Game monetization discussions tend to focus on what to monetize broadly (gameplay or cosmetics) as well as how to price it. As someone might imagine, these are crucial and foundational discussions to have. So naturally, therefore, it makes sense to invest a lot of human capital into optimizing them. Increasingly, however, I’ve become convinced that just making lots of stuff trumps all other optimizations. Instead of being an afterthought, supply-side considerations deserve to be front and center.Continue reading “Why I’m a Supply-Side Game Economist”
Everyone’s favorite former Rovio employee is a prolific writer on F2P games; the closest we have to a Fukuyama. Seufert has covered a range of topics, but none more important than internal organization.
Seufert argues for a number of institutional policies to surround analysts with within an organization. Frequently, analytics and data are as much about the appearance of sophistication as they are actual value adds. This need not be the case. The confusion arises over where the value of data lies. Perhaps ironically, data’s value doesn’t lie in the data, but rather in the data analyst.
In most organizations, analytics reports to product teams, a mistake, Eric argues. Often product managers face the principal – agent problem: their incentives and the companies do not align. Product managers want to successfully manage products and will present the narrative they are doing so. This is inefficient for companies who often wish to assess the true performance and trajectory of a portfolio. When an analyst’s career path depend on a product manager their narratives will often match. With organizational independence from product teams, analyst’s incentives align closer to the companies, providing more objective analysis.
Not just an accountability watchdog, real analyst value revolves around the ability to drive product roadmaps. At it’s highest order, analytics is a forward looking discipline, not a backward looking one. By experimenting and studying human behavior, analysts find levers that pull certain responses. This creates opportunities to exploit these levers. Do currency pinches increase monetization? Are new gotcha characters or new levels driving revenue? Should we invest more in reducing load times or UI changes? Using theory driven empirical investigation analysts can move companies towards better outcomes than competitors. If organizations don’t allow analysts to pursue these questions, they’ll become cheerleaders for product teams. On the other hand, if first order information (RR, ARPU) is not accessible or automated, analysts will forever be running the hamster wheel of reporting. This is one of the more overlooked points Eric argues for.
I think this suggests a dual mandate of analysts: (1) accountability of features and (2) what features are worth developing. This creates a natural tension of not only playing the role of watchdog to product managers but partners as well. It is the duty of good analysts to navigate this relationship successfully.