Predictive geomarketing for retail locations optimization
Angel Gomez - Founder & CEO @ Roofstreet
Angel Gomez
Founder & CEO

"A few years ago, geolocation data was collected though put aside for later. Only Waze did a little prediction, but in reality there was no service that could make the user's life easier.", says Angel Gomez who decided to create Roofstreet in 2015. He wanted to optimize these trips.

After two years of research, the company has developed an artificial intelligence capable of analysing the geolocation data of millions of people, studying their past journeys, their points of interest and estimating their future journeys.

The first is predictive: Roofstreet provides mobility applications with users' travel expectations. This makes it possible to proactively provide them with information on their next trips. This technology could also enable public mobility players, such as Transdev and Keolis, already customers, to optimise their transport lines.
The second part is statistical and aimed at another market, that of retail: travel data (the number of pedestrians passing in front of a window or their profile for example) are used to optimise location and advice. Date is anonymized and valued on the retail and marketing markets. Roofstreet customers have access to an analysis platform to study the behaviour of our fellow citizens in compliance with the DGMP.

Studies show that when we travel, we often have a preferred itinerary. By analysing our journeys, Roofstreet is right 7 times out of 10, ten to twelve hours early, in other words from morning to evening! This is highly useful in the retail market, and could also be of interest for other players such as taxis, car rental companies, or relay point delivery services.

Roofstreet is based in Paris.