It's a tale old as time. You start off with an idea. It sounds great. The feedback says it's great. So the plan proceeds. But then you realize this is happening:
We (myself, the ITP and NYU Poly collaborators) had developed visual prototypes for a moviegoing and movieticketing app. Its features included variable pricing, the social event aspect of moviegoing, and other features that acknowledge that the decision to attend a movie is not motivated only by price.
It seems we made a car and forgot the engine. The heart of the project remains answering (or giving the best go of it possible) whether or not dynamic or variable pricing would bring in uncaptured demand. Although great research has been uncovered throughout the last several quarters, we haven't clearly answered that question. Part of it was due to lack of data. But all our work isn't for naught, it's just that a shift, a pivot is needed.
For the remainder of the fellowship, we're building the engine: building models and running simulations and making assumptions about what variable pricing would do to attendance and revenues. "If X is reduced by Y%, what happens to Z?" Financial 10-Ks for theater exhibitors will be useful to building hypothetical profit-and-loss statements, and we've found some comparable industries (that do variable pricing). In the end, we'll build infographics of our results and a comprehensive whitepaper of this year's research. And then, present our prototype.
It's tempting to say, "why didn't we do this first?" but there were some big challenges. Firstly, when we couldn't get the data sources required, I was uncomfortable with just building simulations off of assumptions. Plus, there was already academic literature out there about variable pricing's merits; what else could we add? So I jumped straight into the prototype phase. But as some wise advisors mentioned, these simulations are just a start. We'll keep it as simple as possible. We're opening up the conversation and gladly invite others to point out what is wrong, how we can improve our assumptions, and adjust accordingly.
Stay tuned for more progress updates! This is what we want in the end: