Method and system for identifying users across mobile and desktop devices

A non-transitory computer readable medium comprising instructions for performing a method, the method comprising:

• obtaining a collection of mappings between pairs of identifiers using deterministic ID bridging, wherein the mapping between a pair of identifiers indicates that the identifiers are associated with a common user;
• training a probabilistic classifier using the collection of mappings between pairs of identifiers, wherein the probabilistic classifier is trained to generate a probability that two input identifiers are associated with a particular common user;
• obtaining a first identifier associated with a first device and a second identifier associated with a second device;
• using the probabilistic classifier to determine a probability that the first identifier and the second identifier are associated with a first user:
• bridging the first identifier and the second identifier based on a determination, made by the probabilistic classifier, that the probability that first identifier and the second identifier are associated with the first user satisfies a specified level of confidence;
• and
• attributing, using the bridge, a conversion on a website accessed using the second device, wherein the conversion is attributed when the user accesses the webpage within a predetermined period of time after viewing an advertisement on the first device.

A system comprising:

• one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising:
• obtaining a collection of mappings between pairs of identifiers using deterministic ID bridging, wherein the mapping between a pair of identifiers indicates that the identifiers are associated with a common user;
• training a probabilistic classifier using the collection of mappings between pairs of identifiers, wherein the probabilistic classifier is trained to generate a probability that two input identifiers are associated with a particular common user;
• obtaining a first identifier associated with a first device;
• obtaining a second identifier associated with a second device;
• using the probabilistic classifier to determine a probability that the first identifier and the second identifier are associated with a first user:
• bridging the first identifier and the second identifier based on a determination, made by the probabilistic classifier, that the probability that first identifier and the second identifier are associated with the first user satisfies a specified level of confidence;
• and
• attributing, using the bridge, a conversion on a website accessed using the second device following presentation of content on the first device.