Using data from a prominent online platform for launching new digital products, we document that the composition of the platform’s ‘beta testers’ on the day a new product is launched has a systematic and persistent impact on the new product’s success. Specifically, we use word embedding methods to classify products launched on this platform as more or less focused on the needs of women customers, and show that female-focused products launched on a typical day – when the majority of beta testers are male – experience 30% less growth and are 3.5 percentage points less likely to be operating a year after launch. Exploiting exogenous variation in the composition of users who visit the platform we find that this product gender gap shrinks to zero on days when more female beta testers are present on the website, suggesting that it is the composition of early users, rather than unobserved differences in the growth potential of products catering to women, that is driving our results. Our findings highlight the importance of understanding sampling bias in entrepreneurial experiments and how such bias may lead to a dearth of innovations aimed at consumers who are underrepresented among early-users. (Joint work with Rembrand Koning and Ruiqing Cao)
Ansprechpartner: Rainer Widmann