forces? What are the implications for the pace at which consumers go online? Amara's Law claims that we tend to overestimate change in the short run, and underestimate it in the long run.
The sales representatives at Designs by Kate (DBK) sell private label jewelry at hosted parties and through online social media channels. They are also responsible for recruiting, training, and managing new sales reps. CEO and founder Kate Creevey designed the commission plan to encourage sales reps to build teams and become "leaders" for their teams. The strategy has been very successful over the company's first five years. Now the CEO is concerned that growth in top-line revenue is slowing, possibly due to an unwillingness by current sales representatives to build and manage their own sales teams. A survey reveals that many sales reps believe their incomes from jewelry sales decline when they add members to their sales teams due to increased competition for hosting parties within the same geographic area. The CEO must revisit the commission structure to determine if it is still an effective incentive. The case includes a quantitative assignment that students should complete as part of case analysis.
Google search had helped Demand Media grow to be a $1.9 billion online publisher. Then, social media and smartphone apps began to change the way people navigated the Internet. How should Demand Media respond? The business ran on a radically new model in which a stable of 10,000 freelance contributors supplied content, the Internet's search engines brought it 75 million readers each month, and advertising generated revenue. It took the guesswork out of content production, with algorithms that indicated which topics were being searched and created content accordingly. Demand treated its 5,000 online articles published per day as an investment, not a cost, a reversal of the traditional media model. In addition to being able to infer consumers' interests with its algorithm, the company had a formula for estimating the lifetime value of each piece of content. As the business models of print and broadcast media declined, Demand had figured out how to leverage digital and social media tools to bring down the costs of creating content and to find an audience. In spring 2011, executives at the five-year-old company were pleased with the company's billion dollar IPO, the biggest Internet IPO since Google's, but changes in consumer behavior on the Internet were obliging a review of the model.
Cheezburger Network was a Web publisher of humorous, user-contributed content, using social media for dissemination, and selling advertising against the traffic of 1 billion page views per quarter. In January 2011, it raised $30 million in venture capital for the network of 50 websites that featured an entertaining array of user-generated content. Beginning with a site based on pictures of cats with whimsical captions, it had grown into a small but impressive digital empire, riding waves of viral content. CEO Ben Huh prided himself on his ability to go from idea to implementation in just a few days, but this just-in-time method made strategic planning difficult. Profitable from day one and with $5 million of revenue across 50 brand identities, Huh's challenge was to evaluate his growth to date, to look critically at the digital media landscape, and to figure out how to best to spend the $30 million.