CN112163874A - After-sale service system for e-commerce platform - Google Patents
After-sale service system for e-commerce platform Download PDFInfo
- Publication number
- CN112163874A CN112163874A CN202011195990.0A CN202011195990A CN112163874A CN 112163874 A CN112163874 A CN 112163874A CN 202011195990 A CN202011195990 A CN 202011195990A CN 112163874 A CN112163874 A CN 112163874A
- Authority
- CN
- China
- Prior art keywords
- customer
- commodity
- service
- store
- marking
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/01—Customer relationship services
- G06Q30/015—Providing customer assistance, e.g. assisting a customer within a business location or via helpdesk
- G06Q30/016—After-sales
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/101—Collaborative creation, e.g. joint development of products or services
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/20—Administration of product repair or maintenance
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Tourism & Hospitality (AREA)
- Quality & Reliability (AREA)
- Development Economics (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Game Theory and Decision Science (AREA)
- Educational Administration (AREA)
- Data Mining & Analysis (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses an after-sale service system for an e-commerce platform, which relates to the technical field of after-sale service of the e-commerce platform and solves the technical problems that in the prior art, a closest store cannot be reasonably selected for a customer, the after-sale service time is prolonged, the cost is increased, and the working efficiency is reduced; the store address and the mobile phone number of the customer service staff of the store are sent to the mobile phone terminal of the customer, the customer receives the store address and mails the commodity to the selected store in an express delivery mode, the store closest to the customer is selected, cost is reduced, meanwhile work efficiency is improved, and after-sale waiting time of the customer is reduced.
Description
Technical Field
The invention relates to the technical field of after-sale service of an e-commerce platform, in particular to an after-sale service system for the e-commerce platform.
Background
Along with the continuous increase of the accumulated sales volume of the electric commercial product market, the after-sale claim data volume is also continuously increased, the problem points of the product quality and the reliability of parts in mass after-sale claim data are visually and quickly formed and input, the after-sale part quality statistical analysis is manually performed, the workload is high, the efficiency is not high, and professional quality evaluation such as fault parts PPM is difficult to perform. The subsequent old piece return management, claim evaluation, claim management and the like of the after-sale quality information are manually expanded, and the improvement of the claim rate is hindered in management. After-sales service is the most important link after sales. The goodness of the after-market service can affect the satisfaction of the consumer. When purchasing, the customer is relieved of the forms of doubt and sway in terms of regulations such as warranty of the product and after-sales service, and the purchase of the product is decided. The high-quality after-sale service can be calculated as a product of brand economy, in the society with intense market competition, with the improvement of the right-maintaining consciousness of consumers and the change of consumption concept, the consumers do not pay attention to the product per se any more, and under the condition that the quality and the performance of similar products are similar, the companies with the high-quality after-sale service are more willing to be selected.
However, in the prior art, the nearest store cannot be reasonably selected for the customer, the after-sales service time is prolonged, the cost is increased, and the working efficiency is reduced.
Disclosure of Invention
The invention aims to provide an after-sales service system for an e-commerce platform, which analyzes customer service data through a customer service distribution unit, reasonably distributes the customer service data to obtain the customer service data, obtains a service coefficient Qk of a customer service staff through a formula, judges the service quality of the customer service staff if the service coefficient Qk of the customer service staff is more than or equal to a service coefficient threshold value, marks the customer service staff as a priority arrangement staff, and then sends the name of the priority arrangement staff to the after-sales service platform; if the service coefficient Qk of the customer service staff is smaller than the service coefficient threshold value, judging that the service quality of the customer service staff is poor, marking the customer service staff as a person to be learned, and then sending the person to be learned to an after-sales service platform; the customer service staff are divided according to the capacity, the customer service staff with strong capacity are arranged preferentially, and the working efficiency and quality are improved.
The purpose of the invention can be realized by the following technical scheme:
an after-sale service system for an e-commerce platform comprises a customer analysis unit, a store selection unit, a commodity damage assessment unit, a customer service distribution unit, an after-sale service platform, a registration unit and a database;
the store selection unit is used for selecting a proper store and recycling problem commodities fed back by the customer, and the specific selection and recycling process is as follows:
SS 1: the method comprises the steps that a customer sends an after-sale service application to an after-sale service platform through a mobile phone terminal, the after-sale service platform receives the after-sale service application of the customer, then obtains time for the customer to purchase a commodity, compares the time for the customer to purchase the commodity with the current time, obtains duration for the customer to purchase the commodity, marks the duration for the customer to purchase the commodity as purchase duration, compares the purchase duration with the quality guarantee period of the commodity, marks the commodity as a quality guarantee commodity if the purchase duration is within the quality guarantee period range, and marks the commodity as a non-quality guarantee commodity if the purchase duration is not within the quality guarantee period range;
SS 2: the after-sale service platform generates a store selection signal and sends the store selection signal to a store selection unit, the store selection unit acquires a receiving address of a customer, acquires store addresses around the receiving address, screens out the store address closest to the receiving address and marks the store as a selected store;
SS 3: the method comprises the steps that a store address and a mobile phone number of a customer service person of the store are sent to a mobile phone terminal of a customer, the customer mails a commodity to a selected store in an express way after receiving the store address, and the customer pays a mailing cost;
SS 4: and the selected store generates a commodity loss assessment signal after receiving the commodity, and sends the commodity loss assessment signal to the commodity loss assessment unit.
Further, the registration login unit is used for submitting customer information and customer service staff information through mobile phone terminals for registration, sending the customer information and the customer service staff who are successfully registered to the database for storage, generating a login account number by the after-sales service platform and sending the login account number to the mobile phone terminal of the customer, the customer activating the login account number by sending a verification code through the mobile phone terminal and sending the time for activating the account number to the database for storage, the customer information comprises the name, the age, the occupation and the mobile phone number for real-name authentication of the customer, and the customer service staff information comprises the name, the age, the occupation and the mobile phone number for real-name authentication of the customer.
Further, the customer analysis unit is configured to analyze customer data, sort an after-sales processing sequence of the customer, where the customer data includes a number of times that the customer purchases a commodity within one month, a total price of the purchased commodity, and a number of times that the customer participates in a review, and mark the customer as i, i ═ 1, 2.
Step one, acquiring the times of purchasing commodities by a customer in one month, and marking the times of purchasing commodities by the customer in one month as Ci;
step two, acquiring the total price of the commodities purchased by the customer in one month, and marking the total price of the commodities purchased by the customer in one month as Zi;
thirdly, obtaining the number of times that the client participates in the comment within one month, and marking the number of times that the client participates in the comment within one month as Pi;
step four, passing through a formula
Obtaining a client active coefficient Xi, wherein c1, c2 and c3 are all preset proportional coefficients, and c1 is larger than c2 and c3 is larger than 0;
step five, acquiring the time of activating the login account by the client in the database, comparing the time of activating the login account with the current time of the system, acquiring the registration time of the client, and marking the registration time of the client as Si;
step six, obtaining an analysis coefficient Ki of a customer through a formula Ki ═ beta (Xi × v1+ Si × v2), wherein v1 and v2 are preset proportional coefficients, and v1 is more than v 2;
and seventhly, marking the customers for after-sale service as after-sale service customers, enabling the after-sale service customers to be in one-to-one correspondence with the analysis coefficients, then sequencing the after-sale service customers according to the sequence of the analysis coefficients from large to small, and carrying out after-sale service processing on the after-sale service customers according to the sequence of the sequencing.
Further, the customer service distribution unit is configured to analyze customer service data and reasonably distribute customers, where the customer service data includes a ratio of the number of times of complaints to the number of times of good comments of customer service staff within one month, a total number of after-sale services of customers completed within one month, and a frequency of complaints within one month, and the customer service staff is marked as k, where k is 1, 2.
S1: acquiring the ratio of the number of complaints received by the customer service personnel within one month to the number of good comments, and marking the ratio of the number of complaints received by the customer service personnel within one month to the number of good comments as Bk;
s2: acquiring the total number of the customer after-sale services completed by the customer service staff within one month, and marking the total number of the customer after-sale services completed by the customer service staff within one month as Sk;
s3: acquiring the frequency of complaining the customer service personnel within one month, and marking the frequency of complaining the customer service personnel within one month as Pk;
s4: by the formula
Acquiring a service coefficient Qk of a customer service staff, wherein a1, a2 and a3 are all preset proportionality coefficients, and a1 is greater than a2 is greater than a3 is greater than 0;
s5: comparing the service coefficient Qk of the customer service personnel with a service coefficient threshold value:
if the service coefficient Qk of the customer service staff is larger than or equal to the service coefficient threshold, judging that the service quality of the customer service staff is high, marking the customer service staff as a priority arrangement staff, and then sending the name of the priority arrangement staff to an after-sales service platform;
and if the service coefficient Qk of the customer service staff is less than the service coefficient threshold value, judging that the service quality of the customer service staff is poor, marking the customer service staff as a person to be learned, and then sending the person to be learned to the after-sales service platform.
Further, the commodity damage assessment unit is used for analyzing commodity information and judging damage of the commodity, the commodity information comprises quality data, wear data and component data, the quality data is the sum of the weight of components inside the commodity and the weight of a shell of the commodity, the wear data is the scratch number of the outer surface of the commodity, the component data is the difference value between the hardness of the outer surface of a commodity component and the standard hardness of the outer surface of a component material, the commodity is marked as o, o is 1, 2, and w is a non-zero positive integer, and the specific analysis and judgment process is as follows:
l1: acquiring the sum of the weight of the internal elements of the commodity and the weight of the outer shell of the commodity, and marking the sum of the weight of the internal elements of the commodity and the weight of the outer shell of the commodity as Hw;
l2: acquiring the number of scratches on the outer surface of the commodity, and marking the number of scratches on the outer surface of the commodity as Sw;
l3: acquiring the difference value between the outer surface hardness of the commodity part and the outer surface standard hardness of the part material, and marking the difference value between the outer surface hardness of the commodity part and the outer surface standard hardness of the part material as Yw;
l4: by the formula
Obtaining a loss assessment coefficient Xw of a commodity, wherein s1, s2 and s3 are all preset proportional coefficients, and s1 is larger than s2 is larger than s3 is larger than 0;
l5: comparing the damage assessment coefficient Xw of the commodity with a damage assessment coefficient threshold value:
if the loss assessment coefficient Xw of the commodity is not less than the loss assessment coefficient threshold value, judging that the commodity is damaged, generating an artificial damage signal and sending the artificial damage signal to an after-sales service platform, if the commodity is a quality guarantee commodity, the after-sales service platform subsidies postage to a mobile phone terminal of a customer and returns the commodity to the customer, meanwhile, marking the customer as an abnormal customer, and if the commodity is a non-quality guarantee commodity, returning the commodity to the customer and marking the customer as a problem customer;
if the damage assessment coefficient Xw of the commodity is less than the damage assessment coefficient threshold value, the commodity is judged to be naturally damaged, a natural damage signal is generated and sent to an after-sales service platform, if the commodity is a quality assurance commodity, the after-sales service platform subsidies postage to a mobile phone terminal of a client and posts a new commodity to the client, if the commodity is a non-quality assurance commodity, the commodity is maintained, a maintenance fee list is sent to the client, and if the client agrees to maintain, the commodity is maintained and the commodity after maintenance is posted to the client.
Compared with the prior art, the invention has the beneficial effects that:
1. in the invention, a proper store is selected through a store selection unit, problem commodities fed back by a customer are recovered, the customer sends an after-sale service application to an after-sale service platform through a mobile phone terminal, the after-sale service platform receives the after-sale service application of the customer, then obtains the time for the customer to purchase the commodities, compares the time for purchasing the commodities with the current time, obtains the time for the customer to purchase the commodities, marks the time for purchasing the commodities as purchase time, compares the purchase time with the warranty period of the commodities, marks the commodities as warranty commodities if the purchase time is in the warranty period range, and marks the commodities as non-warranty commodities if the purchase time is not in the warranty period range; the after-sale service platform generates a store selection signal and sends the store selection signal to a store selection unit, the store selection unit acquires a receiving address of a customer, acquires store addresses around the receiving address, screens out the store address closest to the receiving address and marks the store as a selected store; the method comprises the steps that a store address and a mobile phone number of a customer service person of the store are sent to a mobile phone terminal of a customer, the customer mails a commodity to a selected store in an express way after receiving the store address, and the customer pays a mailing cost; a selected store generates a commodity loss assessment signal after receiving the commodity and sends the commodity loss assessment signal to a commodity loss assessment unit; the nearest store is selected for the customer, so that the cost is reduced, the working efficiency is improved, and the after-sale waiting time of the customer is reduced;
2. in the invention, customer service data are analyzed by a customer service distribution unit, customers are reasonably distributed, the ratio of the number of complaints received by customer service staff within one month to the number of commented complaints, the total number of after-sale services of the customers completed within one month by the customer service staff and the frequency of complaints received by the customer service staff within one month are obtained, the service coefficient Qk of the customer service staff is obtained by a formula, if the service coefficient Qk of the customer service staff is more than or equal to the threshold value of the service coefficient, the service quality of the customer service staff is judged, the customer service staff is marked as a priority arrangement staff, and then the name of the priority arrangement staff is sent to an after-sale service platform; if the service coefficient Qk of the customer service staff is smaller than the service coefficient threshold value, judging that the service quality of the customer service staff is poor, marking the customer service staff as a person to be learned, and then sending the person to be learned to an after-sales service platform; the customer service staff are divided according to the capacity, the customer service staff with strong capacity are arranged preferentially, and the working efficiency and quality are improved.
Drawings
In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
Fig. 1 is a schematic block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, an after-sale service system for e-commerce platform includes a customer analysis unit, a store selection unit, a commodity damage assessment unit, a customer service distribution unit, an after-sale service platform, a registration unit and a database;
the registration login unit is used for submitting client information and customer service staff information through a mobile phone terminal for registration, sending the client information and the customer service staff who are successfully registered to a database for storage, generating a login account number by an after-sales service platform and sending the login account number to a mobile phone terminal of a client, activating the login account number by the client through a verification code sent by the mobile phone terminal, sending the time for activating the account number to the database for storage, wherein the client information comprises the name, the age, the occupation and the mobile phone number for authenticating the real name of the client, and the customer service staff information comprises the name, the age, the occupation and the mobile phone number for authenticating the real name of the client;
the customer analysis unit is used for analyzing customer data and sequencing an after-sale processing sequence of a customer, wherein the customer data comprises the times of purchasing commodities, the total price of purchasing commodities and the times of participating in comments of the customer within one month, the customer is marked as i, i is 1, 2, and.
Step one, acquiring the times of purchasing commodities by a customer in one month, and marking the times of purchasing commodities by the customer in one month as Ci;
step two, acquiring the total price of the commodities purchased by the customer in one month, and marking the total price of the commodities purchased by the customer in one month as Zi;
thirdly, obtaining the number of times that the client participates in the comment within one month, and marking the number of times that the client participates in the comment within one month as Pi;
step four, passing through a formula
Obtaining a client active coefficient Xi, wherein c1, c2 and c3 are all preset proportional coefficients, and c1 is larger than c2 and c3 is larger than 0;
step five, acquiring the time of activating the login account by the client in the database, comparing the time of activating the login account with the current time of the system, acquiring the registration time of the client, and marking the registration time of the client as Si;
step six, obtaining an analysis coefficient Ki of a customer through a formula Ki ═ beta (Xi × v1+ Si × v2), wherein v1 and v2 are preset proportional coefficients, and v1 is more than v 2;
marking the customers for after-sale service as after-sale service customers, corresponding the after-sale service customers to the analysis coefficients one by one, then sequencing the after-sale service customers according to the sequence of the analysis coefficients from large to small, and performing after-sale service processing on the after-sale service customers according to the sequence of the sequencing;
the customer service distribution unit is used for analyzing customer service data and reasonably distributing customers, the customer service data comprises the ratio of the number of times of complaints to the number of times of good comments of customer service staff within one month, the total number of after-sale services of the customers completed within one month and the frequency of complaints within one month, the customer service staff is marked as k, and k is 1, 2, a.
S1: acquiring the ratio of the number of complaints received by the customer service personnel within one month to the number of good comments, and marking the ratio of the number of complaints received by the customer service personnel within one month to the number of good comments as Bk;
s2: acquiring the total number of the customer after-sale services completed by the customer service staff within one month, and marking the total number of the customer after-sale services completed by the customer service staff within one month as Sk;
s3: acquiring the frequency of complaining the customer service personnel within one month, and marking the frequency of complaining the customer service personnel within one month as Pk;
s4: by the formula
Acquiring a service coefficient Qk of a customer service staff, wherein a1, a2 and a3 are all preset proportionality coefficients, and a1 is greater than a2 is greater than a3 is greater than 0;
s5: comparing the service coefficient Qk of the customer service personnel with a service coefficient threshold value:
if the service coefficient Qk of the customer service staff is larger than or equal to the service coefficient threshold, judging that the service quality of the customer service staff is high, marking the customer service staff as a priority arrangement staff, and then sending the name of the priority arrangement staff to an after-sales service platform;
if the service coefficient Qk of the customer service staff is smaller than the service coefficient threshold value, judging that the service quality of the customer service staff is poor, marking the customer service staff as a person to be learned, and then sending the person to be learned to an after-sales service platform;
the store selecting unit is used for selecting a proper store and recycling problem commodities fed back by the customer, and the specific selection recycling process is as follows:
SS 1: the method comprises the steps that a customer sends an after-sale service application to an after-sale service platform through a mobile phone terminal, the after-sale service platform receives the after-sale service application of the customer, then obtains time for the customer to purchase a commodity, compares the time for the customer to purchase the commodity with the current time, obtains duration for the customer to purchase the commodity, marks the duration for the customer to purchase the commodity as purchase duration, compares the purchase duration with the quality guarantee period of the commodity, marks the commodity as a quality guarantee commodity if the purchase duration is within the quality guarantee period range, and marks the commodity as a non-quality guarantee commodity if the purchase duration is not within the quality guarantee period range;
SS 2: the after-sale service platform generates a store selection signal and sends the store selection signal to a store selection unit, the store selection unit acquires a receiving address of a customer, acquires store addresses around the receiving address, screens out the store address closest to the receiving address and marks the store as a selected store;
SS 3: the method comprises the steps that a store address and a mobile phone number of a customer service person of the store are sent to a mobile phone terminal of a customer, the customer mails a commodity to a selected store in an express way after receiving the store address, and the customer pays a mailing cost;
SS 4: a selected store generates a commodity loss assessment signal after receiving the commodity and sends the commodity loss assessment signal to a commodity loss assessment unit;
the commodity damage assessment unit is used for analyzing commodity information and judging damage of the commodity, the commodity information comprises quality data, wear data and component data, the quality data are sum of weight of components inside the commodity and weight of a shell of the commodity, the wear data are scratch quantity of outer surfaces of the commodity, the component data are difference values of outer surface hardness of commodity parts and outer surface standard hardness of part materials, the commodity is marked to be o, o is 1, 2, a.
L1: acquiring the sum of the weight of the internal elements of the commodity and the weight of the outer shell of the commodity, and marking the sum of the weight of the internal elements of the commodity and the weight of the outer shell of the commodity as Hw;
l2: acquiring the number of scratches on the outer surface of the commodity, and marking the number of scratches on the outer surface of the commodity as Sw;
l3: acquiring the difference value between the outer surface hardness of the commodity part and the outer surface standard hardness of the part material, and marking the difference value between the outer surface hardness of the commodity part and the outer surface standard hardness of the part material as Yw;
l4: by the formula
Obtaining a loss assessment coefficient Xw of a commodity, wherein s1, s2 and s3 are all preset proportional coefficients, and s1 is larger than s2 is larger than s3 is larger than 0;
l5: comparing the damage assessment coefficient Xw of the commodity with a damage assessment coefficient threshold value:
if the loss assessment coefficient Xw of the commodity is not less than the loss assessment coefficient threshold value, judging that the commodity is damaged, generating an artificial damage signal and sending the artificial damage signal to an after-sales service platform, if the commodity is a quality guarantee commodity, the after-sales service platform subsidies postage to a mobile phone terminal of a customer and returns the commodity to the customer, meanwhile, marking the customer as an abnormal customer, and if the commodity is a non-quality guarantee commodity, returning the commodity to the customer and marking the customer as a problem customer;
if the damage assessment coefficient Xw of the commodity is less than the damage assessment coefficient threshold value, judging that the commodity is naturally damaged, generating a natural damage signal and sending the natural damage signal to an after-sales service platform, if the commodity is a quality assurance commodity, the after-sales service platform subsidies postage to a mobile phone terminal of a client and posts a new commodity to the client, if the commodity is a non-quality assurance commodity, maintaining the commodity and sending a maintenance fee list to the client, and if the client agrees to maintain, maintaining the commodity and posting the commodity after maintenance to the client;
the client identification unit is used for analyzing client marking data and dividing clients, the client marking data comprises frequency data and duration data, the frequency data is the sum of the times of marking the clients as abnormal clients and the times of marking the clients as problem clients, the duration data is the sum of the interval duration of marking the clients as abnormal clients and the interval duration of marking the clients as problem clients, and the specific analysis and division process is as follows:
LL 1: acquiring the sum of the times of marking the customer as an abnormal customer and the times of marking the customer as a problem customer, and marking the sum of the times of marking the customer as the abnormal customer and the times of marking the customer as the problem customer as CSi;
LL 2: acquiring the sum of the interval duration marked as the abnormal client and the interval duration marked as the problem client, and marking the sum of the interval duration marked as the abnormal client and the interval duration marked as the problem client as JGi;
LL 3: acquiring an abnormal coefficient FXi of a customer through a formula FXi-CSi × f1+ JGi × f2, wherein f1 and f2 are both preset proportional coefficients, and f1 > f2 > 0;
LL 4: comparing the anomaly coefficient FXi of the customer with an anomaly coefficient threshold:
if the abnormal coefficient FXi of the client is larger than or equal to the abnormal coefficient threshold, generating an abnormal signal and freezing a login account corresponding to the client;
if the customer's anomalous coefficient FXi < the anomalous coefficient threshold, a normal signal is generated and the customer is marked as a normal customer.
The working principle of the invention is as follows:
an after-sale service system for an e-commerce platform is characterized in that during work, a proper store is selected through a store selection unit, problem commodities fed back by a customer are recovered, the customer sends an after-sale service application to the after-sale service platform through a mobile phone terminal, the after-sale service platform receives the after-sale service application of the customer, then the time for the customer to purchase the commodities is obtained, the time for the customer to purchase the commodities is compared with the current time, the duration for the customer to purchase the commodities is obtained and marked as the purchase duration, the purchase duration is compared with the warranty period of the commodities, if the purchase duration is in the warranty period range, the commodities are marked as warranty commodities, and if the purchase duration is not in the warranty period range, the commodities are marked as non-warranty commodities; the after-sale service platform generates a store selection signal and sends the store selection signal to a store selection unit, the store selection unit acquires a receiving address of a customer, acquires store addresses around the receiving address, screens out the store address closest to the receiving address and marks the store as a selected store; the method comprises the steps that a store address and a mobile phone number of a customer service person of the store are sent to a mobile phone terminal of a customer, the customer mails a commodity to a selected store in an express way after receiving the store address, and the customer pays a mailing cost; and the selected store generates a commodity loss assessment signal after receiving the commodity, and sends the commodity loss assessment signal to the commodity loss assessment unit.
The above formulas are all calculated by taking the numerical value of the dimension, the formula is a formula which obtains the latest real situation by acquiring a large amount of data and performing software simulation, and the preset parameters in the formula are set by the technical personnel in the field according to the actual situation.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (5)
1. An after-sale service system for an e-commerce platform is characterized by comprising a customer analysis unit, a store selection unit, a commodity damage assessment unit, a customer service distribution unit, an after-sale service platform, a registration unit and a database;
the store selection unit is used for selecting a proper store and recycling problem commodities fed back by the customer, and the specific selection and recycling process is as follows:
SS 1: the method comprises the steps that a customer sends an after-sale service application to an after-sale service platform through a mobile phone terminal, the after-sale service platform receives the after-sale service application of the customer, then obtains time for the customer to purchase a commodity, compares the time for the customer to purchase the commodity with the current time, obtains duration for the customer to purchase the commodity, marks the duration for the customer to purchase the commodity as purchase duration, compares the purchase duration with the quality guarantee period of the commodity, marks the commodity as a quality guarantee commodity if the purchase duration is within the quality guarantee period range, and marks the commodity as a non-quality guarantee commodity if the purchase duration is not within the quality guarantee period range;
SS 2: the after-sale service platform generates a store selection signal and sends the store selection signal to a store selection unit, the store selection unit acquires a receiving address of a customer, acquires store addresses around the receiving address, screens out the store address closest to the receiving address and marks the store as a selected store;
SS 3: the method comprises the steps that a store address and a mobile phone number of a customer service person of the store are sent to a mobile phone terminal of a customer, the customer mails a commodity to a selected store in an express way after receiving the store address, and the customer pays a mailing cost;
SS 4: and the selected store generates a commodity loss assessment signal after receiving the commodity, and sends the commodity loss assessment signal to the commodity loss assessment unit.
2. The after-sale service system for the e-commerce platform as claimed in claim 1, wherein the registration login unit is used for a customer and a customer service person to submit customer information and customer service person information through a mobile phone terminal for registration, and send the customer information and the customer service person which are successfully registered to the database for storage, the after-sale service platform generates a login account and sends the login account to the mobile phone terminal of the customer, the customer activates the login account by sending a verification code through the mobile phone terminal, and sends the time for activating the login account to the database for storage, the customer information comprises the name, the age, the occupation and the mobile phone number for authenticating the real name of the customer service person, and the customer service person information comprises the name, the age, the occupation and the mobile phone number for authenticating the real name of the customer service person.
3. The after-sales service system for the e-commerce platform according to claim 1, wherein the customer analysis unit is configured to analyze customer data and sort an after-sales processing sequence of the customer, the customer data includes a number of times that the customer purchases goods, a total price of the purchased goods, and a number of times that the customer participates in a review within one month, and the customer is marked as i, i ═ 1, 2.
Step one, acquiring the times of purchasing commodities by a customer in one month, and marking the times of purchasing commodities by the customer in one month as Ci;
step two, acquiring the total price of the commodities purchased by the customer in one month, and marking the total price of the commodities purchased by the customer in one month as Zi;
thirdly, obtaining the number of times that the client participates in the comment within one month, and marking the number of times that the client participates in the comment within one month as Pi;
step four, passing through a formula
Obtaining a client active coefficient Xi, wherein c1, c2 and c3 are all preset proportional coefficients, and c1 is larger than c2 and c3 is larger than 0;
step five, acquiring the time of activating the login account by the client in the database, comparing the time of activating the login account with the current time of the system, acquiring the registration time of the client, and marking the registration time of the client as Si;
step six, obtaining an analysis coefficient Ki of a customer through a formula Ki ═ beta (Xi × v1+ Si × v2), wherein v1 and v2 are preset proportional coefficients, and v1 is more than v 2;
and seventhly, marking the customers for after-sale service as after-sale service customers, enabling the after-sale service customers to be in one-to-one correspondence with the analysis coefficients, then sequencing the after-sale service customers according to the sequence of the analysis coefficients from large to small, and carrying out after-sale service processing on the after-sale service customers according to the sequence of the sequencing.
4. The after-sales service system for the e-commerce platform is characterized in that the customer service distribution unit is used for analyzing customer service data and reasonably distributing customers, the customer service data comprises the ratio of the number of complaints to the number of good comments of the customer service staff in one month, the total number of after-sales services of the customers completed in one month and the frequency of complaints in one month, the customer service staff is marked as k, k is 1, 2, a.
S1: acquiring the ratio of the number of complaints received by the customer service personnel within one month to the number of good comments, and marking the ratio of the number of complaints received by the customer service personnel within one month to the number of good comments as Bk;
s2: acquiring the total number of the customer after-sale services completed by the customer service staff within one month, and marking the total number of the customer after-sale services completed by the customer service staff within one month as Sk;
s3: acquiring the frequency of complaining the customer service personnel within one month, and marking the frequency of complaining the customer service personnel within one month as Pk;
s4: by the formula
Acquiring a service coefficient Qk of a customer service staff, wherein a1, a2 and a3 are all preset proportionality coefficients, and a1 is greater than a2 is greater than a3 is greater than 0;
s5: comparing the service coefficient Qk of the customer service personnel with a service coefficient threshold value:
if the service coefficient Qk of the customer service staff is larger than or equal to the service coefficient threshold, judging that the service quality of the customer service staff is high, marking the customer service staff as a priority arrangement staff, and then sending the name of the priority arrangement staff to an after-sales service platform;
and if the service coefficient Qk of the customer service staff is less than the service coefficient threshold value, judging that the service quality of the customer service staff is poor, marking the customer service staff as a person to be learned, and then sending the person to be learned to the after-sales service platform.
5. The after-sales service system for the e-commerce platform as claimed in claim 1, wherein the commodity damage assessment unit is configured to analyze commodity information and perform damage assessment on the commodity, the commodity information includes quality data, wear data and component data, the quality data is the sum of the weight of components inside the commodity and the weight of a shell of the commodity, the wear data is the number of scratches on the outer surface of the commodity, the component data is the difference between the hardness of the outer surface of a component of the commodity and the standard hardness of the outer surface of the component material, the commodity is marked as o, o 1, 2.
L1: acquiring the sum of the weight of the internal elements of the commodity and the weight of the outer shell of the commodity, and marking the sum of the weight of the internal elements of the commodity and the weight of the outer shell of the commodity as Hw;
l2: acquiring the number of scratches on the outer surface of the commodity, and marking the number of scratches on the outer surface of the commodity as Sw;
l3: acquiring the difference value between the outer surface hardness of the commodity part and the outer surface standard hardness of the part material, and marking the difference value between the outer surface hardness of the commodity part and the outer surface standard hardness of the part material as Yw;
l4: by the formula
Obtaining a loss assessment coefficient Xw of a commodity, wherein s1, s2 and s3 are all preset proportional coefficients, and s1 is larger than s2 is larger than s3 is larger than 0;
l5: comparing the damage assessment coefficient Xw of the commodity with a damage assessment coefficient threshold value:
if the loss assessment coefficient Xw of the commodity is not less than the loss assessment coefficient threshold value, judging that the commodity is damaged, generating an artificial damage signal and sending the artificial damage signal to an after-sales service platform, if the commodity is a quality guarantee commodity, the after-sales service platform subsidies postage to a mobile phone terminal of a customer and returns the commodity to the customer, meanwhile, marking the customer as an abnormal customer, and if the commodity is a non-quality guarantee commodity, returning the commodity to the customer and marking the customer as a problem customer;
if the damage assessment coefficient Xw of the commodity is less than the damage assessment coefficient threshold value, the commodity is judged to be naturally damaged, a natural damage signal is generated and sent to an after-sales service platform, if the commodity is a quality assurance commodity, the after-sales service platform subsidies postage to a mobile phone terminal of a client and posts a new commodity to the client, if the commodity is a non-quality assurance commodity, the commodity is maintained, a maintenance fee list is sent to the client, and if the client agrees to maintain, the commodity is maintained and the commodity after maintenance is posted to the client.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011195990.0A CN112163874A (en) | 2020-10-30 | 2020-10-30 | After-sale service system for e-commerce platform |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011195990.0A CN112163874A (en) | 2020-10-30 | 2020-10-30 | After-sale service system for e-commerce platform |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112163874A true CN112163874A (en) | 2021-01-01 |
Family
ID=73865393
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011195990.0A Pending CN112163874A (en) | 2020-10-30 | 2020-10-30 | After-sale service system for e-commerce platform |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112163874A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113139857A (en) * | 2021-05-17 | 2021-07-20 | 武汉阿杜拉电子商务有限公司 | Electronic commerce platform merchant store intelligent management method, system, equipment and computer storage medium |
| CN114897358A (en) * | 2022-05-11 | 2022-08-12 | 浙江开心果数智科技有限公司 | After-sale service distribution method suitable for marketing service platform |
| CN116483041A (en) * | 2023-05-05 | 2023-07-25 | 广州特纳信息科技有限公司 | Intelligent control system based on Internet of things and big data analysis |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1588402A (en) * | 2004-07-13 | 2005-03-02 | 尹雄鹰 | Method for service item power limit establishment, location preservation and location inquiry |
| CN103606085A (en) * | 2013-11-01 | 2014-02-26 | 北京京东尚科信息技术有限公司 | Method of issuing after-sale service data and server |
| CN106127488A (en) * | 2016-06-14 | 2016-11-16 | 北京鼎力合创信息技术有限公司 | A kind of high in the clouds after-sale service system |
| CN106600299A (en) * | 2016-12-29 | 2017-04-26 | 江西博瑞彤芸科技有限公司 | Data processing method for after-sales service |
| CN107527213A (en) * | 2017-08-28 | 2017-12-29 | 安徽天恩信息科技有限公司 | A kind of after-sale service management platform and its method |
| CN110060066A (en) * | 2018-01-16 | 2019-07-26 | 安徽怡秒连接通信技术股份有限公司 | A kind of electronics industry processing system after sale |
| CN110276641A (en) * | 2019-06-19 | 2019-09-24 | 深圳市聚星易科技有限公司 | A kind of Xian Xia shops electric business management system |
| CN110766276A (en) * | 2019-09-19 | 2020-02-07 | 南京嗯哇智能科技有限公司 | Device, method, equipment and storage medium for nearby distribution of maintenance tasks |
| CN111210314A (en) * | 2020-01-13 | 2020-05-29 | 湖州朗讯信息科技有限公司 | Mall system |
| CN111210239A (en) * | 2020-01-13 | 2020-05-29 | 杭州沃朴物联科技有限公司 | Method, apparatus and medium for processing after-sales information |
| CN111667276A (en) * | 2019-03-08 | 2020-09-15 | 昆山瀚海信息科技有限公司 | Product after-sale management system |
| CN111833069A (en) * | 2019-03-27 | 2020-10-27 | 上海彧胄寓丰智能科技有限公司 | Logistics after-sale maintenance system based on supply of goods |
-
2020
- 2020-10-30 CN CN202011195990.0A patent/CN112163874A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1588402A (en) * | 2004-07-13 | 2005-03-02 | 尹雄鹰 | Method for service item power limit establishment, location preservation and location inquiry |
| CN103606085A (en) * | 2013-11-01 | 2014-02-26 | 北京京东尚科信息技术有限公司 | Method of issuing after-sale service data and server |
| CN106127488A (en) * | 2016-06-14 | 2016-11-16 | 北京鼎力合创信息技术有限公司 | A kind of high in the clouds after-sale service system |
| CN106600299A (en) * | 2016-12-29 | 2017-04-26 | 江西博瑞彤芸科技有限公司 | Data processing method for after-sales service |
| CN107527213A (en) * | 2017-08-28 | 2017-12-29 | 安徽天恩信息科技有限公司 | A kind of after-sale service management platform and its method |
| CN110060066A (en) * | 2018-01-16 | 2019-07-26 | 安徽怡秒连接通信技术股份有限公司 | A kind of electronics industry processing system after sale |
| CN111667276A (en) * | 2019-03-08 | 2020-09-15 | 昆山瀚海信息科技有限公司 | Product after-sale management system |
| CN111833069A (en) * | 2019-03-27 | 2020-10-27 | 上海彧胄寓丰智能科技有限公司 | Logistics after-sale maintenance system based on supply of goods |
| CN110276641A (en) * | 2019-06-19 | 2019-09-24 | 深圳市聚星易科技有限公司 | A kind of Xian Xia shops electric business management system |
| CN110766276A (en) * | 2019-09-19 | 2020-02-07 | 南京嗯哇智能科技有限公司 | Device, method, equipment and storage medium for nearby distribution of maintenance tasks |
| CN111210314A (en) * | 2020-01-13 | 2020-05-29 | 湖州朗讯信息科技有限公司 | Mall system |
| CN111210239A (en) * | 2020-01-13 | 2020-05-29 | 杭州沃朴物联科技有限公司 | Method, apparatus and medium for processing after-sales information |
Non-Patent Citations (1)
| Title |
|---|
| 杨立钒: "《电子商务网站典型案例评析》", 31 December 2016, 西安电子科技大学出版社 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113139857A (en) * | 2021-05-17 | 2021-07-20 | 武汉阿杜拉电子商务有限公司 | Electronic commerce platform merchant store intelligent management method, system, equipment and computer storage medium |
| CN114897358A (en) * | 2022-05-11 | 2022-08-12 | 浙江开心果数智科技有限公司 | After-sale service distribution method suitable for marketing service platform |
| CN114897358B (en) * | 2022-05-11 | 2023-09-12 | 浙江开心果数智科技有限公司 | After-sales service distribution method suitable for marketing service platform |
| CN116483041A (en) * | 2023-05-05 | 2023-07-25 | 广州特纳信息科技有限公司 | Intelligent control system based on Internet of things and big data analysis |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112163874A (en) | After-sale service system for e-commerce platform | |
| CN109034979B (en) | Quotation system and quotation method | |
| CN110598940A (en) | Logistics order analysis and prediction system based on Internet of things trade | |
| US20090012996A1 (en) | Syndication optimization system | |
| CN108197851A (en) | A kind of e-commerce mostly single flow distribution method with address | |
| CN111833158A (en) | Industry design product frame-type bid-attracting management platform | |
| CN112036985A (en) | Marketing system of E-commerce operation | |
| CN111127112A (en) | Advertisement putting method, device, equipment and storage medium | |
| CN116051191A (en) | New media advertisement putting recommendation system based on data analysis | |
| Friberg et al. | pricing Strategies in E-commerce: Bricks vs. Clicks | |
| CN112529655A (en) | Electronic commerce transaction system based on mobile phone terminal | |
| Chang et al. | Elasticity of demand for Australian cotton in Japan | |
| CN108470301A (en) | A kind of commodity network method of commerce | |
| CN110675271A (en) | Method for providing best quality insurance scheme for customer | |
| CN112330324A (en) | Electronic commerce transaction system based on mobile phone terminal | |
| CN110910163A (en) | Automobile distribution customer demand analysis method and system based on customer relationship management system | |
| Boyd et al. | The role of dual Entitlement and equity theories in consumers' formation of fair price judgments: an investigation within a business-to-business service setting | |
| CN112365321A (en) | Method for realizing effective supervision and identification of fresh electronic commerce platform multi-merchant commodities | |
| CN106447226A (en) | Real-time assessment interactive system | |
| CN113191857A (en) | Cloud platform e-commerce data processing method and system based on big data | |
| CN115358813A (en) | Cross-border e-commerce platform intelligent operation system | |
| CN114648389A (en) | Electronic commerce information processing system | |
| US20120116893A1 (en) | Auction-based shipment advertising | |
| CN113592525A (en) | Marketing management system based on internet big data | |
| CN111724205A (en) | Vehicle equipment maintenance management expense assessment system and method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |