CRA’s expert was retained to assess whether members of a purported class could be reliably identified from only a list of wireless phone numbers dialed on various dates in the past, and to apply data analytic techniques to assess whether customer responses are a reliable means of identifying which calls, among millions of calls, were made to wrong numbers. CRA’s expert applied sophisticated text matching techniques to compare third-party databases of time-delimited name-and-number registries to assess their error rates with respect to the potential class members. CRA’s expert also matched incoming calls with outgoing called numbers, finding that purported wrong numbers were frequently not in fact wrong numbers for the accused calls.
Addressing low response rates in expert surveys
In this Law360 article, Kristen Backor (a survey and market research expert), Brandon Duke (a litigator), and Yamini Jena (an analyst in litigation consulting)...