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The current work characterizes the users of a VoD streaming space throughuser-personas based on a tenure timeline and temporal behavioral features inthe absence of explicit user profiles. A combination of tenure timeline andtemporal characteristics caters to business needs of understanding theevolution and phases of user behavior as their accounts age. The personasconstructed in this work successfully represent both dominant and nichecharacterizations while providing insightful maturation of user behavior in thesystem. The two major highlights of our personas are demonstration of stabilityalong tenure timelines on a population level, while exhibiting interestingmigrations between labels on an individual granularity and clearinterpretability of user labels. Finally, we show a trade-off between anindispensable trio of guarantees, relevance-scalability-interpretability byusing summary information from personas in a CTR (Click through rate)predictive model. The proposed method of uncovering latent personas, consequentinsights from these and application of information from personas to predictivemodels are broadly applicable to other streaming based products.

A relevance-scalability-interpretability tradeoff with temporally evolving user personas