Field of the Invention:

This invention is about a customer relationship management system that gathers the customer relations units of the companies under the same roof, includes customer relations management and aims to work from a single center.

State of the Art:

In the current system, holdings, institutions, businesses, and other organizations dealing with customers have difficulties in managing data about customers and interacting with them. For example, customer relations professionals today need to develop a personalized service plan for each customer. For the service provider, this approach creates an unnecessary burden on service personnel and increases the costs of service providers. Because service plans are often incomplete or inadequate to meet customers' needs. Although today's customer relationship management systems have been developed to organize large amounts of customer relationship data and try to improve understanding between the organization and its customers, they often fail to provide adequate interfaces and tools to assist the business and the consumer. Lack of adequate tools creates disconnection between assets and customers, often frustrating inefficient ways to communicate and obtain information from the business and its customers.

Patent Number US2016019481A1 issued on Jan. 21, 2016, discloses a customer relationship capacity planning. Methods and apparatuses, including computer program products, are described for customer relationship capacity planning. A computing device receives financial plan attributes associated with a financial plan of a customer and personality characteristics associated with the customer. The computing device determines a relationship complexity score associated with the customer based upon the financial plan attributes and the personality characteristics. The computing device determines a target workload value for customer service managers of the financial services entity based upon the relationship complexity score for a plurality of customers and a past number of relationship service hours associated with the plurality of customers. The computing device allocates the customer to a customer service manager based upon the target workload value and a current workload of the customer service manager. The computing device updates an allocation table that contains information relating to the allocation of customers to customer service managers.

Patent Number US2014040153A1 issued on Feb. 06, 2014, discloses a system and method for providing a configurable web portal builder interfacing with a customer relationship management system. A system and method for a web portal builder that is user-configurable, enables improved customization of a web portal, and provides a highly collaborative environment to various interested entities is described. The web portal builder may generate interfaces such as web portals that expose functionality and data of the backend Consumer Relationship Management ("CRM") system as well as extend CRM functions and data capabilities. The web portal builder may build interfaces for use by entities such as governments, agencies of governments, businesses and others who deal with consumers. The entities may use the interfaces to view and manage consumers, leveraging information stored by or in association with the CRM system. For example, a government social services case manager may use the interfaces to manage information related to consumers (in this case, individuals applying for or receiving various social benefits).

Patent Number TR201620219 issued on Dec. 30, 2016, discloses a method for establishing customer relationship management system development environments. This invention is about a method in which CRM (customer relationship management) development environments, which take hours to install and update and need to work in integration with many systems, are set up and updated in a short time with 5S Lean and reverse engineering methods.

The patent applications discussed above are mentioned in computer-based customer relationship management systems. Although the systems here have been developed for customer satisfaction, they lack any control mechanism for measuring and evaluating customers or removing them from the system as a result of the audit. The aforementioned inventions have been developed to allow the creation of more special forms and to facilitate follow-up with these forms.

Consequently, there is a necessity for a novel technology that is capable of eliminating above mentioned disadvantages, provides a collective working environment by gathering the interactions between service providers and customers on a common server, helps to automate and streamline processes, makes improvements based on the kaizen principle, saves time and money with a large Big Data chain and aims at customer satisfaction as a result of improvements, supervise the institutions by the referees included in the system.

Description of the Invention:

The present invention is a customer relationship management system which can overcome the above-mentioned disadvantages, provides a collective working environment by gathering the interactions between service providers and customers on a common server, helps to automate and streamline processes, makes improvements based on the kaizen principle, saves time and money with a large Big Data chain and aims at customer satisfaction as a result of improvements, supervise the institutions by the referees included in the system.

In order to realize all the objectives mentioned above and which will emerge from the detailed description below, the invention aims to carry out a single-center study that gathers the customer relations units of the companies owned by the holdings under one roof and includes customer relations management. In this way, it puts all holdings in a single center and makes it easier to carry out special studies from within the general.

The customer relations units of the institutions that are members of the inventive system are taking important steps to improve themselves. To standardize the necessity of organizations to follow a transparent policy towards their customers and their customers' institutions and to be impartial, and primarily to provide this standard to institutions. With a large Big Data chain, it saves time, saves money and at the same time professionalizes the relevant units. It is important to be able to use technology in the most efficient way by enabling people to dominate technology. It can ensure that the relevant standards are decided by the referees in the system and the necessity to act with case law. This is achieved by the system when the party deemed unfair by the parties at the end of the disputes is determined to pay a deterrent fee. At this stage, the system will implement its own laws, and it takes responsibility for the work of states in criminal law decisions. The courts are also aimed to be relieved, the system implements its own legal decisions, and if the case is not resolved, of course the states' own official law can come into play.

The inventive system ensures transparency in customer relations with Big Data. The system prevents untrained personnel. It is aimed that the Customer Relations units specifically examine and set the standards of the system. It offers functional and longterm solutions to a problem or suggestion between institutions and customers. It enables customers or institutions to use time, time-oriented, disciplined and efficiency-oriented. The computer-based system allows professional recruitment of customer relations units. It adds a different dimension to the operation of customer relations units with software, and multi-company organizations are integrated into the system via a central server. It is ensured that the disconnection between institutions and sectors is eliminated and they interact with each other. It is possible for every institution in every sector to standardize the solutions on standard issues and to take the leadership of the institutions that will set an example by other institutions. Creating a global solution union at the top with Big Data and Customer Relationship Management Association for organizations in the same sector that are completely independent of each other and acting with different decisions, customer acquisition and protection of existing customers by the institution are ensured by ensuring a quality standard. In addition, the invention facilitates the work of institutions in this way and ensures that the customer relations units of the institutions can be in touch from a single point. The development of the inventive system was carried out with the knowledge that the investment in the future is based on Big Data. Here, virtual money is in question, in fact, to advance a system together with people, to advance people, and continuity, change, innovation is a priority, and innovation and the Kaizen principle are the only criteria.

All the advantages of the product subject to the invention will be understood more clearly thanks to the scheme given below and the detailed explanation written by making references to this scheme, and therefore the evaluation should be made by taking this scheme and detailed description into consideration.

Brief Description of the Drawings:

The invention will now be described with reference to the accompanying figures, so that the features of the invention will be more clearly understood and appreciated, but not by limiting the invention to these particular embodiments. On the contrary, it is intended to cover all alternatives, modifications and equivalents that may be included within the scope of the invention as defined by the appended claims. It should be understood that the details are shown only for the purpose of illustrating preferred embodiments of the present invention and are provided the most useful and easily understood descriptions of both the method and the rules and conceptual features of the invention. In these drawings;

Figure 1 The schematic view of the system subject to the invention.

The figures that will help to understand the present invention are numbered as indicated in the attached picture and are given below with their names.

Disclosure of References:

1. Server

2. Classification Unit 3. Integrated Unit

4. Data Storage Unit

5. Request Module

6. Processor Unit

7. Suggestion Module

8. Approval Module

9. Notification Module

10. Control Unit

Detailed Disclosure of the Invention:

The present invention is comprised of server (1), classification unit (2), integrated unit

(3), data storage unit (4), request module (5), processor unit (6), suggestion module (7), approval module (8), notification module (9) and control unit (10).

In the system of the invention, the institutions are grouped primarily by the classification unit (2) as iron and steel, textile, food, plastic and glass-ceramic industries and institutions affiliated with the sectors. The system especially focuses on the problems, customer requests, suggestions and problems of member companies with their customers. In another arrangement of the system, there is a control unit (10), in which at least 5 institutions in each sector are members of the system and 5 software experts or engineers each has an arbitration board that examines the customer relations management of the institutions that are members of the system. In this system, the software systems used by the institutions are integrated into the invention and the titles required for the system are defined according to the institutions. The system, which is created over big data, is integrated into the software used by the companies and their customers over a central server (1) by the software it contains. In this way, the data shared between the institution and the customer are transferred to the data storage unit

(4) by the server (1) of the system. Here, all the data (input and output stage) in the suggestions, requests and problem parameters of the customers are separated and fall into the headings in the system subject to the invention. While these data come to the inventive system, they become a separate area of the institution of each sector, and suggestions and requests in this field, transaction sharing (the steps implemented in it may be related to other units of the institution), transaction solution (collected information), delivered solution, post-solution feedback ( notification from the customer to the institution), implementation time and improvement actions, problem repeat buttons in this field are processed by the processor unit (6) of the system and in this process, the interaction of customer relations units between the institution and its customers is monitored and artificial intelligence-based inferences are made from all data inputs and outputs. The problem here may only be in customer relations units. In this case, only the feedback received by the customer to the notification module (9) is important. These notifications are automatically sent to the notification module (9). But first of all, the system attaches importance to the mechanism of supervising and directing customer relations units. This system acts depending on the sectors with Big Data. Each sector can use different software types, but the system operates the software types owned by the institutions in an integrated manner by a new top software integrated unit (3). In this way, the invention creates areas for observing, tracking, collecting and processing data in customer relations from the system of the institutions it is integrated with. Since these data will enter the inventive system from one point for each sector and they need to provide feedback in a different field, a second area where direct contact with the institutions is developed. Various buttons are defined in the system which is the subject of the invention. Here, the buttons coming to the system from the institutions and causing the process progress are defined to the software systems of the institutions. These buttons are as follows: a- Suggestions and Requests: The suggestion and request box of the registered institutions is opened with a separate button for each institution. These buttons are named as request module (5). b- Submitted: When suggestions and requests are transmitted to the system, the information that the box has been opened is reported by the central system as "transmitted" to the other party. c- Suggestions and Requests 2: Suggestions and requests are sent to the system by the institutions via the central server (1). In other words, the solutions in their own fields are sent to each institution in items. For example; For institution A, items 1 and 2, for institution B items 1, 2, 3, and 4 are conveyed to the relevant institution in the form of problem- solving headings. d- Worked topics (headings): As soon as one of the solution items is selected and delivered to the system by the institution (within the process path area of the institution), a red and yellow button lights up in that tab in the system. The colorings given here are for illustrative purposes and may vary. Since there are fields belonging to each institution on the software, each area reacts in itself. The path in the flow of this panel is the 'work items panel'. Here, Firm A may request Title 2 to be studied and Firm B to study Title 1. Here, the options to work with are decided. Within this phase, the required deadlines for working on the titles are also communicated to the front. e- Submitted 2: The works worked are forwarded to the institutions as a first-stage solution, and when the screen is displayed by the institution when it is delivered with the selected item, there is a yellow-red warning point in the system. The areas of the institutions that are members of the system are defined in the central system, and the areas where the institution is in contact with the central system are also defined in the institutions. f- The choice has been made: When the institution chooses the solutions that can be applied among the solutions sent by the system's suggestion module (7), a notification is sent again under the heading “The selection has been made” in the central system. However, the thing to note here is that while working on selected titles, different alternatives can also work under the heading. These alternatives support the topics (subject) they choose. g- Selected: The alternatives selected here contain issues that can be resolved in a short time and can be notified and suggested solutions in a short time. Since the alternatives are conveyed in more detail, the solution is selected in all aspects and the entire previous solution flow is also approved. In this case, the area belonging to the relevant institution turns completely green. Here, the application is started and the amount of time required by the system to solve the relevant problem, the longer it is in observation and follow-up. h- Telecommuting (via software): After the feedback from the institutions is automatically dropped into the system, when the institution experiences the repetition of the problem with the customer, the areas provided by the customers and the institutions in their own fields and with the member institutions are examined by the software included in the processor unit (6) and the big data reshaped according to the result. i- Submitted 3: As a result of the approval of the counterparty of these recommendations conveyed by the suggestion module (7) to the institution, they are shown as "3 Submitted " to the screen of that institution with a button that lights up in red and yellow. The soot area, which was previously green, turns into blue. This means that the solution to be presented to the institution is in a situation of adding something new. j- Pot and Results: Here, the steps for a new system are transparently transmitted to the institution with their main headings, that is, the main points and the data processed into the ladle are included as feedback in the results section. The two titles are in the same button, but since the deadline will be given according to the process of learning, execution and advancement in terms of the use of solutions integrated into the system and located in the crucible, the solutions applied and finalized are transferred to the "results" tab after a while. Information, where the results of the solutions are not efficient, can also be placed here. While the system itself transfers data here, it also has fields that the employees of the institution (customer relations officers) can enter manually. k- Open Data for Use: In case the software transferred to the pot is started to be implemented by the institution, the field belonging to the relevant institution in the system will be yellow and the institution starts to apply one of the last steps. In this case, the simulated study is implemented.

1- Big Pot: Every job that passes through the pot and results section and creates a long-term solution in the results section (every job provided with a new software or an integrated software) is in the big pot and here, without being separated under the name of the institutions, all institutions that are members of the system and It becomes a situation that can benefit. While storing all the steps in the system of the invention, the solutions found at the same time are also stored in the data storage unit (4).

The other things that should be included in the inventive system are as follows: Holding multi-institutional holdings under another heading, that is, under another field, in a separate area, the customer relations units of each institution are integrated into the system, as well as the customer relations units of the holding's institutions. The customer relations management of the institutions of the holding takes place in the system separately and gathered on a single server (1). At this point, with Big Data, multi-company holdings are integrated into the inventive system under one roof. Under a separate heading, links are provided as multi-institutional companies, just like those of other institutions. Since the sectors of these multi-institution companies will be separated from each other, each sector will have a field in the system within itself, but a system that is obliged to ensure that it works in integration with a single point in customer relations. Here, as above, special studies are carried out for institutions, but it is ensured that they are united on a common denominator, and it is acted from the top as if from a customer relations point.

The system of the invention has been developed to assist the operation of customer relations management and to provide control. In this system, communication between institutions, the formation of case law of the customer relations management association with big data, and the classification of companies that are members of the system are made. In the system subject to the invention, communication between institutions is provided through a computer-based central server (1) as follows: Automatic artificial intelligence support for the entire process, including mail traffic between organizations and customers, filled surveys, suggestions and requests, time deadlines for the production of the work or the service provided, contracts made, the date and time of the incoming suggestion or request, the time and date of the feedback and the processor unit (6) containing the Internet of Things (loT). In this process, the central server (1) is aware of all stages, and if the solutions offered to the customer do not work for the customer and the desired satisfactory feedback cannot be provided, a problem box related to that process warns the control unit (10) in the system. By this warning system, all stages before the last point reached are reached gradually. In this way, all data are completely separated from each other according to their locations and titles, and at the same time, institutions belonging to each sector are in their own fields with all their data in the system. It solves the problems with its customers in their fields and will be transferred to them as a solution process, whether the solution of that problem really works or not (although all infrastructures are provided in all aspects), whether it applies the standard and which paths it follows while applying it, despite satisfactory returns to customers, The examination process on whether or not a problem point has occurred is initiated by the control unit (10) controlled over the central server (1). At the end of the specified period, if the institution has resolved this problem with its customer after the completion of the examination process, the solutions that have been found and have been applied and approved are included in the data storage unit (4) with the expression 'BIG POT' provided by Big Data and the institutions that are members of the system. For solutions whose ownership is not known, when they experience the same type of problems, they can retrieve these data from the 'BIG POT', that is, the data storage unit (4). Since customer-originated problems or institution-based problems that continue to cause problems within the period defined by the system will not be resolved, solutions are developed again and an additional period defined by the system is given and is subject to examination during this additional period. If the problem is not resolved during this additional period, it is decided by the control unit (10), which includes the arbitration board included in the system. As a result of this decision, the institution has to impose penalty sanctions against its customers or customers. This is decided within the jurisprudence of the arbitration board. After this situation, institutions that continue to have problems with their customers cannot be integrated into the system. In other words, it means that none of the improvement steps of the institution have taken place. In this way, as this institution will be seen as an excess in the system with the thought that it will also harm the system, the institution is completely terminated after a period of 2 years determined by the system.

In the system subject to invention, the formation of computer-based big data and customer relations management association jurisprudence is as follows: The solutions offered by the institutions to the customers are the new jobs that the experts in the system work and enter the system and the customers put into practice. In this case, there may be an unfair dispute between institutions and their customers. The principle of transparency may have been tried to be damaged, or a party may have tried or suffered damage in any matter. For this reason, in a determined arrangement of the system, 2 people selected from among the members grouped by the classification unit (2) for each sector are appointed to the arbitration board. Among the members, persons who are also responsible for the arbitration board sign a contract within the system to become impartial and transparent decision-makers. Each appointed member of the arbitral tribunal will continue to serve for 5 years, and afterwards, the members of the arbitral tribunal who have been elected for the transfer of duty and who have properly carried out their responsibilities are elected unanimously. The arbitral tribunal becomes the decision-making authority as a result of measuring and evaluating the problems experienced by institutions and customers with the support of the state, and if the problematic party continues the problem (whoever causes a problem) that party pays a price. In addition to removing the member from the system, the amount paid can also be compensation paid to the material and moral party. These options can be increased and this is decided by the referee board voting on the system. Here, a deterrence policy is followed in accordance with international regulations. The purpose of the arbitral tribunal here is to try to prevent the registries of the parties to be blacklisted within the state. The party that does not comply with the decision of the Board is removed from the system membership and acts on its own to solve the problem. The classification unit (2) of the companies that are members of the inventive system is divided into groups by the classification unit (2) as follows: While the system approves the membership of the institutions, it measures how much they can be integrated into the system and decides on its approval. The measurement and evaluation criteria of the system are determined over some point in the system that should be in the system flow. It determines many point measurement and evaluation criteria such as software systems primarily used by institutions, training of customer relations officers who communicate with their customers, and the content and size of feedback from customers. The classification of institutions is made with the criteria taken into account when measuring the customer relations of the institutions, various recommendations are given to the institutions in order to provide efficiency, and the feasibility of guidance, guidance and enforcement is monitored. Due to the fact that every institution is different from each other, institutions apply different methods, policies and procedures. For this reason, the system subject to invention provides the standard in customer relations units, and carries the institution to a further point in every problem they encounter against their customers or in the demands from customers. Thus, the system subject to the invention has implemented a step-by-step improvement policy for each institution. Therefore, the invention makes evaluations within different suggestions and different directions, different applications and different criteria for each institution with artificial intelligence techniques. These evaluations allow institutions to move forward from the classroom they are located in. The path taken by the institutions is taken into consideration and if the institutions that the system pioneers cannot provide the improvement step in the improvement process determined for each institution, they are dismissed from membership.

In the system of the invention, Big Data and artificial intelligence records the graphical scale related to improvement or going back for each institution. The members of the arbitration committee forming the control unit (10) impose sanctions on the institution or its customers upon processing the mathematical findings of artificial intelligence, as well as measuring and evaluating these situations with humanoid factors and including them in the data. These sanctions are also conveyed to the institution's own field under the title of "penal sanctions" with the help of artificial intelligence over the system. The return comes to the system as "in response to the sanction" with a purple warning in the area belonging to the institution. After this stage, the continuation or non-existence of the institution's membership is carried out by the decision of both the arbitration board and the software experts in the system. Such problems and cases that have to be solved with the help of artificial intelligence with the jurisprudence will also be included under the title of 'Black Box' in the system, and the institutions should use the keywords about what kind of problems cause trouble to search buttons and what kind of problems create an irreversible exclusion at the end point. When they write, there are causes and problems without institutions. Here, in fact, there are irreversible mistakes that institutions make while trying to provide solutions. This, of course, does not set a precedent. That is, the classification and class decline or progression of institutions are extremely important.

In an arrangement of the system subject to the invention, there are improvements regarding exam and recruitment. There are no job applications with a resume (CV). Software engineers and software specialists are put through a great test of mathematical ability and intelligence. Each year, 50 people from the relevant department graduates or experts who are interested in this field attend the trainings that last for 1 year (these trainings are theoretical and practical trainings that explain the system in general terms and the operation processes of the system are excluded). Participation of 50 people is the first to apply and those who will fill 50. Then, at the end of each year, these 50 people have exams prepared by using the data obtained as a result of technical and graphical calculations prepared by "Big Data". The data processed in Big Data is connected to each other with the help of artificial intelligence in the terms of entry to the system subject to the invention, processing, separation, sharing, application, continuity, feedback with the help of artificial intelligence and connecting to each sector separately by creating an additional system to the above system (not segregated for institutions) It takes place under the title of 'Big Data Association and Processable Data'. The above headings are collected under the title of 'Big Data Union and Processable Data'. Here, all data are filtered and collected in another crucible as "Question What- Answer What". The questions and answers here constitute the exam questions and answers for 50 people at the end of the training. In the score scale, 5 people who give correct answers to at least 70 out of 100 questions after a 100-question exam are entitled to work as software experts in the system. For example, if 2 people get 70 points, the system prepares a more difficult special question for 2 people and these questions are sent to the candidates. Big Data filters and prepares questions in its own right. Each year, 5 software experts take their place in the system and the result of the exam falls on the connection area sent to the examiners over the Big Data of the system and they are asked to check the area 1 week after the exam. The number of wrong and correct answers they entered and given to the exam questions are also shown on their screens.