Mint.com today has rolled out the beta of a new service called Mint Data that takes the tons of anonymous shopping data it receives, and turns it into a searchable database of retailers. Similar to the way Google’s Alexa categorizes the popularity of a website by its unique visitors, total views, and inbound links, Mint Data ranks a retailer’s popularity by the average purchase price and number of purchases per month.
The information comes from the anonymous spending data of the more than 4 million Mint users, and Mint breaks it down into which categories people are spending their money on (such as food, dining, entertainment, etc,) the specific businesses that they’re patronizing, and the city in which they’re spending their money.
It’s actually quite a powerful tool to give to both consumers and small business owners. With Mint Data, for example, a user could learn that the hotel in Maryland where the most money is being spent is the Raddisson in downtown Baltimore, where the average purchase price is 7.07, well above the state’s average hotel bill, which is just around 0. This doesn’t necessarily translate to popularity, though, and Mint Data gives the hotel a 7 out of 10 for popularity, based on the frequency of transactions there.
“When we first crossed the million-user mark, we looked at the stories the anonymous, aggregated customer data could tell about the economy,” said Aaron Patzer, Mint founder and vice president/general manager of Intuit’s Personal Finance Group. “Now, we have enough users in enough cities across America to give a distinct, anonymous look at the country’s economy down to the city level. What do we spend on restaurants? Which stores are a particular town’s favorites? How has the downturn affected things like coffee or bars? People may use the information they find to help them make better money decisions.”
Right now, Mint Data has listings in 300 U.S. cities where users can check out the local spending habits.