System and method for identifying similar queries by a customer on different digital channels in a multichannel contact center

1 . A computerized-method for improving queries operation in a multichannel contact center, said computerized-method comprising:

operating a stream processing application for each new query of a customer to store query-related data and to identify one or more queries of the customer in a cloud-contact data store,

wherein the cloud-contact data store is having one or more interactions-queue types; when the one or more queries of the customer have been identified:

(i) operating a repetition module on the identified one or more queries of the customer to filter out two or more queries having a common query-topic;

(ii) operating a Natural Language Understanding (NLU) module on the filtered two or more queries having a common topic to identify two or more identical queries,

wherein each query of the identified two or more identical queries have a unique query identification number; and

(iii) handling the two or more identical.

2 . The computerized-method of claim 1 , wherein the handling of the two or more identical queries is operated by:

(i) operating a primary channel identification module to determine a primary channel-type for a query to be resolved, from the identified two or more identical queries,

wherein the query has a query identification number;

(ii) reducing a priority of all queries having a different query identification number than the query to be resolved, in each related interactions-queue type;

(iii) having an agent interacting with the customer regarding the query to be resolved, via the primary channel-type; and

(iv) removing all queries having a different query identification number than the query to be resolved from each related interactions-queue type, after the query to be resolved has been marked as resolved.

3 . The computerized-method of claim 1 , wherein the query-related data comprising: a customer identification-number; a query identification-number; a channel-type; a query initiation-time; an estimated wait-time; and a query-topic.

4 . The computerized-method of claim 3 , wherein the stream processing application is identifying one or more queries of the customer based on the customer identification-number.

5 . The computerized-method of claim 1 , wherein after the determining of the primary channel-type for the query to be resolved, the computerized-method is further comprising sending a notification to the customer as to the customer preferred primary channel-type and wherein upon customer updating the determined primary channel-type when the primary channel-type is different than the customer preferred primary channel-type.

6 . The computerized-method of claim 1 , wherein the primary channel identification module to determine the primary channel-type is operating by checking a wait-time of each interactions-queue type and selecting the primary channel-type according to related channel-type of an interactions-queue having a lowest wait-time.

7 . The computerized-method of claim 1 , wherein when the computerized-method is operating in a cloud computing environment, before operating the stream processing application, the computerized-method is further comprising, selecting a tenant from a data store of tenants, every duty cycle period, to operate the stream processing application for each new query of a customer in the cloud-contact data store of the selected tenant.

8 . A computerized-system for improving queries operation in a multichannel contact center, said computerized-system comprising:

one or more processors;

a cloud-contact data store; and

a memory to store the cloud contact data store,

said one or more processors are configured to operate a stream processing application for each new query of a customer, said stream processing application is operated to store query-related data and to identify one or more queries of the customer in the cloud-contact data store,

wherein the cloud-contact data store is having one or more interactions-queue types;

when the one or more queries of the customer have been identified, said one or more processors are further configured to:

(i) operate a repetition module on the identified one or more queries of the customer to filter out two or more queries having a common query-topic;

(ii) operate a Natural Language Understanding (NLU) module on the filtered two or more queries having a common topic to identify two or more identical queries,

wherein each query of the identified two or more identical queries have a unique query identification number; and

(iii) handle the two or more identical queries.