Rodriguez v. Google LLC 20-cv-04688-RS (N.D. Cal. Jan. 3, 2024) reaching a conclusion that Google was not unjustly enriched. Furthermore, Google bears the burden of quantifying recouped profits. Google relies on Hart to argue that Lasinski's methods suffer an attribution problem. In that case, the plaintiffs calculated gross revenue minus costs equal unjustly retained benefit. By contrast, Lasinski further apportioned his calculations by how many class devices had their WAA/sWAA off, a value provided to Lasinski by Google. Lasinski's models do not speculate on hypothetical scenarios, but Google's own practices. c. The actual damages model is not unreliable for being used in a different case Google argues that Lasinski's actual damages model should be excluded because it is “cribbed” from another case. However, that by itself should not preclude Lasinski's actual damages model. See Brown, 2023 WL 5029899 at *6 (discussing a similar damages calculation but for restitutionary damages). As it did in that case, Google tries to argue that Lasinski does not rationalize “pegging actual damages to a one-time $3 payment per device.” Daubert Mot. at 18. However, as the court in Brown already noted, “The $3 rate is derived from looking at what Google actually pays Screenwise participants for agreeing to allow Google to collect their browsing data.” Id. (emphasis added). The simple fact that this model was utilized in another case averring Google mishandled private data does not warrant exclusion. d. Lasinski's models are not “cherry-picked” Google argues Lasinski's damages model “cherrypicked” his actual damages model from “a single survey.” Daubert Mot. at 19. Google insists that because Lasinski could not explain why $4 or $2, or any other figure, would also be appropriate, the $3 is a cherry-picked figure. It also argues that because Lasinski referred to the $3 valuation as “conservative” in his deposition, this must also mean that it is inaccurate. However, Google 23 incorrectly characterizes the actual damages *23 calculation as being randomly picked from a single survey. In fact, Lasinski provided analysis and compared market studies to explain why he settled on the Screenwise panel and the $3 figure. He provided insight as to why the payments made by Google to the Screenwise participants offers a strong basis for an actual damages model. Lasinski explored other programs that pay users for their data, and ultimately generated a model based on an actual, baseline payment made by Google to track actual consumer data. e. Actual damages need not account for variances as they are based on the market value Google's final argument is that Lasinski's actual damages model does not account for variances among class members and risks grossly undercompensating and overcompensating others. Google makes three arguments to this end: first, that some users are willing to let analytics providers access their data for free. Second, Lasinski overlooks the “diversity of user attitudes” related to privacy. Third, Lasinski never showed actual economic injury to the class. However, as Brown points out, where there is unjust enrichment, “restitution can be measured by either: (a) the value of benefit to the defendant; (b) the cost to plaintiff of conferring such benefit; (c) the market value of the benefit; or (d) the price the defendant has expressed a willingness to pay, if the defendant's asset may be treated valid on the question of price.” 2023 WL 5029899 at *7 (quoting Rest. 3d of Restitution and Unjust Enrichment § 49). In that case as here, Lasinski appropriately built his model around the price Google was willing to pay for users' privacy and this “objective standard” warrants denial of Google's motion. To the extent that users have mixed attitudes related to privacy - all class members shared at least one uniform attitude related to privacy, evidenced by their uniform conduct of switching WAA/sWAA off. Therefore, as to the uniform conduct of the class, the actual 14