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There are a growing number of persuasive technology apps and systems that aim to make individuals (and therefore society) healthier, greener, more financially sound, smarter, happier, and so on. Analysis of such technologies often focuses on the aggregate results, for example the total percentage of residential electricity saved across households. However, an aggregate focus misses important aspects of the behavioral responses at an individual level. This talk focuses on experiments and models that examine behavior at the level of the individual, and demonstrates how such analyses could guide the effective design of behavior change technologies and better predict their impacts on different users’ segments.