Intelligent soft package sales prediction system

Abstract

The invention relates to an intelligent soft package sales prediction system, and the system comprises a data collection and edge calculation module which is used for obtaining the sales data of a sales terminal and transmitting the sales data to an edge calculation node for processing; the data service module is used for managing and controlling the point-of-sale sales data and the affiliated data; the intelligent analysis module is used for performing historical sales analysis and historical sales external factor analysis on the soft package sales data and generating a prediction report and a model; and the visual application module is used for converting the data into a form which is easy to understand and analyze and displaying the data on a terminal. Based on artificial intelligence and a big data technology, an accurate sales prediction model is constructed by collecting and analyzing various data sources of historical sales and the like of the home soft decoration industry, and home soft decoration enterprises are helped to better predict sales conditions and market trends, so that sales strategies and decisions are made.

Description

Technical Field

[0001] The present invention relates to the field of sales forecasting, and in particular to a sales forecasting system applied to the soft furnishing industry or other retail industries with similar change rules. Background Art

[0002] The domestic soft furnishing market started late. It has only been in the past decade that soft furnishing art accessories have been accepted by society, and the industry attributes are not mature. In recent years, the industry has grown several times faster under the stimulation of profits. It will be a huge industrial chain. Art accessories, as an important part of soft furnishing, are characterized by "younger, more professional, and more specialized". The market potential is also very huge. This type of demand is very typical in second- and third-tier cities.

[0003] Sales forecasting refers to the prediction and estimation of sales in the future by analyzing market trends, competition, product characteristics and other factors. The intelligent soft furnishing sales forecasting system can make sales forecasts by analyzing historical sales data and market data, helping soft furnishing companies to better understand market demand and sales trends and formulate more scientific and effective sales plans and strategies. The significance of sales forecasting is that it can help companies prepare for the market in advance, reduce inventory costs and risks, and improve sales efficiency and profitability. Summary of the invention

[0004] In view of this, the present invention provides an intelligent soft furnishing sales forecasting system, which can build an accurate sales forecasting model by collecting and analyzing various data sources such as historical sales of the home furnishing soft furnishing industry, so as to help home furnishing soft furnishing companies better predict sales and market trends, and thus formulate sales strategies and decisions.

[0005] The above-mentioned object of the present invention is achieved by the following technical solution: an intelligent soft furnishing sales forecasting system, characterized in that it includes: Data collection and edge computing module, used to obtain sales data from sales terminals and transmit it to edge computing nodes for processing; Data service module, used to manage and control point-of-sale sales data and ancillary data; Intelligent analysis module, used to analyze the historical sales data and external factors of the historical sales of soft furnishings and generate forecast reports and models; The visualization application module is used to convert data into a form that is easy to understand and analyze and present it on the terminal.

[0006] The edge computing modules typically perform computing at the edge of a device or network to reduce latency and network traffic in data transmission to the cloud; these modules can process data using various machine learning and artificial intelligence algorithms to provide real-time decisions and feedback; edge computing modules can also be used to encrypt and securely process data to ensure data privacy and security.

[0007] The sales data is transmitted through various transmission protocols, including MQTT, CoAP, HTTP, etc.

[0008] In the intelligent soft decoration sales forecasting system described in the present invention, the data service module includes system integration such as MES and ERP: the MES system is mainly used for the management and control of the soft decoration production process, including production planning, work order management, production scheduling, quality management, equipment management, etc.; the ERP system is mainly used for the management and planning of enterprise resources, including sales management, procurement management, inventory management, financial management, etc.

[0009] In the intelligent soft furnishing sales forecasting system of the present invention, the data service module includes the following functions: Data integration: Integrate and convert data from different sales terminals; Data storage: Store data in reliable and efficient data storage systems, including relational databases, NoSQL databases, etc. Data processing: processing and converting data, such as data cleaning, data conversion, data aggregation, etc.; Data security: Provide data security and access control mechanisms to ensure data privacy and security.

[0010] In the intelligent soft furnishing sales forecasting system described in the present invention, the historical sales external factors include multiple data sources such as market trend data of the soft furnishing industry and customer behavior data.

[0011] Customer behavior data includes customer behaviors and preferences as well as unstructured data such as customer feedback and comments.

[0012] In the intelligent soft furnishing sales forecasting system of the present invention, the generation of forecast reports and models is specifically as follows: Collect and analyze various data sources such as historical sales data, market trend data, customer behavior data, etc. of the home furnishing industry; Use technologies such as machine learning and deep learning to generate forecast reports and build accurate soft furnishing sales forecast models.

[0013] In the intelligent soft furnishing sales forecasting system of the present invention, the main functions of the visualization application module include: Data visualization: Visualize and present data to users to help them understand and analyze the data; Charts and Graphs: Use visualization elements such as charts and graphs to transform data into a form that is easy to understand and analyze; Interactive visualization: Use interactive visualizations to allow users to freely explore and analyze data to gain deeper insights; Data dashboard: Use data dashboards to visualize key indicators and data to help users better monitor and manage data. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 is a schematic diagram of an intelligent soft furnishing sales forecasting system in an embodiment of the present invention;

[0015] Figure 2 is a schematic diagram of an edge computing module of an intelligent soft furnishing sales prediction system in an embodiment of the present invention;

[0016] Figure 3 It is a structural diagram of the data service module of the intelligent soft furnishing sales forecasting system in an embodiment of the present invention. Figure 4 It is a flow chart of the visualization application module of the intelligent soft furnishing sales forecasting system in an embodiment of the present invention. Implementation

[0017] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments.

[0018] like Figure 1 FIG. 1 is a schematic diagram of an intelligent soft furnishing sales forecasting system in an embodiment of the present invention. The intelligent soft furnishing sales forecasting system provided by the present invention mainly includes a data collection and edge computing module, a data service module, an intelligent analysis module and a visualization application module.

[0019] In the embodiment provided by the present invention, the system communicates with multiple service terminals set up at the sales point and provides a comprehensive operation platform for users through the terminals. The intelligent soft decoration sales forecasting system can communicate with the service terminals of these sales points. In this embodiment, the intelligent soft decoration sales forecasting system can communicate with sales terminal 1, sales terminal 2, etc. and obtain sales data from these terminals.

[0020] like Figure 2 As shown, the edge computing module in the intelligent soft furnishing sales prediction system provided by the present invention mainly includes an edge device, a communication module, a security module, an edge computing module and a shared database.

[0021] The edge computing modules typically perform computing at the edge of a device or network to reduce latency and network traffic in data transmission to the cloud; these modules can process data using various machine learning and artificial intelligence algorithms to provide real-time decisions and feedback; edge computing modules can also be used to encrypt and securely process data to ensure data privacy and security.

[0022] The data collection and edge computing module is connected to the data service module to process the point-of-sale sales data in the sales forecast database and manage the obtained sales data and ancillary data. In the embodiment provided by the present invention, the sales data includes information such as sales volume and sales category. The ancillary data includes store data and promotion data.

[0023] In the intelligent soft furnishing sales forecasting system described in the present invention, sales data is transmitted through various transmission protocols, including MQTT, CoAP, HTTP, etc.

[0024] like Figure 3 As shown, in the intelligent soft furnishing sales forecasting system of the present invention, the data service module includes MES, ERP and other system integrations: The MES system is mainly used for the management and control of the soft furnishing production process, including production planning, work order management, production scheduling, quality management, equipment management, etc. The ERP system is mainly used for the management and planning of enterprise resources, including sales management, procurement management, inventory management, financial management, etc. The PDM system manages and controls product data, including data on product design, manufacturing, maintenance, quality control, etc.

[0025] The intelligent analysis module is connected to the data collection and edge computing module and the data service module, and is used to perform historical sales analysis and external factor analysis of historical sales on the sales data and the ancillary data. In the embodiment provided by the present invention, these external factors include factors such as the number of stores and promotion activities. The intelligent analysis module performs historical sales analysis and external factor analysis of historical sales on the sales data on an annual basis, and can also perform historical sales analysis and external factor analysis of historical sales on the sales data based on the sales point.

[0026] In the embodiment provided by the present invention, historical sales analysis obtains sales data by analyzing sales situations at sales points, including sales amount, sales volume, customer information, product information, etc.

[0027] In the embodiment provided by the present invention, the intelligent analysis module will generate a forecast report and model for sales forecasting based on the results of historical sales analysis and external factor analysis of historical sales. The forecast report can be a sales forecast made according to the year. Since soft furnishing sales data has a high demand uncertainty, this module uses machine learning and deep learning technologies to develop a nonlinear fashion sales forecast model and generate an objective and reliable soft furnishing sales plan to assist soft furnishing companies in their sales forecasting decision-making process. The forecasting model adopts a top-down forecasting method, that is, first predicting the annual sales of the entire company, and then on this basis, through historical proportion analysis, predicting the annual sales of each sales point of the company.

[0028] The visualization application module is connected to the data acquisition and edge computing module, the data service module, and the intelligent analysis module. Figure 4 As shown, in the embodiment provided by the present invention, the visualization application module uses visualization elements such as charts and graphs to convert data into a form that is easy to understand and analyze; the terminal visualizes and presents the data to the user to help the user understand and analyze the data; using interactive visualization, the user can freely explore and analyze the data to gain deeper insights; the data dashboard visualizes key indicators and data to help users better monitor and manage data.

[0029] In summary, the intelligent fashion sales forecasting system provided by the present invention collects and analyzes various data sources such as historical sales of the home furnishing industry, uses heuristic and error back propagation neural network technology to provide accurate and reliable mid-term sales forecasts for soft furnishing companies to conduct sales forecasting activities, and builds an accurate sales forecasting model to help home furnishing companies better predict sales and market trends, thereby formulating sales strategies and decisions. The system can also be further improved to meet the sales forecasting needs of various retail companies.

[0030] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and embodiments, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. An intelligent soft furnishing sales forecasting system, It is characterized in that include: Data collection and edge computing module, used to obtain sales data from sales terminals and transmit it to edge computing nodes for processing; Data service module, used to manage and control point-of-sale sales data and ancillary data; Intelligent analysis module, used to analyze the historical sales data and external factors of the historical sales of soft furnishings and generate forecast reports and models; The visualization application module is used to convert data into a form that is easy to understand and analyze and present it on the terminal.

2. The intelligent soft furnishing sales forecasting system according to claim 1, It is characterized in that The edge computing modules typically perform computing at the edge of a device or network to reduce latency and network traffic in data transmission to the cloud; these modules can process data using various machine learning and artificial intelligence algorithms to provide real-time decisions and feedback; edge computing modules can also be used to encrypt and securely process data to ensure data privacy and security.

3. The intelligent soft furnishing sales forecasting system according to claim 1, It is characterized in that The sales data is transmitted through various transmission protocols, including MQTT, CoAP, HTTP, etc.

4. The intelligent soft furnishing sales forecasting system according to claim 1, It is characterized in that The data service module includes MES, ERP and other system integration: The MES system is mainly used for the management and control of the soft furnishing production process, including production planning, work order management, production scheduling, quality management, equipment management, etc. The ERP system is mainly used for the management and planning of enterprise resources, including sales management, procurement management, inventory management, financial management, etc.

5. The intelligent soft furnishing sales forecasting system according to claim 1, It is characterized in that The data service module includes the following functions: Data integration: Integrate and convert data from different sales terminals; Data storage: Store data in reliable and efficient data storage systems, including relational databases, NoSQL databases, etc. Data processing: processing and converting data, such as data cleaning, data conversion, data aggregation, etc.; Data security: Provide data security and access control mechanisms to ensure data privacy and security.

6. The intelligent soft furnishing sales forecasting system according to claim 1, It is characterized in that Historical sales external factors include market trend data of the soft furnishing industry, customer behavior data and other data sources.

7. The intelligent soft furnishing sales forecasting system according to claim 6, It is characterized in that Customer behavior data includes customer behaviors and preferences as well as unstructured data such as customer feedback and comments.

8. The intelligent soft furnishing sales forecasting system according to claim 1, It is characterized in that The generation of the forecast report and model is specifically as follows: Collect and analyze various data sources such as historical sales data, market trend data, customer behavior data, etc. of the home furnishing industry; Use technologies such as machine learning and deep learning to generate forecast reports and build accurate soft furnishing sales forecast models.

9. The intelligent soft furnishing sales forecasting system according to claim 1, It is characterized in that The main functions of the visualization application module include: Data visualization: Visualize and present data to users to help them understand and analyze the data; Charts and Graphs: Use visualization elements such as charts and graphs to transform data into a form that is easy to understand and analyze; Interactive visualization: Use interactive visualizations to allow users to freely explore and analyze data to gain deeper insights; Data dashboard: Use data dashboards to visualize key indicators and data to help users better monitor and manage data.

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