Software product optimization identification through natural language processing
Software product optimization is provided. Expressed sentiment in a set of opted in user-to-user business-related conversations among a group of users corresponding to an entity is associated with a software product in response to determining that the software product is identified by mentioned keywords in the set of opted in user-to-user business-related conversations based on a keyword corpus. It is determined whether the expressed sentiment associated with the software product is negative sentiment. A related software product listed in a software product catalog of the entity is identified as an optimization to the software product in response to determining that the expressed sentiment associated with the software product is negative sentiment. A recommendation to implement the related software product as the optimization to the software product is generated. The recommendation to implement the related software product as the optimization to the software product is sent to the group of users.
1 . A computer-implemented method for software product optimization, the computer-implemented method comprising:
associating, by a computer, expressed sentiment in a set of opted in user-to-user business-related conversations among a group of users corresponding to an entity with a software product in response to the computer, using a natural language processing and understanding model, determining that the software product is identified by mentioned keywords in the set of opted in user-to-user business-related conversations among the group of users corresponding to the entity based on a keyword corpus during execution of the software product;
determining, by the computer, using the natural language processing and understanding model, whether the expressed sentiment associated with the software product is negative sentiment;
identifying, by the computer, a related software product listed in a software product catalog of the entity as an optimization to the software product in response to the computer, using the natural language processing and understanding model, determining that the expressed sentiment associated with the software product is negative sentiment;
generating, by the computer, a recommendation to implement the related software product as the optimization to the software product;
sending, by the computer, the recommendation to implement the related software product as the optimization to the software product to the group of users corresponding to the entity using an optimal notification application;
receiving, by the computer, an input to implement the related software product as the optimization to the software product; and
automatically implementing, by the computer, the related software product as the optimization to the software product in response to receiving the input to increase at least one of usage, performance, functionality, capability of the software product.
2 . The computer-implemented method of claim 1 , wherein the set of opted in user-to-user business-related conversations comprise both verbal and textual conversations.
3 . The computer-implemented method of claim 1 , further comprising:
receiving, by the computer, feedback from the group of users corresponding to the entity regarding implementation of the related software product as the optimization to the software product; and
utilizing, by the computer, the feedback from the group of users corresponding to the entity regarding the implementation of the related software product as the optimization to the software product to retrain the natural language processing and understanding model to increase accuracy of software product optimization recommendations.
4 . The computer-implemented method of claim 1 , further comprising:
performing, by the computer, an analysis of a current inventory of the entity;
determining, by the computer, whether a current inventory level of the related software product is greater than a defined minimum inventory threshold level for the related software product based on the analysis of the current inventory of the entity; and
determining, by the computer, that the related software product is available for the optimization of the software product in response to the computer determining that the current inventory level of the related software product is greater than the defined minimum inventory threshold level for the related software product based on the analysis of the current inventory of the entity.
5 . The computer-implemented method of claim 1 , further comprising:
determining, by the computer, the optimal notification application corresponding to the group of users based on at least one of type of content to be included in the recommendation, context of the set of opted in user-to-user business-related conversations among the group of users corresponding to the entity, user preferences, and location of the related software product in the software product catalog of the entity.
6 . The computer-implemented method of claim 1 , further comprising:
receiving, by the computer, consent from the group of users corresponding to the entity to access and process the set of opted in user-to-user business-related conversations among the group of users occurring via the set of opted in user-to-user communication applications that includes at least one of verbal communications and textual communications among the group of users;
accessing, by the computer, the software product catalog corresponding to the entity that includes a plurality of software products corresponding to the entity; and
accessing, by the computer, the set of opted in user-to-user communication applications to process the set of opted in user-to-user business-related conversations among the group of users.
7 . The computer-implemented method of claim 1 , further comprising:
performing, by the computer, using the natural language processing and understanding model, an analysis of the set of opted in user-to-user business-related conversations among the group of users corresponding to the entity occurring via the set of opted in user-to-user communication applications;
determining, by the computer, using the natural language processing and understanding model, a context of the set of opted in user-to-user business-related conversations among the group of users corresponding to the entity based on the analysis of the set of opted in user-to-user business-related conversations; and
identifying, by the computer, using the natural language processing and understanding model, the expressed sentiment and the mentioned keywords in the set of opted in user-to-user business-related conversations among the group of users corresponding to the entity based on the context of the set of opted in user-to-user business-related conversations.
8 . The computer-implemented method of claim 1 , wherein the optimization of the software product using the related software product expands at least one of usage, performance, functionality, and capability of the software product.
9 . A computer system for software product optimization, the computer system comprising:
a communication fabric;
a set of computer-readable storage media connected to the communication fabric, wherein the set of computer-readable storage media collectively stores program instructions; and
a set of processors connected to the communication fabric, wherein the set of processors executes the program instructions to:
associate expressed sentiment in a set of opted in user-to-user business-related conversations among a group of users corresponding to an entity with a software product in response to determining, using a natural language processing and understanding model, that the software product is identified by mentioned keywords in the set of opted in user-to-user business-related conversations among the group of users corresponding to the entity based on a keyword corpus during execution of the software product;
determining, using the natural language processing and understanding model, whether the expressed sentiment associated with the software product is negative sentiment;
identifying a related software product listed in a software product catalog of the entity as an optimization to the software product in response to determining, using the natural language processing and understanding model, that the expressed sentiment associated with the software product is negative sentiment;
generate a recommendation to implement the related software product as the optimization to the software product;
send the recommendation to implement the related software product as the optimization to the software product to the group of users corresponding to the entity using an optimal notification application;
receiving, by the computer, an input to implement the related software product as the optimization to the software product; and
automatically implementing, by the computer, the related software product as the optimization to the software product in response to receiving the input to increase at least one of usage, performance, functionality, capability of the software product.
10 . The computer system of claim 9 , wherein the set of opted in user-to-user business-related conversations comprise both verbal and textual.
11 . The computer system of claim 9 , wherein the set of processors further executes the program instructions to:
receive feedback from the group of users corresponding to the entity regarding implementation of the related software product as the optimization to the software product; and
utilize the feedback from the group of users corresponding to the entity regarding the implementation of the related software product as the optimization to the software product to retrain the natural language processing and understanding model to increase accuracy of software product optimization recommendations.
12 . The computer system of claim 9 , wherein the set of processors further executes the program instructions to:
perform an analysis of a current inventory of the entity;
determine whether a current inventory level of the related software product is greater than a defined minimum inventory threshold level for the related software product based on the analysis of the current inventory of the entity; and
determine that the related software product is available for the optimization of the software product in response to determining that the current inventory level of the related software product is greater than the defined minimum inventory threshold level for the related software product based on the analysis of the current inventory of the entity.
13 . The computer system of claim 9 , wherein the set of processors further executes the program instructions to:
determine the optimal notification application corresponding to the group of users based on at least one of type of content to be included in the recommendation, context of the set of opted in user-to-user business-related conversations among the group of users corresponding to the entity, user preferences, and location of the related software product in the software product catalog of the entity.
14 . A computer program product for software product optimization, the computer program product comprising a set of computer-readable storage media having program instructions collectively stored therein, the program instructions executable by a computer to cause the computer to:
associate expressed sentiment in a set of opted in user-to-user business-related conversations among a group of users corresponding to an entity with a software product in response to determining, using a natural language processing and understanding model, that the software product is identified by mentioned keywords in the set of opted in user-to-user business-related conversations among the group of users corresponding to the entity based on a keyword corpus during execution of the software product;
determining, using the natural language processing and understanding model, whether the expressed sentiment associated with the software product is negative sentiment;
identifying a related software product listed in a software product catalog of the entity as an optimization to the software product in response to determining, using the natural language processing and understanding model, that the expressed sentiment associated with the software product is negative sentiment;
generate a recommendation to implement the related software product as the optimization to the software product;
send the recommendation to implement the related software product as the optimization to the software product to the group of users corresponding to the entity using an optimal notification application;
receiving, by the computer, an input to implement the related software product as the optimization to the software product; and
automatically implementing, by the computer, the related software product as the optimization to the software product in response to receiving the input to increase at least one of usage, performance, functionality, capability of the software product.
15 . The computer program product of claim 14 , wherein the set of opted in user-to-user business-related conversations comprise both verbal and textual conversations.
16 . The computer program product of claim 14 , wherein the program instructions further cause the computer to:
receive feedback from the group of users corresponding to the entity regarding implementation of the related software product as the optimization to the software product; and
utilize the feedback from the group of users corresponding to the entity regarding the implementation of the related software product as the optimization to the software product to retrain the natural language processing and understanding model to increase accuracy of software product optimization recommendations.
17 . The computer program product of claim 14 , wherein the program instructions further cause the computer to:
perform an analysis of a current inventory of the entity;
determine whether a current inventory level of the related software product is greater than a defined minimum inventory threshold level for the related software product based on the analysis of the current inventory of the entity; and
determine that the related software product is available for the optimization of the software product in response to determining that the current inventory level of the related software product is greater than the defined minimum inventory threshold level for the related software product based on the analysis of the current inventory of the entity.
18 . The computer program product of claim 14 , wherein the program instructions further cause the computer to:
determine the optimal notification application corresponding to the group of users based on at least one of type of content to be included in the recommendation, context of the set of opted in user-to-user business-related conversations among the group of users corresponding to the entity, user preferences, and location of the related software product in the software product catalog of the entity.
19 . The computer program product of claim 14 , wherein the program instructions further cause the computer to:
receive consent from the group of users corresponding to the entity to access and process the set of opted in user-to-user business-related conversations among the group of users occurring via the set of opted in user-to-user communication applications that includes at least one of verbal communications and textual communications among the group of users;
access the software product catalog corresponding to the entity that includes a plurality of software products corresponding to the entity; and
access the set of opted in user-to-user communication applications to process the set of opted in user-to-user business-related conversations among the group of users.
20 . The computer program product of claim 14 , wherein the program instructions further cause the computer to:
perform, using the natural language processing and understanding model, an analysis of the set of opted in user-to-user business-related conversations among the group of users corresponding to the entity occurring via the set of opted in user-to-user communication applications;
determine, using the natural language processing and understanding model, a context of the set of opted in user-to-user business-related conversations among the group of users corresponding to the entity based on the analysis of the set of opted in user-to-user business-related conversations; and
identify, using the natural language processing and understanding model, the expressed sentiment and the mentioned keywords in the set of opted in user-to-user business-related conversations among the group of users corresponding to the entity based on the context of the set of opted in user-to-user business-related conversations.