We measure street traffic, store visits, and people behavior around the city, parks, inside specifics spaces as museums, parks and festivals, stores, restaurants or public transport.
Our plug & play footscan sensors analyzes large volumes of data in real time, in a non-intrusive way and always guaranteeing customer privacy.
We provide a very easy to deploy and cost efficient solution.
A “plug&play” solution, very easy installation that offers a reliable and continuous behaviour analysis on bus lines passengers.
Forget one-time surveys and take decisions on real time data. You’ll be able to analyze what’s going on right now, how passengers use bus lines along different seasons and which connections they use the most.
You’ll be also able to offer wifi service in the bus, both as a communication channel to your customers and to offer the passenger free or paid internet.
An easy to deploy solution, totally invisible to the visitor, that empowers the park manager with a continuous and reliable vision of visitor flow and behaviours on public spaces.
Foot Analytics measures the use of the space, both by local citizens, tourists and occasional visitors, helping to adapt the services according the visitor flow in each specific area.
You’ll have a continuous control on the use of the different zones of the park, an analysis of its points of interest, access routes and paths, and a powerful tool to measure the impact and events in the park (time spent in each interest point or zone of the park).
Our solution Connected Market by Foot Analytics offers an essential tool to measure and understand how the food market relation evolves with its environment.
You will be able to measure number of visits, unique number of customers, loyalty indicators, new customers or repeat visitors, …
We will provide a communication channel between the food market and the visitor to enhance customer loyalty in a simple and very effective way.
The data is shown in very intuitive and easy to understand widgets in our powerful web dashboard on which data can be aggregated by time tables, specific dates or weekday averages.
