How to enroll
swidg is a closed carpool platform. This means that we offer our solution to (large) companies, hospitals, schools and campuses. For each customer we create an isolated virtual group, which can be accessed only by the population of that customer (employees, students, …).
As a user you will only be matched with your “colleagues” in your closed group and it is free .
Depending on the choice of the customer, swidg offers two options to build the carpool population. The first and most effective option is by mass upload of all the employees at once (of course under clear GDPR agreements). With the second option those interested can register individually.
1. Mass upload
In case of a mass upload, the employer has a GDPR based agreement with swidg to exchange data of its employees. swidg will load all necessary data of the target population on the platform before the app is launched. swidg can handle datasets of thousands of people in one go. The swidg algorithm will calculate all potential matches for all individuals for all the days in their work schedule upfront.
When the app is opened to the employees, they need to enroll via mail and sms validation, but can then immediately find matches which are relevant for them. All personal settings like start and destination location, work schedules, email, … are uploaded upfront.
2. Pre-registration
If the mass upload is not preferred, then a gradual recruitment phase of the carpool population is supported. The flow chart below describes the different steps.
Four steps for users to access the platform:
Scan the QR code provided by your employer or institution.
This will open an e-form on which you can provide your general carpool parameters and register.
Install the free app from the app store.
The first time in the app, go via "Sign up" to finalize your account.
The carpool parameters that you have provided are instantly set in your matching profile and you can immediately check your carpool matches for a specific day.
You can see the detailed enrollment flow below.
