Crowdsourced employee reviews: a predictor of stock returns?
A growing amount of literature examines the relationship between financial performance and employee sentiment, as measured by crowdsourced company ratings and reviews. In particular, recent studies assess the ability of these datasets to forecast stock returns and earnings surprises, since changes in employee satisfaction levels can signal shifts in the economic condition of the firm. In this report we 1) highlight the predictive characteristics of employee feedback data, 2) discuss the limitations of these datasets and offer possible solutions, and 3) provide a market summary of crowdsourced employee review datasets.
Many studies find that companies with significant improvements in employee-authored reviews and ratings outperform firms with declines. One study by BAML found that shares of companies with high Glassdoor ratings outperformed those with low ratings almost by 5% per year from 2013-2018.
A previous Neudata report highlighted studies that attribute the relationship between employee satisfaction and company performance to productivity levels – satisfied employees tend to work harder for longer tenures. A recent study by the Journal of Financial Economics, offers an alternative explanation for the relationship. The paper argues that changes to employee satisfaction can signal fundamental information about the firm, before it is made public and embedded into stock prices.