Each year, an increasing number of college student survey respondents are accessing online surveys using smartphones, instead of desktop computers (Sarraf, Brooks, & Cole, 2014). In 2011, about 4% of respondents to the National Survey of Student Engagement (NSSE) used a smartphone, but by 2014 the proportion increased to about 18%. The widespread adoption of smartphones among college students has prompted discussions among some institutional and higher education researchers about data quality and appropriate survey formats. Some research suggests that there is little or no substantive difference for users accessing web surveys on tablets as compared to desktop machines, but the user experience on a smartphone is recognized to be significantly different than the other devices (Buskirk & Andrus, 2012). This has caused some researchers to optimize their online surveys for smartphones, however research is limited about how this may affect survey data quality. Using results from a five-institution experiment using the 2014 National Survey of Student Engagement (NSSE) the current study details the impact that smartphone optimization has on a survey with over one-hundred questions. Study research questions center on how various data quality indicators are effected by optimizing a survey for smartphones, including item skipping, completion time, scale factor structure, and response option differentiation (straight-lining). Based on their recent experience, presenters will offer insights into developing a smartphone-optimized version of a relatively long survey.