This web analytics case involves a venture capital company that made investments in a start-up company that provided a cloud-based marketing data analytics service. When considering its decision to invest in the company, the venture capital firm relied on representations that the company had made regarding the platform’s average monthly and daily users. After the venture capital fund made its investment. it was discovered that both the average monthly and daily user figures provided by the startup were exaggerated, in many cases grossly so. The start-up’s founders contended that the metrics were incorrect due to an innocent mistake, and that they did not mean to intentionally mislead potential investors.
Question(s) For Expert Witness
- 1. Do you have extensive experience analyzing these metrics?
- 2. How important is it for a company to disclose the correct metrics?
- 3. How critical are these metrics in the industry?
Expert Witness Response E-020490
I have extensive experience analyzing MAU/DAU metrics in various capacities. Clearly, MAU/DAU data is one of, if not the most, defining measure of a software platform or application. I have seen a number of situations where apps have misrepresented this data, affecting valuation, approval, and more. These metrics are absolutely critical in the industry, and any founder would be aware of their crucial importance in investment decisions. As a result, I find it unlikely that they were not in some way complicit in the misrepresentation of these numbers.
This data analytics expert earned his BS in Economics/Statistics from the University of North Dakota and his Master’s Degree in Applied Statistics from The Ohio State University. He is a former senior quantitative analyst at Mattel, where he worked on digital channel analytics covering paid search, display advertising, and website visitation. As an instructor of Database Marketing Analytics at Rocky Mountain Direct Marketing Association, he taught marketers the principles of audience segmentation, marketing effectiveness measurement, and concepts like lifetime value and a/b testing. He then moved on to serve as the Director of Analytics at Data Logix Inc, where he led audience modeling, digital campaign effectiveness measurement, and digital platform reporting. Their products included syndicated audience segments, on/offline measurement solutions, and some digital media execution. This expert continued his career at Conversant Inc., a tech firm building individual-level profiles of consumers across web browsers, smartphones, and tablets. At conversant, he managed three analytic groups — audience lab, analytic development, and media analytics. Recently, this expert became an Analytic Engineer at a technology firm that provides mobile measurement & user intelligence solutions for enterprise marketers.