App Store Economics – Low-Volume App Market Economics

I talked previously about optimizing revenues in a top-charts, high-volume App Store market setting, and the inherent pressures of competition, visibility, and consumer demand. I also discussed how these pressures cause app suppliers to receive the greatest benefit from lowering prices to induce volume purchases.

If you recall, the discussion stemmed from David Smith’s two (admittedly anecdotal) hypotheses:

1. Initially higher pricing signals an inherent value to the market.


2. If your app is in the top rankings, lowering the price serves to prolong ranked status and increases overall revenue.

I’d like to discuss the former claim now, and determine if higher prices do in fact signal inherent value. What about situations where an app isn’t on the top charts, where demand is relatively stable over time, or perhaps the app fills a very specific need?

I’d like to postulate that apps existing in this situation exist in a relatively price insensitive market. Why? These apps aren’t being discovered through random browsing or scanning the top charts. These apps aren’t being purchased on a whim; instead, they are being selectively sought out. The customer is looking for a specific need to be filled, a job to be done.

In cases like this, price serves as a very different signaling mechanism. Whereas in the earlier discussion a low-price prompted compulsive purchasing – not dissimilar to advertising a sale on candy at the checkout lane of a grocery – now, price may command a certain valuation from the consumer. A low-priced app trying to fill a specific need may be seen as having some sort of deficit which forces it to command a lower market price.

More importantly though, purchasers who have been found the app’s listing by searching for a specific need are likely predisposed to compare apps by e feature set they advertise, rather than the sticker price. If an app fails to meet a specific need, the price will hardly matter to the consumer.

In either case, whether signaling or by capturing the inherent value users place on an app deigned to meet a specific need, developers of apps with stable purchase throughout may in fact increase their net revenues through a price increase. I think the line is less clear than in the case of high-volume purchasing, though. Too high a price commanded by the app may put it out of the range of reason for their customers.

There are still many questions to be answered regarding the market though. These last two posts have illuminated the more predictable reaches of the App Store market, and the steady-state behavior of each. But that says nothing about how apps arrive at their steady-state behavior.

In dynamic systems, we deem this sort of analysis a “phase plane” plot. Attractors, such as these high and low-volume states, define equilibria and steady-state behavior. But often what makes a system interesting is how these points are reached, and more practically, what outside agents with an interest in reaching said attractors, such as the developers that make a living off the apps, can do to perturb the system one way or another.

And so there is much left to discuss. Do more attractor states exist with the network? What kind of stability do these states exhibit? And where do the boundaries between these points lie, and what influences their magnitude and direction? With more analysis, some or all of these questions can be answered.