In this research, we conceptually examine the use of personas in an age of large-scale online analytics data. Based on the criticism and benefits outlined in prior work and by practitioners working with online data, we formulate the major arguments for and against the use of personas given real-time online analytics data about customers, analyze these arguments, and demonstrate areas for the productive employment of data-driven personas by leveraging online analytics data in their creation. Our key tenet is that data-driven personas are located between aggregated and individual customer statistics. At their best, digital data-driven personas capture the coverage of the customer base attributed to aggregated data representations while retaining the interpretability of individual-level analytics; they benefit from powerful computational techniques and novel data sources. We discuss how digital data-driven personas can draw from technological advancements to remedy the notable concerns voiced by scholars and practitioners, including persona validation, inconsistency problem, and long development times. Finally, we outline areas of future research of personas in the context of online analytics. We argue that to survive in the rapidly developing online customer analytics industry, personas must evolve by adopting new practices.