Lift reporting system
AssigneeSnap Inc.
InventorsSimon Hollands, Li Shi, Amit Adur, Mattia Fumagalli, Crystal Pan
Life of this patent
Estimating the term…
Abstract
A lift reporting system to perform operations that include: accessing user behavior data associated with one or more machine-learned (ML) models, the ML models associated with identifiers; determining causal conversions associated with the ML models based on the user behavior data, the causal conversions comprising values; performing a comparison between the values that represents the causal conversions; determining a ranking of the ML models based on the comparison; and causing display of a graphical user interface (GUI) that includes a display of identifiers associated with ML models.
Claims20
A system comprising:
- at least one processor;
- at least one memory component storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising:
- accessing first user behavior data associated with a first machine-learned (ML) model and second user behavior data associated with a second ML model, the first ML model associated with a first identifier and the second ML model associated with a second identifier;
- determining a first set of causal conversions associated with the first ML model based on the first user behavior data, the first set of causal conversions comprising a first value:
- determining a second set of causal conversions associated with the second ML model based on the second user behavior data, the second set of causal conversions comprising a second value;
- performing a comparison between the first value that represents the first set of causal conversions and the second value that represents the second set of causal conversions;
- determining a ranking of the first ML model and the second ML model based on the comparison;
- and
- causing display of a graphical user interface (GUI) that includes a display of the first identifier associated with the first ML model and the second identifier associated with the second ML model based on the ranking.
A method comprising:
- accessing first user behavior data associated with a first machine-learned (ML) model and second user behavior data associated with a second ML model, the first ML model associated with a first identifier and the second ML model associated with a second identifier;
- determining a first set of causal conversions associated with the first ML model based on the first user behavior data, the first set of causal conversions comprising a first value;
- determining a second set of causal conversions associated with the second ML model based on the second user behavior data, the second set of causal conversions comprising a second value;
- performing a comparison between the first value that represents the first set of causal conversions and the second value that represents the second set of causal conversions;
- determining a ranking of the first ML model and the second ML model based on the comparison;
- and
- causing display of a graphical user interface (GUI) that includes a display of the first identifier associated with the first ML model and the second identifier associated with the second ML model based on the ranking.
A non-transitory computer-readable storage medium storing instructions that, when executed by at least one processor, cause the at least one processor to perform operations comprising:
- accessing first user behavior data associated with a first machine-learned (ML) model and second user behavior data associated with a second ML model, the first ML model associated with a first identifier and the second ML model associated with a second identifier;
- determining a first set of causal conversions associated with the first ML model based on the first user behavior data, the first set of causal conversions comprising a first value;
- determining a second set of causal conversions associated with the second ML model based on the second user behavior data, the second set of causal conversions comprising a second value;
- performing a comparison between the first value that represents the first set of causal conversions and the second value that represents the second set of causal conversions;
- determining a ranking of the first ML model and the second ML model based on the comparison;
- and
- causing display of a graphical user interface (GUI) that includes a display of the first identifier associated with the first ML model and the second identifier associated with the second ML model based on the ranking.
Dependencies are inferred from the claim text.