Description:FIELD OF INVENTION

[001] The present invention relates to a system and method for evaluating impact metric of products and services. Particularly, the present invention relates to evaluating impact metric of products and services of an organization by a system integrated through a machine learning model-based system.

BACKGROUND OF THE INVENTION

[002] In today’s data driven world, understanding the impact of products and services is crucial for businesses to make informed decisions. A product/service metric is a comprehensive measure that evaluates the overall effect of a product or service on various aspect of business, including customer satisfaction, revenue growth, market share, and operational efficiency. Such metrics provide valuable insights into the performance and value contribution of products or services. The presently available devices or calculators are unable to compute such complex metrics effectively.

[003] Moreover, the inability of the presently available devices to integrate and analyze diverse data sources further hampers the accurate determination of products and services impact metrics. Businesses generate vast amount of data from various channels, including online platforms, customer feedback systems, and internal operations. The lack of cohesive system to aggregate process, and analyze this data results in fragmented insights, limiting the strategic decision making capabilities of organizations.

[004] The presently available diverse tools and software provides significant enhancing, analysing and decision-making processing. Prominent examples include Microsoft Excel, QuickBooks, SAP (Systems, Applications, and Products), Bloomberg Terminal, and Power BI (Business Intelligence), each serving distinct purposes to facilitate comprehensive data analysis. Analytical calculators and spreadsheets, while being useful, often fall short in automating benchmarking processes and integrating diverse data sources, making obtained metrics prone to error and inefficiencies. Furthermore, traditional tools lack contextual analysis and predictive analytics capabilities, hindering their ability to generate accurate insights and forecasts.

[005] There are several patent applications that disclose a system and method to obtain different metrics. One such United States patent application US4035627A discloses a battery powered hand-held calculator for performing arithmetic, trigonometric and logarithmic functions and displaying the results thereof is provided with a clock mode which performs the function of a clock and displays real time or the function of a stopwatch and stores and displays the times at which recorded events have taken place. However, the cited invention does not provide advance metrics to assess product/service performance.

[006] In order to overcome the problem associated with state of arts, there is a need for the development of an efficient machine learning based system for determining product and/ or service impact metric.

OBJECTIVE OF THE INVENTION

[007] The primary objective of the present invention is to provide a system and method for evaluating impact metric of products and services of an organization.

[008] Another objective of the present invention is to provide a streamlined and automated assessment of products and services of an organization among customers.

[009] Another objective of the present invention is to leverage advance machine learning models to analyse complex dataset, identify patterns, and generate precise product/service impact metric.

[0010] Another objective of the present invention is to provide an extensive product/service impact metric based on wide range of parameters.

[0011] Another objective of the present invention is to utilize machine learning models that indicate and forecast future performance trends.

[0012] Another objective of the present invention is to assist organizations to improve the precision of product/service impact metric evaluation and reduce manual effort by leveraging advanced analytical capabilities.

[0013] Yet another objective of the present invention is to provide comprehensive assessment that support strategic planning and resource allocation.

[0014] Yet another objective of the present invention is to help organizations developing products/services aligning well with the need of consumers.

[0015] Other objectives and advantages of the present invention will become apparent from the following description taken in connection with the accompanying drawings, wherein, by way of illustration and example, the aspects of the present invention are disclosed.

BRIEF DESCRIPTION OF DRAWINGS
[0016] The present invention will be better understood after reading the following detailed description of the presently preferred aspects thereof with reference to the appended drawings, in which the features, other aspects and advantages of certain exemplary embodiments of the invention will be more apparent from the accompanying drawing in which:

[0017] Figure 1 illustrates a block diagram of a system for evaluating impact metric of products and services of an organization.
SUMMARY OF THE INVENTION
[0018] The present invention relates to a system for evaluating impact metric of products/services of an organization. The system comprising: a computing device to receive input data and instructions by a user; an input device connected to the computing device and communicably connected to the processor for the user to provide input data and instructions to initiate analysis of the input data for evaluating impact metrics of product and services of an organization; a processor integrated into the computing device to process the input data received from the user; a server wirelessly connected to the processor to receive and store the processed input data; a machine learning module installed in the server to evaluate impact metrics of product and services of an organization based on the processed input data; and a display installed and connected to the computing device to display the evaluated impact metrics of product and services of an organization; and a memory integrated into the computing device and connected to the processor to store the input data and evaluated impact metrics of product and services of an organization. The present invention also provides a method for evaluating impact metric of products/services of an organization. The method comprising steps of: providing input data and instructions to the computing device through the input device; storing the input data in the memory integrated into the computing device; transmitting the input data to the processor through the computing device to process/analyze the input data based on the instructions received by the user; transmitting the processed input data through the processor integrated in the computing device to the server wirelessly connected to the computing device; analyzing the processed input data received by the server through the machine learning module installed in the server to evaluate impact metric of products and services of the organization; storing the evaluated impact metric of products and services of the organization, by the server; transmitting the evaluated impact metric of products and services of the organization from the server to the computing device wirelessly to display the evaluating impact metric of products and services of the organization on the display connected to the computing device.

DETAILED DESCRIPTION OF INVENTION
[0019] The following detailed description and embodiments set forth herein below are merely exemplary out of the wide variety and arrangement of instructions which can be employed with the present invention. The present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. All the features disclosed in this specification may be replaced by similar other or alternative features performing similar or same or equivalent purposes. Thus, unless expressly stated otherwise, they all are within the scope of the present invention.

[0020] Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope of the invention. In addition, descriptions of well-known functions and constructions are omitted for clarity and conciseness.

[0021] The terms and words used in the following description and claims are not limited to the bibliographical meanings but are merely used to enable a clear and consistent understanding of the invention. Accordingly, it should be apparent to those skilled in the art that the following description of exemplary embodiments of the present invention are provided for illustration purpose only and not for the purpose of limiting the invention.

[0022] It is to be understood that the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise.

[0023] It should be emphasized that the term “comprises/comprising” when used in this specification is taken to specify the presence of stated features, integers, steps, or components but does not preclude the presence or addition of one or more other features, integers, steps, components, or groups thereof.

[0024] Accordingly, the present invention relates to a system and method for evaluating impact metric of products and services. Particularly, the present invention relates to evaluating impact metric of products and services of an organization by a system integrated through a machine learning model-based system.

[0025] In an embodiment, as shown in Figure 1, the system (100) comprises a computing device (102), a processor (104) integrated into the computing device (102), a display (106) connected to the computing device (102); an input device (108) connected to the computing device (102) and communicably connected to the processor (104), a memory (110) integrated into the computing device (102) and connected to the processor (104), a server (112) wirelessly connected to the processor (104), and a machine learning module (114) installed in the server (112).
[0026] The computing device (102) may be configured to receive input data as well as the instructions for the processor (104) to initiate analysis of the input data to evaluate impact metric of products/services of an organization, wherein the input data and instructions are provided by a user through an input device (108). In an exemplary embodiment, the computing device (102) may be selected from a group consisting of, such as, but not limited to, a computer, laptop, calculator, etc.
[0027] The input data provided by the user comprises of a plurality of pre-defined parameters that are used for evaluating impact metric of products/services of an organization. In an exemplary embodiment, the input data may be selected from a group consisting of such as, but not limited to, number of active users per product/service; customer acquisition rate (monthly/quarterly); customer retention rate; net promoter score (NPS); customer lifetime value (CLV); revenue per customer; time to achieve specific mission milestones; percentage of target market reached; brand awareness percentage; customer satisfaction score; number of positive customer testimonials; social media engagement rate for brand related content; product/service usage frequency; number of customer needs addressed by the product/service; time saved or value added for customers (quantified); number of social or environmental goals achieved (if applicable to the vision); market share percentage; year-over-year growth rate; number of new products/services launched aligned with the vision; percentage of employees who can articulate the company's vision and mission, the achievement of macro-level targets, the primary focus of the entrepreneurs, etc., or combination thereof.
[0028] In an exemplary embodiment, the input device (108) may be selected from a group consisting of, such as, but not limited to, a physical keyboard, touch-screen keyboard, mouse, etc.
[0029] The processor (104) may be configured to process/analyze input data on receiving the user’s instructions from the computing device (102) and thereafter wirelessly transmit data to the server (112) for evaluation of impact metric of product/services of the organization by the machine learning module (114). In an exemplary embodiment, the processed input data may be transmitted to the server (112) through Wi-Fi, Bluetooth, Ethernet, GPRS module, and the like.
[0030] The server (112) receives processed data from the processor (104) and stores the processed input data. In an exemplary embodiment, the server (112) may store data in an architecture selected from a group consisting of, such as, but not limited to, Recurrent Neural Network (RNN) model architecture, an auto encoder, and the like. The machine learning module (114) installed in the server (112) evaluates impact metric of products/services of the organization based on the processed input data. The server (112) wirelessly transmits the evaluated impact metric of products/services of the organization to the computing device (102) through such as, but not limited to, Wi-Fi, Bluetooth, etc., for displaying the evaluated impact metric of products/services of the organization through the display (106) for the user.

[0031] The machine learning module (114) may be trained on datasets encompassing a wide range of pre-defined parameters to evaluate impact metric of products/services of the organization, thereby providing an assessment of performance of products/services of the organization among consumers. The machine learning module (114) is trained to assign weightage to each pre-defined parameter, which involves segregating the data for training the machine learning module (114) into training data, which is used to train the machine learning module (114) and testing data, which is used to determine the performance of the trained machine learning module (114). In an exemplary embodiment, the machine learning module (114) may be selected from a group consisting of such as, but not limited to, linear regression, polynomial regression, random forest model, and the like, thereby making the process of assigning weight dynamic and automatic.

[0032] The machine learning module (114) also provides data-driven recommendations based on the input data. The machine learning module (114) is trained on training data of various industries and companies so as to evaluate a calibrated score reflective of the products/services’ performance. In an exemplary embodiment, the machine learning module (114) is configured to evaluate the calibrated score based upon assigned weight, through a model selected from a group consisting of such as, but not limited to, linear regression, polynomial regression, random forest model, and the alike.

[0033] The memory (110) may be configured to store the data and instructions provided by the user and the evaluated impact metric of products/service of an organization. In an exemplary embodiment, the memory may be selected from a group consisting of, such as, but not limited to, flash memory, secondary memory, cache memory, and the alike.

[0034] In an embodiment, the present invention also provides method for evaluating impact metric of products/services of the organization using the system (100), comprises the following steps:
• providing input data and instructions to the computing device (102) through the input device (108);
• storing the input data in the memory (110) integrated into the computing device (102);
• transmitting the input data to the processor (104) through the computing device (102) to process/analyze the input data based on the instructions received by the user;
• transmitting the processed input data through the processor (104) integrated in the computing device (102) to the server (112) wirelessly connected to the computing device (102);
• analyzing the processed input data received by the server (112) through the machine learning module (114) installed in the server (112) to evaluate impact metric of products and services of the organization;
• storing the evaluated impact metric of products and services of the organization, by the server (112);
• transmitting the evaluated impact metric of products and services of the organization from the server (112) to the computing device (102) wirelessly to display the evaluating impact metric of products and services of the organization on the display (106) connected to the computing device (102).

[0035] The input data provided by the user comprises of a plurality of pre-defined parameters that are used for evaluating impact metric of products/services of the organization. In an exemplary embodiment, the input data may be selected from a group consisting of such as, but not limited to, number of active users per product/service; customer acquisition rate (monthly/quarterly); customer retention rate; net promoter score (NPS); customer lifetime value (CLV); revenue per customer; time to achieve specific mission milestones; percentage of target market reached; brand awareness percentage; customer satisfaction score; number of positive customer testimonials; social media engagement rate for brand related content; product/service usage frequency; number of customer needs addressed by the product/service; time saved or value added for customers (quantified); number of social or environmental goals achieved (if applicable to the vision); market share percentage; year-over-year growth rate; number of new products/services launched aligned with the vision; percentage of employees who can articulate the company's vision and mission, the achievement of macro-level targets, the primary focus of the entrepreneurs, etc., or combination thereof..
[0036] In an exemplary embodiment, the computing device may be selected from a group consisting of such as, but not limited to, a computer, laptop, calculator, etc.

[0037] In another exemplary embodiment, the input device (108) may be selected from a group consisting of, such as, but not limited to, a physical keyboard, touch-screen keyboard, mouse, etc.

[0038] In yet another exemplary embodiment, the memory may be selected from a group consisting of, such as, but not limited to, flash memory, secondary memory, cache memory, and the alike.

[0039] The instructions provided by the user include the instructions for analyzing the input data by the processor (104) for evaluating impact metric of products/services of the organization.

[0040] In yet another exemplary embodiment, the server (112) may store data in an architecture selected from a group consisting of, such as, but not limited to, Recurrent Neural Network (RNN) model architecture, an auto encoder, and the like.

[0041] The advantages of the present invention are enlisted herein:
• The present invention provides a streamlined and automated assessment of products and services of an organization among customers.
• The present invention leverages advance machine learning models to analyse complex dataset, identify patterns, and generate precise product/service impact metric.
• The present invention provides an extensive product/service impact metric based on wide range of parameters.
• The present invention utilizes machine learning models that indicate and forecast future performance trends.
• The present invention assists organizations to improve the precision of product/service impact metric evaluation and reduce manual effort by leveraging advanced analytical capabilities.
• The present invention provides comprehensive assessment that support strategic planning and resource allocation.
• The present invention helps organizations to develop products/services aligning well with the need of consumers.

[0042] While this invention has been described in connection with what is presently considered to be the most practical and preferred embodiment, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, is intended to cover various modifications and equivalent arrangements included within the scope of the appended claims.
, Claims:1. A system for evaluating impact metric of products and services of an organization, comprising:
(a) a computing device (102) to receive input data and instructions by a user;
(b) an input device (108) connected to the computing device (102) and communicably connected to the processor (104) for the user to provide input data and instructions to initiate analysis of the input data for evaluating impact metrics of product and services of an organization;
(c) a processor (104) integrated into the computing device (102) to process the input data received from the user;
(d) a server (112) wirelessly connected to the processor (104) to receive and store the processed input data;
(e) a machine learning module (114) installed in the server (112) to evaluate impact metrics of product and services of an organization based on the processed input data; and
(f) a display (106) installed and connected to the computing device (102) to display the evaluated impact metrics of product and services of an organization; and
(g) a memory (110) integrated into the computing device (102) and connected to the processor (104) to store the input data and evaluated impact metrics of product and services of an organization.
2. The system (100) as claimed in claim 1, wherein the computing device (102) is selected from a group consisting of a computer, calculator, and laptop.
3. The system (100) as claimed in claim 1, wherein the input data comprises of, number of active users per product/service; customer acquisition rate (monthly/quarterly); customer retention rate; net promoter score (NPS); customer lifetime value (CLV); revenue per customer; time to achieve specific mission milestones; percentage of target market reached; brand awareness percentage; customer satisfaction score; number of positive customer testimonials; social media engagement rate for brand related content; product/service usage frequency; number of customer needs addressed by the product/service; time saved or value added for customers (quantified); number of social or environmental goals achieved (if applicable to the vision); market share percentage; year-over-year growth rate; number of new products/services launched aligned with the vision; percentage of employees who can articulate the company's vision and mission, the achievement of macro-level targets, the primary focus of the entrepreneurs, etc., or combination thereof.
4. The system (100) as claimed in claim 1, wherein the input device (108) is selected from a group consisting of, a physical keyboard, touch-screen keyboard, mouse, or a combination thereof.
5. The system (100) as claimed in claim 1, wherein the machine learning module (114) is configured for continuous refinement through iterative training to alleviate reliance on human intervention.
6. The system (100) as claimed in claim 1, wherein the machine learning module (114) is configured to attribute weightage to pre-defined parameters based on a machine learning model.
7. The system (100) as claimed in claim 1, wherein the machine learning model is trained on datasets encompassing a wide range of pre-defined parameters to evaluate impact metrics of products/services of the organization.
8. The system (100) as claimed in claim 7, wherein the machine learning model is selected from a group consisting of linear regression, polynomial regression, and random forest model.
9. A method for determining evaluating impact metric of products/services of the organization using the system as claimed in claim 1, comprising steps of:
• providing input data and instructions to the computing device (102) through the input device (108);
• storing the input data in the memory (110) integrated into the computing device (102);
• transmitting the input data to the processor (104) through the computing device (102) to process/analyze the input data based on the instructions received by the user;
• transmitting the processed input data through the processor (104) integrated in the computing device (102) to the server (112) wirelessly connected to the computing device (102);
• analyzing the processed input data received by the server (112) through the machine learning module (114) installed in the server (112) to evaluate impact metric of products and services of the organization;
• storing the evaluated impact metric of products and services of the organization, by the server (112);
• transmitting the evaluated impact metric of products and services of the organization from the server (112) to the computing device (102) wirelessly to display the evaluating impact metric of products and services of the organization on the display (106) connected to the computing device (102).
10. The method as claimed in claim 9, wherein the method comprise a step of providing iterative training to machine learning module (114) for continuous refinement.