priceonomics – data mining and analytics with public data on the web

I came across the startup priceonomics and I love how it combines a clear expression of value with simplicity.  Search a product you like and it shows you the price range and distribution, price change over time, and also the option to receive an e-mail regarding the product if it appears at a good price.

What I love about this startup immediately:

*Data mining: these prices are pulled from all over the web

*Analysis: the distribution of prices is presented, and used to determine when there is a good deal for a consumer

*Design: all of this is under a simple to use interface- making the tool very accessible and easy to explore with.

*No sign up: I don’t have to sign up anywhere to use this. There is no social element. I don’t have to share. This is so refreshing.

I use some of these skills on a day to day: (1) getting public data from the web (scraping, APIs, or database download), and  (2) running some sort of data analysis.  Yes- I realize that’s very vague, but what I find most compelling is that this startup combines those skills with a simple interface and creates a consumer product out of it. What other products would be useful, following a similar approach: combining public data available on the web, analytics, and clear design?  I would love to see some consumer analytic products come out that are not open ended, that have some target sector, and that make use of publicly available data.

In some ways this reminds me of the sophisticated https://www.decide.com/, which uses machine learning of tons of consumer electronics data to help you know the best time to buy a product you’re interested in.  See this NYTimes Bits article  for more details on Decide.  The company was founded by Oren Etzioni  who is also behind Farecast (which was acquired by Bing Travel)- a company that helped you determine the best time to buy plane tickets.

What other sectors or problems could benefit with this type of product? I imagine it begins with thinking of where we would need it on a day to day- the sort of data we collect, wade through, and decide upon on a day to day.  Where is it frustrating and where can it be made simpler?  With priceonomics, on buying most products, with Decide, on consumer electronics, and with Farecast, on plane tickets.  I immediately start brainstorming in potential areas of opportunity- as jump off points- nutrition, health, education, and jobs.