Systems and methods for job segmentation and corresponding need identification
Systems and methods for job segmentation and identification of unmet needs are provided. An example method includes receiving, from a user, identification of a job to be performed. The method also includes obtaining a set of job steps corresponding to segmentation of the job to be performed and obtaining a set of product features for a product designed to assist with completion of the job to be performed. The method further includes assigning each product feature of the set of product features to a corresponding job step of the set of job steps, assigning respective effort scores to the set of job steps, assigning respective measures of importance to the set of product features based on the respective effort scores, and causing the set of product features to be presented to the user with the respective measures of importance.
1 . A method of visualizing job segmentation, the method comprising:
for each respective user in a plurality of users, wherein the plurality of users comprises more than two users:
receiving, in electronic form, via a selection of a first graphical user interface element from a respective user, in a plurality of users, an identification of a first job, wherein the first job is defined by the respective user and to be performed by a user, in the plurality of users, different from the respective user;
generating a plurality of job steps corresponding to the first job, wherein each respective job step in the plurality of job steps is associated with a corresponding segmentation, in a plurality of segmentations, of the first job, each corresponding segmentation associated with a discrete contribution to deem completion of the first job;
generating a plurality of product features for a first product designed to assist the user, in the plurality of users, with completion of the first job, wherein each respective product feature in the plurality of product features is associated with a corresponding function, in a plurality of functions, provided by the first product;
assigning each respective product feature of the plurality of product features to a corresponding job step of the plurality of job steps;
generating a respective effort score for each job step in the plurality of job steps based, at least in part, on (i) a corresponding classification, in a plurality of classifications, assigned to the user and (ii) a feedback dataset associated with a second job performed by a set of users, in the plurality of users, different from the user and the respective user by performing a process comprising:
forming a taxonomy of data by converting, via at least one classification model in a plurality of classification models, the feedback dataset from a native format into a predetermined structured format, the converting comprising:
converting a first data element of the feedback dataset from the native format of an audio data format into a predetermined structured format of a text file format, and
converting a second data element of the feedback dataset from the native format of a plain text format into the predetermined structured format that defines each variable of a polynomial equation and deconstructs the polynomial equation into a plurality of unit operations, and the taxonomy of data comprises the plurality of classifications determined by the plurality of classification models and is uniquely formed for the first job
assigning a corresponding plurality of measures of importance to each respective product feature in the plurality of product features based on the respective effort score, wherein the corresponding plurality of measures of importance comprises at least one cost value and at least one temporal value associated with producing the first product; and
causing the plurality of product features to be presented to the respective user with the corresponding plurality of measures of importance in accordance with a ranked order of the corresponding plurality of measures of importance.
2 . The method of claim 1 , wherein the generating the plurality of job steps corresponding to segmentation of the first job to be performed comprises:
providing the identification of the first job to be performed and one or more instructions to a language model; and
in response to providing the identification of the first job to be performed, receiving the plurality of job steps from the language model.
3 . The method of claim 2 , wherein the one or more instructions is provided to the language model in a markdown table.
4 . The method of claim 2 , wherein the method further comprises providing a plurality of predetermined job steps to the language model.
5 . The method of claim 4 , wherein the plurality of predetermined of example job steps is provided in as a structured data array.
6 . The method of claim 1 , wherein the method further comprises causing the plurality of job steps to be presented to the respective user with the respective effort score.
7 . The method of claim 6 , wherein the plurality of job steps is presented in an order of completion for the first job to be performed.
8 . The method of claim 1 , wherein the method further comprises obtaining the corresponding classification of a type of person to perform the first job to be performed.
9 . The method of claim 1 , wherein the method further comprises obtaining a second plurality of effort scores corresponding to a second classification in the plurality of classifications;
assigning the second plurality of effort scores to the plurality of job steps; and
causing the plurality of job steps to be presented to the respective user with the respective effort score and the second plurality of effort scores.
10 . The method of claim 1 , wherein the at least one cost value comprises a return on investment (ROI) value for the first product.
11 . The method of claim 1 , wherein the method further comprises obtaining a plurality of unmet needs for the plurality of users that correspond to the plurality of job steps, wherein the corresponding plurality of measures of importance is based on the plurality of unmet needs.
12 . The method of claim 11 , wherein the plurality of unmet needs are obtained from a second language model in response to inputting the plurality of job steps and second instructions to the second language model.
13 . The method of claim 12 , wherein the plurality of job steps are input into the second language model as a data array.
14 . The method of claim 12 , further comprising providing a plurality of example needs to the second language model.
15 . The method of claim 1 , wherein the method further comprises receiving a second plurality of job steps from the respective user;
assigning at least a subset of the plurality of product features to the second plurality of job steps; and
generating a second respective effort score for each job step in the second plurality of job steps.
16 . The method of claim 1 , wherein the generating the plurality of job steps, the generating the plurality of product features, the assigning each respective product feature, the generating the respective effort score, the assigning the corresponding plurality of measures, and the causing the set of product features is performed without human intervention.
17 . A computing system comprising at least one processor and a memory storing a set of instructions for execution by the at least one processor, the set of instructions comprising instructions for:
for each respective user in a plurality of users, wherein the plurality of users comprises more than two users:
receiving, in electronic form, via a selection of a first graphical user interface element from a respective user, in a plurality of users, an identification of a first job, wherein the first job is defined by the respective user and to be performed by a user, in the plurality of users, different from the respective user;
generating a plurality of job steps corresponding to the first job, wherein each respective job step in the plurality of job steps is associated with a corresponding segmentation, in a plurality of segmentations, of the first job, each corresponding segmentation associated with a discrete contribution to deem completion of the first job;
generating a plurality of product features for a first product designed to assist the user, in the plurality of users, with completion of the first job, wherein each respective product feature in the plurality of product features is associated with a corresponding function, in a plurality of functions, provided by the first product;
assigning each respective product feature of the plurality of product features to a corresponding job step of the plurality of job steps;
generating a respective effort score for each job step in the plurality of job steps based, at least in part, on (i) a corresponding classification, in a plurality of classifications, assigned to the user and (ii) a feedback dataset associated with a second job performed by a set of users, in the plurality of users, different from the user and the respective user by performing a process comprising:
forming a taxonomy of data by converting, via at least one classification model in a plurality of classification models, the feedback dataset from a native format into a predetermined structured format, the converting comprising:
converting a first data element of the feedback dataset from the native format of an audio data format into a predetermined structured format of a text file format, and
converting a second data element of the feedback dataset from the native format of a plain text format into the predetermined structured format that defines each variable of a polynomial equation and deconstructs the polynomial equation into a plurality of unit operations, and
the taxonomy of data comprises the plurality of classifications determined by the plurality of classification models and is uniquely formed for the first job
assigning a corresponding plurality of measures of importance to each respective product feature in the plurality of product features based on the respective effort score, wherein the corresponding plurality of measures of importance comprises at least one cost value and at least one temporal value associated with producing the first product; and
causing the plurality of product features to be presented to the respective user with the corresponding plurality of measures of importance in accordance with a ranked order of the corresponding plurality of measures of importance.
18 . A non-transitory computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing system, cause the computing system to perform a method comprising:
for each respective user in a plurality of users, wherein the plurality of users comprises more than two users:
receiving, in electronic form, via a selection of a first graphical user interface element from a respective user, in a plurality of users, an identification of a first job, wherein the first job is defined by the respective user and to be performed by a user, in the plurality of users, different from the respective user;
generating a plurality of job steps corresponding to the first job, wherein each respective job step in the plurality of job steps is associated with a corresponding segmentation, in a plurality of segmentations, of the first job, each corresponding segmentation associated with a discrete contribution to deem completion of the first job;
generating a plurality of product features for a first product designed to assist the user, in the plurality of users, with completion of the first job, wherein each respective product feature in the plurality of product features is associated with a corresponding function, in a plurality of functions, provided by the first product;
assigning each respective product feature of the plurality of product features to a corresponding job step of the plurality of job steps;
generating a respective effort score for each job step in the plurality of job steps based, at least in part, on (i) a corresponding classification, in a plurality of classifications, assigned to the user and (ii) a feedback dataset associated with a second job performed by a set of users, in the plurality of users, different from the user and the respective user by performing a process comprising:
forming a taxonomy of data by converting, via at least one classification model in a plurality of classification models, the feedback dataset from a native format into a predetermined structured format, the converting comprising:
converting a first data element of the feedback dataset from the native format of an audio data format into a predetermined structured format of a text file format, and
converting a second data element of the feedback dataset from the native format of a plain text format into the predetermined structured format that defines each variable of a polynomial equation and deconstructs the polynomial equation into a plurality of unit operations, and the taxonomy of data comprises the plurality of classifications determined by the plurality of classification models and is uniquely formed for the first job
assigning a corresponding plurality of measures of importance to each respective product feature in the plurality of product features based on the respective effort score, wherein the corresponding plurality of measures of importance comprises at least one cost value and at least one temporal value associated with producing the first product; and
causing the plurality of product features to be presented to the respective user with the corresponding plurality of measures of importance in accordance with a ranked order of the corresponding plurality of measures of importance.