Applying option thinking to value experiential marketing content

ABSTRACT

Investments in new marketing offerings are notoriously risky, as they require firms to make judgments about an uncertain future. The authors develop an option-thinking framework for valuing and selecting new marketing offerings that combines real-options theory with virtual markets. They apply the framework and demonstrate its power empirically in the context of experiential content, where valuing marketing offerings constitutes a particularly challenging issue. Specifically, they test the proposed option-thinking framework in two experiential settings (movies and professional team sports) and compare it to current managerial practice. Each experiential setting deals with a common managerial marketing challenge. Study 1 examines extending a brand into a new category, and Study 2 investigates ingredient branding. The proposed framework provides managers with an empirical approach that enables them to consider the “value of waiting” when making investment decisions that involve uncertainty regarding future market developments.

Disclosure statement

The authors declare that they have no conflict of interest.

Notes

² In general, the choice of an appropriate price aggregation function depends on the VM environment. In markets with periods of strong price fluctuation or sudden price shifts due to rather short-term effects, the mean price (as compared to the last price) is arguably the preferred price aggregation function.

³ Note that the option price on the expiration date equals the price on the valuation date as it was paid at the valuation date; likewise, the exercise price is fixed at the valuation date as it is one of the input parameters used to determine the option price.

⁴ The market for filmed entertainment has been undergoing several changes since the time period for which we collected our data, such as the rise of streaming services and both backward and forward vertical integration between channels (e.g., Netflix as distributor now also producing films, Disney as producer now also distributing films). However, with few exceptions, major films are still released in movie theaters before they are made available via home entertainment channels and the success of films in theaters still plays a fundamental role – it attracts the attention of audiences and largely predetermines the economic fate of a new film. So, while changes have occurred and will continue to occur, we have confidence that the logic of success predictions through VMs has largely remained the same and is valid for evolving forms of distribution.

⁵ Note that a studio should only exercise an option if the underlying movie is predicted to be profitable, which made it reasonable to assume that exercising the option entailed producing the movie.

⁶ Because the HSX predicts box office revenues only for the first four weeks after release, we applied a scaling factor to translate the HSX predictions into predictions of the total box office revenues. To calculate the scaling factor for Uptown Girls, we divided the total box office revenues of each of the movies in the sample except Uptown Girls by the box office revenues they generated in the first four weeks and took the mean. This procedure resulted in expected total box office revenues for Uptown Girls, SUCCESS_{UptownGirlsT1}, of $42,094,825.

⁷ Using the Black-Scholes model resulted in a very similar option price of $42,920. Comparing all 61 Black-Scholes prices with the binomial model prices revealed highly similar results (mean absolute difference = $1,007, which corresponds to a mean percentage difference of 2.95%).

⁸ As study 1 considers realized book adaptations, for which actual production budgets are available, we opted to use these “objective” values (rather than ex-ante estimates) in our illustrative application. Importantly, as budgeting is a crucial aspect of any film project (Vogel, 2015) and investors often expect the ex-ante production costs to match closely the ex-post values, we believe that our ex-post values are robust proxies that do not systematically over- or underestimate the values managers would use when applying the proposed option-thinking framework

⁹ The absolute amount of the option price might appear relatively small in comparison to other facets of the production costs. However, purchasing options for all available content, including those for which the probability of exercising the option and turning it into a product (movie) is low, would probably disqualify the studio from future content acquisitions, creating a serious disadvantage for the studio.

¹⁰ We collected the transfer fees from transfermarkt.de, one of the largest internet databases for soccer player values and transfers. Note that it was not possible to use transfermarkt.de to derive a VM-based success prediction and its volatility as players are not traded on this platform.

¹¹ This procedure can be easily adapted to more than two possible developments to represent more complex situations.

¹² We collected this data from transfermarkt.de, one of the largest internet databases for soccer player values and transfers. Note that we cannot use transfermarkt.de to derive a VM-based success prediction and its volatility as players are not traded on this platform.

Additional information

Funding

The work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) [VO 1555/1-1].