But they outlined that migrating to IP-based location data offers more accurate, real-time geo-mapping. By using a unique correction algorithm that ties together travel data, with IP-based geo-mapping, to two other sources, this corrects both the size of the zip code's volume and the impact of traffic in the O&D.
Utilising DOT DB1B and Census data, combined with travel data, allows for robust correction that improves over time with intelligent learning, spotting recurring errors and making automated corrections to provide logical, fully adjusted results showing a customer's residential location as well as their departure and destination.
This unique algorithm can be utilised to remove the limitations of location data. Traditionally this has been tied to a customer address through their credit card, it can now offer passenger information through their destination.
It uses the same methodology, but instead of correcting with Census data, hospitality industry data is used to scale the sample to correct the destination zip code. Whereas previous data highlighted the destination as Nashville, you can know understand how many visitors are staying in Brentwood, Donnelson, or Franklin.
“This algorithm runs the data for every zip code in the US,” said Cambron. “If you need to compare your market with a competitor you can do that on an apples by apples basis.”