US 12,147,924 B2
Method and system for dynamic adaptive routing of deferrable work in a contact center
Bayu Wicaksono, Laurel, MD (US); Travis Humphreys, Crownsville, MD (US); William D'Attilio, Brownsburg, IN (US); Johnson Tse, Markham (CA); and Abel Chen, Markham (CA)
Assigned to Genesys Cloud Services, Inc., Menlo Park, CA (US)
Filed by Genesys Cloud Services, Inc., Menlo Park, CA (US)
Filed on Sep. 30, 2021, as Appl. No. 17/491,398.
Claims priority of provisional application 63/085,373, filed on Sep. 30, 2020.
Prior Publication US 2022/0101220 A1, Mar. 31, 2022
Int. Cl. G06Q 10/00 (2023.01); G06F 40/40 (2020.01); G06Q 10/0631 (2023.01); G06Q 10/0633 (2023.01); H04M 3/51 (2006.01); H04M 3/523 (2006.01)
CPC G06Q 10/0633 (2013.01) [G06F 40/40 (2020.01); G06Q 10/063112 (2013.01); H04M 3/5175 (2013.01); H04M 3/5233 (2013.01); H04M 2203/402 (2013.01)] 20 Claims
OG exemplary drawing
 
15. A system related to optimizing a workflow in a contact center in which deferrable work interactions are prioritized and assigned to agents for handling, the system comprising:
a processor; and
a memory, wherein the memory stores instructions that, when executed by the processor, cause the processor to perform the steps of:
providing:
a plurality of natural language processing (NLP) models, each NLP model being configured to accept text from a given deferrable work interaction as an input and generate NLP scores indicating how the given deferrable work interaction rates in accordance with a characteristic, wherein to generate the NLP scores of the given deferrable work interaction, each NLP model generates a sparse vector representation of the given deferrable work interaction;
a priority model configured to accept as inputs the scores generated from the plurality of NLP models and generate a priority score related to a priority characteristic indicating how the given deferrable work interaction should be prioritized for handling relative to other ones of the deferrable work interactions;
receiving the deferrable work interactions;
using text derived from the deferrable working interactions as inputs to the plurality of NLP models to generate the NLP scores for each of the deferrable work interactions;
using the generated NLP scores as inputs to the priority model to generate the priority score for each of the deferrable work interactions;
using the generated NLP scores to identify one or more candidate agents of the agents for handling each of the deferrable work interactions;
receiving an inbound work forecast for the contact center that predicts inbound work levels expected over one or more future work periods;
receiving, in relation to the one or more future work periods, agent work schedule data describing anticipated work schedules for the agents;
using an optimization process to generate an optimized workflow for the deferrable work interactions, wherein, for each of the deferrable work interactions, the optimized workflow comprises an assignment in which a selected agent is selected from the candidate agents for handling the deferrable work interaction and a target timeframe is scheduled for handling of the deferrable work interaction; and
routing each of the deferrable work interactions in accordance with the assignments of the optimized workflow;
wherein the optimization process is configured to optimize according to the following factors:
the priority score generated for each of the deferrable work interactions;
an expected availability over the one or more future work periods of the one or more candidate agents identified for each of the deferrable work interactions as determined from:
the agent work schedule data over the one or more future work periods; and
the predicted inbound work levels over the one or more future work periods given the inbound work forecast.