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Ever wonder why gasoline prices are higher in some parts of town and lower in others?
The Cincinnati Enquirer's summer project answers some questions and lays out a template for how you can adapt this idea for your own community. For the last eight years, the paper's assistant business editor, Mark Wert, has supervised the reporters who handle gasoline-price stories for the paper.
Wert tells me:
During that time, we have kept a database of the daily average price in Southwest Ohio and Northern Kentucky, so we have great historic data from the
Oil Price Information Service (OPIS). It's very helpful in analyzing trends, doing year-to-date comparisons and then computing how much, more or less, typical drivers have spent.
But a few years ago, reporter James Pilcher took a class in mapping software and we hit on the idea of mapping the actual individual prices from stations as a way to look at patterns. This year, Pilcher teamed up with reporter Greg Korte to look at two months' worth of data that OPIS provided from more than 700 local stations.
Their report harnesses that data to confirm that a lot of what people know about gasoline prices is true. The data were used to come up with six secrets that we printed daily -– you pay more near an interstate and way out in the sticks and you’ll pay less at big-box retailers that offer low prices for customers with loyalty cards or memberships, are two examples -– followed by the Sunday explainer on how all this works (specifically, how Cincinnati and a few other cities have extraordinarily sharp competition for gasoline sales and that benefits consumers).
Besides giving us a weeklong series of Page 1 copy, it gave us hyper local data -– an average price for gasoline by ZIP code. We also pushed all of these stories on our Web site, garnering a lot of comments in the process. (Our biggest hits probably came from the story saying that Tuesday was the best day to buy gas -– and that it didn't have much to do with deliveries.) Finally, the reporters went on the local public radio station to discuss their findings.
Here is the lineup of stories and headlines that ran in late July:
This is a good lesson in what I call "leveraging your digital assets." By that I mean we should ask ourselves: What information do we collect on a regular basis and what use might that information have beyond the daily use? How can we compile it and analyze what long-term trends the data suggest?
