Patent ID: 11966953
Assignee: INTUIT INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 8:
9. A system for evaluating usage of a product, said system comprising:
a non-volatile memory; and
a processor coupled to the memory, the processor configured to:
receive a list of customers using a first version of the product;
receive customer usage and interaction data associated with the product for each customer identified on the input list of customers;
obtain initial training data for training a machine learning evaluation model;
filter outliers that skew data distribution from the initial training data to obtain filtered training data;
train the model with the filtered training data, wherein the model is based on a multilayer perceptron neural network and includes multiple hidden layers; and
for each customer identified on the input list of customers:
extracting evaluation features from the input customer usage and interaction data, wherein the evaluation features include at least a marketing channel used by the customer to obtain the first version of the product and data associated with user interactions with the product indicating transactions of at least the following types: linking bank accounts, adding service items, and inviting users to use the product,
processing the evaluation features by at least compensating for class imbalance and skewness,
applying the processed customer usage and interaction data evaluation features to a trained machine learning evaluation model, and
performing, by the trained machine learning evaluation model, a classification process to predict a likelihood that the customer will obtain a second version of the product, wherein the likelihood is determined according to the types of the transactions such that a degree of likelihood is increased for the customer performing transactions of each of the types relative to other customers performing transactions of fewer than all of the types.