Methods for anonymously tracking and/or analysing web and/or internet visitors

Abstract

Methods are provided for anonymously tracking and/or analyzing Web-based flow or movement of individual subjects and/or objects. In particular, there is provided a computer-implemented method for enabling anonymous estimation of the amount and/or flow of individuals, in a population moving and/or coinciding between two or more Web-based subject states. The method includes receiving identifying data from two or more individuals; generating, online and by one or more processors, an anonymized identifier for each individual; and storing: the anonymized identifier of each individual together with data representing a Web-based subject state; and/or a skew measure of such an anonymized identifier.

1 - 57 . (canceled) 
     
     
         58 . A computer-implemented method for enabling anonymous estimation of the amount and/or flow of individual subjects and/or objects, referred to as individuals, in a population of individuals, moving and/or coinciding between two or more Web-based states, said method comprising the steps:
 receiving identifying data from two or more individuals;   generating, online and by one or more processors, an anonymized identifier for each individual, wherein anonymization into an anonymous identifier takes place effectively online, that is in real-time and/or near real-time, immediately deleting the identifying information after processing; and   storing: the anonymized identifier of each individual together with data representing a Web-based state; and/or a skew measure of such an anonymized identifier.   
     
     
         59 . The method of  claim 58 , wherein the identifying data is correlated in some way with the population flow and wherein the skew measure is decorrelating and/or the anonymized identifier is generated with a decorrelation module and/or a decorrelating hashing module 
     
     
         60 . The method of  claim 58 , wherein the anonymized identifier is an anonymous skew measure and the anonymized skew measure is generated based on a stored anonymous identifier skew measure to which noise has been added at one or more moments, or the anonymized identifier is generated by adding noise to the identifying data. 
     
     
         61 . The method of  claim 58 , wherein any two stored anonymized identifiers or identifier skew measures are not linkable to each other with a high probability, i.e. there is no pseudonymous identifier linking the Web-based states in the stored data, and/or a single individual present in one Web-based state cannot be reidentified in another Web-based state with high, i.e. non-anonymous, probability using the anonymous identifier skew measures. 
     
     
         62 . The method of  claim 58 , wherein the anonymized identifier is a group identity, and the group identity of each individual is stored together with data representing Web-based state; and/or a counter per Web-based state and group identity, or the group identity of each individual is stored together with data describing online activity; and/or a counter per online activity and group identity. 
     
     
         63 . The method of  claim 58 , wherein the Web-based states are Web-based tempo-spatial locations or localities, and/or the Web-based states are based on domain, URL, URI, state of a Web service, API request, viewed impressions, time spent, clicks, scrolls, categories of mouse movements and/or data sent to a Web server. 
     
     
         64 . The method of  claim 62 , wherein activity data representative of one or more actions or activities of each individual is also stored together with the corresponding group identity and data describing Web-based state. 
     
     
         65 . The method of  claim 58 , further comprising the step of generating a population flow measure between two Web-based states. 
     
     
         66 . A computer-implemented method for generating a measure of flow or movement of individual subjects and/or objects, referred to as individuals, between Web-based states, said method comprising the steps:
 configuring one or more processors to receive anonymous identifier skew measures generated based on identifiers from visits and/or occurrences of individuals to and/or in each of two Web-based states;   generating, using said one or more processors, a population flow measure between two Web-based states by comparing the anonymous identifier skew measures between the Web-based states; and   storing said population flow measure to a memory.   
     
     
         67 . The method of  claim 66 , wherein the Web-based states are based on domain, URL, URI, state of a Web service, API request, viewed impressions, time spent, clicks, scrolls, categories of mouse movements and/or data sent to a Web server. 
     
     
         68 . The method of  claim 66 , wherein the anonymous identifier skew measures are counters of group identities. 
     
     
         69 . The method of  claim 66 , wherein a single visitor present in one Web-based state cannot be reidentified in another Web-based state with high, i.e. non-anonymous, probability using the anonymous identifier skew measures, and/or any two stored anonymized identifier skew measures are not linkable to each other, i.e. there is no pseudonymous identifier linking the Web-based states in the stored data. 
     
     
         70 . The method of  claim 66 , wherein the population flow measure is also generated based on information about noise samples used to anonymize the data. 
     
     
         71 . The method of  claim 66 , wherein the configuring step includes configuring one or more processors to receive counters of anonymous and approximately independently distributed group identities originating from visits of individuals to each of two Web-based states; and the generating step includes generating a population flow measure between two Web-based states using a linear correlation between counters of group identities for each of the two Web-based states. 
     
     
         72 . The method of  claim 58 , wherein the individuals are Web and/or Internet visitors visiting a number of Web sites/pages, and/or the identifying information representative of an individual includes identifying information of an Internet connected device and/or user. 
     
     
         73 . The method of  claim 66 , wherein the individuals are Web and/or Internet visitors visiting a number of Web sites/pages, and/or the identifying information representative of an individual includes identifying information of an Internet connected device and/or user. 
     
     
         74 . The method of  claim 58 , wherein the identifying information includes a unique identifier assigned to an Internet connected device and/or user such as an Internet Protocol (IP) address and/or cookie-based identifying information and/or a browser fingerprint, and/or identifying information from one or more online user accounts. 
     
     
         75 . The method of  claim 66 , wherein the identifying information includes a unique identifier assigned to an Internet connected device and/or user such as an Internet Protocol (IP) address and/or cookie-based identifying information and/or a browser fingerprint, and/or identifying information from one or more online user accounts. 
     
     
         76 . The method of  claim 58 , wherein the amount and/or flow of individuals moving and/or coinciding between two or more Web-based states includes the flow of visitors from one web site or domain to another, or from one online Web activity to another. 
     
     
         77 . The method of  claim 66 , wherein the amount and/or flow of individuals moving and/or coinciding between two or more Web-based states includes the flow of visitors from one web site or domain to another, or from one online Web activity to another. 
     
     
         78 . A computer-program product comprising a non-transitory computer-readable medium having stored thereon a computer program, wherein the computer program comprises instructions, which when executed by at least one processor, cause the at least one processor to perform the computer-implemented method of  claim 58 .