With more than four million users, Mint’s personal finance platform no doubt has a massive amount of data that it can mine regarding consumer’s spending habits. In fact, the site already uses some of this data to show seasonal trends. Today, the Intuit owned company is launching its realtime customer data insights to the public, after soft launching the product almost two months ago.
Mint Data aggregates anonymous spending data from Mint’s users to give you realtime insight on what people are spending on across the country. For example, the platform lists the most popular restaurants in San Francisco (by visits), the top shopping spots in New York City (by highest average spend), and the highest spending cities in the U.S.
Mint Data will also show spending data both by average purchase price and by popularity, which is defined by number of transactions per month. The rankings can be viewed by category, such as “food and dining,” by specific business, and broken down to the city level. For example, Mint Data shows that the average spend at a Starbucks in New York City is $5.38. The site also compares this to the average spend at coffee shops overall, which is slightly higher.
In terms of actual regional data, you can choose from 300 cities in the U.S. to compare spending. And Mint.com users can compare their own personal finance and spending habits by category or merchant against averages in their area, or against the national average.
As a consumer product, this data is pretty fascinating, and a great way to get a little more insight as to how your spending stacks up against the rest of the consumers in your city or at a particular store. I can imagine that that some of this data could be mined even deeper to compare demographics and spending.
When the mobile payment service