Informatization consultation analysis system for intelligent distribution

Abstract

The invention discloses an intelligent distribution informatization consultation analysis system, and belongs to the technical field of data analysis. The system comprises the following steps: S1, a data acquisition module acquires various data required by the consultation analysis system in an operation process, and stores the data in a data storage module; and S2, the questions needing to be consulted are submitted to a consultation analysis system through a consultation submitting module. When the consultation teams are intelligently allocated according to the allocation recommendation index of each team, the consultation team with the highest allocation recommendation index for the current consultation type problem is intelligently allocated to perform consultation service on the current consultation problem, so that the current most suitable consultation team can be intelligently allocated to perform consultation service for consultants; through multi-data comprehensive analysis, unreasonable distribution caused by single data analysis or dependence on artificial experience is avoided.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and in particular to an information-based consulting analysis system for intelligent allocation. Background Art

[0002] With the rapid development of information technology, the volume of various consulting services has increased sharply. Traditional consulting allocation methods often rely on manual experience and are difficult to efficiently and accurately allocate consulting tasks to the most suitable consultants, resulting in low consulting processing efficiency and low customer satisfaction. Moreover, there is a lack of quantitative evaluation of the allocation effect, and it is impossible to continuously optimize the allocation strategy. Therefore, there is an urgent need for an information-based system that can achieve intelligent allocation and deeply analyze the allocation effect. Summary of the Invention

[0003] Object of the Invention: The object of the present invention is to provide an information-based consulting analysis system for intelligent allocation, which can solve the problem that traditional consulting allocation methods are difficult to efficiently and accurately allocate consulting tasks to the most suitable consultants.

[0004] Technical Solution: To solve the above technical problems, according to one aspect of the present invention, more specifically, it is an information-based consulting analysis system for intelligent allocation, and the system includes the following steps: S1. The data acquisition module collects various data required during the operation of the consulting analysis system and stores them in the data storage module; S2. The consulting submission module submits the questions to be consulted to the consulting analysis system; S3. The analysis and processing module obtains the total number of current consulting type customers served by each team from the storage module, the number of satisfied customers after the team's consulting service, the number of customers with effective feedback from the team, the duration of each current consulting type consulting service of the team, and the duration of each such type of consulting service of all consulting teams, and comprehensively analyzes the above data to obtain the allocation recommendation index of the team for the current consulting type problem; S4. The intelligent allocation module receives the allocation recommendation index of each team for the current consulting type problem analyzed and processed by the analysis and processing module, and intelligently allocates consulting teams according to the allocation recommendation index of each team; S5. Conduct consulting communication through the consulting communication module, and evaluate and feedback on this consulting communication through the evaluation feedback module; S6. The analysis and processing module obtains the response duration of each consultation, the service duration of each consultation, and the daily consultation duration of each consulting team from the storage module, and comprehensively analyzes the above data to obtain the intelligent allocation evaluation index of the consulting analysis system; S7. The display reminder module displays the intelligent allocation evaluation index of the consultation analysis system obtained by the analysis and processing module, sets the threshold of the intelligent allocation evaluation index of the consultation analysis system, and gives a warning reminder according to the comparison result between the intelligent allocation evaluation index of the consultation analysis system and the set threshold of the intelligent allocation evaluation index of the consultation analysis system.

[0005] Furthermore, when the evaluation feedback module conducts an evaluation, users who have been served by each team's consultation can give evaluations of satisfied, dissatisfied, effective, ineffective, and no longer using the consultation team.

[0006] Furthermore, when the analysis and processing module conducts analysis and processing, it will obtain the total number of current consultation type customers served by each team, the number of customers satisfied after the team's consultation service, the number of customers with effective feedback from the team, the duration of each current consultation type consultation service of the team, and the duration of each such type of consultation service of all consultation teams, and comprehensively analyze the above data to obtain the allocation recommendation index of the team for the current consultation type problem:

[0007] Among them, is the allocation recommendation index of the team for the current consultation type problem, is the total number of customers served by the team, is the number of customers satisfied after the team's consultation service, is the number of customers with effective feedback from the team, is the duration of each current consultation type consultation service of the team, is the duration of each such type of consultation service of all consultation teams, is the evaluation score given by the current consultation customer to the team, with a value of 0 or 1, and ML is the busyness score of the team, with a value of 0 or 1.

[0008] Furthermore, when the evaluation score is given, when the team is evaluated by the current consultation customer as no longer using the consultation team, takes a value of 1. When the team is not evaluated by the current consultation customer or the current consultation customer's evaluation of the team is other than no longer using the consultation team, takes a value of 0; when the busyness score is given, when the team is providing consultation services for other customers, ML takes a value of 1, and when the team is not providing consultation services for other customers, ML takes a value of 0.

[0009] Furthermore, when the intelligent allocation module intelligently allocates a consultation team according to the allocation recommendation index of each team, it will intelligently allocate the consultation team with the highest allocation recommendation index of the team for the current consultation type problem to provide consultation services for the current consultation problem.

[0010] Furthermore, when performing analysis and processing, the analysis and processing module obtains the response time of each consultation, the service time of each consultation, and the consultation time of each consultation team per day, and obtains the intelligent allocation evaluation index of the consultation analysis system through comprehensive analysis of the above data:

[0011] Among them, is the intelligent allocation evaluation index of the consultation analysis system, k is a constant with a value of 0.04, and is is the response time of each consultation, s is the total number of consultations in the consultation analysis system, is the processing time of each consultation, is a constant with a value of 120, is a constant with a value of 20, is the processing duration of each team per day, is the total number of consultation teams in the consultation system, is the number of days of consultation service.

[0012] Furthermore, the intelligent allocation evaluation index of the consultation analysis system can be used to evaluate the intelligent allocation effect of the consultation analysis system. The higher the intelligent allocation evaluation index of the consultation analysis system, the better the intelligent allocation effect of the consultation analysis system, and vice versa, the worse the intelligent allocation effect of the consultation analysis system.

[0013] Furthermore, when the display and reminder module gives a warning reminder, when the intelligent allocation evaluation index of the consultation analysis system is greater than the threshold of the set intelligent allocation evaluation index of the consultation analysis system, no warning reminder is given. Otherwise, a warning reminder is given to optimize and adjust the allocation logic.

[0014] Beneficial effects: By obtaining the total number of current consulting type customers served by each team, the number of satisfied customers after the team's consulting service, the number of customers with effective feedback for the team, the duration of each current consulting type consulting service provided by the team, and the duration of each such type of consulting service provided by all consulting teams, and comprehensively analyzing the above data to obtain the allocation recommendation index of the team for current consulting type problems. When intelligently allocating consulting teams based on the allocation recommendation index of each team, the consulting team with the highest allocation recommendation index for the current consulting type problems of the team will be intelligently allocated to provide consulting services for the current consulting problem. It can achieve intelligent allocation to the most suitable current consulting team to provide consulting services for the inquirer. Through comprehensive analysis of multiple data, it can avoid unreasonable allocation caused by single data analysis or relying on manual experience. By obtaining the response duration of each consultation, the service duration of each consultation, and the daily consultation duration of each consulting team, and comprehensively analyzing the above data to obtain the intelligent allocation evaluation index of the consulting analysis system. The higher the intelligent allocation evaluation index of the consulting analysis system, the better the intelligent allocation effect of the consulting analysis system; conversely, the worse the intelligent allocation effect of the consulting analysis system. It can real-time grasp the current intelligent allocation effect of the consulting analysis system. At the same time, when the intelligent allocation evaluation index of the consulting analysis system is not greater than the threshold value of the set intelligent allocation evaluation index of the consulting analysis system, a warning reminder will be given to optimize and adjust the allocation logic, and it can timely discover the problems existing in the intelligent allocation of the consulting analysis system and give a warning reminder in a timely manner. Description of the Drawings

[0015] Figure 1 It is a schematic diagram of the system principle. Detailed Implementation Manner

[0016] To make the technical solutions of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0017] Embodiment 1 First, the data acquisition module collects various data required during the operation of the consulting analysis system, and the data storage module stores and manages the various data required during the operation of the consulting analysis system collected by the data acquisition module and the evaluation data of the evaluation feedback module.

[0018] After the inquirer submits the problem to be consulted to the consulting analysis system through the consulting submission module, the analysis and processing module obtains the total number of current consulting type customers served by each team, the number of satisfied customers after the team's consulting service, the number of customers with effective feedback for the team, the duration of each current consulting type consulting service provided by the team, and the duration of each such type of consulting service provided by all consulting teams, and comprehensively analyzes the above data to obtain the allocation recommendation index of the team for current consulting type problems:

[0019] Among them, is the allocation recommendation index of the team for questions of the current consultation type, is the total number of customers served by the team, is the number of customers satisfied after the team's consultation service, is the number of customers with effective feedback from the team, is the duration of each consultation service of the current consultation type by the team, is the duration of each consultation service of this type by all consultation teams, is the score assigned by the current consulting customer to the team, with a value of 0 or 1, and ML is the busyness score of the team, with a value of 0 or 1. When the team is evaluated by the current consulting customer as no longer using the consulting team, it takes a value of 1. When the team is not evaluated by the current consulting customer or the evaluation of the current consulting customer for the team is other evaluations other than no longer using the consulting team, it takes a value of 0; when assigning the busyness score, when the team is providing consulting services for other customers, ML takes a value of 1, and conversely, when the team is not providing consulting services for other customers, ML takes a value of 0. Thus, the consulting team with the highest allocation recommendation index for questions of the current consultation type is intelligently assigned to provide consulting services for the current consultation problem. Through comprehensive analysis of multiple data, it avoids unreasonable allocation caused by single data analysis or relying on manual experience.

[0020] And the analysis and processing module will obtain the response duration of each consultation, the service duration of each consultation, and the daily consultation duration of each consultation team, and obtain the intelligent allocation evaluation index of the consultation analysis system through comprehensive analysis of the above data:

[0021] Among them, is the intelligent allocation evaluation index of the consultation analysis system, is the response time of each consultation, s is the total number of consultations of the consultation analysis system, is the processing time of each consultation, is a constant with a value of 120, is a constant with a value of 20, is the daily processing duration of each team, is the total number of consultation teams in the consultation system, The number of days for consulting services, so as to evaluate the intelligent allocation effect of the consulting analysis system according to the intelligent allocation evaluation index of the consulting analysis system. The higher the intelligent allocation evaluation index of the consulting analysis system, the better the intelligent allocation effect of the consulting analysis system. On the contrary, it means that the intelligent allocation effect of the consulting analysis system is worse. At the same time, when the intelligent allocation evaluation index of the consulting analysis system is not greater than the threshold value of the preset intelligent allocation evaluation index of the consulting analysis system, a warning reminder is carried out through the warning reminder module to optimize and adjust the allocation logic, and the problems existing in the intelligent allocation of the consulting analysis system can be discovered in time and a warning reminder can be given in time.

[0022] Example 2 When obtaining the allocation recommendation index of the team for the current consulting type problem through comprehensive analysis, there is = 120, = 135, = 149 = 25, = 35, = 0, = 0, then there is:

[0023] At this time, the allocation recommendation index of the team for the current consulting type problem is compared with the allocation recommendation index of other teams for the current consulting type problem. If the allocation recommendation index of the team for the current consulting type problem is the largest among the allocation recommendation indexes of all teams for the current consulting type problem, then the team is assigned to the current consultant. Otherwise, the team with the largest allocation recommendation index among the allocation recommendation indexes of other teams for the current consulting type problem is assigned to the current consultant.

[0024] Example 3 When calculating the intelligent allocation evaluation index of the consulting analysis system, there is = 0.67, = 45, = 120, = 22.8, then there is;

[0025] At this time, the intelligent allocation evaluation index of the consulting analysis system is compared with the preset threshold value of the intelligent allocation evaluation index of the consulting analysis system When it is the case, no warning reminder is carried out; when it is the case, a warning reminder is carried out to optimize and adjust the allocation logic.

[0026] The above-described embodiments merely represent several implementation manners of the present invention. The description thereof is relatively specific and detailed, but it should not be construed as a limitation to the scope of the patent for the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all fall within the protection scope of the present invention. Therefore, the protection scope of the patent for the present invention shall be subject to the appended claims.

Claims

1. An information-based consulting and analysis system with intelligent allocation, characterized in that, The system includes the following steps: S1. The data acquisition module collects various data required during the operation of the consultation analysis system and stores them in the data storage module; S2. The consultation submission module submits the questions to be consulted to the consultation analysis system; S3. The analysis and processing module obtains the total number of current consultation type customers served by each team, the number of satisfied customers after the team's consultation service, the number of customers with effective feedback from the team, the duration of each current consultation type consultation service of the team, and the duration of each such consultation service of all consultation teams from the storage module, and comprehensively analyzes the above data to obtain the allocation recommendation index of the team for the current consultation type questions; S4. The intelligent allocation module receives the allocation recommendation index of each team for the current consultation type questions obtained by the analysis and processing module, and intelligently allocates the consultation team according to the allocation recommendation index of each team; S5. Consultation communication is carried out through the consultation communication module, and evaluation and feedback on this consultation communication are carried out through the evaluation feedback module; S6. The analysis and processing module obtains the response duration of each consultation, the service duration of each consultation, and the consultation duration of each consultation team per day from the storage module, and comprehensively analyzes the above data to obtain the intelligent allocation evaluation index of the consultation analysis system; S7. The display and reminder module displays the intelligent allocation evaluation index of the consultation analysis system obtained by the analysis and processing module, sets the threshold of the intelligent allocation evaluation index of the consultation analysis system, and gives a warning reminder according to the comparison result of the intelligent allocation evaluation index of the consultation analysis system and the set threshold of the intelligent allocation evaluation index of the consultation analysis system.

2. The information-based consulting and analysis system with intelligent allocation according to claim 1, characterized in that: When the evaluation feedback module conducts evaluation, users who have received consultation services from each team can give evaluations of satisfied, dissatisfied, effective, ineffective, and no longer using the consultation team.

3. An information-based consulting and analysis system with intelligent allocation according to claim 2, characterized in that: When the analysis and processing module conducts analysis and processing, it will obtain the total number of current consultation type customers served by each team, the number of satisfied customers after the team's consultation service, the number of customers with effective feedback from the team, the duration of each current consultation type consultation service of the team, and the duration of each such consultation service of all consultation teams, and comprehensively analyze the above data to obtain the allocation recommendation index of the team for the current consultation type questions: ； Among them, is the allocation recommendation index of the team for questions of the current consultation type, is the total number of customers served by the team, is the number of customers satisfied after the team's consultation service, is the number of customers with effective feedback from the team, is the duration of each consultation service of the current consultation type by the team, is the duration of each consultation service of this type by all consultation teams, is the score assigned by the current consulting customer to the team, with its value being 0 or 1, and ML is the busyness score assigned to the team, with its value being 0 or 1.

4. An information-based consulting and analysis system with intelligent allocation according to claim 3, characterized in that: When the evaluation score is assigned, when the team is evaluated by the current consulting client as no longer using the consulting team, the value is 1. When the team is not evaluated by the current consulting client or the current consulting client's evaluation of the team is other than no longer using the consulting team, the value is 0; when the busy score is assigned, when the team is providing consulting services for other clients, ML takes the value of 1, and when the team is not providing consulting services for other clients, ML takes the value of 0.

5. An information-based consulting and analysis system with intelligent allocation according to claim 4, characterized in that: When the intelligent allocation module intelligently allocates the consultation team according to the allocation recommendation index of each team, it will intelligently allocate the consultation team with the highest allocation recommendation index of the team for the current consultation type questions to provide consultation services for the current consultation questions.

6. An information-based consulting and analysis system with intelligent allocation according to claim 1, characterized in that: When the analysis and processing module conducts analysis and processing, it will obtain the response duration of each consultation, the service duration of each consultation, and the consultation duration of each consultation team per day, and comprehensively analyze the above data to obtain the intelligent allocation evaluation index of the consultation analysis system: ； Among them, is the intelligent allocation evaluation index of the consultation analysis system, k is a constant with a value of 0.04, is the response time for each consultation, s is the total number of consultations of the consultation analysis system, is the processing time for each consultation, is a constant with a value of 120, is a constant with a value of 20, is the processing duration per day for each team, is the total number of consultation teams in the consultation system, is the number of days of the consultation service.

7. An information-based consulting and analysis system with intelligent allocation according to claim 6, characterized in that: The intelligent allocation evaluation index of the consultation analysis system can be used to evaluate the intelligent allocation effect of the consultation analysis system. The higher the intelligent allocation evaluation index of the consultation analysis system, the better the intelligent allocation effect of the consultation analysis system, and vice versa.

8. An information-based consulting and analysis system with intelligent allocation according to claim 6, characterized in that: When the display reminder module gives a warning reminder, if the intelligent allocation evaluation index of the consultation analysis system is greater than the threshold value of the intelligent allocation evaluation index set for the consultation analysis system, no warning reminder will be given. Otherwise, a warning reminder will be given to optimize and adjust the allocation logic.

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