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Increasing deployment of technologies and AI-infused analytics to deliver personalized offerings amplifies consumers' privacy concerns and challenges their trust in the firm. Mitigating customers' privacy concerns and communicating personalization benefits is a challenge for firms; yet little is known to differentiate strategies that overcome from those that exacerbate these challenges. To address this challenge, this research conceptualizes transparency, control, adaptation, collaboration as the primary privacy-personalization strategies, based on existing literature and firms' practices. Privacy-personalization strategies can be defined as strategies that maybe, or are, implemented by firms to manage privacy and personalization, i.e., encourage customers to release personal data by mitigating their privacy concerns and communicating personalization payoffs. Firms can use either adaptation or collaboration strategy to deliver personalization payoffs, whereas transparency and control emphasize on protecting consumer privacy during the process. Using trust theory, we conceptualize that privacy-personalization strategies impact consumer continuance behavior through firm's trustworthiness. Together, our studies will advance the literature on privacy and personalization strategies and provide insights for firms in designing effective privacy strategies. [ABSTRACT FROM AUTHOR]