CN113592525A - Marketing management system based on internet big data - Google Patents

Abstract

The invention discloses a marketing management system based on internet big data, which is used for solving the problems of how to reasonably screen consumers, how to accurately calculate the member grade, how to keep real and active members and how to improve after-sale service; the system comprises a data acquisition module, a processor, a storage module, an analysis module, a priority module, a marketing module, a member database, a management module and an after-sales service module; the marketing management system is based on the screening value M_iThe method screens consumers reasonably, selects preferred consumers as targets, and is convenient for better marketing products; using formulas

Obtaining membership engagement D_i(ii) a Through membership engagement D_iJudging the participation degree of the member according to the size; using the formula F_i＝MH_i*w1+D_iW2 obtaining the gradeValue F_i(ii) a By rank value F_iJudging the grade of the member according to the size of the member, thereby more reasonably distributing the member; passing loss value LS_iJudging the adhesion degree of the consumer; and then the member is cleaned up, thereby keeping the real member.

Description

Marketing management system based on internet big data

Technical Field

The invention relates to the technical field of marketing, in particular to a marketing management system based on internet big data.

Background

The big data marketing management system is a software system which combines the unique identity information code technology of products and a market consumption management method to realize consumer information acquisition and consumption behavior analysis and can be an independent anti-counterfeiting extended value-added service software platform. The consumption management system can realize the functions of consumption information collection and analysis, consumption behavior analysis and management, member points, gift exchange, member lottery, anti-counterfeiting inquiry, logistics tracking and the like. The functions can be flexibly combined, and the system is a bridge for real-time communication between enterprises and consumers and a powerful tool for enterprise marketing.

Disclosure of Invention

The invention aims to provide a marketing management system based on internet big data.

The technical problem to be solved by the invention is as follows:

(1) how to reasonably screen consumers so as to enable merchants to have better marketing;

(2) how to accurately calculate membership grade so as to distribute reasonable rights and interests;

(3) how to retain real and active members and improve after-sales services;

the purpose of the invention can be realized by the following technical scheme: a marketing management system based on internet big data comprises a data acquisition module, a processor, a storage module, an analysis module, a priority module, a marketing module, a member database, a management module and an after-sale service module;

the data acquisition module is used for acquiring personal data and consumption data of consumers; the personal data comprises names and contact information; the consumer data includes a product, a price to purchase the product, and a date of purchase; the data acquisition module sends the personal data and the consumption data of the consumers to the processor; the processor receives the personal data and the consumption data of the consumers sent by the data acquisition module and sends the data to the storage module for storage; the analysis module is used for analyzing personal data and consumption data of the consumer; the analysis module comprises the following analysis steps:

the method comprises the following steps: set the consumer of the acquisition as X_i(i ═ 1 … … n); setting the product purchased by the consumer as A_i(i ═ 1 … … n); product produced by birthArticle label classification B_i(i ═ 1 … … n); the price corresponding to the price of the purchased product Ai is marked as C_i(i ═ 1 … … n); purchase product A_iThe purchase date of (D) is recorded as T_i(i ═ 1 … … n); product label classification B_iThe inner part comprises a plurality of products B_ij，(j＝1……n)；

Step two: consumer purchases product A_iWith product B_ijMatching is carried out; is embodied in that when a consumer purchases product A₁And B₁₁If the same, outputting the product label classification B₁；

Step three: dividing the consumption time of consumers into three grades of TA at the early stage of a month, TB at the middle stage of the month and TC at the end stage of the month; wherein, TA at the beginning of the month is No. 1 to No. 10; the metaphase of the moon TB is No. 11 to No. 20; the end of month TC numbers 21 to 31;

step four: will purchase date T_iMatching with the consumption time of the consumer; specifically, when the purchase date is No. 1 to No. 10, the date is TA of early month; purchase product A_iThe price corresponding to (2) is recorded as C_iSumming to obtain the monthly purchase value M_TA(ii) a When the purchase date is from 11 to 20, the date is the lunar period TB; purchase product A_iThe price corresponding to (2) is recorded as C_iSumming to obtain monthly purchase value M_TB(ii) a When the purchase date is 21 to 31, the date is the month end TC; purchase product A_iThe price corresponding to (2) is recorded as C_iSumming to obtain the monthly purchase value M_TC；

Step five: using formula M_i＝M_TA*J1+M_TB*J2+M_TCObtaining consumer X from J3_iScreening value M of_i(ii) a Wherein J1, J2 and J3 are fixed values of preset proportions;

step six: according to the screening value M_iScreening consumers for the size of (2); will M_i>Consumer X of k2_iMarking as a preferred consumer; will k1<M_i<Consumer X of k2_iMarking as an optional consumer; will M_i<k1 is marked as a non-selected consumer, wherein k1 and k2 are preset screening fixed values;

the analysis module sends the product label classification of the preferred consumer and the optional consumer, as well as the early monthly purchase value, the mid-monthly purchase value and the late monthly purchase value to the preferred module; the product label classification and the early month purchase value, the middle month purchase value and the end month purchase value are marked as purchase data; the preferred module receives and stores the purchase data of the preferred consumers and the optional consumers sent by the analysis module; the marketing module is used for sending preferred product information and a member registration information table to preferred consumers and optional consumers; the preferred product information is product information and preferential information of consumer product label classification; the member registration information table is used for filling registration information by a consumer; the extraction module is used for extracting the consumers filling the member registration information table and the purchase data corresponding to the consumers and sending the purchase data to the member database; the member database receives the consumers who fill in the member registration information table and the purchasing data corresponding to the consumers sent by the extraction module, and marks the consumers as members for storage;

the management module is used for carrying out grade calculation, distribution, management and maintenance on the members in the member database; the management module comprises an activity sending unit, a communication unit, a collecting unit, a calculating unit, a distributing unit, a management unit and a maintenance unit; the activity sending unit is used for sending preferential activities to the members; the communication unit is used for communication among members and communication between the members and merchants; the acquisition unit is used for acquiring the time and the times of participation of the members in preferential activities, the times of book communication among the members and the times of communication between the members and merchants; the acquisition unit transmits the acquired time and times of participation of the members in preferential activities, the times of book communication among the members and the times of communication between the members and merchants to the calculation unit; the calculation unit receives and calculates the time and the times of participation of the members in preferential activities, the times of book communication among the members and the times of communication between the members and merchants, which are sent by the acquisition unit; the specific calculation steps are as follows:

s1: setting the starting time of preferential starting release to be t_j(ii) a The time of the member participating in the preferential activity is recorded as t_i；

S2: using the formula t_ij＝t_i-t_jAcquiring and obtaining member participation preferential activity time t_ij；

S3: setting the number of times of the member participating in preferential activities to be P_jNumber of times of exchanging books between members P_b(ii) a The number of times of communication between the member and the merchant is recorded as P_c；

S4: using formulas

Obtaining membership engagement D_i(ii) a Wherein u1, u2, u3 and u4 are fixed values;

s5: setting the purchase value of the member as MH_i(ii) a Wherein; MH_i＝M_TA+M_TB+M_TC；

S6: using the formula F_i＝MH_i*w1+D_iW2 obtaining grade value F_i(ii) a Wherein w1 and w2 are fixed values of a preset ratio;

the calculating unit sends the grade value to the distributing unit; the distribution unit receives the grade value sent by the calculation unit and distributes the grade value; the distribution process is as follows:

a: setting Member level to G_i(i ═ 1 … … n); setting Member level to G_iThe range value is (h)_i-1，h_i]；

B: rank value F_iThe member level of the conference is G_iRange value (h)_i-1，h_i]Matching, which is specifically shown as follows: current grade value h₂<F1≤h₃(ii) a Outputs the member grade G₃；

The management unit is used for collecting the unconsumed product time and the unconsumed activity times of the members and calculating and cleaning the loss value, and the specific calculation and cleaning steps are as follows:

SS 1; setting a member non-consumption product time to Y_i(i-1 … … n) with a number of non-participating activities of Z_i，(i＝1……n)；

SS 2: using formulas

Is obtained to obtainLoss value LS_i；

SS 3: setting a preset cleaning value to be Q1;

SS 4: loss value LS_iComparison with a cleaning value of Q1; when LS_i-Q1>0; cleaning up the member;

the maintenance unit is used for sending short messages, voice and call return visits to the members.

Further, the after-sale service module is used for visualization service of consumers and merchants; the after-sale service module comprises a visual unit, a replacement refund unit, an evaluation acquisition unit and a gift paying unit; the visual unit is used for the after-sale communication of the product between the consumer and the merchant; the replacement refund unit is used for carrying out product replacement and refund on a consumer and a merchant; the evaluation acquisition unit acquires the evaluation value of the product by the consumer; the gift paying unit is used for calculating the amount of an extra gift to be paid and a gift corresponding to the amount; the gift claim unit comprises the following specific calculation steps:

the method comprises the following steps: setting the evaluation value of the consumer as Ni; the price corresponding to the price of the purchased product Ai is marked as C_i；

Step two: for Ni and C_iSetting a preset value; setting a preset value of Ni as g 1; setting C_iThe preset value of (2) is recorded as g 2;

step three: using the formula PF_i＝N_i*g1+C_iG2 obtaining the payment value PF_i；

Step four: setting the claim gift as R_i(i ═ 1 … … n); claim gift R_iThe corresponding price interval is (f)_i-1，f_i]；

Step five: claim value PF_iGift R with paying_iMatching the corresponding price intervals; is particularly shown when f₅<PF₁≤f₆(ii) a Then the claim gift R is output₆。

The invention has the beneficial effects that:

(1) the invention analyzes the personal data and the consumption data of the consumer through the analysis module; using formula M_i＝M_TA*J1+M_TB*J2+M_TCObtaining consumer X from J3_iScreening value M of_i(ii) a According to the screening value M_iThe method screens consumers reasonably, selects preferred consumers as targets, and is convenient for better marketing products;

(2) the invention utilizes the formula

Obtaining membership engagement D_i(ii) a Through membership engagement D_iJudging the participation degree of the member according to the size; using the formula F_i＝MH_i*w1+D_iW2 obtaining grade value F_i(ii) a By rank value F_iJudging the grade of the member according to the size of the member, thereby more reasonably distributing the member;

(3) the invention utilizes the formula

Obtaining loss value LS_i(ii) a Loss value LS_iComparison with a cleaning value of Q1; when LS_i-Q1>0; cleaning up the member; passing loss value LS_iJudging the adhesion degree of the consumer; loss value LS_iThe larger the size, the lower the adhesion, when the loss value LS of the member_iGreater than a cleaning value Q1; cleaning the member; thereby preserving real members;

(4) the invention utilizes the formula PF_i＝N_i*g1+C_iG2 obtaining the payment value PF_i(ii) a Claim value PF_iGift R with paying_iMatching the corresponding price intervals; by rational calculation of the extra payout value PF_iSelecting an appropriate gift reduces the level of complaints about after-sales services, thereby increasing consumer satisfaction.

Drawings

The invention will be further described with reference to the accompanying drawings.

Fig. 1 is a schematic block diagram of an internet big data based marketing management system of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious 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, the present invention is a marketing management system based on internet big data, including a data acquisition module, a processor, a storage module, an analysis module, a priority module, a marketing module, a member database, a management module, and an after-sale service module;

the data acquisition module is used for acquiring personal data and consumption data of consumers; the personal data comprises names and contact information; consumer data includes the product, the price at which the product was purchased, and the date of purchase; the data acquisition module sends the personal data and the consumption data of the consumers to the processor; the processor receives the personal data and the consumption data of the consumers sent by the data acquisition module and sends the data to the storage module for storage; the analysis module is used for analyzing the personal data and the consumption data of the consumers; the analysis module comprises the following analysis steps:

the method comprises the following steps: set the consumer of the acquisition as X_i(i ═ 1 … … n); setting the product purchased by the consumer as A_i(i ═ 1 … … n); product label classification B_i(i ═ 1 … … n); the price corresponding to the price of the purchased product Ai is marked as C_i(i ═ 1 … … n); purchase product A_iThe purchase date of (D) is recorded as T_i(i ═ 1 … … n); product label classification B_iThe inner part comprises a plurality of products B_ij，(j＝1……n)；

Step two: consumer purchases product A_iWith product B_ijMatching is carried out; is embodied in that when a consumer purchases product A₁And B₁₁If the same, outputting the product label classification B₁；

Step three: dividing the consumption time of consumers into three grades of TA at the early stage of a month, TB at the middle stage of the month and TC at the end stage of the month; wherein, TA at the beginning of the month is No. 1 to No. 10; the metaphase of the moon TB is No. 11 to No. 20; the end of month TC numbers 21 to 31;

step four: matching the purchase date Ti with the consumption time of the consumer; specifically, when the purchase date is No. 1 to No. 10, the date is TA of early month; purchase product A_iThe price corresponding to (2) is recorded as C_iSumming to obtain the monthly purchase value M_TA(ii) a When the purchase date is from 11 to 20, the date is the lunar period TB; purchase product A_iThe price corresponding to (2) is recorded as C_iSumming to obtain monthly purchase value M_TB(ii) a When the purchase date is 21 to 31, the date is the month end TC; purchase product A_iThe price corresponding to (2) is recorded as C_iSumming to obtain the monthly purchase value M_TC；

Step five: using formula M_i＝M_TA*J1+M_TB*J2+M_TCObtaining consumer X from J3_iScreening value M of_i(ii) a Wherein J1, J2 and J3 are fixed values of preset proportions;

step six: according to the screening value M_iScreening consumers for the size of (2); will M_i>Consumer X of k2_iMarking as a preferred consumer; will k1<M_i<Consumer X of k2_iMarking as an optional consumer; will M_i<k1 is marked as a non-selected consumer, wherein k1 and k2 are preset screening fixed values; according to the screening value M_iThe method screens consumers reasonably, selects preferred consumers as targets, and is convenient for better marketing products;

the analysis module sends the product label classification of the preferred consumer and the optional consumer, as well as the early monthly purchase value, the mid-monthly purchase value and the end-monthly purchase value to the preferred module; the product label classification and the early month purchase value, the middle month purchase value and the end month purchase value are marked as purchase data; the preferred module receives and stores the purchase data of the preferred consumers and the optional consumers sent by the analysis module; the marketing module is used for sending and sending the preferred product information and the member registration information table to the preferred consumers and the optional consumers; the preferred product information is product information and preferential information of consumer product label classification; the product information comprises product functions and prices, the preferential information comprises product discount prices and gift presentation, and the member registration information table is used for filling registration information by consumers; the extraction module is used for extracting the consumers filling the member registration information table and the purchase data corresponding to the consumers and sending the purchase data to the member database; the member database receives the consumers who fill in the member registration information table and the purchasing data corresponding to the consumers which are sent by the extracting module and marks the consumers as members for storage;

the management module is used for carrying out grade calculation, distribution, management and maintenance on the members in the member database; the management module comprises an activity sending unit, a communication unit, a collecting unit, a calculating unit, a distributing unit, a management unit and a maintenance unit; the activity sending unit is used for sending preferential activities to the members; the communication unit is used for communication among members and communication between the members and merchants; the acquisition unit is used for acquiring the time and the times of participation of the members in preferential activities, the times of book communication among the members and the times of communication between the members and merchants; the acquisition unit transmits the acquired time and times of participation of the members in preferential activities, the times of book communication among the members and the times of communication between the members and merchants to the calculation unit; the calculation unit receives and calculates the time and the times of participation of the members in preferential activities, the times of book communication among the members and the times of communication between the members and merchants, which are sent by the acquisition unit; the specific calculation steps are as follows:

s1: setting the starting time of preferential starting release to be t_j(ii) a The time of the member participating in the preferential activity is recorded as t_i；

S2: using the formula t_ij＝t_i-t_jAcquiring and obtaining member participation preferential activity time t_ij；

S3: setting the number of times of the member participating in preferential activities to be P_jNumber of times of exchanging books between members P_b(ii) a The number of times of communication between the member and the merchant is recorded as P_c；

S4: using formulas

Obtaining membership engagement D_i(ii) a Wherein u1, u2, u3 and u4 are fixed values; through membership engagement D_iParameters of size-judging memberAnd degree;

s5: setting the purchase value of the member as MH_i(ii) a Wherein; MH_i＝M_TA+M_TB+M_TC；

S6: using the formula F_i＝MH_i*w1+D_iW2 obtaining grade value F_i(ii) a Wherein w1 and w2 are fixed values of a preset ratio; by rank value F_iJudging the grade of the member according to the size of the member, thereby more reasonably distributing the member;

the calculating unit sends the grade value to the distributing unit; the distribution unit receives the grade value sent by the calculation unit and distributes the grade value; the distribution process is as follows:

a: setting Member level to G_i(i ═ 1 … … n); setting Member level to G_iThe range value is (h)_i-1，h_i]；

B: rank value F_iThe member level of the conference is G_iRange value (h)_i-1，h_i]Matching, which is specifically shown as follows: current grade value h₂<F1≤h₃(ii) a Outputs the member grade G₃；

The management unit is used for collecting the time of unconsumed products and the number of times of non-participation in activities of the members and calculating and cleaning the loss value, and the specific calculation and cleaning steps are as follows:

SS 1; setting a member non-consumption product time to Y_i(i-1 … … n) with a number of non-participating activities of Z_i，(i＝1……n)；

SS 2: using formulas

Obtaining loss value LS_i；

SS 3: setting a preset cleaning value to be Q1;

SS 4: loss value LS_iComparison with a cleaning value of Q1; when LS_i-Q1>0; cleaning up the member; passing loss value LS_iJudging the adhesion degree of the consumer; loss value LS_iThe larger the size, the lower the adhesion, when the loss value LS of the member_iGreater than a cleaning value Q1; cleaning the member; thereby ensuringLeaving a real member;

the maintenance unit is used for sending short messages, voice and call return visits to the members.

The after-sale service module is used for visual service of consumers and merchants; the after-sale service module comprises a visual unit, a replacement refund unit, an evaluation acquisition unit and a gift paying unit; the visual unit is used for the after-sale communication of the product between the consumer and the merchant; the communication between the merchant and the consumer is realized through the visual unit, so that the problems are better solved, and the relationship between the consumer and the merchant is increased; the replacement refund unit is used for carrying out product replacement and refund on a consumer and a merchant; the evaluation acquisition unit acquires the evaluation value of the product by the consumer; the gift paying unit is used for calculating the amount of an extra gift to be paid and a gift corresponding to the amount; the gift claim unit comprises the following specific calculation steps:

the method comprises the following steps: setting the evaluation value of the consumer as Ni; the price corresponding to the price of the purchased product Ai is marked as C_i；

Step two: for Ni and C_iSetting a preset value; setting a preset value of Ni as g 1; setting C_iThe preset value of (2) is recorded as g 2;

step three: using the formula PF_i＝N_i*g1+C_iG2 obtaining the payment value PF_i；

Step four: setting the claim gift as R_i(i ═ 1 … … n); claim gift R_iThe corresponding price interval is (f)_i-1，f_i]；

Step five: claim value PF_iGift R with paying_iMatching the corresponding price intervals; is particularly shown when f₅<PF₁≤f₆(ii) a Then the claim gift R is output₆(ii) a By rational calculation of the extra payout value PF_iThereby improving the satisfaction degree of consumers;

the invention has the beneficial effects that:

(1) the invention analyzes the personal data and the consumption data of the consumer through the analysis module; using formula M_i＝M_TA*J1+M_TB*J2+M_TCJ3 get disappearPayer X_iScreening value M of_i(ii) a According to the screening value M_iThe method screens consumers reasonably, selects preferred consumers as targets, and is convenient for better marketing products;

(2) the invention utilizes the formula

Obtaining membership engagement D_i(ii) a Through membership engagement D_iJudging the participation degree of the member according to the size; using the formula F_i＝MH_i*w1+D_iW2 obtaining grade value F_i(ii) a By rank value F_iJudging the grade of the member according to the size of the member, thereby more reasonably distributing the member;

(3) the invention utilizes the formula

Obtaining loss value LS_i(ii) a Loss value LS_iComparison with a cleaning value of Q1; when LS_i-Q1>0; cleaning up the member; passing loss value LS_iJudging the adhesion degree of the consumer; loss value LS_iThe larger the size, the lower the adhesion, when the loss value LS of the member_iGreater than a cleaning value Q1; cleaning the member; thereby preserving real members;

(4) the invention utilizes the formula PF_i＝N_i*g1+C_iG2 obtaining the payment value PF_i(ii) a Claim value PF_iGift R with paying_iMatching the corresponding price intervals; by rational calculation of the extra payout value PF_iSelecting an appropriate gift reduces the level of complaints about after-sales services, thereby increasing consumer satisfaction.

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 (2)

1. A marketing management system based on Internet big data is characterized by comprising a data acquisition module, a processor, a storage module, an analysis module, a priority module, a marketing module, a member database, a management module and an after-sale service module;

the data acquisition module is used for acquiring personal data and consumption data of consumers; the personal data comprises names and contact information; the consumer data includes a product, a price to purchase the product, and a date of purchase; the data acquisition module sends the personal data and the consumption data of the consumers to the processor; the processor receives the personal data and the consumption data of the consumers sent by the data acquisition module and sends the data to the storage module for storage; the analysis module is used for analyzing personal data and consumption data of the consumer; the analysis module comprises the following analysis steps:

the method comprises the following steps: set the consumer of the acquisition as X_i(i ═ 1 … … n); setting the product purchased by the consumer as A_i(i ═ 1 … … n); product label classification B_i(i ═ 1 … … n); the price corresponding to the price of the purchased product Ai is marked as C_i(i ═ 1 … … n); purchase product A_iThe purchase date of (D) is recorded as T_i(i ═ 1 … … n); product label classification B_iThe inner part comprises a plurality of products B_ij，(j＝1……n)；

Step two: consumer purchases product A_iWith product B_ijMatching is carried out; is embodied in that when a consumer purchases product A₁And B₁₁If the same, outputting the product label classification B₁；

Step three: dividing the consumption time of consumers into three grades of TA at the early stage of a month, TB at the middle stage of the month and TC at the end stage of the month; wherein, TA at the beginning of the month is No. 1 to No. 10; the metaphase of the moon TB is No. 11 to No. 20; the end of month TC numbers 21 to 31;

step four: will purchase date T_iMatching with the consumption time of the consumer; specifically, when the purchase date is No. 1 to No. 10, the date is TA of early month; purchase product A_iThe price corresponding to (2) is recorded as C_iSumming to obtain the monthly purchase value M_TA(ii) a When the purchase date is from 11 to 20, the date is the lunar period TB; purchase product A_iThe price corresponding to (2) is recorded as C_iSumming to obtain monthly purchase value M_TB(ii) a When the purchase date is 21 to 31, the date is the month end TC; purchase product A_iThe price corresponding to (2) is recorded as C_iSumming to obtain the monthly purchase value M_TC；

Step five: using formula M_i＝M_TA*J1+M_TB*J2+M_TCObtaining consumer X from J3_iScreening value M of_i(ii) a Wherein J1, J2 and J3 are fixed values of preset proportions;

step six: according to the screening value M_iScreening consumers for the size of (2); will M_i>Consumer X of k2_iMarking as a preferred consumer; will k1<M_i<Consumer X of k2_iMarking as an optional consumer; will M_i<k1 is marked as a non-selected consumer, wherein k1 and k2 are preset screening fixed values;

the analysis module sends the product label classification of the preferred consumer and the optional consumer, as well as the early monthly purchase value, the mid-monthly purchase value and the late monthly purchase value to the preferred module; the product label classification and the early month purchase value, the middle month purchase value and the end month purchase value are marked as purchase data; the preferred module receives and stores the purchase data of the preferred consumers and the optional consumers sent by the analysis module; the marketing module is used for sending preferred product information and a member registration information table to preferred consumers and optional consumers; the preferred product information is product information and preferential information of consumer product label classification; the member registration information table is used for filling registration information by a consumer; the extraction module is used for extracting the consumers filling the member registration information table and the purchase data corresponding to the consumers and sending the purchase data to the member database; the member database receives the consumers who fill in the member registration information table and the purchasing data corresponding to the consumers sent by the extraction module, and marks the consumers as members for storage;

the management module is used for carrying out grade calculation, distribution, management and maintenance on the members in the member database; the management module comprises an activity sending unit, a communication unit, a collecting unit, a calculating unit, a distributing unit, a management unit and a maintenance unit; the activity sending unit is used for sending preferential activities to the members; the communication unit is used for communication among members and communication between the members and merchants; the acquisition unit is used for acquiring the time and the times of participation of the members in preferential activities, the times of book communication among the members and the times of communication between the members and merchants; the acquisition unit transmits the acquired time and times of participation of the members in preferential activities, the times of book communication among the members and the times of communication between the members and merchants to the calculation unit; the calculation unit receives and calculates the time and the times of participation of the members in preferential activities, the times of book communication among the members and the times of communication between the members and merchants, which are sent by the acquisition unit; the specific calculation steps are as follows:

s1: setting the starting time of preferential starting release to be t_j(ii) a The time of the member participating in the preferential activity is recorded as t_i；

S2: using the formula t_ij＝t_i-t_jAcquiring and obtaining member participation preferential activity time t_ij；

S3: setting the number of times of the member participating in preferential activities to be P_jNumber of times of exchanging books between members P_b(ii) a The number of times of communication between the member and the merchant is recorded as P_c；

S4: using formulas

Obtaining membership engagement D_i(ii) a Wherein u1, u2, u3 and u4 are fixed values;

s5: setting the purchase value of the member as MH_i(ii) a Wherein; MH_i＝M_TA+M_TB+M_TC；

S6: using the formula F_i＝MH_i*w1+D_iW2 obtaining grade value F_i(ii) a Wherein w1 and w2 are fixed values of a preset ratio;

the calculating unit sends the grade value to the distributing unit; the distribution unit receives the grade value sent by the calculation unit and distributes the grade value; the distribution process is as follows:

a: setting Member level to G_i(i ═ 1 … … n); setting Member level to G_iThe range value is (h)_i-1，h_i]；

B: rank value F_iThe member level of the conference is G_iRange value (h)_i-1，h_i]Matching, which is specifically shown as follows: current grade value h₂<F1≤h₃(ii) a Outputs the member grade G₃；

The management unit is used for collecting the unconsumed product time and the unconsumed activity times of the members and calculating and cleaning the loss value, and the specific calculation and cleaning steps are as follows:

SS 1; setting a member non-consumption product time to Y_i(i-1 … … n) with a number of non-participating activities of Z_i，(i＝1……n)；

SS 2: using formulas

Obtaining loss value LS_i；

SS 3: setting a preset cleaning value to be Q1;

SS 4: loss value LS_iComparison with a cleaning value of Q1; when LS_i-Q1>0; cleaning up the member;

the maintenance unit is used for sending short messages, voice and call return visits to the members.

2. The internet big data-based marketing management system of claim 1, wherein the after-sales service module is used for consumer and merchant visualization service; the after-sale service module comprises a visual unit, a replacement refund unit, an evaluation acquisition unit and a gift paying unit; the visual unit is used for the after-sale communication of the product between the consumer and the merchant; the replacement refund unit is used for carrying out product replacement and refund on a consumer and a merchant; the evaluation acquisition unit acquires the evaluation value of the product by the consumer; the gift paying unit is used for calculating the amount of an extra gift to be paid and a gift corresponding to the amount; the gift claim unit comprises the following specific calculation steps:

the method comprises the following steps: setting the evaluation value of the consumer as Ni; the price corresponding to the price of the purchased product Ai is marked as C_i；

Step two: for Ni and C_iSetting a preset value; setting a preset value of Ni as g 1; setting C_iThe preset value of (2) is recorded as g 2;

step three: using the formula PF_i＝N_i*g1+C_iG2 obtaining the payment value PF_i；

Step four: setting the claim gift as R_i(i ═ 1 … … n); claim gift R_iThe corresponding price interval is (f)_i-1，f_i]；

Step five: claim value PF_iGift R with paying_iMatching the corresponding price intervals; is particularly shown when f₅<PF₁≤f₆(ii) a Then the claim gift R is output₆。

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