Sales management system for mobile communication products

Abstract

The invention provides a sales management system for mobile communication products. The system comprises the steps of collecting inventory state parameters of the mobile communication products; on the basis of the inventory state parameters, sales trend prediction of each sales channel is obtained through calculation; determining a sales strategy optimization function of a preset sales channel according to the sales trend prediction; determining market demand state information of a sales management system of the mobile communication product based on the inventory state parameters; determining a price adjustment function of the preset sales channel according to the market demand state information; determining a sales management gain coefficient of the preset sales channel according to a preset boundary condition, the sales strategy optimization function and the price adjustment function; and based on the sales management gain coefficient, controlling the preset sales channel to optimize the sales management of the mobile communication product. According to the invention, the efficiency of sales management and the market response speed can be improved, and the competitiveness of sales channels is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of mobile communication products, and more specifically, to a sales management system and device for mobile communication products. Background Art

[0002] In the field of mobile communication product sales, with the intensification of market competition and the diversification of consumer demand, the traditional sales management model has been unable to meet the rapidly changing needs of the market. Existing sales management systems often rely on static inventory management and simple sales data analysis, lacking the ability to respond to market dynamics in real time. In addition, these systems often lack flexibility and foresight in the formulation of sales strategies, making it difficult to adapt to changes in market trends, resulting in inventory backlogs or out-of-stock situations.

[0003] The existing technical principles mainly rely on simple statistical analysis of historical sales data, without considering the combined impact of multiple factors such as product prices, inventory, and promotional activities. This leads to low accuracy in sales forecasts and a lack of scientific basis for sales strategy adjustments. At the same time, market price adjustments are usually based on experience rather than systematic analysis, making it difficult to achieve the optimal pricing strategy.

[0004] In the process of implementing the embodiments of the present invention, the inventors found that there are at least the following problems or defects in the prior art: the existing sales management system cannot effectively integrate and analyze multi-source data, resulting in a lack of data support for the formulation of sales strategies; the sales trend prediction model is not precise enough, making it difficult to accurately predict market changes; the sales strategy and price adjustment lack a dynamic optimization mechanism, making it difficult to quickly respond to market changes; the analysis of market demand status information is not in-depth enough, resulting in inaccurate formulation of sales strategies. Summary of the invention

[0005] The invention provides a sales management system and device for mobile communication products.

[0006] In a first aspect of the present invention, there is provided a sales management system for mobile communication products, comprising:

[0007] Collect inventory status parameters of mobile communication products;

[0008] Based on the inventory status parameters, calculate and obtain sales trend forecasts for each sales channel;

[0009] Determine a sales strategy optimization function for a preset sales channel based on the sales trend forecast;

[0010] Based on the inventory status parameters, determining market demand status information of the sales management system of the mobile communication product;

[0011] Determining a price adjustment function of the preset sales channel according to the market demand status information;

[0012] Determining the sales management gain coefficient of the preset sales channel according to the preset boundary conditions, the sales strategy optimization function and the price adjustment function;

[0013] Based on the sales management gain coefficient, the preset sales channel is controlled to optimize the sales management of the mobile communication product.

[0014] Further, the inventory status parameters include: product inventory, product sales rate, first moment inventory status parameters and second moment inventory status parameters;

[0015] The inventory status parameters at the first moment include: one or more of: product model, product price, product inventory, product sales, product return rate, product warranty period and product promotion activities;

[0016] The inventory status parameters at the second moment include: one or more of: product model, product price, product inventory, product sales volume, product return rate, product warranty period and product promotion activities.

[0017] Further, the sales trend forecast includes product demand forecast and market trend forecast;

[0018] Obtaining the sales trend forecast through a sales trend forecasting model;

[0019] The sales trend prediction model includes: a product demand model and a market trend model;

[0020] The calculating of the sales trend forecast based on the inventory status parameter comprises:

[0021] Based on the inventory status parameters, calculate the change trends of product sales volume, product return volume and product inventory volume;

[0022] Determine product demand forecast through a product demand model according to the inventory status parameters, product sales volume, product return volume and product inventory change trends;

[0023] According to the change trends of the inventory status parameters, product sales volume, product return volume and product inventory volume, the market trend forecast is determined through a market trend model.

[0024] Furthermore, the general formula of the product demand model is:

[0025] ΔD=K p ΔP+K i ·ΔI+K l ΔL

[0026] Among them, ΔD is used to characterize the trend forecast generated by product demand, K p , K i , K l They represent the impact coefficients of product price, inventory and promotion activities respectively. ΔP, ΔI and ΔL represent the product price, inventory and promotion intensity after the change respectively.

[0027] The general formula of the market trend model is:

[0028] ΔM=K p ΔP+K i ·ΔI+K l ΔL

[0029] Among them, ΔM is used to characterize the trend forecast generated by market trends, K p , K i , K l They represent the impact coefficients of product price, inventory and promotion activities respectively. ΔP, ΔI and ΔL represent the product price, inventory and promotion intensity after the change respectively.

[0030] Furthermore, the determining of the sales strategy optimization function of the preset sales channel according to the sales trend forecast includes: calculating the product demand forecast of each sales channel according to the product demand model;

[0031] Calculating the market trend forecast of each of the sales channels according to the market trend model;

[0032] Determining a sales trend function for each of the sales channels based on a product demand forecast and a market trend forecast for each of the sales channels;

[0033] Determining a sales strategy optimization index function for each of the sales channels according to the sales trend function of each of the sales channels, wherein the sales strategy optimization index is used to indicate the contribution of the sales channel to the sales management optimization effect;

[0034] A sales strategy optimization function is determined according to the sales strategy optimization indicator function of each of the sales channels.

[0035] Furthermore, the preset sales channel includes a first channel and a second channel;

[0036] The sales trend function of the first channel is specifically:

[0037] ΔD1=K p1 ΔP1+K i1 ΔI1+K l1 ΔL1

[0038] The sales trend function of the second channel is specifically:

[0039] ΔD2=K p2 ΔP2+K i2 ·ΔI2+K l2 ΔL2

[0040] The sales strategy optimization index function is:

[0041]

[0042] Where, ΔD total Forecast of total sales trends.

[0043] The sales strategy optimization function is:

[0044] J1(K1,K2)=log(η1+η2+1)

[0045] Furthermore, the preset sales channel includes a first channel and a second channel;

[0046] The market demand status information is specifically:

[0047]

[0048] Among them, P step is the change in demand, H is the market inertia time constant, D is the market damping coefficient, α i is the weight coefficient of the i-th sales channel, T i is the response time of the i-th sales channel, K SG is the proportion of traditional sales channels, K DFIG is the proportion of direct sales channels; Δω is the market demand disturbance.

[0049] Furthermore, the price adjustment function is:

[0050]

[0051] Among them, Δω max0 It is the difference between the lowest demand response point and the initial demand of the mobile communication product sales management system under the influence of market changes when no sales management is invested; is the solution of the following equation:

[0052]

[0053] Among them, Δω max is the maximum demand deviation, t max is the moment when the system reaches the maximum demand deviation, and m·Δω is the ratio of the two.

[0054] Further, the determining the sales management gain coefficient of the preset sales channel according to the preset boundary conditions, the sales strategy optimization function and the price adjustment function includes: determining the sales strategy optimization function and the price adjustment function as a dual objective function;

[0055] Utilizing the preset boundary conditions, optimizing the dual objective function to obtain the sales management gain coefficient;

[0056] The dual objective function is: maxJ1,J2;

[0057] The preset boundary conditions are:

[0058] J1 is the sales strategy optimization function, J2 is the price adjustment function; P(x)=0 is the inventory equality constraint, ω min is the lower limit of market demand, K max is an empirical constant.

[0059] In a second aspect of the present invention, there is provided a sales management device for mobile communication products, comprising:

[0060] Acquisition module, data processing module and control module;

[0061] The collection module is used to collect inventory status parameters of mobile communication products;

[0062] The data processing module is used to calculate the sales trend forecast through a preset sales trend forecasting model based on the inventory status parameters, and the sales trend forecast is used to indicate the sales trend of the mobile communication product under the state corresponding to the inventory status parameters; determine the sales strategy optimization function of the preset sales channel according to the sales trend forecast; determine the market demand status information of the sales management system of the mobile communication product based on the inventory status parameters; determine the price adjustment function of the preset sales channel according to the market demand status information; determine the sales management gain coefficient of the preset sales channel according to the preset boundary conditions, the sales strategy optimization function and the price adjustment function;

[0063] The control module is used to control the preset sales channel to optimize the sales management of mobile communication products based on the sales management gain coefficient.

[0064] The above-mentioned embodiments of the present invention have at least the following beneficial effects: the sales management system of the present invention can more accurately predict the future sales of products by collecting inventory status parameters of mobile communication products and calculating sales trend forecasts based on these parameters. The system further determines the sales strategy optimization function based on the sales trend forecast, and determines the price adjustment function in combination with the market demand status information, which can effectively optimize the sales strategy and price, thereby improving sales efficiency and market competitiveness. In addition, the system can further optimize the sales management process and realize dynamic adjustment of sales strategies by determining the sales management gain coefficient to control the sales channels.

[0065] The system can also improve the accuracy of forecasts and reduce the risk of inventory backlogs and out-of-stocks by continuously optimizing and adjusting the sales trend forecast model. At the same time, by analyzing market demand status information in real time, sales strategies and prices can be adjusted in a timely manner to adapt to market changes. This dynamic optimization mechanism makes sales management more flexible and efficient, and helps to improve the performance and sales performance of mobile communication products in the market. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] The above and other objects, features and advantages of the exemplary embodiments of the present invention will become readily understood by reading the detailed description below with reference to the accompanying drawings. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-limiting manner, in which:

[0067] Figure 1 A schematic diagram of a flow chart of a sales management system for mobile communication products provided by an embodiment of the present invention;

[0068] Figure 2 A schematic diagram of the structure of a sales management device for mobile communication products provided by an embodiment of the present invention;

[0069] Figure 3 The schematic diagram schematically shows the structure of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0070] The principles and spirit of the present invention will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are provided only to enable those skilled in the art to better understand and implement the present invention, and are not intended to limit the scope of the present invention in any way. On the contrary, these embodiments are provided to make the present invention more thorough and complete, and to fully convey the scope of the present invention to those skilled in the art.

[0071] Those skilled in the art will appreciate that the embodiments of the present invention may be implemented as a system, device, apparatus, method or computer program product. Therefore, the present invention may be implemented in the following forms, namely: complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0072] It should be noted that any number of elements in the drawings is for illustration rather than limitation, and any naming is only for distinction and does not have any limiting meaning.

[0073] Reference below Figure 1 , Figure 1 The following is a flow chart of a sales management system for mobile communication products provided by an embodiment of the present invention. Figure 1 As shown, a sales management system 100 for mobile communication products includes:

[0074] Step 101, collecting inventory status parameters of mobile communication products;

[0075] Step 102, based on the inventory status parameters, calculate and obtain sales trend forecasts for each sales channel;

[0076] Step 103, determining a sales strategy optimization function for a preset sales channel according to the sales trend forecast;

[0077] Step 104, determining the market demand status information of the sales management system of the mobile communication product based on the inventory status parameter;

[0078] Step 105, determining a price adjustment function of the preset sales channel according to the market demand status information;

[0079] Step 106, determining the sales management gain coefficient of the preset sales channel according to the preset boundary conditions, the sales strategy optimization function and the price adjustment function;

[0080] Step 107: Based on the sales management gain coefficient, control the preset sales channel to optimize the sales management of the mobile communication product.

[0081] It should be noted that the system of this embodiment first collects inventory status parameters of mobile communication products, including but not limited to product inventory, sales rate, inventory status parameters at the first moment and the second moment. Through these parameters, the system can monitor and analyze the sales dynamics of products in real time and provide basic data for subsequent sales trend prediction.

[0082] Specifically, inventory status parameters may include information such as product model, product price, product inventory, product sales, product return rate, product warranty period, and product promotion activities. These parameters can be obtained in real time through direct connection between the system and the databases of retailers, distributors, and manufacturers. For example, the system can set parameters such as triggering a replenishment reminder when the product inventory falls below a certain threshold, or adjusting the promotion strategy when the product sales rate exceeds expectations.

[0083] Preferably, the system may further include a collection process, such as automatically updating the inventory status by integrating barcode scanning or RFID technology.

[0084] Furthermore, the system can set up a forecasting model that not only considers the current inventory status parameters, but also combines historical sales data and market trends to predict future sales trends, thereby providing more accurate sales strategy optimization suggestions.

[0085] In some embodiments, the inventory status parameters include: product inventory, product sales rate, first moment inventory status parameters, and second moment inventory status parameters;

[0086] The inventory status parameters at the first moment include: one or more of: product model, product price, product inventory, product sales, product return rate, product warranty period and product promotion activities;

[0087] The inventory status parameters at the second moment include: one or more of: product model, product price, product inventory, product sales volume, product return rate, product warranty period and product promotion activities.

[0088] It should be noted that, in this embodiment, the inventory status parameters collected by the system are further subdivided into parameters at the first moment and the second moment, so as to facilitate more accurate dynamic analysis. The first moment parameter may include the current state of the product, while the second moment parameter may reflect the state of the product after a specific time interval.

[0089] Specifically, the inventory status parameters at the first moment may include product model, product price, product inventory, product sales, product return rate, product warranty period, and product promotion activities. These parameters can be obtained through a real-time data collection system. For example, by integrating with a point-of-sale system POS, the system can automatically update product sales and return rates. The inventory status parameters at the second moment can be predicted or estimated based on the data at the first moment to reflect the expected status at a certain moment in the future.

[0090] Preferably, the system can use time series analysis or machine learning algorithms to predict the inventory status parameters at the second moment. For example, the system can set an algorithm that predicts the inventory status of the next week based on historical sales data and seasonal trends. In addition, the system can also set thresholds, and when the predicted inventory level approaches these thresholds, replenishment or promotion activities are automatically triggered to optimize inventory management.

[0091] In some embodiments, the sales trend forecast includes product demand forecast and market trend forecast;

[0092] Obtaining the sales trend forecast through a sales trend forecasting model;

[0093] The sales trend prediction model includes: a product demand model and a market trend model;

[0094] The calculating of the sales trend forecast based on the inventory status parameter comprises:

[0095] Based on the inventory status parameters, calculate the change trends of product sales volume, product return volume and product inventory volume;

[0096] Determine product demand forecast through a product demand model according to the inventory status parameters, product sales volume, product return volume and product inventory change trends;

[0097] According to the change trends of the inventory status parameters, product sales volume, product return volume and product inventory volume, the market trend forecast is determined through a market trend model.

[0098] It should be noted that in this embodiment, sales trend forecasting is one of the core functions of the system, which includes two parts: product demand forecasting and market trend forecasting. The system uses the sales trend forecasting model to predict future sales by analyzing the collected inventory status parameters.

[0099] Specifically, a product demand forecasting model can predict the future demand for a specific product based on historical sales data, market research results, and consumer behavior analysis. Market trend forecasting models can take into account macroeconomic factors, industry dynamics, and competitor strategies. These models can be implemented through statistical analysis, machine learning, or artificial intelligence algorithms. For example, the system can set up an algorithm that uses regression analysis to predict product sales and time series analysis to predict market trends.

[0100] Preferably, the system may further include a sales trend prediction model, for example, by integrating social media analysis to capture consumer sentiment and market hot spots, so as to more accurately predict market trends.

[0101] Furthermore, the system can also set up a feedback mechanism to continuously adjust and optimize the parameters of the forecast model according to actual sales results to improve the accuracy of the forecast. It is also possible to consider introducing external data sources, such as weather data, holiday schedules, etc., which can also affect product demand and market trends.

[0102] In some embodiments, the product demand model is generally formulated as follows:

[0103] ΔD=K p ΔP+K i ·ΔI+K l ΔL

[0104] Among them, ΔD is used to characterize the trend forecast generated by product demand, K p , K i , K l They represent the impact coefficients of product price, inventory and promotion activities respectively. ΔP, ΔI and ΔL represent the product price, inventory and promotion intensity after the change respectively.

[0105] The general formula of the market trend model is:

[0106] ΔM=K p ΔP+K i ·ΔI+K l ΔL

[0107] Among them, ΔM is used to characterize the trend forecast generated by market trends, K p , K i , K l They represent the impact coefficients of product price, inventory and promotion activities respectively. ΔP, ΔI and ΔL represent the product price, inventory and promotion intensity after the change respectively.

[0108] It should be noted that in this embodiment, the product demand model and the market trend model are the core components of the sales trend forecast. These two models quantify the product demand and market trend through specific formulas to predict future sales.

[0109] Specifically, the product demand model can be expressed as follows:

[0110] PD=α·P+β·S+γ·M

[0111] Among them, PD represents the predicted product demand, P, S, and M represent the influence coefficients of product price, inventory, and promotion intensity respectively. α, β, and γ represent the changed product price, inventory, and promotion intensity respectively. These parameters can be determined through market research, historical sales data analysis, and promotion effect evaluation.

[0112] A similar formula can be used for the market trend model:

[0113] MT=δ·P+∈·S+ζ·M

[0114] Among them, MT represents the predicted market trend, δ, ∈, ζ represent the influence coefficients of product price, inventory and promotion activities on market trend respectively. The setting of these parameters is also based on market analysis and historical data.

[0115] Preferably, the system can use advanced data analysis techniques, such as machine learning algorithms, to automatically adjust and optimize the parameters of these models. For example, a neural network can be used to learn the relationship between price, inventory, and promotional activities and sales volume, and predict future sales trends.

[0116] Furthermore, the system can also set up an adaptive mechanism to dynamically adjust model parameters according to market feedback and changes in sales data to improve the accuracy of predictions and the ability to respond to market changes.

[0117] In some embodiments, determining the sales strategy optimization function of the preset sales channel according to the sales trend forecast includes: calculating the product demand forecast of each sales channel according to the product demand model;

[0118] Calculating the market trend forecast of each of the sales channels according to the market trend model;

[0119] Determining a sales trend function for each of the sales channels based on a product demand forecast and a market trend forecast for each of the sales channels;

[0120] Determining a sales strategy optimization index function for each of the sales channels according to the sales trend function of each of the sales channels, wherein the sales strategy optimization index is used to indicate the contribution of the sales channel to the sales management optimization effect;

[0121] A sales strategy optimization function is determined according to the sales strategy optimization indicator function of each of the sales channels.

[0122] It should be noted that, in this embodiment, the determination of the sales strategy optimization function is achieved by analyzing product demand forecasts and market trend forecasts. This step involves converting the forecast results into specific sales strategies to optimize the performance of sales channels.

[0123] Specifically, the sales strategy optimization function may include the following steps:

[0124] 1. Based on the product demand model, calculate the product demand forecast for each sales channel.

[0125] 2. Based on the market trend model, calculate the market trend forecast for each sales channel separately.

[0126] 3. Combine product demand forecast and market trend forecast to determine the sales trend function for each sales channel.

[0127] 4. Based on the sales trend function, determine the sales strategy optimization indicator function, which indicates the contribution of the sales channel to the sales management optimization effect.

[0128] 5. Based on the sales strategy optimization indicator function, determine the final sales strategy optimization function.

[0129] Preferably, the system can use a multi-objective optimization algorithm to determine the sales strategy optimization function. For example, a genetic algorithm or a particle swarm optimization algorithm can be used to find the best sales strategy, which can find the optimal sales strategy while meeting multiple goals, such as maximizing sales and minimizing inventory costs.

[0130] Furthermore, the system can also set up a module to simulate the market environment for testing and evaluating new sales strategies before implementation to ensure the effectiveness of the strategies.

[0131] In some embodiments, the preset sales channel includes a first channel and a second channel;

[0132] The sales trend function of the first channel is specifically:

[0133] ΔD1=K p1 ΔP1+K i1 ΔI1+K l1 ΔL1

[0134] The sales trend function of the second channel is specifically:

[0135] ΔD2=K p2 ΔP2+K i2 ΔI2+K l2 ΔL2

[0136] The sales strategy optimization index function is:

[0137]

[0138] Where, ΔD total Forecast of total sales trends.

[0139] The sales strategy optimization function is:

[0140] J1(K1,K2)=log(η1+η2+1)

[0141] It should be noted that, in this embodiment, the preset sales channels are divided into a first channel and a second channel, and each channel has its own specific sales trend function. These functions are used to predict the sales situation of each channel and provide a basis for optimizing sales strategies.

[0142] Specifically, the sales trend functions of the first channel and the second channel may have the following forms:

[0143] Sales trend function of the first channel: ST1 = a1·P1+b1·S1+c1·M1

[0144] Sales trend function of the second channel: ST2 = a2·P2+b2·S2+c2·M2

[0145] Among them, ST1 and ST2 represent the sales trends of the first channel and the second channel respectively, P1 and P2 represent product prices, S1 and S2 represent inventory levels, and m1 and m2 represent the intensity of promotion activities. The coefficients a1, b1, c1 and a2, b2, c2 can be obtained through the analysis of historical sales data, reflecting the sensitivity of different channels to price, inventory and promotion activities.

[0146] Preferably, the system may further include a sales strategy optimization indicator function, for example:

[0147] The sales strategy optimization index function of the first channel: O1 = f1 (ST1)

[0148] The sales strategy optimization index function of the second channel: O2 = f2 (ST2)

[0149] Among them, f1 and f2 are functions for adjusting sales strategies based on sales trend forecasts, which can be linear or nonlinear, and are used to indicate the contribution of each channel to the sales management optimization effect. These functions can be dynamically adjusted based on market feedback and sales data to improve the adaptability and effectiveness of sales strategies.

[0150] More specifically, the system can use machine learning models to automatically learn and adjust these optimization indicator functions. For example, a decision tree or random forest algorithm can be used to analyze the impact of different sales strategies on sales trends, and the sales strategy optimization indicator function can be adjusted accordingly.

[0151] Furthermore, the system can also set up a real-time monitoring module to track the actual effect of the sales strategy after implementation, and further optimize the sales strategy based on this feedback information.

[0152] In some embodiments, the preset sales channel includes a first channel and a second channel;

[0153] The market demand status information is specifically:

[0154]

[0155] Among them, P step is the change in demand, H is the market inertia time constant, D is the market damping coefficient, α i is the weight coefficient of the i-th sales channel, T i is the response time of the i-th sales channel, K SG is the proportion of traditional sales channels, K DFIG is the proportion of direct sales channels; Δω is the market demand disturbance.

[0156] It should be noted that, in this embodiment, the determination of the market demand status information is achieved by comprehensively considering the weights and response times of multiple sales channels. This method can more accurately reflect the actual market demand and provide a basis for price adjustment.

[0157] Specifically, the market demand status information can be calculated by the following formula:

[0158]

[0159] Among them, MD represents the market demand status information, k is the market inertia time constant, and w i is the weight coefficient of the i-th sales channel, θ i is the response time of the ith sales channel, t is the time variable, and Δ is the market demand disturbance. These parameters can be determined through market research, historical sales data analysis, and feedback from sales channels.

[0160] Preferably, the system may further include a price adjustment function, for example:

[0161] PA(P1,P2)=D0-λ1·P1+λ2·P2

[0162] Among them, PA represents the price adjustment function, D0 is the difference between the lowest point of demand response and the initial demand when no sales management is invested, λ1 and λ2 are adjustment coefficients, and P1 and P2 are the prices of the first channel and the second channel respectively. These coefficients can be optimized through market testing and sales data analysis to achieve the best sales effect.

[0163] More specifically, the system can use dynamic programming or reinforcement learning algorithms to dynamically adjust the parameters of the price adjustment function. For example, the values ​​of λ1 and λ2 can be automatically adjusted according to market feedback and changes in sales data to achieve the optimal pricing strategy. In addition, the system can also set up a module to simulate the market environment for testing and evaluation before implementing a new pricing strategy to ensure the effectiveness of the strategy.

[0164] In some embodiments, the price adjustment function is:

[0165]

[0166] Among them, Δω max0 It is the difference between the lowest demand response point and the initial demand of the mobile communication product sales management system under the influence of market changes when no sales management is invested; is the solution of the following equation:

[0167]

[0168] Among them, Δω max is the maximum demand deviation, t max is the moment when the system reaches the maximum demand deviation, and m·Δω is the ratio of the two.

[0169] It should be noted that, in this embodiment, the determination of the sales management gain coefficient involves optimizing the sales strategy optimization function and the price adjustment function as a dual objective function. This step aims to balance the relationship between sales strategy optimization and price adjustment to maximize the overall gain of sales management.

[0170] Specifically, the dual objective function can be expressed as:

[0171] F=(f1(ST),f2(PA))

[0172] Among them, f1 and f2 are the sales strategy optimization function and price adjustment function respectively, ST represents the sales trend, and PA represents the price adjustment. These two functions need to be considered simultaneously to find the best sales strategy and price adjustment plan. The preset boundary conditions can include inventory equality constraints, market demand lower limits, and empirical constants.

[0173] Preferably, the system can use a multi-objective optimization algorithm, such as a genetic algorithm, a particle swarm optimization or a multi-objective evolutionary algorithm, to find the optimal solution to the dual-objective function. These algorithms can find the best balance between sales strategy optimization and price adjustment while satisfying the preset boundary conditions.

[0174] More specifically, the system can set up an optimization framework, which includes the following steps:

[0175] 1. Define the objective function and constraints.

[0176] 2. Choose a suitable multi-objective optimization algorithm.

[0177] 3. Run the algorithm to find the optimal solution.

[0178] 4. Adjust sales strategies and prices based on the optimal solution.

[0179] 5. Monitor implementation results and make adjustments based on feedback.

[0180] In addition, the system can also introduce a real-time data feedback mechanism to dynamically adjust the parameters of the optimization algorithm to ensure that the sales management gain coefficient can adapt to market changes. It can also consider introducing external factors such as seasonal changes and economic conditions to further improve the accuracy and effectiveness of optimization.

[0181] In some embodiments, determining the sales management gain coefficient of the preset sales channel according to the preset boundary conditions, the sales strategy optimization function and the price adjustment function includes: determining the sales strategy optimization function and the price adjustment function as a dual objective function;

[0182] Utilizing the preset boundary conditions, optimizing the dual objective function to obtain the sales management gain coefficient;

[0183] The dual objective function is: maxJ1,J2;

[0184] The preset boundary conditions are:

[0185] J1 is the sales strategy optimization function, J2 is the price adjustment function; P(x)=0 is the inventory equality constraint, ω min is the lower limit of market demand, K max is an empirical constant.

[0186] It should be noted that in this embodiment, the sales management device is a system integrating multiple modules, which is used to realize the automation and optimization of mobile communication product sales management. The device optimizes the sales management process by collecting and processing data and controlling sales channels.

[0187] Specifically, the sales management device includes the following key modules:

[0188] 1. Collection module: used to collect inventory status parameters of mobile communication products.

[0189] 2. Data processing module: Based on the collected data, the sales trend forecast is calculated through the preset sales trend forecast model, and the sales strategy optimization function and price adjustment function are determined.

[0190] 3. Control module: According to the sales management gain coefficient, control the sales channels to optimize sales management.

[0191] These modules work together to ensure that every aspect of sales management can be optimized based on real-time data and predictive models.

[0192] Preferably, the sales management device may further include its functions and operation steps, for example:

[0193] 1. The acquisition module can be integrated with a barcode scanner, RFID reader or integrated with an enterprise resource planning ERP system to automatically collect inventory data.

[0194] 2. The data processing module can adopt advanced data analysis technologies, such as machine learning algorithms, to improve the accuracy of sales trend forecasts and automatically adjust sales strategies and prices based on the forecast results.

[0195] 3. The control module can be set to monitor sales in real time and dynamically adjust sales strategies based on market feedback and changes in sales data.

[0196] More specifically, the device can introduce UI and UX design, so that operators can easily monitor sales, adjust parameters and implement sales strategies. In addition, the device can also integrate report generation tools to facilitate management to analyze sales data and evaluate the effectiveness of sales strategies. In order to improve the adaptability and flexibility of the system, it is also possible to consider developing a mobile application that allows sales staff to update inventory status and sales in real time on the spot.

[0197] The above-mentioned embodiments of the present invention have the following beneficial effects: the mobile communication product sales management system of the present invention can provide a sales management strategy that comprehensively considers inventory status, sales trend forecast, market demand status information and price adjustment. By collecting and analyzing inventory status parameters, the system can accurately calculate the sales trend forecast, and then determine the sales strategy optimization function and price adjustment function. This data-driven method can improve the accuracy of sales forecasts, optimize sales strategies, improve sales efficiency, and effectively control inventory levels, reducing the risk of inventory backlogs and out-of-stocks.

[0198] In addition, the system can optimize sales channels and realize dynamic adjustment of sales management by determining the sales management gain coefficient. This method can enhance the adaptability and flexibility of sales channels, enable them to respond quickly to market changes, and improve the competitiveness of sales channels. At the same time, by accurately adjusting prices, it can better meet market demand, improve customer satisfaction, increase market share, and bring economic benefits to the sales of mobile communication products.

[0199] like Figure 2 As shown, in some embodiments, a sales management device 200 for mobile communication products includes:

[0200] Acquisition module, data processing module and control module;

[0201] The collection module is used to collect inventory status parameters of mobile communication products;

[0202] The data processing module is used to calculate the sales trend forecast through a preset sales trend forecasting model based on the inventory status parameters, and the sales trend forecast is used to indicate the sales trend of the mobile communication product under the state corresponding to the inventory status parameters; determine the sales strategy optimization function of the preset sales channel according to the sales trend forecast; determine the market demand status information of the sales management system of the mobile communication product based on the inventory status parameters; determine the price adjustment function of the preset sales channel according to the market demand status information; determine the sales management gain coefficient of the preset sales channel according to the preset boundary conditions, the sales strategy optimization function and the price adjustment function;

[0203] The control module is used to control the preset sales channel to optimize the sales management of mobile communication products based on the sales management gain coefficient.

[0204] It is understandable that the modules recorded in the sales management device 200 for mobile communication products are similar to those in the reference Figure 1 Therefore, the operations, features and beneficial effects described above for the sales management system for mobile communication products are also applicable to the sales management device 200 for mobile communication products and the modules contained therein, and will not be repeated here.

[0205] Reference below Figure 3 , which shows a schematic diagram of a structure 300 of an electronic device suitable for implementing some embodiments of the present invention. The electronic devices in some embodiments of the present invention may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 3 The terminal device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0206] like Figure 3 As shown, the electronic device 300 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the electronic device 300 are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0207] Typically, the following devices may be connected to the I / O interface 305: input devices 306 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 307 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 308 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 309. The communication devices 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 3 The electronic device 300 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead. Figure 3 Each block shown in the figure may represent one device, or may represent multiple devices as required.

[0208] Furthermore, the storage medium of the embodiment of the present application stores program instructions that can implement all the above methods, wherein the program instructions can be stored in the above storage medium in the form of a software product, including several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or terminal devices such as a computer, a server, a mobile phone, and a tablet.

[0209] The above descriptions are only some preferred embodiments of the present invention and an explanation of the technical principles used. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present invention is not limited to the technical solutions formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above inventive concept. For example, the above features are replaced with (but not limited to) technical features with similar functions disclosed in the embodiments of the present invention to form a technical solution.

Claims

1. A sales management system for mobile communication products, characterized in that: The system performs the following steps, including: Collect inventory status parameters of mobile communication products; Based on the inventory status parameters, calculate and obtain sales trend forecasts for each sales channel; Determine a sales strategy optimization function for a preset sales channel based on the sales trend forecast; Based on the inventory status parameters, determining market demand status information of the sales management system of the mobile communication product; Determining a price adjustment function of the preset sales channel according to the market demand status information; Determining the sales management gain coefficient of the preset sales channel according to the preset boundary conditions, the sales strategy optimization function and the price adjustment function; Based on the sales management gain coefficient, the preset sales channel is controlled to optimize the sales management of the mobile communication product.

2. The system according to claim 1, characterized in that: The inventory status parameters include: product inventory, product sales rate, first moment inventory status parameters and second moment inventory status parameters; The inventory status parameters at the first moment include: one or more of: product model, product price, product inventory, product sales, product return rate, product warranty period and product promotion activities; The inventory status parameters at the second moment include: one or more of: product model, product price, product inventory, product sales volume, product return rate, product warranty period and product promotion activities.

3. The system according to claim 1, characterized in that The sales trend forecast includes product demand forecast and market trend forecast; Obtaining the sales trend forecast through a sales trend forecasting model; The sales trend prediction model includes: a product demand model and a market trend model; The calculating of the sales trend forecast based on the inventory status parameter comprises: Based on the inventory status parameters, calculate the change trends of product sales volume, product return volume and product inventory volume; Determine product demand forecast through a product demand model according to the inventory status parameters, product sales volume, product return volume and product inventory change trends; According to the change trends of the inventory status parameters, product sales volume, product return volume and product inventory volume, the market trend forecast is determined through a market trend model.

4. The system according to claim 3, characterized in that The general formula of the product demand model is: ΔD=K p ·ΔP+K i ·ΔI+K l ·ΔL Among them, ΔD is used to characterize the trend forecast generated by product demand, K p , K i , K l They represent the impact coefficients of product price, inventory and promotion activities respectively. ΔP, ΔI and ΔL represent the product price, inventory and promotion intensity after the change respectively. The general formula of the market trend model is: ΔM=K p ·ΔP+K i ·ΔI+K l ·ΔL Among them, ΔM is used to characterize the trend forecast generated by market trends, K p , K i , K l They represent the impact coefficients of product price, inventory and promotion activities respectively. ΔP, ΔI and ΔL represent the product price, inventory and promotion intensity after the change respectively.

5. The system according to claim 3, characterized in that The step of determining the sales strategy optimization function of the preset sales channel according to the sales trend forecast includes: calculating the product demand forecast of each sales channel according to the product demand model; Calculating the market trend forecast of each of the sales channels according to the market trend model; Determining a sales trend function for each of the sales channels based on a product demand forecast and a market trend forecast for each of the sales channels; Determining a sales strategy optimization index function for each of the sales channels according to the sales trend function of each of the sales channels, wherein the sales strategy optimization index is used to indicate the contribution of the sales channel to the sales management optimization effect; A sales strategy optimization function is determined according to the sales strategy optimization indicator function of each of the sales channels.

6. The system according to claim 5, characterized in that The preset sales channels include a first channel and a second channel; The sales trend function of the first channel is specifically: ΔD1=K p1 ·ΔP1+K i1 ·ΔI1+K l1 ·ΔL1 The sales trend function of the second channel is specifically: ΔD2=K p2 ·ΔP2+K i2 ·ΔI2+K l2 ·ΔL2 The sales strategy optimization index function is: Where, ΔD total Forecast of total sales trends. The sales strategy optimization function is: J1(K1,K2)=log(eta1+eta2+1).

7. The system according to any one of claims 1 to 6, characterized in that: The preset sales channels include a first channel and a second channel; The market demand status information is specifically: Among them, P step is the change in demand, H is the market inertia time constant, D is the market damping coefficient, α i is the weight coefficient of the i-th sales channel, T i is the response time of the i-th sales channel, K SG is the proportion of traditional sales channels, K DFIG is the proportion of direct sales channels; Δω is the market demand disturbance.

8. The system according to claim 7, characterized in that The price adjustment function is: Among them, Δω max0 It is the difference between the lowest demand response point and the initial demand of the mobile communication product sales management system under the influence of market changes when no sales management is invested; is the solution of the following equation: Among them, Δω max is the maximum demand deviation, t max is the moment when the system reaches the maximum demand deviation, and m·Δω is the ratio of the two.

9. The system according to any one of claims 3 to 8, characterized in that: The step of determining the sales management gain coefficient of the preset sales channel according to the preset boundary conditions, the sales strategy optimization function and the price adjustment function comprises: determining the sales strategy optimization function and the price adjustment function as a dual objective function; Utilizing the preset boundary conditions, optimizing the dual objective function to obtain the sales management gain coefficient; The dual objective function is: maxJ1, J2; The preset boundary conditions are: J1 is the sales strategy optimization function, J2 is the price adjustment function; P(x)=0 is the inventory equality constraint, ω min is the lower limit of market demand, K max is an empirical constant.

10. A sales management device for mobile communication products, characterized in that: include: Acquisition module, data processing module and control module; The collection module is used to collect inventory status parameters of mobile communication products; The data processing module is used to calculate the sales trend forecast based on the inventory status parameter through a preset sales trend forecast model, and the sales trend forecast is used to indicate the sales trend of the mobile communication product under the state corresponding to the inventory status parameter; Determine a sales strategy optimization function for a preset sales channel based on the sales trend forecast; Based on the inventory status parameter, determining the market demand status information of the sales management system of the mobile communication product; determining the price adjustment function of the preset sales channel according to the market demand status information; Determining the sales management gain coefficient of the preset sales channel according to the preset boundary conditions, the sales strategy optimization function and the price adjustment function; The control module is used to control the preset sales channel to optimize the sales management of mobile communication products based on the sales management gain coefficient.

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