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Recent success of data-centric services rests upon delayed or two-step transaction models. In a first transaction services such as online search or social networks are offered for free. In exchange consumers provide data like clicking behavior or details about their identity. In a second step, service providers turn into data providers selling or using data for targeting purposes, e.g. online advertising or credit inquiries. As success of such services witnesses consumers generously give away data. However, many studies also observe a high appreciation for privacy. Privacy is the claim of individuals to determine for themselves how information about them is handled. Information deficits about data usage prevent consumers from enforcing this claim. As a condition for information asymmetries, information deficits may threaten market efficiency. We propose a model for measuring consumer information deficits in two-step transactions of data-centric services. Evidence of information deficits will support policy makers and software engineers in improving Transparency Enhancing Technology (TET) as tools for effective signaling and screening.