Using data on mobile Internet usage of thousands of individuals, we provide some of the first analyses linking mobile usage to key demographics such as income. We find a reverse-U relationship between mobile Internet usage and income—notably different than the monotonically declining relationship found on home devices. This pattern suggests that data caps are particularly binding on low-income users. We then construct a simple model of mobile Internet usage that incorporates demand features suggested by our empirical finding and prior empirical findings on device adoption and usage. After abstracting away from cost and two-sided market considerations, we solve the model, and through comparative statics, identify demand conditions for which usage-based pricing (via a data cap) is, or is not, revenue enhancing. Key insights from this analysis are: (1) the tendency toward demand-driven price discrimination is hill-shaped (increasing then decreasing) in the number of low-income users and eventually declining in high-income users, and (2) a relatively high (low) proportion of total value attained from relatively low usage levels by low-income (high-income) users increases the tendency toward demand-driven price discrimination. Hence, to the extent that a market has a large number of low-income users and/or high-income users attain a higher proportion of their total value at the cap than low-income users, the use of caps by providers is more likely driven by cost (or other non-demand-side) considerations than by revenue enhancement. Lastly, additional analysis shows a largely monotonically increasing relationship between income and usage intensity (measured as page views in a session), suggesting that, ceteris paribus, price discrimination strategies may be more effective if tied to usage intensity rather than duration.