Last month, the Second Circuit heard oral argument in what had seemed like the most consequential consumer class-action appeal in that court in years: three consolidated cases involving “flushable” hygienic wipes. Both sides of the class-action bar were at the edge of their seat waiting for the Second Circuit’s guidance on several controversial issues of class-action law, including the appropriate standard for reviewing damages models at the class-certification stage. Earlier this week, however, the Second Circuit essentially punted, sending the cases back to the district court for “further factual development.” This is a frustrating result, but reading between the lines, class-action defendants may have reasons for cautious optimism.
Proving Retail Sales Figures In Consumer Class Actions: Different Approaches Lead To Very Different Results
To prove damages in a consumer class action, the named plaintiff must show—among other things—how many units of the defendant’s product were purchased by consumers in the relevant state (or states). This is easier said than done. Manufacturers generally keep records of their own wholesale transactions—i.e., how much product they shipped to distributors or large retail chains. But they generally don’t have direct visibility into sales at the retail level, since they aren’t a party to those transactions. If not all of the product sold at wholesale ends up being purchased by consumers, manufacturers’ records may not reflect this. Likewise, if the product that a manufacturer ships to an address in State A (e.g., a regional distribution center) ends up being moved to State B before reaching store shelves, manufacturers’ records will not reflect this either. What, then, is a class-action plaintiff to do?
Over the last few years, “conjoint analysis” has become the methodology du jour for false advertising plaintiffs seeking to demonstrate they can calculate class-wide damages. Conjoint analysis is so named because it is used to study the joint effects of multiple product attributes on consumers’ choices. At bottom, conjoint analysis uses survey data to measure the strength of consumers’ preferences for particular product features. Or, put differently, it tries to isolate how much people care about an individual product attribute in a multi-feature product (in a more scientific manner than just asking them directly).