Patent ID: 11972454
Assignee: POSHMARK, INC.
Field: IT methods for management (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method comprising:
receiving first channel data associated with a first channel, the first channel data comprising a historical probability of conversion for the first channel;
receiving second channel data associated with a second channel, the second channel data comprising a historical probability of conversion for the second channel;
receiving a plurality of first channel events associated with a specific user and related to the first channel, each of the plurality of first channel events having a time of occurrence and a sub-type;
receiving a plurality of second channel events associated with the specific user and related to the second channel, each of the plurality of second channel events having a time of occurrence and a sub-type;
determining that a conversion event occurred associated with the specific user;
responsive to determining that the conversion event occurred, determining a first attribution value for the first channel by:
filtering out any of the plurality of first channel events that have a time of occurrence that exceeds a specific threshold of time;
calculating a probability of conversion for each of the remaining plurality of first channel events using the first channel data, the sub-type of each of the remaining plurality of first channel events, and the time of occurrence of each of the remaining plurality of first channel events; and
summing the calculated probabilities of conversion for each of the remaining plurality of first channel events;

determining a second attribution value for the second channel by:
filtering out any of the plurality of second channel events that have a time of occurrence that exceeds the specific threshold of time;
calculating a probability of conversion for each of the remaining plurality of second channel events using the second channel data, the sub-type of each of the remaining plurality of second channel events, and the time of occurrence of each of the remaining plurality of second channel events; and
summing the calculated probabilities of conversion for each of the remaining plurality of second channel events;

sending the first attribution value and the second attribution value to a computing device for display;
feeding data sets from different channels including probability curves and channel events into a machine learning model; and
using the machine learning model to identify at least one attribution trigger point or response as new channel data is provided.