Patent ID: 11966934
Assignee: WESCO DISTRIBUTION, INC.
Field: IT methods for management (Electrical engineering)
Classification: CPC G | IPC G

Claim 14:
15. A non-transitory computer readable medium containing program instructions for predicting opportunities for special pricing agreements (SPA) that when executed, cause a computer to:
receive a user input indicating a stock keeping unit (SKU), a customer name representative of a customer, and one or more filters corresponding to the SKU or the customer name;
search an SPA database to retrieve a set of SPA data associated with the SKU and the customer name, the set of SPA data including: (i) a customer type associated with the customer, (ii) a customer address associated with the customer, and (iii) any historical SPAs corresponding to the customer;
filter, by executing a machine learning (ML) model configured to prioritize SPA data within the set of SPA data based on the one or more filters by applying a decision tree, the set of SPA data to generate a filtered set of SPA data, wherein the decision tree is trained to output the filtered set of SPA data by:
inputting, into the decision tree, feature vectors representing training SPA data and labels classifying the training SPA data,
determining, by the decision tree, classifications corresponding to the training SPA data, and
adjusting weights or parameters of the decision tree based on the classifications and the labels;

predict, by applying the ML model to the filtered set of SPA data, a set of SPA opportunities that each have a respective cost and a respective confidence interval and that satisfy a confidence interval threshold by inputting the filtered set of SPA data into the ML model;
determine a first SPA opportunity that corresponds to a highest respective confidence interval relative to the respective confidence interval of each SPA opportunity in the set of SPA opportunities, and a second SPA opportunity that corresponds to a lowest cost of the respective cost of each SPA opportunity in the set of SPA opportunities;
transmit a notification of the first SPA opportunity and the second SPA opportunity for display to the customer;
track an outcome of a transmission of the first SPA opportunity or the second SPA opportunity to the customer; and
retrain the ML model based on the outcome indicating an acceptance or a rejection of the first SPA opportunity or the second SPA opportunity by the customer.