Online ordering cooperation system and method
Through the online ordering collaboration system, customer needs are predicted using factors such as customer identity type and order frequency, which solves the problems of transaction management between enterprises and enterprises, improves transaction synergy and reliability, simplifies the transaction process and improves customer satisfaction.
Patent Information
- Application Number
- CN202411558936.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-01
- Publication Date
- 2025-03-04
AI Technical Summary
The existing technology cannot effectively manage huge transactions between enterprises, resulting in problems such as missed orders and delayed orders, reducing customer satisfaction rates and increasing the difficulty of monitoring transaction channels.
It provides an online ordering collaboration system, including the client and enterprise side. By obtaining customer identity type, order frequency, order product SKU quantity, order seasonal sales and product inventory level and other factors, it predicts customer demand, and sets corresponding functional modules on the client and enterprise side to improve transaction synergy and reliability.
By predicting customer demand and market trends, improve online transaction synergy and reliability, simplify transaction processes, improve corporate management efficiency, reduce the risk of missed orders, and improve customer satisfaction.
Smart Images
Figure CN119558927A_ABST
Abstract
Description
Technical Field
[0001] The present application mainly relates to the field of e-commerce, and in particular to an online ordering collaboration system and method. Background Art
[0002] Transactions between enterprises are different from transactions between individual merchants and enterprises. Commodity transactions between enterprises often involve huge transaction volumes, with orders of tens of thousands. As the volume of business continues to increase, the complexity of business management also increases significantly. Existing technologies generally use internal management systems such as ERP systems to manage actual business. However, with the development of science and technology, the volume of transactions between enterprises has increased sharply. Currently, systems for business management between enterprises such as ERP systems can no longer meet market demand. Therefore, there will be phenomena such as wrong orders, missed orders, and delayed orders, resulting in a decrease in customer satisfaction. At the same time, due to the continuous expansion of business volume, the difficulty of monitoring transaction channels has also increased significantly. Due to the huge transaction amount, it is easy to cause trouble for channel customers to reconcile accounts, approval troubles, and analysis troubles. Therefore, this field urgently needs an online ordering collaboration system that can solve the above problems to effectively manage transactions between enterprises. Summary of the invention
[0003] The technical problem to be solved by this application is to provide an online ordering collaboration system that can help predict customer needs and market trends and improve the collaboration and reliability of online transactions.
[0004] To solve the above technical problems, the present application provides an online ordering collaboration system, including a client, through which customers conduct order transactions; an enterprise side, the client sends order transaction information to the enterprise side, the enterprise side includes a customer management module, an order processing module, a product management module and a statistical processing module, the customer management module is configured to obtain the customer identity type (CT), the order processing module is configured to obtain the customer's order frequency (OF), the number of SKUs of order products (SKU Count) and the order season sales (SC), the product management module is configured to obtain the product inventory level (IvT) of the enterprise side, wherein the statistical processing module predicts customer demand based on the customer identity type (CT), the order frequency (OF), the number of SKUs of order products (SKUCount), the order season sales (SC) and the product inventory level (IvL).
[0005] Optionally, the order processing module is further configured to obtain the order basic sales volume β0, and the statistical processing module is further configured to obtain the sales tolerance ∈ t .
[0006] Optionally, the statistical processing module further includes using the following formula to predict the customer demand Sales t+1 :
[0007] Sales t+1 =β0+β1OF t +β2CT t +β3SKUCount t +β4IvL t +β5SC t +∈ t
[0008] Among them, the OF t is the customer's order frequency within time t, the CT t is the customer identity type within time t, the SKUCount t is the SKU quantity of the order item within time t, and the IvL t is the commodity inventory level IvL in time t, the SC t is the order season sales within time t, β1 is the influence of the customer order frequency on the customer demand, β2 is the influence of the customer identity type on the customer demand, β3 is the influence of the order product SKU quantity on the customer demand, β4 is the influence of the product inventory level IvL on the customer demand, and β5 is the influence of the order season sales on the customer demand.
[0009] Optionally, the client includes a product display module, and the enterprise end transmits the differential product display information to the product display module of the client for display to the customer.
[0010] Optionally, the client comprises a policy management module, and the policy management module is configured to perform an automated policy applicability evaluation according to the promotion policy.
[0011] Optionally, the client further includes a checkout module and an order management module, the checkout module is configured to encrypt and transmit transaction payment information, and the order management module is configured to obtain the order transaction information and send the order transaction information to the enterprise end.
[0012] Optionally, the commodity management module at the enterprise end is further configured to perform differentiated price management for different customers according to the customer identity type (CT).
[0013] Optionally, the enterprise end further includes a price management module and an approval management module, wherein the price management module is configured to flexibly price commodities, and the approval management module is configured to approve various processes of order transactions.
[0014] Optionally, the enterprise end also includes a financial management module and a report management module, the financial management module is configured to review, reconcile and / or manage invoices on financial data, and the report management module is configured to display and analyze daily operating reports.
[0015] To solve the above technical problems, the present application provides an online ordering collaboration method, which is applicable to the online ordering collaboration system as described above, and includes the following steps: obtaining customer identity type (CT), customer order frequency (OF), order item SKU quantity (SKU Count), order season sales (SC) and commodity inventory level (IvT); predicting customer demand based on the customer identity type (CT), the order frequency (OF), the order item SKU quantity (SKU Count), the order season sales (SC) and the commodity inventory level (IvT).
[0016] Compared with the prior art, this application measures customer demand through factors such as customer identity type CT, customer order frequency OF, order product SKU number SKU Count, order season sales SC, and product inventory level IvT, which can help predict customer demand and market trends and improve the coordination and reliability of online transactions. Furthermore, setting functional modules such as product display module, policy management module, checkout module, and order management module on the client side can help customers conduct online transactions better, and setting functional modules such as customer management module, order processing module, product management module, statistical processing module, price management module, approval management module, financial management module, and report management module on the enterprise side can help corporate customers better manage transactions and comprehensively improve corporate management efficiency. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] The accompanying drawings are included to provide a further understanding of the present application. They are included and constitute a part of the present application. The accompanying drawings illustrate embodiments of the present application and together with the present specification serve to explain the principles of the present application. In the accompanying drawings:
[0018] Figure 1 This is a module diagram of an online ordering collaboration system in one embodiment of the present application;
[0019] Figure 2 It is a flowchart of an online ordering collaboration method in one embodiment of the present application. DETAILED DESCRIPTION
[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of the present application. For ordinary technicians in this field, the present application can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.
[0021] As shown in this application and claims, unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the terms "include" and "comprise" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.
[0022] Unless otherwise specifically stated, the relative arrangement, numerical expressions and numerical values of the parts and steps set forth in these embodiments do not limit the scope of the present application. At the same time, it should be understood that, for ease of description, the sizes of the various parts shown in the accompanying drawings are not drawn according to the actual proportional relationship. The technology, method and equipment known to those of ordinary skill in the relevant field may not be discussed in detail, but in appropriate cases, the technology, method and equipment should be considered as a part of the authorization specification. In all examples shown and discussed here, any specific value should be interpreted as being merely exemplary, rather than as a limitation. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters represent similar items in the following drawings, so that once a certain item is defined in an accompanying drawing, it does not need to be further discussed in subsequent drawings.
[0023] In the description of the present application, it should be understood that the directions or positional relationships indicated by directional words such as "front, back, up, down, left, right", "lateral, vertical, perpendicular, horizontal" and "top, bottom" are usually based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present application and simplifying the description. Unless otherwise specified, these directional words do not indicate or imply that the device or element referred to must have a specific direction or be constructed and operated in a specific direction, and therefore cannot be understood as limiting the scope of protection of the present application; the directional words "inside and outside" refer to the inside and outside relative to the contours of each component itself.
[0024] For ease of description, spatially relative terms such as "above", "above", "on the upper surface of", "above", etc. may be used here to describe the spatial positional relationship between a device or feature and other devices or features as shown in the figure. It should be understood that spatially relative terms are intended to include different orientations of the device in use or operation in addition to the orientation described in the figure. For example, if the device in the accompanying drawings is inverted, the device described as "above other devices or structures" or "above other devices or structures" will be positioned as "below other devices or structures" or "below other devices or structures". Thus, the exemplary term "above" can include both "above" and "below". The device can also be positioned in other different ways (rotated 90 degrees or in other orientations), and the spatially relative descriptions used here are interpreted accordingly.
[0025] In addition, it should be noted that the use of words such as "first" and "second" to define components is only for the convenience of distinguishing the corresponding components. If not otherwise stated, the above words have no special meaning and cannot be understood as limiting the scope of protection of this application. In addition, although the terms used in this application are selected from well-known and commonly used terms, some terms mentioned in the specification of this application may be selected by the applicant at his or her discretion, and their detailed meanings are explained in the relevant parts of the description of this article. In addition, it is required to understand this application not only by the actual terms used, but also by the meaning implied by each term.
[0026] This application refers to Figure 1 An online ordering collaborative system 10 (hereinafter referred to as "collaborative system 10") is proposed. The collaborative system 10 includes a client and an enterprise side, and information can be synchronized and shared between the client and the enterprise side. Enterprise customers can conduct order transactions through the client in the collaborative system 10, and the client sends the acquired enterprise customer order transaction information to the enterprise side. Exemplarily, the customer order transaction information includes information such as the enterprise customer's order amount, order amount, order frequency, and order type. Exemplarily, data synchronization is performed between the client and the enterprise side through an API. The collaborative system 10 may include multiple clients, and one enterprise side can manage multiple clients at the same time. This application does not impose any restrictions on this.
[0027] Furthermore, the enterprise side mainly includes a customer management module, an order processing module, a commodity management module and a statistical processing module. Specifically, the customer management module is configured to obtain the customer identity type (Customer Type, referred to as CT). In the collaborative system 10, customers will be classified into levels, for example, customers will be divided into high-value customers, mid-range customers and low-value customers. Different types of customers have different purchasing potential, purchasing behavior and purchasing preferences. The collaborative system 10 obtains customer levels as an influencing factor for predicting customer needs and market trends, and can better predict the purchasing patterns and trends of different customer groups, thereby more accurately positioning products and services. In this embodiment, the staff of the enterprise merchant can view and edit customer information through the customer management module, master customer data, and improve the integration of data information.
[0028] Furthermore, the enterprise side also includes an order processing module, which is configured to obtain the customer's order frequency (Order Frequency, referred to as OF), the number of SKUs of order items (SKU Count), the seasonal sales of orders (Seasonality Count, referred to as SC), and the basic sales of orders β0. Among them, the customer order frequency is the ratio of the number of customer orders to the total number of orders of the enterprise merchant, the number of SKUs of order items is the total sales quantity of a specific product of the enterprise merchant, the seasonal sales of orders is the total sales amount of a specific product of the enterprise merchant in a certain season, and the basic sales of orders β0 is the average sales of the enterprise merchant over a period of time. The order processing module can also automatically manage the confirmation and delivery process of orders.
[0029] In this embodiment, the collaborative system 10 obtains customer order frequency, order item SKU quantity, order seasonal sales, and order basic sales β0 as influencing factors for predicting customer demand and market trends, and comprehensively considers factors such as customer activity, seasonal factors, and corporate merchant service capabilities to predict customer demand and market trends, thereby improving the comprehensiveness and reliability of the prediction.
[0030] On the other hand, the enterprise side also includes a commodity management module, which is configured to obtain the commodity inventory level (Inventory Level, referred to as IvT) of the enterprise side. The collaborative system 10 obtains the commodity inventory level to predict customer demand and market trends, and enables enterprise merchants to better understand the current inventory of commodities, so as to reasonably allocate commodity inventory to meet customer needs.
[0031] Furthermore, the staff of enterprise merchants can monitor inventory levels and generate replenishment reminders through the product management module, and enable staff to timely update product information and pricing strategies, maintain basic product information, set product release strategies, and manage product batches. Inventory levels can accurately predict demand, avoid excessive inventory and related costs, ensure that inventory levels are synchronized with demand, and improve capital liquidity.
[0032] In this embodiment, the enterprise end also includes a statistical processing module, which is configured to predict customer demand based on customer identity type (CT), order frequency (OF), order commodity SKU quantity (SKUCount), order season sales (SC) and commodity inventory level (IvL). The statistical processing module is also configured to obtain sales tolerance ∈ t , sales tolerance ∈ t Other factors that affect market trends and customer needs can be taken into account, and the uncertainty of the forecast can be quantified to improve the accuracy of the forecast.
[0033] In this embodiment, the statistical processing module can use the following formula to predict customer demand Sales: t+1 :
[0034] Sales t+1 =β0+β1OF t +β2CT t +β3SKUCount t +β4IvL t +β5SC t +∈ t
[0035] Among them, OF t is the customer order frequency within time t, CT t is the customer identity type at time t, SKUCount t is the number of SKUs of the ordered items within time t, IvL t IvL is the inventory level of goods in time t, SC t is the order season sales within time t, β1 is the influence of customer order frequency on customer demand, β2 is the influence of customer identity type on customer demand, β3 is the influence of order commodity SKU quantity on customer demand, β4 is the influence of commodity inventory level IvL on customer demand, and β5 is the influence of order season sales on customer demand.
[0036] On the other hand, the client includes a product display module. The enterprise side transmits differentiated product display information to the product display module of the client side for display to customers. The product display module can dynamically load information from the product database and display it to users in a structured and visually attractive way, showing customers detailed product descriptions, specifications, prices, inventory status, pictures and other information. Differentiated product display means that the enterprise side will display different products to customers of different levels according to the division of internal customer levels.
[0037] Furthermore, the client also includes a policy management module, which is configured to perform automated policy applicability evaluations based on promotional policies. The policy management module can apply various promotional policies, such as discounts, coupons, or point rewards, when customers place orders. The policy management module dynamically evaluates consumer policies, so corporate customers can view applicable policies and price changes after policy application during the ordering process through the policy management module. Since the collaborative system 10 is mainly aimed at transactions between corporate customers and corporate merchants, the transaction volume is often tens of thousands, and information such as preferential policies cannot be communicated to corporate customers in a timely manner. Therefore, through the setting of the policy management module, the convenience of corporate customers when purchasing is further improved, which can further facilitate customers and improve customer satisfaction. In this embodiment, the policy management module can also adjust prices during peak or trough demand to maximize profits.
[0038] In this embodiment, the client also includes a checkout module, which is configured to encrypt and transmit transaction payment information. The checkout module allows customers to conduct transactions through various existing payment software, and can guide customers to enter the secure payment page to ensure the security of payment information through encrypted transmission. After the customer completes the payment, the collaborative system 10 will update the order status in a timely manner, and the customer can query the transaction history and account fund status in the personal account through the collaborative system 10. The checkout module also allows customers to pre-charge to improve the convenience of transactions. For transactions between enterprises that are often worth tens of millions, the transaction security of corporate customers can be guaranteed through the checkout module, further improving the reliability of the collaborative system 10.
[0039] Furthermore, the client also includes an order management module, which is configured to obtain order transaction information and send the order transaction information to the enterprise end. The order management module allows the user to query the order list by entering the order number or other identifier, and the order management module will provide the customer with detailed information of the order, including the list of goods, price, estimated delivery time, etc. In this embodiment, the order management module also includes an order statistics function, which enables the user to track the overall status and historical trends of the order. Through the setting of the order management module, the user can obtain various information of large orders in a timely manner, which is convenient for the customer to manage the order and further improves the customer satisfaction.
[0040] In this embodiment, the client also has a registration and login module, which provides a user-friendly interface and allows new customers to create accounts online. Customers can quickly complete the registration process by entering necessary personal information and business-related data, such as company name, contact person, contact information, business license and other legal person or corporate identity verification information. Customers can also securely access their accounts through the login module. On the other hand, the client also provides a master-sub-account management module. In order to meet the needs of corporate customers for multi-user management, this module allows customers to create a master account and multiple subordinate sub-accounts. The master account can manage different sub-accounts and set basic information and permissions for subordinate sub-accounts.
[0041] Furthermore, the commodity management module on the enterprise side is also configured to perform differentiated price management for different customers based on the customer identity type CT. In some embodiments, differentiated price management means that for high-consumption customer groups, high-quality and high-priced commodities will be recommended, while for low-consumption customer groups, more high-quality and low-priced commodities will be displayed. Through differentiated price management, clear grade prices, regional prices, etc. can be set for customers of different levels, and prices can be intelligently analyzed through the merchant's region and grade system. Customers of different levels cannot communicate with each other and cannot see each other's prices. Differentiated price management can take into account the needs of different customers and provide customers with different needs with commodities at suitable prices.
[0042] In this embodiment, the enterprise side also includes a price management module and an approval management module. Among them, the price management module allows enterprises to flexibly set price strategies according to different sales channels, customer categories and order quantities to adapt to market changes and competition needs and achieve dynamic pricing. The approval management module is configured to approve various processes of order transactions, providing a centralized approval workflow for the staff of enterprise merchants. The approval management module covers key business nodes such as customer account opening, order processing, and financial recognition, which improves the transparency and approval efficiency of business processes.
[0043] Furthermore, the enterprise side also includes a financial management module and a report management module. The financial management module integrates financial audit, reconciliation and invoice management functions, realizes the automation and standardization of financial management, and can provide merchants with detailed transaction records and reconciliation reports after customer transactions, improving the accuracy of financial data and the efficiency of financial processes. The report management module is configured to display and analyze daily operation reports, which can help companies gain insight into business trends, evaluate business performance, and help managers make decisions. The financial management module can also provide companies with accurate forecasts of future revenue, help with financial planning and budgeting, and optimize procurement and production costs by predicting demand.
[0044] On the other hand, the present application also refers to Figure 2 An online ordering collaboration method 20 is proposed, which is applicable to the online ordering collaboration system proposed in any embodiment of the present application, such as the above-mentioned online ordering collaboration system 10. Figure 2 A flowchart of an online ordering collaboration method 20 is shown. The flowchart is used in this application to illustrate the operations performed by the system according to the embodiment of the present application. It should be understood that the previous or following operations are not necessarily performed precisely in order. On the contrary, various steps can be processed in reverse order or simultaneously. At the same time, other operations can be added to these processes, or one or more operations can be removed from these processes. Specifically, the online ordering collaboration method 20 includes the following steps:
[0045] S1: Get customer identity type (CT), customer order frequency (OF), order item SKU quantity (SKUCount), order season sales (SC), and item inventory level (IvT);
[0046] S2: Forecast customer demand based on customer identity type (CT), order frequency (OF), order SKU quantity (SKU Count), order season sales (SC), and product inventory level (IvT).
[0047] The online ordering collaboration system provided by the present application is a collaborative transaction system with high supply chain transparency. It measures customer demand through factors such as customer identity type CT, customer order frequency OF, order product SKU number SKU Count, order season sales SC, and product inventory level IvT, which can help predict customer demand and market trends, improve the collaboration and reliability of online transactions, and enable corporate merchants and corporate customers to respond quickly to market changes and simplify operational procedures during transactions. Furthermore, setting functional modules such as product display module, policy management module, checkout module, and order management module on the client side can help customers better conduct online transactions, and setting functional modules such as customer management module, order processing module, product management module, statistical processing module, price management module, approval management module, financial management module, and report management module on the enterprise side can help corporate customers better manage transactions and comprehensively improve enterprise management efficiency.
[0048] The basic concepts have been described above. Obviously, for those skilled in the art, the above application disclosure is only an example and does not constitute a limitation of the present application. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements and amendments to the present application. Such modifications, improvements and amendments are suggested in the present application, so such modifications, improvements and amendments still belong to the spirit and scope of the exemplary embodiments of the present application.
[0049] At the same time, the present application uses specific words to describe the embodiments of the present application. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of the present application. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different positions in this specification does not necessarily refer to the same embodiment. In addition, some features, structures or characteristics in one or more embodiments of the present application can be appropriately combined.
[0050] Similarly, it should be noted that in order to simplify the description of the disclosure of this application and thus help understand one or more application embodiments, in the above description of the embodiments of this application, multiple features are sometimes merged into one embodiment, figure or description thereof. However, this disclosure method does not mean that the features required by the object of this application are more than the features mentioned in the claims. In fact, the features of the embodiments are less than all the features of the single embodiment disclosed above.
[0051] In some embodiments, numbers describing the number of components and attributes are used. It should be understood that such numbers used in the description of the embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise specified, "about", "approximately" or "substantially" indicate that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may change according to the required features of individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the general method of retaining digits. Although the numerical domains and parameters used to confirm the breadth of their range in some embodiments of the present application are approximate values, in specific embodiments, the setting of such numerical values is as accurate as possible within the feasible range.
[0052] Although the present application has been described with reference to the current specific embodiments, ordinary technicians in this technical field should recognize that the above embodiments are only used to illustrate the present application, and various equivalent changes or substitutions may be made without departing from the spirit of the present application. Therefore, as long as the changes and modifications to the above embodiments are within the essential spirit of the present application, they will fall within the scope of the claims of the present application.
Claims
1. An online ordering collaboration system, characterized in that: include Client, through which the customer places an order transaction; Enterprise side, the client sends the order transaction information to the enterprise side, the enterprise side includes a customer management module, an order processing module, a product management module and a statistical processing module, the customer management module is configured to obtain the customer identity type (CT), the order processing module is configured to obtain the customer's order frequency (OF), the number of order product SKUs (SKUCount) and the order season sales (SC), the product management module is configured to obtain the product inventory level (IvT) of the enterprise side, wherein the statistical processing module is configured to predict customer demand based on the customer identity type (CT), the order frequency (OF), the number of order product SKUs (SKUCount), the order season sales (SC) and the product inventory level (IvL).
2. The collaborative system according to claim 1, characterized in that: The order processing module is further configured to obtain the order basic sales volume β0, and the statistical processing module is further configured to obtain the sales tolerance ∈ t .
3. The collaborative system according to claim 2, characterized in that: The statistical processing module also includes using the following formula to predict the customer demand Sales t+1 : Sales t+1 =β0+β1OF t +β2CT t +β3SKUCount t +β4IvL t +β5SC t +∈ t Among them, the OF t is the customer's order frequency within time t, the CT t is the customer identity type within time t, the SKUCount t is the SKU quantity of the order item within time t, and the IvL t is the commodity inventory level IvL in time t, the SC t is the order season sales within time t, β1 is the influence of the customer order frequency on the customer demand, β2 is the influence of the customer identity type on the customer demand, β3 is the influence of the order product SKU quantity on the customer demand, β4 is the influence of the product inventory level IvL on the customer demand, and β5 is the influence of the order season sales on the customer demand.
4. The collaborative system according to claim 1, characterized in that: The client includes a product display module, and the enterprise end transmits the differential product display to the product display module of the client to display it to the customer.
5. The collaborative system according to claim 1, characterized in that: The client comprises a policy management module, and the policy management module is configured to perform an automated policy applicability evaluation according to a promotion policy.
6. The collaborative system according to claim 1, characterized in that: The client also includes a checkout module and an order management module. The checkout module is configured to encrypt and transmit transaction payment information, and the order management module is configured to obtain the order transaction information and send the order transaction information to the enterprise end.
7. The collaborative system according to claim 1, characterized in that: The commodity management module at the enterprise end is also configured to perform differentiated price management for different customers according to the customer identity type (CT).
8. The collaborative system according to claim 1, characterized in that: The enterprise end also includes a price management module and an approval management module. The price management module is configured to flexibly price commodities, and the approval management module is configured to approve various processes of order transactions.
9. The collaborative system according to claim 1, characterized in that: The enterprise end also includes a financial management module and a report management module. The financial management module is configured to review, reconcile and / or manage invoices for financial data, and the report management module is configured to display and analyze daily operation reports.
10. An online ordering collaboration method, applicable to the online ordering collaboration system as claimed in claims 1 to 9, characterized in that: The steps include: Get customer identity type (CT), customer order frequency (OF), order item SKU quantity (SKU Count), order season sales (SC), and item inventory level (IvT); The customer demand is predicted according to the customer identity type (CT), the order frequency (OF), the SKU quantity of the ordered goods (SKU Count), the order season sales (SC) and the commodity inventory level (IvT).