Description:FIELD OF INVENTION
[001] The present invention relates to a marketing effectiveness evaluating system and a method thereof. Particularly, the present invention relates to evaluating marketing effectiveness by a system integrated through a machine learning model-based system.
BACKGROUND OF THE INVENTION
[002] Evaluation of marketing effectiveness is the measurement of marketing strategies and campaigns to achieve its target of increasing the revenue. Marketing effectiveness covers impacts created by all the marketing activities. It also encompasses many added metrics and indices comprising customer acquisition cost, market shares, customer engagement, amongst others. By analyzing these metrics, the efficiency impact of the marketing effort can be measured.
[003] The effectiveness of marketing needs to be measured to evaluate the positive return on investments, improved marketing campaigns, and gaining competitive advantages. Besides, the data-driven insights are required for making informed decisions, and determining the best data-driven decisions based on evidence. There are plenty of such known systems for evaluating marketing effectiveness by measuring all these metrics or indices. Moreover, for properly measuring marketing effectiveness, it is essential to determine the relevant metrics that are involved around the market to achieve a certain objective. One patent document WO2017086315A1 disclosed a customer acquisition support system and method for effectively implementing the customer acquisition support method, in order to assist acquisition of actual customers by enabling sufficient increase in business efficiency, business effectiveness, and customer satisfaction, by adopting an appropriate business approach for each potential customer. However, the cited prior art document does not disclose the evaluation of other important parameters/metrics except customer acquisition support to determine the marketing performance. The other commonly known marketing effectiveness measuring system does not disclose the precise determination method, and the accurate determining of the impact of marketing strategies, which is very much crucial to maximize the profit.
[004] Therefore, in order to overcome the challenges associated with the state of the art, there is a need to develop an efficient system for evaluating market effectiveness, thereby maximizing the return on investment and achieving the goal of driving market growth and success.
OBJECTIVE OF THE INVENTION
[005] The primary objective of the present invention is to provide a marketing effectiveness evaluating system and a method thereof.
[006] Another objective of the present invention is to provide an efficient system integrated with a machine learning model for analyzing the marketing effectiveness, enabling the long-term increase in revenue.
[007] Another objective of the present invention is to provide data-driven insights to take informed and strategic decisions, thereby enabling an organization to make data-driven decisions to the strategies.
[008] Yet another objective of the present invention is to provide a system for measuring market effectiveness of an organization by providing the strategy to increase its revenue and to decrease its cost of customer acquisition.
[009] Another objective of the present invention is to provide a system to evaluate impact on marketing activities, such as, market share changes, new customers added, investment costs, profit changes, audience engagement, customer engagement, etc.
[0010] 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
[0011] 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:
[0012] Figure 1 illustrates a block diagram of the system for evaluating marketing effectiveness.
SUMMARY OF THE INVENTION
[0013] The present invention relates to a marketing effectiveness evaluating system. The system comprising a computing device (102) to receive input data and instructions by a user; an input device (108) connected to the computing device (102); a processor (104) integrated into the computing device (102) to process the input data received from the user; a server (112) wirelessly connected to the processor (104) to receive and store the processed input data; a machine learning module (114) installed in the server (112) to evaluate marketing effectiveness based on the processed input data; a display (106); and a memory (110) integrated into the computing device (102) and connected to the processor (104) to store the input data and evaluated marketing effectiveness data. The input data may be plurality of predefined parameters/metrics, which may be selected from a group consisting of such as, but not limited to, number of deals, customer acquisition costs, new customers, total orders, market share changes, sales of auxiliary products, investment costs, salesperson efficiency, customer engagement scores market concentration (Herfindahl-Hirschman Index), pricing changes, profit changes, customer lifespan, customer satisfaction metrics (NPS), story effectiveness scores, audience engagement with narratives, feedback incorporation rate, organic sharing metrics of brand stories, or any combinations thereof.
[0014] The present invention also relates to a method for evaluating marketing effectiveness using the system. The method comprises the steps of: providing input data and instructions to a computing device (102) through an input device (108); storing the input data in a 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 a server (112) wirelessly connected to the computing device (102); analyzing the processed input data received by the server (112) through a machine learning module (116) installed in the server (112) to evaluate market effectiveness; storing the evaluated market effectiveness data by the server (112) through a storage architecture; transmitting the evaluated market effectiveness data from the server (112) to the computing device (102) wirelessly to display the evaluated market effectiveness data on a display (106) installed and connected to the computing device (102).
DETAILED DESCRIPTION OF INVENTION
[0015] 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.
[0016] 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.
[0017] 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.
[0018] It is to be understood that the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise.
[0019] 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, steps, components, or groups thereof.
[0020] Accordingly, the present invention relates to a marketing effectiveness evaluating system and a method thereof. Particularly, the present invention relates to evaluating marketing effectiveness by a system integrated through a machine learning model-based system to evaluate the success of market operations.
[0021] In an embodiment, as shown in Figure 1, the system (100) comprising 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).
[0022] The computing device (102) may be configured to receive input data as well as the instructions for the processor (104) to initiate the analysis of the input data for evaluating marketing effectiveness, 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.
[0023] The input data provided by the user comprises of a plurality of pre-defined parameters/metrics that are used for evaluating marketing effectiveness. In an exemplary embodiment, the input data may be selected from a group consisting of such as, but not limited to, number of deals, customer acquisition costs, new customers, total orders, market share changes, sales of auxiliary products, investment costs, salesperson efficiency, customer engagement scores market concentration (Herfindahl-Hirschman Index), pricing changes, profit changes, customer lifespan, customer satisfaction metrics (NPS), story effectiveness scores, audience engagement with narratives, feedback incorporation rate, organic sharing metrics of brand stories, or any combinations thereof.
[0024] 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.
[0025] The processor (104) may be configured to process/evaluate 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 marketing effectiveness 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.
[0026] The server (112) receives processed data from the processor (104) and stores the processed input data through an architecture. The machine learning module (114) installed in the server (112) evaluates marketing effectiveness based on the processed input data. The server (112) wirelessly transmits the evaluated marketing effectiveness data to the computing device (102) through such as, but not limited to, Wi-Fi, Bluetooth, etc., for displaying the evaluated marketing effectiveness data through the display (106) for the user. In an exemplary embodiment, the architecture to store the processed input data may be selected from, but not limited to, Recurrent Neural Network (RNN), Autoencoder, and the like.
[0027] The machine learning module (114) may be trained on datasets encompassing a wide range of pre-defined parameters to determine/evaluate marketing effectiveness, thereby providing an assessment of the marketing effectiveness, of an organizations. 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.
[0028] The memory (110) may be configured to store the input data provided by the user as well as the evaluated marketing effectiveness data. 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 like.
[0029] The instructions provided by the user include the instructions for analyzing the input data by the processor for evaluating marketing effectiveness.
[0030] In an embodiment, the present invention also provides a method for evaluating marketing effectiveness, using the system of the present invention. The method comprises the following steps:
• providing input data and instructions to a computing device (102) through an input device (108);
• storing the input data in a 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 a server (112) wirelessly connected to the computing device (102);
• analyzing the processed input data received by the server (112) through a machine learning module (116) installed in the server (112) to evaluate marketing effectiveness;
• storing the evaluated marketing effectiveness by the server (112) through a storage architecture;
• transmitting the marketing effectiveness data from the server (112) to the computing device (102) wirelessly to display the evaluated marketing effectiveness data on a display (106) installed and connected to the computing device (102).
[0031] The input data provided by the user comprises of a plurality of pre-defined parameters/metrics that are used for evaluating marketing effectiveness. In an exemplary embodiment, the input data may be selected from a group consisting of such as, but not limited to, number of deals, customer acquisition costs, new customers, total orders, market share changes, sales of auxiliary products, investment costs, salesperson efficiency, customer engagement scores market concentration (Herfindahl-Hirschman Index), pricing changes, profit changes, customer lifespan, customer satisfaction metrics (NPS), story effectiveness scores, audience engagement with narratives, feedback incorporation rate, organic sharing metrics of brand stories, or any combinations thereof.
[0032] The computing device (102) may be configured to receive input data as well as the instructions for the processor (104) to initiate the analysis of the input data for evaluating marketing effectiveness, 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.
[0033] 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.
[0034] In another 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.
[0035] 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 like.
[0036] The advantages of the present invention are enlisted herein:
• The present invention provides an organization to assess the efficiency and impact of their marketing efforts for optimizing their marketing strategies.
• The present invention analyses the market activities for generating positive return/profits on investments.
• The present invention provides competitive advantage, and helps to surpass the competitors and retain the customers for a long run.
• The present invention utilizes machine learning models to offer provides data-driven insights for making strategic decisions.

[0037] 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:WE CLAIM:

1. A marketing effectiveness evaluating system, comprising:
• a computing device (102) to receive input data and instructions by a user;
• 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 marketing effectiveness;
• a processor (104) integrated into the computing device (102) to process the input data received from the user;
• a server (112) wirelessly connected to the processor (104) to receive and store the processed input data through a model architechture;
• a machine learning module (114) installed in the server (112) to evaluate marketing effectiveness based on the processed input data; and
• a display (106) installed and connected to the computing device (102) to display the evaluated marketing effectiveness data; and
• a memory (110) integrated into the computing device (102) and connected to the processor (104) to store the input data and evaluated marketing effectiveness data.
2. The system (100) as claimed in claim 1, wherein the computing device (102) is selected from computer, laptop, calculator.
3. The system (100) as claimed in claim 1, wherein the input data comprises of a selected from a group consisting of: number of deals, customer acquisition costs, new customers, total orders, market share changes, sales of auxiliary products, investment costs, salesperson efficiency, customer engagement scores market concentration (Herfindahl-Hirschman Index), pricing changes, profit changes, customer lifespan, customer satisfaction metrics (NPS), story effectiveness scores, audience engagement with narratives, feedback incorporation rate, organic sharing metrics of brand stories, or any combinations thereof.
4. The system (100) as claimed in claim 1, wherein the input device (108) is a physical keyboard, touch-screen keyboard, and mouse.
5. The system (100) as claimed in claim 1, wherein the server (112) employs a Recurrent Neural Network (RNN) model architecture for data storage.
6. The system (100) as claimed in claim 5, wherein the Recurrent Neural Network (RNN) model architecture is trained on datasets encompassing a wide range of pre-defined input parameters to evaluate marketing effectiveness to improve decision-making by the organization.
7. The system (100) as claimed in claim 1, wherein machine learning module (114) is configured for continuous refinement through iterative training to alleviate reliance on human intervention.
8. The system (100) as claimed in claim 1, wherein machine learning module (114) is configured to attribute weightage to pre-defined input data as compared to the standard industrial norms.
9. The system (100) as claimed in claim 1, wherein the machine learning module (114) may be selected from a group consisting of linear regression, polynomial regression, and random forest model.

10. The method for evaluating marketing effectiveness using the system (100) as claimed in claim 1, comprises the steps of:
• providing input data and instructions to a computing device (102) through an input device (108);
• storing the input data in a 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 a server (112) wirelessly connected to the computing device (102);
• analyzing the processed input data received by the server (112) through a machine learning module (114) installed in the server (112) to evaluate marketing effectiveness;
• storing the evaluated marketing effectiveness data by the server (112);
• transmitting the evaluated marketing effectiveness data from the server (112) to the computing device (102) wirelessly to display the evaluated marketing effectiveness data on a display (106) installed and connected to the computing device (102).