The public likely wouldn’t characterize Yelp and Google as tools for data-driven decision making. However, examine their respective user experiences in selecting restaurants and it becomes clear that these tools do a better job facilitating data-supported decision making than the business dashboards provided by well-meaning analytics departments in many enterprises.xiv
Yelp and Google took decisions that once relied on anecdotal evidence, intuition, and lived experience and drove people to use empirical data instead. When someone consults Yelp or Google, they can intuitively interpret the data and adjust their decisions, narrow the choice of outcomes, estimate the cost and likelihood of positive utility, and assess the variability and uncertainty of those estimates.1
As Benn Stancil puts it: “We start by looking up reviews on Yelp and Google. We don’t just mechanically favor the restaurants with the highest ratings, but assess the data analytically. Restaurants with fewer stars but more reviews might be better than those with just a handful of reviews; we check the recent reviews to make sure places are still good; we adjust star ratings by price. Once we find places we like, we use Google’s crowd estimates to see if we’ll be able to get a table. We flip through Resy to find reservations, which provides another analytical signal: We’re suspicious of a restaurant with too many openings. And finally, to make sure our chosen restaurant fits into the rest of our evening’s plans, we rely on Google Maps to tell us how we should get there and how long it’ll take.”xv