Mobext ran a study late last year in partnership with mobile consumer analytics firm Cadio which involved a small number of Sprint Wireless subscribers. These opted-in participants agreed to share semi-continuous GPS data with Cadio, meaning their location was logged every 10 minutes.

The 25-54 year-olds who took part were tracked visiting more than 200 places, including shops, airports, hotels, train stations and supermarkets.

Data was analysed and generated findings as follows: panellists who went to Wal-Mart were 60% more likely to dine out than Target customers, but of those Target customers who did dine out, 25% went to a restaurant prior to going to Target while 25% went after.

Mobext sees potential here for using this data to influence retailers to expand their snack food range, say, or to form partnerships with nearby restaurants to drive complementary traffic between stores.

Knowing how often and at what time certain customers like to shop can also help retailers in tailoring their messaging, said Mobext, while analysing travel patterns – the daily commute, for instance – also has benefits for media planning.

Mobext said: “Armed with work and travel data, advertisers can implement creative integrated media executions that begin with traditional and mobile media (during commuting times in the morning); on the PC-based web (during office hours), and back to mobile media (when travelling).”

Another potential boon, according to Mobext: using GPS data makes it possible “to build a bridge between digital ad exposure and real-world offline consumer behaviour”. For example, it should be possible to see whether a person visits a new retail outlet after being served a mobile ad announcing the store opening.

But, the company warns, there are issues to be aware of in getting people to agree to share GPS data. Mobext posits that younger, tech-savvy consumers – particularly those already using location-sharing networks like Foursquare – will be more inclined to share GPS data with brands “in return for appropriate incentives”.

“Other demographics may be more sensitive,” said Mobext. “Some experimentation with incentive structures may be necessary to define an optimal approach that will adequately secure the participation of all required demographic segments.”

The mass of data produced can also be a challenge in itself, particularly when it comes to identifying those data points relevant to marketing efforts. “Stringing together the GPS paths of thousands of participants, overlaying time of day, day of week, as well as targeting advertising by content, quickly becomes a large task,” said Mobext.