Why not then ask those same question one by one every time the user returns to your network. Users give up of use your network if you are too much aggressive during the registration.
Progressively Feeding The Profileīother the user during the registration with 10 different questions is a bad idea. Where they live? How old? Man or Woman? What is the social class? for example. With just a few questions during the registration it is possible to have a lot of insights of who are these users. Also, the registration data is used to profile the users that were just anonymous data and start the data enrichment. If someone decides to conduct their drug business using the venue wifi network and the authorities required the data of users that access that network, the venue owner can provide that. This is a protection for the venue who wants to offer public wifi. Most legislation requires that for public wifi networks, the users must register with their data so that in case of misconduct the user can be identified. The reason for that is have the data of people who are using the network. In public WiFi there is a compulsory step that is the registration.
I mean, people do not connect to the SSID, type the password and done, connected. In public WiFi networks the users don't access the internet like if they were in home. To transform anonymous data in to profiled data the first tool we can use is what we call Captive Portal. But here comes the questions: Who are these people? The Captive Portal I know that returning users spend 10min more than new users in my venue and that new visitors usually goes to the food court first in opposition to return users who goes to the supermarket area first. I know that I have 3.000 visits a day, that from this 3.000 visits 2.500 are returning users and have already visited my venue and that 500 are new visitors, this is their first visit. However anonymous data do not allow me to target people individually based on their profile. Statistical data is pretty cool and we can do a lot of things with it like measure the flow of people, understand the visits and where to invest more marketing campaigns to bring more people to the venue and many other decisions.
In my last article, I wrote about how WiFi Analytics works (brief and superficial introduction for dummies) and how it is possible to get statistical data even when the users are not connected in the WiFi network.