Method and system to detect abandonment behavior
AssigneeIntuit Inc.
InventorsIssam MIYASSI, Byungkyu KANG, Disha SINGLA, Shivakumara NARAYANASWAMY, Vitor R. CARVALHO
Life of this patent
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Abstract
Dynamic machine learning modeling within a special purpose hardware platform to determine platform abandonment risks for each user having exhibited a sequence of behaviors. The enclosed examples address a computer-centric and Internet-centric problem of a service provider system management to lower platform abandonment of users, and further increase product engagement.
Claims20
A computer implemented method for determining a probability of a user abandoning a software-based flow, said method being performed on a computing device and executed by a processor, said method comprising:
- retrieving from at least one data source, data indicating a user's sequence of behaviors;
- training at least one machine learning (ML) model based on the user's sequence of behaviors;
- and
- generating an abandonment probability score for the user based on the user's sequence of behaviors and the trained ML model, wherein the abandonment probability score includes an average abandonment probability score of generated scores from more than one of a variant abandonment model, a fear-uncertainty-death (FUD) model, and a RISK model;
- and
- sending the abandonment probability score to the at least one data source to be included in the data indicating the user's sequence of behavior.
A computing system for determining a probability of a user abandoning a software-based flow, the system comprising:
- one or more processors;
- and
- one or more non-transitory computer-readable storage devices storing computer-executable instructions, the instructions operable to cause the one or more processors to perform operations comprising:
- retrieving from at least one data source, data indicating a user's sequence of behaviors;
- training at least one machine learning (ML) model based on the user's sequence of behaviors;
- and
- generating an abandonment probability score for the user based on the user's sequence of behaviors and the trained ML model, wherein the abandonment probability score includes an average abandonment probability score of generated scores from more than one of a variant abandonment model, a fear-uncertainty-death (FUD) model, and a RISK model;
- and
- sending the abandonment probability score to the at least one data source to be included in the data indicating the user's sequence of behavior to train the at least one ML model.
A computer implemented method for determining a probability of a user abandoning a software-based flow, said method being performed on a computing device and executed by a processor, said method comprising:
- retrieving from at least one data source, data indicating a user's sequence of behaviors;
- training at least one machine learning (ML) model based on the user's sequence of behaviors;
- and
- generating an abandonment probability score for the user based on the user's sequence of behaviors and the trained ML model, wherein the abandonment probability score includes an average abandonment probability score of generated scores from more than one of a variant abandonment model, a fear-uncertainty-death (FUD) model, and a RISK model;
- and
- selectively send at least one message to the user based on the generated abandonment probability score.
Dependencies are inferred from the claim text.