Product promotion evaluation processing method, system, device and storage medium

Abstract

The disclosure provides a product promotion evaluation processing method, system, device and storage medium, wherein the method comprises: obtaining historical access and historical ordering of a user to a product; then obtaining expected access, expected ordering and predicted ordering corresponding to a promotion period; comparing the actual access / ordering of the user in the promotion period with the expected / access ordering to determine whether the promotion of the product achieves the expected effect; if the expected effect is achieved, comparing the promotion ordering with the predicted ordering to obtain the corresponding promotion evaluation result; if the expected effect is not achieved, comparing the ordering of the promotion group and the ordering of the non-promotion group to obtain the corresponding promotion evaluation result. Through the above scheme, the promotion effect can be reasonably and accurately evaluated without performing AB grouping experiments, and good universality and robustness are achieved.

Description

Technical Field

[0001] This disclosure relates to the technical field of e-commerce promotion, specifically to a method, system, device, and storage medium for processing product promotion evaluation. Background Technology

[0002] For product distributors or sales platforms, in order to increase their business-related metrics such as exposure, clicks, and order volume, they usually choose to attract customers through promotional activities during certain periods or on specific holidays. After the promotional activities end, distributors or platforms need to evaluate the effectiveness of the promotion to analyze how many incremental clicks and order conversions were generated compared to not conducting promotions.

[0003] In existing technologies, the evaluation of order growth from promotional activities primarily employs A / B group control experiments: first, the customer group is divided into A and B groups, where group A includes users who do not participate in any promotional activities, and group B includes users who do participate in promotional activities. Then, the order conversion difference between group A and group B is compared to obtain the order growth corresponding to the promotional activity. However, promotional activities are inherently a form of subsidy to users. If promotions are only conducted on certain specific groups, it can easily be perceived as "price discrimination," which, once perceived by users, will have incalculable consequences for distributors and platforms. Therefore, it is necessary to reasonably evaluate the promotional effect of promotional activities in a way that avoids "price discrimination," i.e., when A / B group control experiments are not feasible. Summary of the Invention

[0004] In view of the problems in the prior art, the purpose of this disclosure is to provide a method, system, device and storage medium for processing product promotion evaluation, which overcomes the difficulties of the prior art, enables users to quickly confirm, and helps users achieve accurate travel city management.

[0005] The first aspect of this disclosure provides a method for processing product promotion evaluations, which may specifically include the following steps:

[0006] Obtain users' historical access and order history for specific products;

[0007] Based on historical visit and order data, obtain the expected visit, expected order, and predicted order data for the promotional period;

[0008] Get information on user visits and orders placed for specific products during the promotional period.

[0009] Based on the expected visit volume and promotional visit volume, and / or the expected order volume and promotional order volume, determine whether the promotion for a specific product has achieved the expected results:

[0010] If the expected results are achieved, the corresponding promotion evaluation results are obtained by comparing the promotional order situation with the predicted order situation.

[0011] If the expected results are not achieved, the order situation of the promotional group and the order situation of the non-promotional group will be compared to obtain the corresponding promotion evaluation results.

[0012] In one possible implementation of the first aspect above, the process of obtaining a user's historical access history and historical order history for a specific product includes the following steps:

[0013] Obtain the total number of historical visits and the total number of historical orders within the first preset period, and calculate the average number of visits, the average number of orders, the standard deviation of visits, and the standard deviation of orders for each statistical period within the first preset period.

[0014] In one possible implementation of the first aspect above, the process of obtaining the expected visit and expected order data for the promotional period based on historical visit and order data includes the following steps:

[0015] The expected number of visits is obtained based on the average number of visits and the standard deviation of visits. This expected number of visits is then used as the expected visit volume. The expected number of visits is equal to the sum of the average number of visits and three times the standard deviation of visits.

[0016] The expected order volume is obtained by calculating the average order volume and the standard deviation of the order volume, and the expected order volume is used as the expected order situation. The expected order volume is equal to the sum of the average order volume and three times the standard deviation of the order volume.

[0017] In one possible implementation of the first aspect above, the process of obtaining a user's historical access history and historical order history for a specific product includes the following steps:

[0018] Obtain historical access data and historical order data within a second preset period, the duration of which is longer than the duration of the first preset period;

[0019] The process of obtaining the predicted order volume for the promotional period based on historical visit and order data includes the following steps:

[0020] Based on a pre-set prediction model, and according to historical access data and historical order data, the predicted order volume is calculated for the promotional period when no promotion is implemented.

[0021] The predicted order volume is used as the predicted order situation.

[0022] In one possible implementation of the first aspect above, promotional access includes the total number of times users access a specific product during the promotional period;

[0023] Promotional order data includes the total number of orders placed by users for a specific product during the promotional period;

[0024] The process of determining whether a promotion for a specific product has achieved its intended effect based on expected visit volume versus promotional visit volume, and / or expected order volume versus promotional order volume includes the following steps:

[0025] Determine whether the total number of visits exceeds the expected number of visits to obtain the initial judgment result;

[0026] Determine whether the total number of orders exceeds the expected number of orders to obtain a second judgment result;

[0027] If either the first or second judgment result is yes, it is determined that the promotion of the specific product has achieved the expected effect.

[0028] In one possible implementation of the first aspect above, the process of comparing promotional order status with predicted order status to obtain the corresponding promotional evaluation results includes the following steps:

[0029] Obtain the total number of orders placed by users for a specific product during the promotion period, and then obtain the order difference between the total number of orders and the predicted number of orders;

[0030] The corresponding promotional evaluation results are generated based on the order difference.

[0031] In one possible implementation of the first aspect above, the process of comparing the order placement data of the promotional group and the order placement data of the non-promotional group among users to obtain the corresponding promotional evaluation results includes the following steps:

[0032] Obtain the first order rate of the promotional group and the second order rate of the non-promotional group separately;

[0033] Multiply the difference between the first and second order rates by the number of users in the promotional group to obtain the order difference for the promotional group.

[0034] The corresponding promotional evaluation results are generated based on the difference in orders placed by the promotional group.

[0035] The second aspect of this disclosure provides a product promotion evaluation processing system for implementing the product promotion evaluation processing method provided in the first aspect, characterized in that it includes:

[0036] The historical data acquisition unit is used to acquire users' historical access and order information for specific products.

[0037] The promotion forecasting unit is used to obtain the expected visit, expected order, and predicted order situation for the promotion period based on historical visit and order data.

[0038] The promotional data acquisition unit is used to acquire user access and order information for specific products during the promotional period.

[0039] The promotion evaluation processing unit is used to determine whether the promotion for a specific product has achieved the expected results based on the expected visit volume and the promotional visit volume, and / or the expected order volume and the promotional order volume.

[0040] If the expected results are achieved, the corresponding promotion evaluation results are obtained by comparing the promotional order situation with the predicted order situation.

[0041] If the expected results are not achieved, the order situation of the promotional group and the order situation of the non-promotional group will be compared to obtain the corresponding promotion evaluation results.

[0042] A third aspect of this disclosure provides a processing apparatus for product promotion evaluation, comprising:

[0043] processor;

[0044] Memory, which stores the processor's executable instructions;

[0045] The processor is configured to execute the steps of the product promotion evaluation processing method provided in the first aspect by executing executable instructions.

[0046] A fourth aspect of this disclosure provides a computer-readable storage medium for storing a program that, when executed, implements the steps of the product promotion evaluation processing method provided in the first aspect above.

[0047] Compared with the prior art, this disclosure has the following beneficial effects:

[0048] The technical solution provided in this disclosure enables a reasonable and accurate evaluation of the promotional effect of a product without the need for A / B group experiments, and has good universality and robustness. Attached Figure Description

[0049] Other features, objects, and advantages of this disclosure will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings.

[0050] Figure 1 According to an embodiment of this disclosure, a flowchart illustrating a method for processing product promotion evaluation is provided.

[0051] Figure 2According to an embodiment of this disclosure, a flowchart is provided to obtain the predicted order situation corresponding to the promotion period.

[0052] Figure 3 According to an embodiment of this disclosure, a flowchart is provided to determine whether the promotion of a specific product has achieved the expected results.

[0053] Figure 4a According to an embodiment of this disclosure, a flowchart is provided to compare promotional order placements with predicted order placements to obtain corresponding promotional evaluation results.

[0054] Figure 4b According to an embodiment of this disclosure, a flowchart is provided to compare the order placement status of users in the promotional group and the order placement status of users in the non-promotional group to obtain the corresponding promotional evaluation results.

[0055] Figure 5 According to an embodiment of this disclosure, a schematic diagram of a product promotion evaluation processing system is provided.

[0056] Figure 6 According to an embodiment of this disclosure, a schematic diagram of a processing device for product promotion evaluation is provided.

[0057] Figure 7 According to an embodiment of this disclosure, a schematic diagram of the structure of a computer-readable storage medium is provided. Detailed Implementation

[0058] The following specific examples illustrate the implementation methods of this application. Those skilled in the art can easily understand the other advantages and effects of this application from the content disclosed herein. This application can also be implemented or applied through other different specific embodiments, and various details in this application can be modified or changed according to different viewpoints and application systems without departing from the spirit of this application. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other.

[0059] The embodiments of this application will now be described in detail with reference to the accompanying drawings, so that those skilled in the art can easily implement the application. This application may be embodied in many different forms and is not limited to the embodiments described herein.

[0060] In this application, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics represented in connection with that embodiment or example, which are included in at least one embodiment or example of this application. Furthermore, the specific features, structures, materials, or characteristics represented may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate different embodiments or examples represented in this application, as well as features of different embodiments or examples.

[0061] Furthermore, the terms "first" and "second" are used for illustrative purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the representation of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0062] To clearly illustrate this application, devices unrelated to the description are omitted, and the same or similar constituent elements throughout the specification are given the same reference numerals.

[0063] Throughout this specification, when it is said that a device is "connected" to another device, this includes not only "direct connection" but also "indirect connection" by placing other components in between. Furthermore, when it is said that a device "comprises" a certain constituent element, unless otherwise stated otherwise, this does not exclude other constituent elements, but rather implies that other constituent elements may be included.

[0064] When we say that a device is "above" another device, this can mean that it is directly above the other device, or it can mean that other devices are present in between. Conversely, when we say that a device is "directly" "above" another device, there are no other devices present in between.

[0065] Although the terms first, second, etc., are used in some instances herein to refer to various elements, these elements should not be limited by these terms. These terms are used only to distinguish one element from another. For example, first interface and second interface, etc., are used. Furthermore, as used herein, the singular forms “a,” “an,” and “the” are intended to also include the plural forms unless the context indicates otherwise. It should be further understood that the terms “comprising,” “including,” indicate the presence of features, steps, operations, elements, components, items, kinds, and / or groups, but do not exclude the presence, occurrence, or addition of one or more other features, steps, operations, elements, components, items, kinds, and / or groups. The terms “or” and “and / or” as used herein are interpreted as inclusive, or mean any one or any combination thereof. Thus, “A, B, or C” or “A, B, and / or C” means “any one of: A; B; C; A and B; A and C; B and C; A, B, and C.” Exceptions to this definition will only occur if the combination of elements, functions, steps, or operations is inherently mutually exclusive in some way.

[0066] The technical terms used herein are for reference only to specific embodiments and are not intended to limit the scope of this application. The singular form used herein includes the plural form unless the statement explicitly indicates otherwise. The word "comprising" as used in the specification means to specify a particular characteristic, region, integer, step, operation, element, and / or component, and does not exclude the presence or addition of other characteristics, regions, integers, steps, operations, elements, and / or components.

[0067] Although not explicitly defined, all terms, including technical and scientific terms used herein, shall have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. Terms defined in commonly used dictionaries shall be further interpreted as having a meaning consistent with the relevant technical literature and the content of this present application, and shall not be over-interpreted as having an ideal or overly formulaic meaning unless otherwise defined.

[0068] It is understandable that, as with the aforementioned prior art, there is an urgent need for a method and system to reasonably evaluate the promotional effects of promotional activities when A / B group control experiments are not feasible. Accordingly, this disclosure provides a method, system, device, and computer-readable storage medium for product promotion evaluation. The technical solutions involved in this disclosure will be specifically explained and described below:

[0069] Specifically, in some embodiments of this disclosure, Figure 1 According to a flowchart illustrating a method for processing product promotion evaluations, the products include tangible goods, virtual goods, services, and other content that can be sold through online channels. Figure 1As shown, the processing method for product promotion evaluation includes:

[0070] Step 101: Obtain the user's historical access and order history for a specific product.

[0071] Step 102: Based on historical visit and order data, obtain the expected visit, expected order, and predicted order data for the promotional period. The specific methods for obtaining these data will be briefly explained later.

[0072] Step 103: Obtain user access information and order information for specific products during the promotion period.

[0073] Step 104: Based on the expected visit and promotional visit data, and / or the expected order data and promotional order data, determine whether the promotion of the specific product has achieved the expected effect: if yes, proceed to step 105; otherwise, proceed to step 106.

[0074] Step 105: Obtain the corresponding promotion evaluation results by comparing the promotional order situation with the predicted order situation.

[0075] Step 106: By comparing the order placement data of the promotional group and the order placement data of the non-promotional group among users, the corresponding promotional evaluation results are obtained.

[0076] It is understandable that through steps 101 to 106 above, the actual order volume and website traffic after the promotional activity can be compared with the expected order volume and website traffic without A / B grouping. This allows for a scientific, reasonable, accurate, and efficient acquisition of the promotional effect. The following will further explain and illustrate the specific implementation of steps 101 to 106:

[0077] In the above embodiments, further, in step 101, the process of obtaining users' historical access and order information for a specific product may include the following steps: obtaining the total historical access volume and total historical order volume within a first preset period, so as to calculate the average access volume, average order volume, standard deviation of access volume, and standard deviation of order volume for each statistical period within the first preset period. For example, the first preset period may be seven days before the launch of a promotional activity. By obtaining the total access volume and total order volume for the specific product during these seven days, the daily average access volume and average order volume, as well as the standard deviation of access volume and standard deviation of order volume, can be adaptively obtained. The above data can be obtained directly based on statistical methods, which will not be elaborated here.

[0078] In the above embodiments, further, in step 102, the process of obtaining the expected visit and expected order situation corresponding to the promotion period based on historical visit and historical order situation may include the following steps:

[0079] The expected number of visits is obtained based on the average number of visits and the standard deviation of visits. This expected number of visits is used as the expected visit volume, which is equal to the sum of the average number of visits and three times the standard deviation of visits. The expected number of visits serves as a threshold for determining whether the visit volume has achieved the desired promotional effect; this threshold is numerically set to be equal to the sum of the average and the standard deviation of visits, which is three times the standard deviation.

[0080] Similarly, for expected order volume, the expected order volume can be obtained from the average order volume and the standard deviation of the order volume, and the expected order volume can be used as the expected order volume. The expected order volume is equal to the sum of the average order volume and three times the standard deviation of the order volume.

[0081] In the actual implementation of the above embodiments, the settings for expected visit volume and expected order volume can be adaptively adjusted by those skilled in the art according to actual needs, and are not limited here.

[0082] In the above embodiments, further, in step 102, Figure 2 This diagram illustrates a process for obtaining predicted order volumes for a promotional period. Figure 2 As shown, it may include the following steps:

[0083] Step 201: Obtain historical access data and historical order data within the second preset period. The duration of the second preset period is longer than the duration of the first preset period. It is understood that the second preset period requires longer historical data as training samples to support subsequent order volume predictions; for example, the second preset period could be set to 21 days before the start of a promotional activity. This is not a specific limitation.

[0084] Step 202: Based on a preset prediction model, and according to historical access data and historical order data, predict the predicted order volume for the promotional period when no promotion is implemented. Specifically, in one implementation, the Prophet time series model and user order data in a second preset period can be used for prediction. Those skilled in the art can also choose other suitable prediction models to perform the above prediction action according to actual needs, which are not limited here.

[0085] Step 203: Use the predicted order volume as the predicted order situation. It is understood that through steps 201 to 203 above, the original order volume during the promotional period without promotional activities can be obtained. Comparing this predicted order volume with the actual order volume allows for a reasonable evaluation of the promotional effect.

[0086] In the above embodiments, further, promotional access data includes the total number of visits by users to a specific product during the promotional period; promotional order data includes the total number of orders placed by users for a specific product during the promotional period. According to the above embodiments, in the aforementioned step 104, Figure 3 This diagram illustrates a process for determining whether a promotion for a specific product has achieved the desired effect. Figure 3 As shown, it includes the following steps:

[0087] Step 301: Determine whether the total number of visits is greater than the expected number of visits to obtain the first judgment result.

[0088] Step 302: Determine whether the total order volume exceeds the expected order volume to obtain a second determination result. In one specific implementation of the above embodiment, the execution order of steps 301 and 302 is not important; however, in another specific implementation of the above embodiment, the total order volume can be evaluated first, since the most intuitive evaluation indicator for promotional activities is the actual order volume, so the order volume can be evaluated first. If the order volume does not reach the expected order volume but the number of visits reaches the expected number of visits, it means that although the promotional activity did not bring an increase in orders beyond expectations, it did bring a large number of user visits, which can also be considered as achieving the expected effect of the promotion.

[0089] Step 303: If either the first or second judgment result is yes, determine that the promotion of the specific product has achieved the expected effect. If either of the above results is yes, it means that the number of visits and / or orders in the promotional activity has exceeded the manually set threshold, and the "promotional peak" has been achieved; if both judgment results are no, it means that the number of visits and orders in the promotional activity has not exceeded the manually set threshold, which is the case of "non-promotional peak".

[0090] In the above embodiments, further, in the aforementioned step 105, Figure 4a This diagram illustrates a process for comparing actual promotional orders with predicted orders to obtain corresponding promotional evaluation results. Figure 4a As shown, it may include the following steps:

[0091] Step 401a: Obtain the total number of orders placed by users for a specific product during the promotion period, and then obtain the order difference between the total number of orders and the predicted number of orders.

[0092] Step 401b: Generate the corresponding promotional evaluation results based on the order difference.

[0093] It is understandable that, such as Figure 4aThe promotion evaluation results shown correspond to the "promotion peak" scenario, which means that the promotional activity was relatively strong and significantly increased the overall order volume. Therefore, in the process of evaluating the promotion effect, the total order volume and the predicted order volume during the promotional activity period can be directly compared, and the effect of the promotional activity can be evaluated by the actual order increase.

[0094] In the above embodiments, further, in the aforementioned step 106, Figure 4b This diagram illustrates a process for comparing order placements from promotional groups and non-promotional groups to obtain corresponding promotional evaluation results. Figure 4b As shown, it may include the following steps:

[0095] Step 402a: Obtain the first order rate of the promotional group and the second order rate of the non-promotional group respectively.

[0096] Step 402b: Multiply the difference between the first order rate and the second order rate by the number of users in the promotion group to obtain the order difference for the promotion group.

[0097] Step 402c: Generate corresponding promotion evaluation results based on the order difference of the promotion group.

[0098] It is understandable that, such as Figure 4b The promotion evaluation results shown correspond to the "non-promotion peak" scenario. In this scenario, it indicates that the promotional activity's effect failed to exceed the preset visitor and order thresholds, meaning the promotion's overall order increase was limited. This could be due to the promotion itself being insufficiently attractive to users, or insufficient promotional efforts resulting in a lack of reach or awareness of the promotional information. Therefore, it's necessary to evaluate the promotion's effectiveness based on the order difference between different groups. These different groups refer to those who clicked on the promotional link or page and those who did not. The effectiveness of the promotion is assessed by comparing the order difference between the promotional and non-promotional groups.

[0099] In some embodiments of this disclosure, Figure 5 A product promotion evaluation processing system is shown, used to implement the product promotion evaluation processing method provided in the foregoing embodiments. For example... Figure 5 As shown, the product promotion evaluation processing system 500 may specifically include:

[0100] The historical data acquisition unit 501 is used to acquire users' historical access and order information for specific products.

[0101] The promotion expectation prediction unit 502 is used to obtain the expected visit, expected order and predicted order for the promotion period based on historical visit and order data.

[0102] The promotional data acquisition unit 503 is used to acquire user access information and order information for specific products during the promotional period.

[0103] The promotion evaluation processing unit 504 is used to determine whether the promotion of a specific product has achieved the expected effect based on the expected visit and promotion visit, and / or the expected order and promotion order. If the expected effect is achieved, the corresponding promotion evaluation result is obtained by comparing the promotion order and the predicted order. If the expected effect is not achieved, the corresponding promotion evaluation result is obtained by comparing the order of the promotion group and the order of the non-promotion group among users.

[0104] It is understandable that the functions implemented by the historical data acquisition unit 501 to the promotion evaluation processing unit 504 correspond one-to-one with the actions performed in steps 101 to 106, and will not be elaborated here.

[0105] Those skilled in the art will understand that various aspects of this disclosure can be implemented as a system, method, or program product. Therefore, various aspects of this disclosure can be specifically implemented in the following forms: a completely hardware implementation, a completely software implementation (including firmware, microcode, etc.), or a combination of hardware and software aspects, collectively referred to herein as a "circuit," "module," or "platform."

[0106] Specifically, Figure 6 According to an embodiment of this disclosure, a schematic diagram of a processing device for product promotion evaluation is shown. Referring below... Figure 6 To describe an electronic device 600 according to such an embodiment of the present disclosure. Figure 6 The electronic device 600 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments disclosed herein.

[0107] like Figure 6 As shown, the electronic device 600 is presented in the form of a general-purpose computing device. The components of the electronic device 600 may include, but are not limited to: at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different platform components (including storage unit 620 and processing unit 610), a display unit 640, etc.

[0108] The storage unit stores program code, which can be executed by the processing unit 610, causing the processing unit 610 to perform steps according to various exemplary embodiments of this disclosure. For example, the processing unit 610 can perform actions such as... Figure 1 The steps involved in processing product promotion evaluations are shown below.

[0109] Storage unit 620 may include a readable medium in the form of a volatile storage unit, such as random access memory (RAM) 6201 and / or cache memory 6202, and may further include a read-only memory (ROM) 6203.

[0110] Storage unit 620 may also include a program / utility 6204 having a set (at least one) program module 6205, such program module 6205 including but not limited to: operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0111] Bus 630 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the multiple bus structures.

[0112] Electronic device 600 can also communicate with one or more external devices 700 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 600, and / or with any device that enables electronic device 600 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 650. Furthermore, electronic device 600 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 660. Network adapter 660 can communicate with other modules of electronic device 600 via bus 630. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms.

[0113] This disclosure also provides a computer-readable storage medium for storing a program, which, when executed, implements the steps of a product promotion evaluation processing method. In some possible implementations, various aspects of this disclosure can also be implemented as a program product including program code that, when run on a terminal device, causes the terminal device to perform the steps described in the above-described electronic prescription circulation processing method section of this specification according to various exemplary embodiments of this disclosure.

[0114] Based on the foregoing embodiments, the product promotion evaluation processing device provided in this disclosure can reasonably and accurately evaluate the promotion effect of a product without conducting A / B group experiments, and has good universality and robustness.

[0115] Specifically, Figure 7 According to an embodiment of this disclosure, a schematic diagram of the structure of a computer-readable storage medium is shown. For example... Figure 7 As shown, a program product 800 for implementing the above-described method according to an embodiment of the present disclosure is described. This product may employ a portable compact disc read-only memory (CD-ROM) and include program code, and may run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto. In this document, the readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0116] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0117] Computer-readable storage media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable storage medium may also be any readable medium other than a readable storage medium that can transmit, propagate, or transfer a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0118] Program code for performing the operations of this disclosure can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0119] In summary, based on prediction algorithms such as Prophet time series forecasting, the effectiveness of promotional activities can be evaluated quickly, accurately, and effectively without the need for A / B group control experiments. This method can be widely applied to different business sectors, further providing data support for analysis and decision-making, and has significant potential for widespread adoption.

[0120] The technical solution provided in this disclosure also supports fuzzy queries between train numbers and, based on a pre-configured station management module, can autonomously perform fuzzy matching queries on all data in the enterprise group's upstream query interface when problems or failures occur, thus reducing dependence on the enterprise group's interface. Furthermore, this disclosure supports multilingual queries and feedback, comprehensively improving the user's query convenience, accuracy, and applicability, and has significant potential for widespread adoption.

[0121] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of this disclosure and should not be construed as limiting the specific implementation of this disclosure to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of this disclosure, and all such modifications and substitutions should be considered within the scope of protection of this disclosure.

Claims

1. A method for processing product promotion evaluations, characterized in that, Includes the following steps: Obtain the total number of historical visits and the total number of historical orders within the first preset period, and calculate the average number of visits, the average number of orders, the standard deviation of visits, and the standard deviation of orders for each statistical period within the first preset period, as the historical visit and order information of users for a specific product. The expected visit volume is obtained based on the average visit volume and the standard deviation of the visit volume, where the expected visit volume is equal to the sum of the average visit volume and three times the standard deviation of the visit volume. The expected order volume is obtained based on the average order volume and the standard deviation of the order volume, where the expected order volume is equal to the sum of the average order volume and three times the standard deviation of the order volume. This is to obtain the expected visit volume and expected order volume for the promotional period. Historical access data and historical order data within a second preset period are obtained. The duration of the second preset period is longer than the duration of the first preset period. Based on a preset Prophet time series prediction model, the predicted order volume is predicted when no promotion is implemented during the promotion period, based on the historical access data and historical order data. This predicted order volume is used as the predicted order volume for the promotion period. The system obtains user access and order information for the specific product during the promotional period. The promotional access information includes the total number of visits to the specific product by users during the promotional period, and the promotional order information includes the total number of orders placed by users for the specific product during the promotional period. Determine whether the total number of visits is greater than the expected number of visits to obtain a first determination result, and determine whether the total number of orders is greater than the expected number of orders to obtain a second determination result; If either the first judgment result or the second judgment result is yes, it is determined that the promotion of the specific product has achieved the expected effect. If the expected effect is achieved, the total number of orders placed by users for the specific product during the promotion period is obtained, and then the order difference between the total number of orders and the predicted number of orders is obtained. Based on the order difference, a corresponding promotion evaluation result is generated. If the expected effect is not achieved, the first order rate of the promotion group and the second order rate of the non-promotion group are obtained respectively. The difference between the first order rate and the second order rate is multiplied by the number of users in the promotion group to obtain the order difference of the promotion group. The corresponding promotion evaluation result is generated based on the order difference of the promotion group.

2. A product promotion evaluation processing system, used to implement the product promotion evaluation processing method of claim 1, characterized in that, include: The historical data acquisition unit is used to acquire the total number of historical visits and the total number of historical orders within the first preset period, so as to calculate the average number of visits, the average number of orders, the standard deviation of visits, and the standard deviation of orders for each statistical period within the first preset period, as the historical visit and order situation of users for specific products. The promotion expectation prediction unit is used to obtain the expected visit volume based on the average visit volume and the standard deviation of the visit volume, wherein the expected visit volume is equal to the sum of the average visit volume and three times the standard deviation of the visit volume, and to obtain the expected order volume based on the average order volume and the standard deviation of the order volume, wherein the expected order volume is equal to the sum of the average order volume and three times the standard deviation of the order volume, so as to obtain the expected visit volume and expected order volume corresponding to the promotion period; and to obtain historical visit data and historical order data within a second preset period, wherein the duration of the second preset period is longer than the duration of the first preset period, and based on a preset Prophet time series prediction model, predict the predicted order volume corresponding to the promotion period without promotion based on the historical visit data and historical order data, as the predicted order volume corresponding to the promotion period; The promotional data acquisition unit is used to acquire the promotional access information and promotional order information of users for the specific product during the promotional period. The promotional access information includes the total number of visits to the specific product by users during the promotional period, and the promotional order information includes the total number of orders placed by users for the specific product during the promotional period. The promotion evaluation processing unit is used to determine whether the total number of visits is greater than the expected number of visits to obtain a first judgment result, and to determine whether the total number of orders is greater than the expected number of orders to obtain a second judgment result; if either the first judgment result or the second judgment result is yes, it is determined that the promotion of the specific product has achieved the expected effect; if the expected effect is achieved, the total number of orders placed by users for the specific product during the promotion period is obtained, and then the order difference between the total number of orders and the predicted number of orders is obtained, and a corresponding promotion evaluation result is generated based on the order difference; if the expected effect is not achieved, the first order rate of the promotion group and the second order rate of the non-promotion group are obtained respectively, the difference between the first order rate and the second order rate is multiplied by the number of users in the promotion group to obtain the order difference of the promotion group, and the corresponding promotion evaluation result is generated based on the order difference of the promotion group.

3. A product promotion evaluation processing device, characterized in that, include: processor; A memory in which executable instructions of the processor are stored; The processor is configured to perform the steps of the product promotion evaluation processing method of claim 1 by executing the executable instructions.

4. A computer-readable storage medium for storing a program, characterized in that, When the program is executed by the processor, it implements the steps of the product promotion evaluation processing method as described in claim 1.

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