Chris Hathaway sees basic location information scattered across the websites of hundreds — or thousands — of coffee shop chains, hotel groups, and fast food joints, but argues that it’s almost impossible to do anything more sophisticated with the data than find your closest Starbucks. His company, AggData, is attempting to fill what he sees as a gap in the market; scraping addresses and other facts off company websites to create simple files of store locations that can then be enriched with coordinate data and sold.
Customers for this data include competitors, market researchers, consultants, and even the companies themselves; as is so often the case, it can be easier to buy data on store locations from a third party than to find the authoritative sources within your own organisation. AggData is strongest in the US today, but also offers a growing body of data for other countries. Although the data files are structurally simple, Chris sees plenty of opportunity to continue collecting and selling data to a growing community of customers.
Unlike Factual, which was the focus of last week’s podcast, AggData is not currently interested in combining data from different sources. Customers download separate files on the locations of Starbucks, Peets and Tim Hortons, and not a single aggregated set of coffee shop locations. The AggData model is also predicated upon using their own scripts to extract data from third party sites; asked if he would accept a file of WalMart store locations supplied by WalMart, Hathaway explained why he would — and does — decline.
Following up on a blog post that I wrote at the start of 2012, this is the second in a series of podcasts with key stakeholders in the emerging category of Data Markets. Other conversations, all of which will be published here, have been scheduled with BuzzData, DataMarket.com, Factual, Infochimps, Kasabi, and Microsoft. I am still adding conversations to the series, and intend to talk with more companies and with analysts and investors with insight to share.