Well, there is another solution - the modeling approach of UDL, which predicts where they are expected to be! People move around a city in a way that is the easiest to them, which translates into the shortest routes. The simplest option is to look at street-networks and their connectivity. Centrality or betweenness is one measure of our network analysis, which in essence captures the probability that a person going from a random place A to a random place B will choose to walk a specific street.
We can look into this on a global scale of the whole city to see the main routes through - or on a district or even a local one. Each gives a bit of an information we need to understand the right place for a shop.
The processing of UDL generates these metrics, involves the creation and cleaning of networks and the definition appropriate of district levels. And the data are available directly on our platform for modeling are on demand. We have done this many times already and can do this analysis, practically anywhere in the world.
If you find it useful, let us know and we are happy to support you in your next search 😉.