| CPC G06F 16/951 (2019.01) [G06F 16/9535 (2019.01); G06F 16/9537 (2019.01); G06F 16/9538 (2019.01); G06N 20/00 (2019.01)] | 18 Claims |
|
1. A user experience (UX) assessment system, the system comprising:
one or more processors and one or more storage devices storing instructions thereon that, when executed by the one or more processors, cause the one or more processors to form one or more functional modules comprising:
a first engine configured to collect UX related data from real people represented by customer and employee personas participating in one or more processes;
a second engine configured to identify UX gaps as perceived by the customer and employee personas, the second engine comprising:
a first module communicatively coupled to the database and equipped with a natural language process (NLP) model, a machine learning (ML) model, a neural network (NN) model, or any combinations thereof to analyze and classify the UX related data by sentiment, topic, and intent, wherein the first module is further operable to:
classify with the NLP model, the ML model, and/or the NN model the collected UX related data to a positive, a negative, and a neutral sentiment;
aggregate each sentiment to a respective total ingestion;
assign a principal component factor to each sentiment;
multiply each total ingestion by a respective principal component factor to arrive to an ingestion quotient for each sentiment and to a total ingestion quotient for all sentiments; and
from the total ingestion quotient, derive an ingestion score for the one or more processes;
a second module communicatively coupled to the first module, the second module configured to receive output from the first module based at least in part on the classified UX related data and ingestion score and to assign scores to the classified UX related data based on four dimensions comprising credibility, responsiveness, seamlessness, and engagement, wherein the scores are aggregated by the one or more processes across all or a selected number of the customer and employee personas, by a customer or employee persona across all or selected number of the one or more processes, by a customer or employee persona across all or some participants for the one or more processes, by customer experience (CX) and employee experience (EX) across the one or more processes, by CX and EX across all the customer and employee personas, or any combinations of the foregoing; and
a third module communicatively coupled to the second module, the third module configured to identify UX gaps as perceived by the customer and employee personas based on the scores aggregated in the second module at least by CX and EX across the one or more processes, by CX and EX across all the customer and employee personas, or any combinations of the foregoing, wherein the UX gaps correspond to UX differences as perceived by the customer and employee personas who perform different roles in the one or more processes; and
a third engine configured to receive the identified UX gaps from the second engine and to:
report the identified UX gaps;
auto-generate recommendations to mitigate the identified UX gaps;
monitor and track a progress of executed recommendations;
detect whether corrective actions are required; and
provide status updates about the progress of the executed recommendations and the corrective actions.
|