CN111080127A - User extraction management method and system based on sales data - Google Patents
User extraction management method and system based on sales data Download PDFInfo
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- CN111080127A CN111080127A CN201911297427.1A CN201911297427A CN111080127A CN 111080127 A CN111080127 A CN 111080127A CN 201911297427 A CN201911297427 A CN 201911297427A CN 111080127 A CN111080127 A CN 111080127A
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Abstract
The invention relates to the technical field of sales promotion management, and discloses a user promotion management method and a system based on sales data, which comprises the following steps: establishing a multi-dimensional and multi-object configuration model based on different service scene contents, wherein the multi-dimensional and multi-object configuration model is formed by mutually corresponding the configuration of the same configuration object and the configuration models in multiple configuration dimensions, and mutually corresponding the configuration models in the same configuration dimension and the configuration models in the multiple configuration dimensions; calculating the extraction of the extraction object under different service scene contents according to the extraction form of the established multi-dimensional multi-object extraction configuration model, which specifically comprises the following steps: calculating the percentage by taking the form; calculating a fixed sum withdrawal form; calculating the form of each unit quantity; calculating the long ladder extraction form; short steps are referred to as formal calculations. The invention realizes the technical effect of flexibly and changeably managing and controlling the user service development.
Description
Technical Field
The invention relates to the technical field of sales promotion management, in particular to a user promotion management method and system based on sales data.
Background
In a traditional store operation business mode, when the business of store employees is managed and controlled, simple configuration is often adopted to complete the increase of a plurality of accounts according to profits or amounts. However, in the conventional business promotion management and control mode, the promotion mode is single and cannot flexibly and changeably adapt to the current rapidly-changing marketing environment, so that the working enthusiasm of store employees cannot be effectively improved. Therefore, developing a flexible business proposing model is very necessary to improve the business performance of stores and the coordination of teams.
Disclosure of Invention
Technical problem to be solved
Aiming at the defects of the prior art, the invention provides a user promotion management method based on sales data, which aims to solve the technical problems that the traditional business promotion management and control mode is single and cannot flexibly and changeably adapt to the rapidly-changing marketing environment;
meanwhile, the invention also provides a user contribution management system based on the sales data, and the technical purpose of flexibly and changeably managing and controlling user service contribution is realized through a multi-dimensional and multi-object contribution configuration model.
(II) technical scheme
In order to achieve the purpose, the invention provides the following technical scheme:
a user proposal management method based on sales data comprises the following steps:
the method comprises the following steps: establishing a multi-dimensional and multi-object configuration model based on different service scene contents, wherein the multi-dimensional and multi-object configuration model is formed by mutually corresponding the configuration of the same configuration object and the configuration models in multiple configuration dimensions, and mutually corresponding the configuration models in the same configuration dimension and the configuration models in the multiple configuration dimensions;
step two: calculating the extraction of the extraction object under different service scene contents according to the extraction form of the established multi-dimensional multi-object extraction configuration model, which specifically comprises the following steps:
percentage is calculated in the form of: the extracted dimension type is sales amount, gross profit amount is under the constraint sales category, the sum of the money is calculated as the achievement target, the extracted commodity money is multiplied by the percentage as the extracted money, and the accumulated extraction is achieved by combining the calculation of the extracted difference after the steps are met;
calculation of fixed amount withdrawal form: the types of the extracted dimensions are sales volume, gross profit rate, amount of orders, distribution times, service times, return visit completion rate, registered member number and registered member first purchase number, and the extracted dimensions are extracted according to the configured fixed amount after reaching the standard according to corresponding achievement target parameters;
the calculation per unit quantity is taken as the form: the types of the extracted dimensions are sales volume, order number, service times, return visit times, registered member number and registered member first purchase number, and the extracted dimensions are calculated according to the times multiplied by unit times unit price after reaching the standard according to corresponding achievement target parameters;
calculation of long step abstraction form: comparing the maximum steps according to the achieved amount or the number, and calculating and extracting the corresponding extracted value based on the maximum steps;
specific examples of the long steps are: the product sales amount is 2500 yuan, which maximally meets 2000 yuan steps and is increased to 2500 multiplied by 2%;
short step abstraction form of calculation: calculating the maximum step, and calculating the sum of the subtraction difference value of each step and the previous step.
Further, the step of extracting the configuration model in the first step includes: a sales-based offer configuration model, a gross-interest-rate-based offer configuration model, an order-number-based offer configuration model, a delivery-number-based offer configuration model, a service-number-based offer configuration model, a return-visit completion-rate-based offer configuration model, a registered-member-number-based offer configuration model, and a registered-member-first-purchase-number-based offer configuration model.
A sales data-based user proposal management system comprising: the system comprises a local server and a cloud server running user extraction management system software, and an intelligent terminal and a PC terminal running user extraction management system software;
the local server is in communication connection with the cloud server through network communication equipment;
the intelligent terminal is in communication connection with the cloud server through a wireless public network;
the PC terminal is in communication connection with the cloud server through network communication equipment;
wherein, the user's proposition management system includes: the system comprises a lifting configuration module and a multi-dimensional lifting calculation module.
Further, the main function of the extraction configuration module is to establish extraction configuration models under different business scene contents, and the parameter variable indexes of the extraction configuration models include extraction objects, extraction dimension types, extraction targets, extraction ranges and extraction forms.
(III) advantageous technical effects
Compared with the prior art, the invention has the following beneficial technical effects:
the invention establishes the multi-dimensional and multi-object extraction configuration model based on different business scene contents, and calculates the extraction of the extraction object under different business scene contents according to the extraction form of the established multi-dimensional and multi-object extraction configuration model, thereby realizing the technical effect of flexibly and changeably managing and controlling the user business extraction.
Detailed Description
A user submission management system based on sales data comprises a local server and a cloud server running user submission management system software, and an intelligent terminal and a PC terminal running user submission management system software;
the local server is in communication connection with the cloud server through network communication equipment;
the intelligent terminal is in communication connection with the cloud server through a wireless public network;
the PC terminal is in communication connection with the cloud server through network communication equipment;
wherein, the user's proposition management system includes: the system comprises an extraction configuration module and a multi-dimensional extraction calculation module;
the method comprises the following steps that (A) a configuration extracting module is mainly used for establishing configuration extracting models under different business scene contents, and parameter variable indexes of the configuration extracting models comprise extracting objects, extracting dimension types, extracting targets, extracting ranges and extracting forms;
the mentioned drawing objects include individuals, teams and stores;
the extracted dimension types comprise sales amount, commodity sales quantity, gross profit amount, gross profit rate, order number, member return visit times, member return visit completion rate, registered member number, new member number for completing one-time consumption and service hand charge;
the mentioned target is a preset target value which can be set to be a step; the mentioned extracted target supports the target and the non-target simultaneously; specific examples that support this goal are: after buying the number of the milk bottles, the user can take the number of the milk bottles to extract the milk bottles; specific examples of support for non-present targets are: after buying a plurality of paper diapers, the user can take the number of the milk bottles to pick up the disposable diapers;
the drawing range comprises constraint commodities, brands, categories and service cards;
the extraction form supports fixed amount, percentage, unit quantity, long step extraction and short step extraction;
the configuration model under different service scene contents specifically includes:
(1) sales-based referral configuration model: the dimension type is extracted as sales, the sales is a transaction business type document within a statistical time range, and the sales mode is the sum of transaction running amounts of sales and returned goods;
the target value is extracted as the amount of money;
the extraction range is restricted commodity, brand, category and service card;
the form of the extraction is percentage and fixed amount;
(2) and (3) configuring a model based on sales volume: the dimension type is extracted as sales volume which is a transaction business type document in a statistical time range, and the sales mode is the sum of the number of sold and returned commodities;
extracting the target value as quantity;
the extraction range is restricted commodity, brand, category and service card;
the form of the data is a fixed amount and a unit quantity;
(3) the method comprises the following steps of (1) extracting a configuration model based on gross profit amount: the extracted dimension type is gross profit amount which is a transaction business type document within a statistical time range, and the selling mode is the sum of the gross profit amounts of the commodities sold and returned;
the target value is extracted as the amount of money;
the extraction range is restricted commodity, brand, category and service card;
the form of the extraction is percentage and fixed amount;
(4) the method comprises the following steps of (1) extracting a configuration model based on the gross interest rate: the extracted dimension type is the gross profit rate which is a transaction business type document in a statistical time range, and the selling mode is the gross profit rate of goods sold and returned; the gross interest rate is gross interest amount/sales amount (sum of gross interest amount of the associated commodities-sum of return gross interest amount of the associated commodities)/(sum of sales amount of the associated commodities-sum of return gross interest amount of the associated commodities);
extracting the target value as percentage, wherein the value range is 0-1;
the extraction range is restricted commodity, brand, category and service card;
the form of the short step is extracted to be a fixed sum and can not be configured;
(5) configuration model based on the amount of orders: the extracted dimension type is order number which is a transaction business type document in a statistical time range, and the sales mode is sales and return transaction order number; the order number is the sales order number of the associated commodity-the return order number of the associated commodity;
extracting the target value as quantity;
the extraction range is restricted commodity, brand, category and service card;
the form of the data is a fixed amount and a unit quantity;
(6) and (3) a configuration model based on delivery times: the dimension type is extracted as the delivery times, and the delivery times are the sum of the delivery times of the associated commodity transaction flow in the statistical time range and the sum of the associated commodity return orders;
extracting the target value as quantity;
the extraction range is restricted commodity, brand, category and service card;
the form of the data is a fixed amount and a unit quantity;
(7) and (3) an extraction configuration model based on service times: the dimension type is extracted as the service times which is the sum of the service times of service personnel associated with the service item reservation ticket in the statistical time range;
extracting the target value as quantity;
extracting a range as a constraint service card;
the form of the data is a fixed amount and a unit quantity;
(8) and (3) setting a configuration model based on the return visit times: the extracted dimension type is the number of return visits, and the number of return visits is the total number of successful return visits of the consultant in the statistical time range; only counting the return visit subjects with the start-stop dates contained in the date range;
extracting the target value as quantity;
the extraction range is none;
the form of the data is a fixed amount and a unit quantity;
(9) and (3) performing configuration model extraction based on return visit completion rate: the type of the extracted dimension is a return visit completion rate which is the total successful times of the consultant return visit members/the total number of the return visit members associated with the return visit subjects within the statistical time range; only counting the return visit subjects with the start-stop dates contained in the date range;
the extraction target value is percentage, and the value range is 0-1;
the extraction range is none;
the form of the short step is extracted to be a fixed sum and can not be configured;
(10) and (3) a configuration model based on registered membership: the dimension type is provided as the number of registered members, and the number of registered members is the sum of the registration success times of the visit associated members within the statistical time range;
extracting the target value as quantity;
the extraction range is none;
the form of the sum is fixed amount and the amount of each bill;
(11) a configuration model of the first purchase number based on registered members: the extracted dimension type is the number of first purchases of the registered members, the number of first purchases of the registered members is the sum of the number of members who successfully register the visit associated members within the statistical time range and generate the transaction running quantity larger than 1, and the returned goods are correspondingly deducted;
extracting the target value as quantity;
the extraction range is none;
the form of the sum is fixed amount and the amount of each bill;
the function of the multi-dimensional extraction calculation module is mainly to calculate the extraction under different service scene contents based on the established extraction configuration model;
a user proposal management method based on sales data comprises the following steps:
the method comprises the following steps: establishing a multi-dimensional and multi-object configuration model based on different service scene contents, wherein the multi-dimensional and multi-object configuration model is formed by mutually corresponding the configuration of the same configuration object and the configuration models in multiple configuration dimensions, and mutually corresponding the configuration models in the same configuration dimension and the configuration models in the multiple configuration dimensions; namely: the extraction of one or more than one extraction object and one or more than one extraction configuration model are in corresponding relation;
wherein, the configuration model comprises: a sales-based offer configuration model, a gross profit rate-based offer configuration model, an order number-based offer configuration model, a delivery number-based offer configuration model, a service number-based offer configuration model, a return visit completion rate-based offer configuration model, a registered member number-based offer configuration model;
step two: calculating the extraction of the extraction object under different service scene contents according to the extraction form of the established multi-dimensional multi-object extraction configuration model, which specifically comprises the following steps:
percentage is calculated in the form of: the extracted dimension type is sales amount, gross profit amount is under the constraint sales category, the sum of the money is calculated as the achievement target, the extracted commodity money is multiplied by the percentage as the extracted money, and the accumulated extraction is achieved by combining the calculation of the extracted difference after the steps are met;
calculation of fixed amount withdrawal form: the types of the extracted dimensions are sales volume, gross profit rate, amount of orders, distribution times, service times, return visit completion rate, registered member number and registered member first purchase number, and the extracted dimensions are extracted according to the configured fixed amount after reaching the standard according to corresponding achievement target parameters;
the calculation per unit quantity is taken as the form: the types of the extracted dimensions are sales volume, order number, service times, return visit times, registered member number and registered member first purchase number, and the extracted dimensions are calculated according to the times multiplied by unit times unit price after reaching the standard according to corresponding achievement target parameters;
calculation of long step abstraction form: comparing the maximum steps according to the achieved amount or the number, and calculating and extracting the corresponding extracted value based on the maximum steps;
specific examples of the long steps are: the product sales amount is 2500 yuan, which maximally meets 2000 yuan steps and is increased to 2500 multiplied by 2%;
short step abstraction form of calculation: calculating the maximum step, and calculating the sum of subtraction difference lifting values of each previous step and the previous step;
specific examples of short steps are: the product sale is 3500 yuan, which meets the 1000, 2000 and 3000 yuan, and the withdrawal amount is (2000-.
Claims (4)
1. A user proposal management method based on sales data is characterized by comprising the following steps:
the method comprises the following steps: establishing a multi-dimensional and multi-object configuration model based on different service scene contents, wherein the multi-dimensional and multi-object configuration model is formed by mutually corresponding the configuration of the same configuration object and the configuration models in multiple configuration dimensions, and mutually corresponding the configuration models in the same configuration dimension and the configuration models in the multiple configuration dimensions;
step two: calculating the extraction of the extraction object under different service scene contents according to the extraction form of the established multi-dimensional multi-object extraction configuration model, which specifically comprises the following steps:
percentage is calculated in the form of: the extracted dimension type is sales amount, gross profit amount is under the constraint sales category, the sum of the money is calculated as the achievement target, the extracted commodity money is multiplied by the percentage as the extracted money, and the accumulated extraction is achieved by combining the calculation of the extracted difference after the steps are met;
calculation of fixed amount withdrawal form: the types of the extracted dimensions are sales volume, gross profit rate, amount of orders, distribution times, service times, return visit completion rate, registered member number and registered member first purchase number, and the extracted dimensions are extracted according to the configured fixed amount after reaching the standard according to corresponding achievement target parameters;
the calculation per unit quantity is taken as the form: the types of the extracted dimensions are sales volume, order number, service times, return visit times, registered member number and registered member first purchase number, and the extracted dimensions are calculated according to the times multiplied by unit times unit price after reaching the standard according to corresponding achievement target parameters;
calculation of long step abstraction form: comparing the maximum steps according to the achieved amount or the number, and calculating and extracting the corresponding extracted value based on the maximum steps;
specific examples of the long steps are: the product sales amount is 2500 yuan, which maximally meets 2000 yuan steps and is increased to 2500 multiplied by 2%;
short step abstraction form of calculation: calculating the maximum step, and calculating the sum of the subtraction difference value of each step and the previous step.
2. The method according to claim 1, wherein the configuration model of step one comprises: a sales-based offer configuration model, a gross-interest-rate-based offer configuration model, an order-number-based offer configuration model, a delivery-number-based offer configuration model, a service-number-based offer configuration model, a return-visit completion-rate-based offer configuration model, a registered-member-number-based offer configuration model, and a registered-member-first-purchase-number-based offer configuration model.
3. A user proposal management system based on sales data, comprising: the system comprises a local server and a cloud server running user extraction management system software, and an intelligent terminal and a PC terminal running user extraction management system software;
the local server is in communication connection with the cloud server through network communication equipment;
the intelligent terminal is in communication connection with the cloud server through a wireless public network;
the PC terminal is in communication connection with the cloud server through network communication equipment;
wherein, the user's proposition management system includes: the system comprises a lifting configuration module and a multi-dimensional lifting calculation module.
4. The system according to claim 3, wherein the main function of the composition configuration module is to establish composition configuration models under different business scene contents, and the parameter variable indexes of the composition configuration models include composition objects, composition dimension types, composition targets, composition ranges and composition forms.
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| CN201911297427.1A CN111080127A (en) | 2019-12-17 | 2019-12-17 | User extraction management method and system based on sales data |
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| CN201911297427.1A CN111080127A (en) | 2019-12-17 | 2019-12-17 | User extraction management method and system based on sales data |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112288402A (en) * | 2020-10-30 | 2021-01-29 | 康键信息技术（深圳）有限公司 | Data processing method, device, equipment and storage medium |
| CN112734312A (en) * | 2021-03-31 | 2021-04-30 | 平安科技（深圳）有限公司 | Method for outputting reference data and computer equipment |
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2019
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112288402A (en) * | 2020-10-30 | 2021-01-29 | 康键信息技术（深圳）有限公司 | Data processing method, device, equipment and storage medium |
| CN112734312A (en) * | 2021-03-31 | 2021-04-30 | 平安科技（深圳）有限公司 | Method for outputting reference data and computer equipment |
| CN112734312B (en) * | 2021-03-31 | 2021-07-09 | 平安科技（深圳）有限公司 | Method for outputting reference data and computer equipment |
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Application publication date: 20200428 |