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Customer identification on the website and mobile application

The algorithm of obtaining information about the customer is based on cookies. During the first visit user will  get individual UUID (universally unique identifier). From this time user’s activity is linked with the identifier and stored in databases.

Each request which is sent to the server contains information about the current address, browser, operating system of the user. Thanks to that we are able to assign every event to the customer.

Until user will fill out a form with personal data; email address and / or phone number and  agree to the processing of personal data,  the user is anonymous. At the moment of giving us an email address or a phone, each time user visit our site – will be recognized and identified.

If users agree to the processing of personal data – Crowler – using their e-mail address start searching through a social network to complete their profiles with public data.

Thanks to tracking codes we can monitor users activities on the website and mobile application. By installing additional plug-ins to the platform we can monitor transactions.

Mobile App:

In the case of mobile applications we used UUID which is equivalent of cookies. UUID code is generated based on the device type etc. – because of that we can generate the same UUID for one customer even if the user uninstall our application and install it another time.

 

Related topics

  • Customer unique ID
  • Customer identification in the local stores (POS)
  • Customer identification in the local stores (Bluetooth)
  • Customer identification in the local stores (WiFi)
  • Tracking customer’s behavior on www
  • Tracking customer’s behavior on mobile app
  • Tracking customer’s behavior in local stores (POS)
  • Tracking customer’s behavior in local stores (Bluetooth)
  • Tracking customer’s behavior in local stores (WiFi)
  • Trackingc ustomer’s behavior in social media
  • Real time data
  • Overwriting the data acquired for anonymous after their registration
  • Construction of customer profile – the types of data collected (demographic and behavioral data)

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