We show evidence of the impact on pricing of a new technology providing information on market conditions (supply growth, demand patterns, pricing trends and competitor rates) in the short term rental market. Using a sample of 2,196 housing units over 18 months available on Airbnb in Madrid (Spain), we observe the adoption of this technology by property managers at different points in time for 16% of our observations. Our Propensity Score Matching (PSM) estimates support the evidence of a greater market transparency obtained through the adoption of this technology, with a signicant increase in revenues obtained through a reduced average daily price and increased occupancy. Overall, our results are robust to several model selections dealing with

a potential endogeneity issue. We also show some preliminary evidence of property managers increasingly engaging in dynamic pricing after the adoption of this technology. Particularly, revenue growth seems to be generated through a small price drop leading to a rise in occupancy at the top end of the price distribution, rather than at the bottom end, where a signicant and much higher price drop is not able to generate the necessary occupancy growth to obtain an overall increase in revenues.