Choice Architecture, Privacy Valuations, and Selection Bias in Consumer Data

How much do consumers’ privacy valuations change under the influence of choice architecture? How does this influence affect the efficiency of data collection, by changing not only the quantity of data collected but also its representativeness? To answer these questions, we run a large-scale choice experiment to elicit consumers’ valuation for their Facebook data while randomizing two common choice frames: default and price anchor. An opt-out default decreases valuations by 14%-22% compared to opt-in, while a $0–50 price anchor decreases valuation by 37%-53% compared to a $50–100 anchor. Moreover, in some consumer segments, the susceptibility to frame influence negatively correlates with consumers’ average valuation. Our results suggest that conventional frame optimization practices with a goal to maximize the supply of data can have opposite effects on its representativeness: A bias exacerbating effect emerges when consumers’ privacy valuations and frame effects are negatively correlated. On the other hand, such a volume-maximizing frame may also mitigate the bias by getting a high percentage of consumers into the sample data, thereby improving its coverage