Data isn’t just the numbers or facts apparent on the surface: it often has a hidden secret that many companies miss out on.

That secret is location information. Whether it’s deliberate geotagging or simply tracking back through the IP address of an internet connection, there’s a good chance that any transaction or other online activity you look at has an associated location. That’s also true of all sorts of offline data, whether the location clue is a postcode, an area code or the name of a local authority.

Location details gathered from data can bring a company additional insight in two ways. The first is straightforward categorisation: for instance, a letting agent will want to target marketing at areas where home ownership rates are low. But there’s also a second way — using location details as a bridge between different sets of data. This could be varied data covering different subjects and in different formats.

The key to this approach is often location analytics, which involves displaying the data in visual form. For example, the letting agent might have three sets of data: census figures that show home ownership rates by postcode; Land Registry data showing the frequency of house sales by street; and local authority data showing the number of students by council ward.

As raw data tables, it’s difficult to quickly compare and contrast this data. With location analytics all three data sets can be displayed on the same map, making it easy to spot potential sweet spots. It’s also straightforward to change the emphasis placed on different data — such as avoiding rather than targeting the student market, without having to start from scratch.

The big drawback of using data has always been the difficulty of big picture perspectives when combined with a smaller focused area from the same analysis. Location analytics is the tool that lets you see the whole picture.