An intelligent robot bill of lading management method and system based on the advertising delivery effect

Abstract

The present invention discloses an intelligent robot bill of lading management method and system based on the advertising delivery effect, which relates to the technical field of advertising bill of lading management and includes: collecting the source data of the advertising delivery platform and preprocessing it into standard source data, and storing and constructing a big data storage database according to a preset architecture; then successively extracting data based on this database, comprehensively determining the advertising delivery effect indicators by integrating various types of information, calculating a dynamic threshold based on the source data, and accordingly judging whether to start the bill of lading generation process. If it is started, the preset bill of lading template is filled by combining multiple parties' information and distributed to the optimization platform, tracking the initial optimization process, recording real-time information to determine the initial optimization quality index, and accordingly judging whether to perform secondary optimization. There is also a corresponding bill of lading generation process for new customers. The advantages of the present invention are that the dynamic threshold flexibly adapts to market changes, the bill of lading process is standardized and efficient, the optimization evaluation is closed-loop and iterative, and the advertising delivery accuracy, timeliness and efficiency are comprehensively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of advertising bill of lading management, and particularly to an intelligent robot bill of lading management method and system based on advertising delivery effect. Background Art

[0002] At present, with the booming development of digital marketing, the scale of advertising delivery is increasing day by day, and enterprises are facing the problem of processing a large amount of delivery data. Traditional bill of lading management relies on manual work, which is not only inefficient but also error-prone, and it is difficult to accurately evaluate the delivery effect. Based on this, the intelligent robot bill of lading management method and system have emerged. It can automate and intelligently process the bill of lading process, improve efficiency, accurately analyze the delivery data, help enterprises optimize strategies, enhance the competitiveness of advertisements, and is of great significance.

[0003] In the existing intelligent robot bill of lading management method and system based on advertising delivery effect, in the field of advertising delivery business, due to the diverse types of advertising delivery platforms and the uneven quality of the source data of advertising delivery platforms, it is easy for the management system to deviate in the analysis of the advertising delivery effect indicators corresponding to the standard source data of advertising delivery platforms. Therefore, it is necessary to provide an intelligent robot bill of lading management method and system based on advertising delivery effect to solve the above-mentioned problems. Summary of the Invention

[0004] To solve the above technical problems, an intelligent robot bill of lading management method and system based on advertising delivery effect are provided. This technical solution solves the problem that in the existing intelligent robot bill of lading management method and system based on advertising delivery effect, in the field of advertising delivery business, due to the diverse types of advertising delivery platforms and the uneven quality of the source data of advertising delivery platforms, it is easy for the management system to deviate in the analysis of the advertising delivery effect indicators corresponding to the standard source data of advertising delivery platforms.

[0005] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0006] An intelligent robot bill of lading management method based on advertising delivery effect, comprising:

[0007] Collect the source data of the advertising delivery platform, and perform data preprocessing on the source data of the advertising delivery platform to obtain the standard source data of the advertising delivery platform;

[0008] Organize and store the standard source data of the advertising delivery platform according to a preset data structure to obtain a big data storage database;

[0009] Based on the big data storage database, sequentially extract the standard source data of the advertising delivery platform, and determine the advertising delivery effect indicators corresponding to the standard source data of the advertising delivery platform;

[0010] Obtain the dynamic threshold of the advertising placement effect indicator corresponding to the advertising placement effect indicator according to the standard source data of the advertising placement platform;

[0011] Based on the advertising placement effect indicator and the dynamic threshold of the advertising placement effect indicator, determine whether it is necessary to perform the bill of lading generation process. If not, continue to monitor the standard source data of the advertising placement platform in the big data storage database. If so, obtain the bill of lading requirement information and the bill of lading impact information;

[0012] Generate and fill the preset bill of lading template based on the bill of lading requirement information, the bill of lading impact information, and the standard source data of the advertising placement platform;

[0013] Distribute the preset bill of lading template to the corresponding advertising placement optimization platform, obtain and initially optimize the advertising placement strategy corresponding to the preset bill of lading template, and at the same time obtain the initial optimization process information;

[0014] Track the initial optimization process information, record the initial real-time processing information, and determine the initial optimization quality index based on the initial real-time processing information and the standard source data of the advertising placement platform;

[0015] Based on the initial optimization quality index, determine whether it is necessary to perform secondary optimization on the advertising placement strategy corresponding to the initially optimized preset bill of lading template. If not, continue to collect the source data of the advertising placement platform. If so, perform secondary optimization.

[0016] In an optional embodiment, based on the big data storage database, the standard source data of the advertising placement platform is sequentially extracted, and the advertising placement effect indicator corresponding to the standard source data of the advertising placement platform is determined. Specifically, it includes:

[0017] Based on the standard source data of the advertising placement platform, obtain the advertising placement platform type information, the advertising placement historical performance data, the customer basic information, and the advertising material information;

[0018] According to the customer basic information, construct a customer basic information parameter matrix, and integrate the standard source data of the advertising placement platform with the same customer basic information parameter matrix to obtain the first standard source data;

[0019] Based on the advertising placement platform type information, divide the first standard source data to obtain the first standard source sub-data;

[0020] Based on the advertising placement historical performance data, through , sequentially obtain the first advertising placement effect indicator corresponding to the first standard source sub-data, where is the first advertising placement effect indicator corresponding to the first standard source sub-data of the th advertising placement platform type, is the The maximum daily active users of an advertising platform of a certain type of advertising platform is the average daily active users of an advertising platform of the is the advertising click-through rate corresponding to the first standard source sub-data of the is the advertising conversion rate corresponding to the first standard source sub-data of the and are the importance weights of the advertising click-through rate and the advertising conversion rate respectively;

[0021] Based on the advertising material information, the first standard source sub-data is divided to obtain the second standard source sub-data, and the advertising material information includes picture-type advertising materials, video-type advertising materials, interactive advertising materials, native advertising materials, full-screen advertising materials, and AR advertising materials;

[0022] Respectively obtain the second advertising placement effect sub-indicators of the second standard source sub-data corresponding to picture-type advertising materials, video-type advertising materials, interactive advertising materials, native advertising materials, full-screen advertising materials, and AR advertising materials;

[0023] Obtain the mean value of the second advertising placement effect sub-indicators as the second advertising placement effect indicator;

[0024] Take the mean value of the first advertising placement effect indicator and the second advertising placement effect indicator as the advertising placement effect indicator corresponding to the advertising platform standard source data.

[0025] In an alternative embodiment, the obtaining of the dynamic threshold value of the advertising placement effect indicator corresponding to the advertising platform standard source data specifically includes:

[0026] Based on the advertising platform standard source data, obtain the initial advertising placement timestamp and the dynamic threshold calculation timestamp of different advertising platforms;

[0027] Obtain the absolute value of the time difference between the initial advertising placement timestamp and the dynamic threshold calculation timestamp corresponding to different advertising platforms to obtain the dynamic threshold calculation time reference value;

[0028] According to the dynamic threshold calculation time reference value, obtain the advertising placement data node cut-off value and the sliding cut-off unit value;

[0029] Use the advertising placement data node cut-off value and the sliding cut-off unit value to perform sliding cut-off on the advertising platform standard source data to obtain the advertising platform standard source cut-off data and the cut-off time period;

[0030] Through Obtain the dynamic indicators of the advertising delivery effect corresponding to the intercepted data of the advertising delivery platform standard source, where is the dynamic indicator of the advertising delivery effect corresponding to the th intercepted data of the advertising delivery platform standard source, is the first advertising delivery effect indicator corresponding to the th intercepted data of the advertising delivery platform standard source, The th second advertising delivery effect indicator corresponding to the intercepted data of the advertising delivery platform standard source;

[0031] Obtain the maximum and minimum values of the dynamic indicators of the advertising delivery effect, and remove the maximum and minimum values of the dynamic indicators of the advertising delivery effect to obtain the average value of the remaining dynamic indicators of the advertising delivery effect, so as to obtain the advertising delivery effect indicator threshold corresponding to the advertising delivery effect indicator;

[0032] Through obtain the dynamic weight corresponding to the advertising delivery effect indicator threshold, where is the dynamic weight corresponding to the advertising delivery effect indicator threshold of the th intercepted data of the advertising delivery platform standard source, is the average daily active users of the th intercepted data of the advertising delivery platform standard source within the intercepted time period, is the maximum daily active users of the th intercepted data of the advertising delivery platform standard source within the intercepted time period;

[0033] Use the product value of the dynamic weight corresponding to the advertising delivery effect indicator threshold and the advertising delivery effect indicator threshold as the advertising delivery effect indicator dynamic threshold corresponding to the advertising delivery effect indicator.

[0034] In an optional embodiment, the generating and populating the preset bill of lading template based on the bill of lading demand information, bill of lading impact information, and advertising delivery platform standard source data specifically includes:

[0035] According to the bill of lading demand information, obtain the advertising campaign name bill of lading information, advertising delivery platform bill of lading information, advertising delivery time bill of lading information, and advertising delivery key indicator bill of lading information;

[0036] Based on the advertising campaign name bill of lading information, determine the advertising material bill of lading information;

[0037] Obtain the advertising delivery platform standard source data with the advertising delivery effect indicator greater than the advertising delivery effect indicator dynamic threshold, and extract the preferred advertising material information from the advertising delivery platform standard source data based on the advertising material bill of lading information;

[0038] Integrate the preferred advertising material information and the advertising material bill of lading information for the first time to obtain the first integrated advertising material bill of lading information;

[0039] Based on the key advertising metrics bill of lading information and the bill of lading impact information, determine the key advertising metrics range matrix;

[0040] According to the first integrated advertising material bill of lading information, the advertising delivery time bill of lading information, and the advertising delivery platform bill of lading information, generate the first bill of lading number information, the first bill of lading date information, and the first basic customer information of the bill of lading;

[0041] Based on the first bill of lading number information, the first bill of lading date information, and the first basic customer information of the bill of lading, generate and fill in the preset bill of lading template.

[0042] In an alternative embodiment, the tracking of the first optimization process information, recording of the first real-time processing information, and determination of the first optimization quality index based on the first real-time processing information and the standard source data of the advertising delivery platform specifically include:

[0043] Based on the first real-time processing information, obtain the real-time information of the advertising delivery platform type, the real-time data of the advertising delivery performance, the real-time basic customer information, the real-time advertising material information, and the first real-time processing time information to obtain the real-time source data of the advertising delivery platform;

[0044] Perform a sliding intercept on the real-time source data of the advertising delivery platform with the advertising delivery data node intercept value, the sliding intercept unit value, and the first real-time processing time information to obtain the real-time intercepted source data of the advertising delivery platform;

[0045] Based on the real-time intercepted source data of the advertising delivery platform, obtain the real-time metrics of the advertising delivery effect;

[0046] According to the real-time metrics of the advertising delivery effect, construct a bar chart of the real-time metrics of the advertising delivery effect;

[0047] Construct a cylinder of the real-time metrics of the advertising delivery effect with the bar chart of the real-time metrics of the advertising delivery effect;

[0048] Based on the key advertising metrics range matrix, through , obtain the key comprehensive advertising metrics threshold value, where is the key comprehensive advertising metrics threshold value, is the first value of the th range in the key advertising metrics range matrix, is the second value of the th range in the key advertising metrics range matrix, is the total number of ranges in the key advertising metrics range matrix;

[0049] Based on the real-time metrics of advertising delivery effects, the intercepted values of advertising delivery data nodes, and the cylinder of real-time metrics of advertising delivery effects, through , obtain the real-time comprehensive metric of advertising delivery effects corresponding to the real-time source data of the advertising delivery platform. Among them, is the pi, is the intercepted value of the advertising delivery data node, is the real-time metric of advertising delivery effects corresponding to the -th real-time intercepted source data of the advertising delivery platform, is the total number of real-time intercepted source data of the advertising delivery platform;

[0050] If the real-time comprehensive metric of advertising delivery effects corresponding to the real-time source data of the advertising delivery platform is greater than or equal to the threshold of the critical comprehensive metric of advertising delivery, then use the real-time comprehensive metric of advertising delivery effects as the initial optimization quality index. Otherwise, the initial optimization quality index is half of the real-time comprehensive metric of advertising delivery effects.

[0051] In an alternative embodiment, if there are new customers who need to conduct advertising delivery and advertising optimization, the bill of lading generation process further includes:

[0052] Obtain the new customer's bill of lading requirement information and the new customer's bill of lading impact information;

[0053] Based on the new customer's bill of lading requirement information, the new customer's bill of lading impact information, and the standard source data of the advertising delivery platform, generate and fill in a preset new bill of lading template;

[0054] Distribute the preset new bill of lading template to the corresponding advertising delivery optimization platform, and conduct delivery and optimization on the corresponding advertising delivery strategy.

[0055] Furthermore, an intelligent robot bill of lading management system based on advertising delivery effects is proposed, which is used to implement the management method as described in any one of the above, including:

[0056] A data acquisition module, which is used to collect the source data of the advertising delivery platform and perform data preprocessing on the source data of the advertising delivery platform to obtain the standard source data of the advertising delivery platform;

[0057] A data management module, which is used to organize and store the standard source data of the advertising delivery platform according to a preset data architecture to obtain a big data storage database, and based on the advertising delivery effect metrics and the dynamic thresholds of the advertising delivery effect metrics, determine whether the bill of lading generation process is required, and based on the initial optimization quality index, determine whether the advertising delivery strategy corresponding to the initially optimized preset bill of lading template needs to be optimized twice;

[0058] An effect index calculation and threshold setting module, which is used to sequentially extract the standard source data of the advertising placement platform based on the big data storage database, determine the advertising placement effect index corresponding to the standard source data of the advertising placement platform, and obtain the dynamic threshold of the advertising placement effect index corresponding to the advertising placement effect index according to the standard source data of the advertising placement platform;

[0059] A bill of lading tracking module, which is used to distribute a preset bill of lading template to the corresponding advertising placement optimization platform, obtain and initially optimize the advertising placement strategy corresponding to the preset bill of lading template, and at the same time obtain the initial optimization process information for tracking the initial optimization process information and recording the initial real-time processing information.

[0060] In an alternative embodiment, the data management module includes:

[0061] A data storage unit, which is used to organize and store the standard source data of the advertising placement platform according to a preset data structure to obtain a big data storage database;

[0062] A data judgment unit, which is used to judge whether a bill of lading generation process needs to be performed based on the advertising placement effect index and the dynamic threshold of the advertising placement effect index, and judge whether the advertising placement strategy corresponding to the initially optimized preset bill of lading template needs to be secondarily optimized based on the initial optimization quality index.

[0063] In an alternative embodiment, the effect index calculation and threshold setting module includes:

[0064] An effect index calculation unit, which is used to sequentially extract the standard source data of the advertising placement platform based on the big data storage database and determine the advertising placement effect index corresponding to the standard source data of the advertising placement platform;

[0065] A threshold setting unit, which is used to obtain the dynamic threshold of the advertising placement effect index corresponding to the advertising placement effect index according to the standard source data of the advertising placement platform.

[0066] In an alternative embodiment, the bill of lading tracking module includes:

[0067] An advertising placement optimization unit, which is used to distribute a preset bill of lading template to the corresponding advertising placement optimization platform, obtain and initially optimize the advertising placement strategy corresponding to the preset bill of lading template, and at the same time obtain the initial optimization process information;

[0068] A tracking unit, which is used to track the initial optimization process information and record the initial real-time processing information.

[0069] Compared with the prior art, the beneficial effects of the present invention are:

[0070] An intelligent robot bill of lading management method and system based on the advertising delivery effect proposed in this solution extracts the standard source data of the advertising delivery platform in sequence through a big data storage database, and determines the advertising delivery effect indicators corresponding to the standard source data of the advertising delivery platform. By comprehensively considering the platform type, historical performance, customer, and material information to determine the indicators, a comprehensive evaluation of the advertising delivery effect is realized, enabling the management system to no longer be limited to single-dimensional considerations, but to comprehensively judge from multiple key perspectives. The obtained effect indicators can accurately reflect the real delivery results and assist in making more practical delivery decisions;

[0071] An intelligent robot bill of lading management method and system based on the advertising delivery effect proposed in this solution obtains the dynamic threshold of the advertising delivery effect indicator corresponding to the advertising delivery effect indicator through the standard source data of the advertising delivery platform, realizing the dynamic adaptation of the threshold. Given the diversity of advertising delivery platforms, it is difficult for fixed thresholds to keep up with the pace. The dynamic threshold can be flexibly adjusted in real time according to factors such as delivery time and platform activity, and can promptly detect the subtle changes in the delivery effect and trigger a reasonable bill of lading process, making the advertising optimization more timely and targeted;

[0072] An intelligent robot bill of lading management method and system based on the advertising delivery effect proposed in this solution generates and fills a preset bill of lading template through the bill of lading requirement information, bill of lading impact information, and standard source data of the advertising delivery platform, realizing the standardized creation of the bill of lading. By integrating key information from multiple parties, the advantage is that it provides a clear and complete guide for subsequent advertising delivery optimization. Different personnel working according to the unified bill of lading template can reduce communication costs and improve collaboration efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 is a flowchart of an intelligent robot bill of lading management method based on the advertising delivery effect proposed by the present invention;

[0074] Figure 2 is a flowchart for obtaining the advertising delivery effect indicators in the present invention;

[0075] Figure 3 is a flowchart for obtaining the dynamic threshold of the advertising delivery effect indicator in the present invention;

[0076] Figure 4 is a system framework diagram of an intelligent robot bill of lading management system based on the advertising delivery effect proposed by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0077] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art can think of other obvious variations.

[0078] Referring to Figure 1 - Figure 4 As shown, an intelligent robot bill of lading management method based on the advertising delivery effect includes:

[0079] Collect the source data of the advertising delivery platform, and perform data preprocessing on the source data of the advertising delivery platform to obtain the standard source data of the advertising delivery platform;

[0080] Organize and store the standard source data of the advertising delivery platform according to the preset data structure to obtain the big data storage database;

[0081] Based on the big data storage database, extract the standard source data of the advertising delivery platform in sequence, and determine the advertising delivery effect indicators corresponding to the standard source data of the advertising delivery platform;

[0082] According to the standard source data of the advertising delivery platform, obtain the dynamic threshold of the advertising delivery effect indicator corresponding to the advertising delivery effect indicator;

[0083] Based on the advertising delivery effect indicator and the dynamic threshold of the advertising delivery effect indicator, judge whether it is necessary to perform the bill of lading generation process. If not, continue to monitor the standard source data of the advertising delivery platform in the big data storage database. If so, obtain the bill of lading demand information and the bill of lading impact information;

[0084] Based on the bill of lading demand information, the bill of lading impact information and the standard source data of the advertising delivery platform, generate and fill in the preset bill of lading template;

[0085] Distribute the preset bill of lading template to the corresponding advertising delivery optimization platform, obtain and initially optimize the advertising delivery strategy corresponding to the preset bill of lading template, and at the same time obtain the initial optimization process information;

[0086] Track the initial optimization process information, record the initial real-time processing information, and determine the initial optimization quality index based on the initial real-time processing information and the standard source data of the advertising delivery platform;

[0087] Based on the initial optimization quality index, judge whether it is necessary to perform secondary optimization on the advertising delivery strategy corresponding to the initially optimized preset bill of lading template. If not, continue to collect the source data of the advertising delivery platform. If so, perform secondary optimization.

[0088] Specifically, based on the advertising delivery effect indicator and the dynamic threshold of the advertising delivery effect indicator, judge whether it is necessary to perform the bill of lading generation process. If the advertising delivery effect indicator is greater than or equal to the dynamic threshold of the advertising delivery effect indicator, it means that the advertising delivery effect of the standard source data of the advertising delivery platform is good and there is no need to perform the bill of lading generation process. Otherwise, the bill of lading generation process is required.

[0089] Further, based on the big data storage database, the standard source data of the advertising placement platform is extracted in sequence, and the advertising placement effect indicators corresponding to the standard source data of the advertising placement platform are determined, specifically including:

[0090] Based on the standard source data of the advertising placement platform, obtain the advertising placement platform type information, advertising placement historical performance data, customer basic information, and advertising material information;

[0091] According to the customer basic information, construct a customer basic information parameter matrix, and integrate the standard source data of the advertising placement platform with the same customer basic information parameter matrix to obtain the first standard source data;

[0092] Based on the advertising placement platform type information, divide the first standard source data to obtain the first standard source sub-data;

[0093] Based on the advertising placement historical performance data, through successively obtain the first advertising placement effect indicators corresponding to the first standard source sub-data, where is the first advertising placement effect indicator corresponding to the first standard source sub-data of the th type of advertising placement platform type, is the maximum daily active users of the advertising placement platform of the th type of advertising placement platform type, is the average daily active users of the advertising placement platform of the th type of advertising placement platform type, is the advertising click-through rate corresponding to the first standard source sub-data of the th type of advertising placement platform type, is the advertising conversion rate corresponding to the first standard source sub-data of the th type of advertising placement platform type, and are the importance weights of the advertising click-through rate and the advertising conversion rate respectively;

[0094] Based on the advertising material information, divide the first standard source sub-data to obtain the second standard source sub-data. The advertising material information includes picture-type advertising materials, video-type advertising materials, interactive advertising materials, native advertising materials, full-screen advertising materials, and AR advertising materials;

[0095] Respectively obtain the second advertising placement effect sub-indicators of the second standard source sub-data corresponding to the picture-type advertising materials, video-type advertising materials, interactive advertising materials, native advertising materials, full-screen advertising materials, and AR advertising materials;

[0096] Obtain the mean value of the second advertising placement effect sub-indicators as the second advertising placement effect indicator;

[0097] Use the mean of the first advertising placement effect indicator and the second advertising placement effect indicator as the advertising placement effect indicator corresponding to the standard source data of the advertising placement platform.

[0098] Specifically, for the second advertising placement effect sub-indicator of the second standard source sub-data corresponding to the picture type advertising material, the second advertising placement effect sub-indicator can be obtained by weighted summation of the click-through rate, display times, exposure volume, conversion rate, etc. of the picture type advertising material. For the second advertising placement effect sub-indicator of the second standard source sub-data corresponding to the video type advertising material, it can be obtained by weighted summation of the number of views, viewing duration, completion rate, skip rate, etc. of the video type advertising material. For the second advertising placement effect sub-indicator of the second standard source sub-data corresponding to the interactive advertising material, it can be obtained by weighted summation of the number of interactions, interaction rate, stay duration, etc. corresponding to the interactive advertising material. For the second advertising placement effect sub-indicator of the second standard source sub-data corresponding to the native advertising material, full-screen advertising material, and AR advertising material, it can be obtained by weighted summation in a similar manner as above.

[0099] Furthermore, according to the standard source data of the advertising placement platform, obtain the dynamic threshold of the advertising placement effect indicator corresponding to the advertising placement effect indicator, specifically including:

[0100] Based on the standard source data of the advertising placement platform, obtain the initial advertising placement timestamp and the dynamic threshold calculation timestamp of different advertising placement platforms;

[0101] Obtain the absolute value of the time difference between the initial advertising placement timestamp and the dynamic threshold calculation timestamp corresponding to different advertising placement platforms to obtain the dynamic threshold calculation time reference value;

[0102] According to the dynamic threshold calculation time reference value, obtain the advertising placement data node cut-off value and the sliding cut-off unit value;

[0103] Use the advertising placement data node cut-off value and the sliding cut-off unit value to perform sliding cut-off on the standard source data of the advertising placement platform to obtain the standard source cut-off data and the cut-off time period of the advertising placement platform;

[0104] Through , obtain the advertising placement effect dynamic indicator corresponding to the standard source cut-off data of the advertising placement platform, where is the advertising placement effect dynamic indicator corresponding to the th standard source cut-off data of the advertising placement platform, is the first advertising placement effect indicator corresponding to the th standard source cut-off data of the advertising placement platform, The th standard source cut-off data of the advertising placement platform corresponding to the second advertising placement effect indicator;

[0105] Obtain the maximum and minimum values of the dynamic indicators of the advertising placement effect, remove the maximum and minimum values of the dynamic indicators of the advertising placement effect, and obtain the average value of the remaining dynamic indicators of the advertising placement effect to obtain the advertising placement effect threshold corresponding to the advertising placement effect indicator;

[0106] Through , obtain the dynamic weight corresponding to the advertising placement effect threshold, where is the dynamic weight corresponding to the advertising placement effect threshold of the intercepted data of the th advertising placement platform standard source, is the average daily active users of the intercepted data of the th advertising placement platform standard source within the intercepted time period, is the maximum daily active users of the intercepted data of the th advertising placement platform standard source within the intercepted time period;

[0107] Use the product value of the dynamic weight corresponding to the advertising placement effect threshold and the advertising placement effect threshold as the advertising placement effect dynamic threshold corresponding to the advertising placement effect indicator.

[0108] Specifically, obtain the initial placement timestamp and the dynamic threshold calculation timestamp of different platforms from the advertising placement platform standard source data, calculate the absolute value of the difference between the two, which is the dynamic threshold calculation reference value. Based on the above reference value, determine the intercepted value of the advertising placement data node and the sliding interception unit value, and use them to slide and intercept the standard source data to obtain the intercepted data and the corresponding intercepted time period. Combine the first and second advertising placement effect indicators corresponding to the intercepted data to calculate the advertising placement effect dynamic indicator corresponding to the advertising placement platform standard source intercepted data. After removing the maximum and minimum values from the effect dynamic indicators, calculate the average value to obtain the advertising placement effect threshold; then calculate the dynamic weight according to the average daily active users and the maximum daily active users of the intercepted data within the intercepted period, and multiply the advertising placement effect threshold by the corresponding dynamic weight to obtain the advertising placement effect dynamic threshold corresponding to the advertising placement effect indicator.

[0109] It is understandable that the standard source data of the advertising placement platform is slidably intercepted with the intercepted value of the advertising placement data node and the sliding interception unit value to obtain the standard source intercepted data of the advertising placement platform and the interception time period. The intercepted value of the advertising placement data node can be understood as the size of each intercepted data block. For example, it is set to 50 data records. It determines the amount of data intercepted each time. The larger the value, the wider the coverage of the intercepted data block, but the computational complexity may increase; the smaller the value, the more refined the intercepted data, and it is more sensitive to short-term fluctuations. This is the distance of each sliding movement, which is assumed to be set to 10 records. A smaller sliding interception unit value means a denser interception and can capture more detailed change trends; a larger value makes the interception process more efficient, but some minor fluctuations may be missed. In the sliding interception process, the starting position starts from the starting position of the standard source data. According to the chronological order of the data records, the first batch of data is framed first. The quantity of this batch of data is the intercepted value of the advertising placement data node. For example, if the data starts from the 1st record, the first 50 records are intercepted as the first data block. After sliding and intercepting the first data block, the interception window is moved downward by the sliding interception unit value. That is, starting from the 11th record, 50 records are intercepted again to form the second data block; then starting from the 21st record, and so on in a cycle until the end of the data is less than a complete intercepted value of the data node. Each time an interception is made, this group of data is saved as the standard source intercepted data of the advertising placement platform, and at the same time, the corresponding time range is recorded, that is, the interception time period. For example, the 50 data records intercepted for the first time correspond to a time span from a year a month a day a to b year b month b day b, and this time span is the interception time period of this interception. By continuously sliding and intercepting, the original large-scale standard source data is finally cut into multiple small data blocks, and each data block is attached with a clear time range, which is convenient for subsequent targeted analysis of the dynamic changes in the advertising placement effect in different time periods.

[0110] Furthermore, based on the bill of lading demand information, the bill of lading impact information, and the standard source data of the advertising placement platform, a preset bill of lading template is generated and filled, specifically including:

[0111] According to the bill of lading demand information, obtain the advertising campaign name bill of lading information, the advertising placement platform bill of lading information, the advertising placement time bill of lading information, and the advertising placement key indicator bill of lading information;

[0112] Based on the advertising campaign name bill of lading information, determine the advertising material bill of lading information;

[0113] Obtain the standard source data of the advertising placement platform where the advertising placement effect index is greater than the dynamic threshold of the advertising placement effect index, and extract the preferred advertising material information from the standard source data of the advertising placement platform based on the advertising material bill of lading information;

[0114] Integrate the preferred advertising material information and the advertising material bill of lading information for the first time to obtain the first integrated advertising material bill of lading information;

[0115] Based on the key advertising metrics bill of lading information and the bill of lading impact information, determine the key advertising metrics range matrix;

[0116] According to the first integrated advertising material bill of lading information, the advertising delivery time bill of lading information, and the advertising delivery platform bill of lading information, generate the first bill of lading number information, the first bill of lading date information, and the first basic customer information of the bill of lading;

[0117] Based on the first bill of lading number information, the first bill of lading date information, and the first basic customer information of the bill of lading, generate and fill in the preset bill of lading template.

[0118] Specifically, the first bill of lading number information can generate a unique bill of lading number according to the preset rules and algorithms, in combination with the first integrated advertising material bill of lading information, the advertising delivery time bill of lading information, and the advertising delivery platform bill of lading information. For example, use a specific coding rule to combine and encrypt the key parts of these information to form an identifying number. Combine the first integrated advertising material bill of lading information, the advertising delivery time bill of lading information, and the advertising delivery platform bill of lading information to generate a unique bill of lading number. For example, use a specific coding rule to combine and encrypt the key parts of these information to form an identifying number.

[0119] Furthermore, track the first optimization process information, record the first real-time processing information, and determine the first optimization quality index based on the first real-time processing information and the standard source data of the advertising delivery platform, specifically including:

[0120] Based on the first real-time processing information, obtain the real-time information of the advertising delivery platform type, the real-time data of the advertising delivery performance, the real-time basic customer information, the real-time advertising material information, and the first real-time processing time information to obtain the real-time source data of the advertising delivery platform;

[0121] Use the advertising delivery data node cut-off value, the sliding cut-off unit value, and the first real-time processing time information to perform sliding cut-off on the real-time source data of the advertising delivery platform to obtain the real-time cut-off source data of the advertising delivery platform;

[0122] Based on the real-time cut-off source data of the advertising delivery platform, obtain the real-time metrics of the advertising delivery effect;

[0123] According to the real-time metrics of the advertising delivery effect, construct a column chart of the real-time metrics of the advertising delivery effect;

[0124] Use the column chart of the real-time metrics of the advertising delivery effect to construct a cylinder of the real-time metrics of the advertising delivery effect;

[0125] Based on the key advertising metrics range matrix, through , obtain the threshold of the key comprehensive index for advertising placement, where is the threshold of the key comprehensive index for advertising placement, is the first value of the th range in the matrix of key index ranges for advertising placement, is the second value of the th range in the matrix of key index ranges for advertising placement, is the total number of ranges in the matrix of key index ranges for advertising placement;

[0126] Based on the real-time index of advertising placement effect, the intercepted value of the advertising placement data node, and the cylinder of the real-time index of advertising placement effect, through , obtain the real-time comprehensive index of advertising placement effect corresponding to the real-time source data of the advertising placement platform, where is the pi, is the intercepted value of the advertising placement data node, is the th real-time index of advertising placement effect corresponding to the real-time intercepted source data of the advertising placement platform, is the total number of the real-time intercepted source data of the advertising placement platform;

[0127] If the real-time comprehensive index of advertising placement effect corresponding to the real-time source data of the advertising placement platform is greater than or equal to the threshold of the key comprehensive index for advertising placement, then use the real-time comprehensive index of advertising placement effect as the initial optimization quality index; otherwise, the initial optimization quality index is half of the real-time comprehensive index of advertising placement effect.

[0128] Specifically, the initial real-time processed information is a data set, from which key information of different categories is sorted out. The real-time information of the advertising placement platform type can indicate the specific platform for current advertising placement, whether it is Douyin, WeChat, or other platforms; the real-time data of advertising placement performance covers dynamic indicators such as real-time click-through rate, conversion rate, and display times; the real-time basic customer information includes the age, gender, geographical distribution, etc. of the customers participating in the interaction at this moment; the real-time information of advertising materials involves whether the currently placed advertisement is in the form of a picture, a video, or other forms, as well as the real-time popularity data of the materials; the initial real-time processing time information accurately records the current moment of data capture and processing. Summing up these information forms the real-time source data of the advertising placement platform.

[0129] It is understandable that the sliding interception of real-time source data uses the intercepted values of the previously set advertising data nodes and the sliding interception unit value, and combines the initial real-time processing time information to perform a sliding interception operation on the real-time source data of the just-integrated advertising platform. Based on the real-time intercepted source data of the advertising platform, the real-time indicators of various advertising effects are calculated according to the above calculation formula of the advertising effect indicators. These indicators may be related to click-through rate, conversion rate, return on investment, etc., and are used to accurately reflect the actual effect of the current advertising.

[0130] The expression formula of the key advertising index range matrix is: , where is the first value of the th range in the key advertising index range matrix, and is the second value of the th range in the key advertising index range matrix.

[0131] Furthermore, if there are new customers who need to conduct advertising and advertising optimization, the bill of lading generation process further includes:

[0132] Obtaining the new customer bill of lading requirement information and the new customer bill of lading impact information;

[0133] Generating and filling a preset new bill of lading template based on the new customer bill of lading requirement information, the new customer bill of lading impact information, and the standard source data of the advertising platform;

[0134] Distributing the preset new bill of lading template to the corresponding advertising optimization platform, and performing advertising and optimization on the corresponding advertising strategies.

[0135] Furthermore, an intelligent robot bill of lading management system based on advertising effects is proposed, which is used to implement the management method as described in any one of the above, including:

[0136] A data collection module, which is used to collect the source data of the advertising platform and perform data preprocessing on the source data of the advertising platform to obtain the standard source data of the advertising platform;

[0137] A data management module, which is used to organize and store the standard source data of the advertising platform according to a preset data architecture to obtain a big data storage database, judge whether the bill of lading generation process needs to be carried out based on the advertising effect indicators and the dynamic thresholds of the advertising effect indicators, and judge whether the advertising strategy corresponding to the initially optimized preset bill of lading template needs to be optimized twice based on the initial optimization quality index;

[0138] Effect Index Calculation and Threshold Setting Module. The Effect Index Calculation and Threshold Setting Module is used to sequentially extract the standard source data of the advertising placement platform based on the big data storage database, determine the advertising placement effect index corresponding to the standard source data of the advertising placement platform, and obtain the dynamic threshold of the advertising placement effect index corresponding to the advertising placement effect index according to the standard source data of the advertising placement platform;

[0139] Bill of Lading Tracking Module. The Bill of Lading Tracking Module is used to distribute the preset bill of lading template to the corresponding advertising placement optimization platform, obtain and initially optimize the advertising placement strategy corresponding to the preset bill of lading template, and at the same time obtain the initial optimization process information for tracking the initial optimization process information and recording the initial real-time processing information.

[0140] Further, the Data Management Module includes:

[0141] Data Storage Unit. The Data Storage Unit is used to organize and store the standard source data of the advertising placement platform according to the preset data architecture to obtain the big data storage database;

[0142] Data Judgment Unit. The Data Judgment Unit is used to judge whether the bill of lading generation process needs to be carried out based on the advertising placement effect index and the dynamic threshold of the advertising placement effect index, and judge whether the advertising placement strategy corresponding to the initially optimized preset bill of lading template needs to be secondary optimized based on the initial optimization quality index.

[0143] Further, the Effect Index Calculation and Threshold Setting Module includes:

[0144] Effect Index Calculation Unit. The Effect Index Calculation Unit is used to sequentially extract the standard source data of the advertising placement platform based on the big data storage database and determine the advertising placement effect index corresponding to the standard source data of the advertising placement platform;

[0145] Threshold Setting Unit. The Threshold Setting Unit is used to obtain the dynamic threshold of the advertising placement effect index corresponding to the advertising placement effect index according to the standard source data of the advertising placement platform.

[0146] Further, the Bill of Lading Tracking Module includes:

[0147] Advertising Placement Optimization Unit. The Advertising Placement Optimization Unit is used to distribute the preset bill of lading template to the corresponding advertising placement optimization platform, obtain and initially optimize the advertising placement strategy corresponding to the preset bill of lading template, and at the same time obtain the initial optimization process information;

[0148] Tracking Unit. The Tracking Unit is used to track the initial optimization process information and record the initial real-time processing information.

[0149] The foregoing has shown and described the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments, and what is described in the above embodiments and the specification is only the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements fall within the scope of the present invention claimed. The scope of protection required by the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent robot bill of lading management method based on advertising effect, characterized in that: include: Collecting source data of the advertising delivery platform and preprocessing the source data of the advertising delivery platform to obtain standard source data of the advertising delivery platform; Organize and store the standard source data of the advertising delivery platform according to a preset data architecture to obtain a big data storage database; Based on the big data storage database, the standard source data of the advertising delivery platform is extracted in sequence, and the advertising delivery effect indicators corresponding to the standard source data of the advertising delivery platform are determined; According to the standard source data of the advertising delivery platform, the dynamic threshold value of the advertising delivery effect indicator corresponding to the advertising delivery effect indicator is obtained; Based on the advertising effect index and the dynamic threshold of the advertising effect index, determine whether the bill of lading generation process is needed. If not, continue to monitor the standard source data of the advertising delivery platform in the big data storage database. If so, obtain the bill of lading demand information and bill of lading impact information; Generate and fill in preset bill of lading templates based on bill of lading demand information, bill of lading impact information and standard source data of the advertising delivery platform; Distribute the preset bill of lading template to the corresponding advertising delivery optimization platform, obtain and initially optimize the advertising delivery strategy corresponding to the preset bill of lading template, and obtain the initial optimization process information; Tracking initial optimization process information, recording initial real-time processing information, and determining the initial optimization quality index based on the initial real-time processing information and standard source data of the advertising delivery platform; Based on the initial optimization quality index, determine whether it is necessary to perform secondary optimization on the advertising delivery strategy corresponding to the preset bill of lading template of the initial optimization. If not, continue to collect source data of the advertising delivery platform. If yes, perform secondary optimization. The method of extracting the standard source data of the advertising delivery platform in sequence based on the big data storage database and determining the advertising delivery effect indicators corresponding to the standard source data of the advertising delivery platform specifically includes: Based on the standard source data of the advertising delivery platform, obtain the advertising delivery platform type information, advertising delivery historical performance data, customer basic information and advertising material information; According to the basic information of the customer, a basic information parameter matrix of the customer is constructed, and the standard source data of the advertising delivery platform with the same basic information parameter matrix of the customer is integrated to obtain the first standard source data; Based on the advertisement delivery platform type information, the first standard source data is divided to obtain first standard source sub-data; Based on the historical performance data of advertising, , sequentially obtain the first advertising effect indicator corresponding to the first standard source sub-data, where: For the a first advertising delivery effect indicator corresponding to the first standard source sub-data of the advertising delivery platform type, For the The maximum daily activity of the advertising platform of the type of advertising platform, For the Average daily activity of advertising platforms of different advertising platform types, For the The click-through rate of the advertisements corresponding to the first standard source data of the type of advertisement delivery platform, For the The advertising conversion rate corresponding to the first standard source data of the advertising delivery platform type, and are the importance weights of ad click rate and ad conversion rate respectively; Based on the advertising material information, the first standard source sub-data is divided to obtain the second standard source sub-data, wherein the advertising material information includes picture type advertising material, video type advertising material, interactive advertising material, native advertising material, full screen advertising material and AR advertising material; Respectively obtain the second advertising delivery effect sub-indicator of the second standard source sub-data corresponding to the image type advertising creative, the video type advertising creative, the interactive advertising creative, the native advertising creative, the full screen advertising creative and the AR advertising creative; Obtaining the average of the second advertising delivery effect sub-indicators as the second advertising delivery effect indicator; Taking the average of the first advertising effect indicator and the second advertising effect indicator as the advertising effect indicator corresponding to the standard source data of the advertising delivery platform; The step of obtaining the dynamic threshold of the advertising delivery effect indicator corresponding to the advertising delivery effect indicator according to the standard source data of the advertising delivery platform specifically includes: Based on the standard source data of the advertising delivery platform, the initial advertising delivery timestamp and dynamic threshold calculation timestamp of different advertising delivery platforms are obtained; Obtain the absolute value of the time difference between the initial advertisement delivery timestamp and the dynamic threshold calculation timestamp corresponding to different advertisement delivery platforms, and obtain the dynamic threshold calculation time reference value; Calculate the time reference value according to the dynamic threshold value, and obtain the advertisement delivery data node interception value and the sliding interception unit value; Using the advertisement delivery data node interception value and the sliding interception unit value, the advertisement delivery platform standard source data is slidingly intercepted to obtain the advertisement delivery platform standard source interception data and the interception time period; pass , obtain the dynamic indicators of advertising effect corresponding to the intercepted data of the standard source of the advertising platform, where: For the Dynamic indicators of advertising effectiveness corresponding to the data intercepted from the standard source of each advertising platform, For the The first advertising effect indicator corresponding to the data intercepted from the standard source of the advertising platform, No. a second advertising delivery effect indicator corresponding to the intercepted data from a standard source of an advertising delivery platform; Obtaining the maximum and minimum values ​​of the dynamic indicators of the advertising delivery effect, removing the maximum and minimum values ​​of the dynamic indicators of the advertising delivery effect, obtaining the average of the remaining dynamic indicators of the advertising delivery effect, and obtaining the advertising delivery effect indicator threshold value corresponding to the advertising delivery effect indicator; pass , obtain the dynamic weight corresponding to the threshold of the advertising effect indicator, where: For the The dynamic weight corresponding to the threshold of the advertising effect index of the standard source intercepted data of the advertising platform, For the The average daily activity of the standard source intercepted data of the advertising delivery platform during the interception time period, For the The maximum daily activity of the standard source intercepted data of an advertising platform within the interception time period; The product value of the dynamic weight corresponding to the advertising delivery effect indicator threshold and the advertising delivery effect indicator threshold is used as the advertising delivery effect indicator dynamic threshold corresponding to the advertising delivery effect indicator; The tracking of the initial optimization process information, recording the initial real-time processing information, and determining the initial optimization quality index based on the initial real-time processing information and the standard source data of the advertising delivery platform specifically include: Based on the initial real-time processing information, obtain the real-time information of the advertising delivery platform type, the real-time data of the advertising delivery performance, the basic real-time information of the customer, the real-time information of the advertising material and the first real-time processing time information, and obtain the real-time source data of the advertising delivery platform; Sliding interception of the real-time source data of the advertising delivery platform is performed using the advertisement delivery data node interception value, the sliding interception unit value and the initial real-time processing time information to obtain the real-time interception source data of the advertisement delivery platform; Based on the advertising delivery platform, source data is intercepted in real time to obtain real-time indicators of advertising delivery effects; According to the real-time indicators of advertising delivery effects, a bar chart of real-time indicators of advertising delivery effects is constructed; Using the real-time indicator bar chart of advertising delivery effect, construct a real-time indicator cylinder of advertising delivery effect; Based on the advertising key indicator range matrix, , obtain the threshold of key comprehensive indicators for advertising delivery, where: It is the threshold value of the key comprehensive indicator of advertising. For the advertising key indicator range matrix The first value in the range, For the advertising key indicator range matrix The second value in the range, The total number of ranges in the key metric range matrix for the ad delivery; Based on the real-time indicators of advertising delivery effects, the intercepted values ​​of advertising delivery data nodes and the real-time indicator cylinders of advertising delivery effects, , obtain the real-time comprehensive indicators of advertising delivery effects corresponding to the real-time source data of the advertising delivery platform, among which, is the circumference of a circle, Intercept the value of the advertisement delivery data node. For the Each advertising platform captures the real-time indicators of advertising effects corresponding to the source data in real time. The total number of source data intercepted in real time by the advertising delivery platform; If the real-time comprehensive index of advertising delivery effect corresponding to the real-time source data of the advertising delivery platform is greater than or equal to the threshold of the key comprehensive index of advertising delivery, the real-time comprehensive index of advertising delivery effect will be used as the initial optimization quality index; otherwise, the initial optimization quality index will be half of the real-time comprehensive index of advertising delivery effect.

2. According to claim 1, an intelligent robot bill of lading management method based on advertising delivery effect is characterized in that: The method of generating and filling a preset bill of lading template based on bill of lading demand information, bill of lading impact information and standard source data of the advertising delivery platform specifically includes: According to the bill of lading demand information, obtain the bill of lading information of the advertising campaign name, the bill of lading information of the advertising delivery platform, the bill of lading information of the advertising delivery time and the bill of lading information of the advertising delivery key indicators; Based on the bill of lading information of the advertising campaign name, determine the bill of lading information of the advertising material; Obtaining standard source data of the advertising delivery platform whose advertising delivery effect index is greater than the dynamic threshold of the advertising delivery effect index, and extracting preferred advertising material information from the standard source data of the advertising delivery platform based on the advertising material bill of lading information; Initially integrating the preferred advertising material information and the advertising material bill of lading information to obtain initial advertising material bill of lading integration information; Determine the key indicator range matrix for advertising based on the bill of lading information and bill of lading impact information of key indicators for advertising; Generate the initial bill of lading number information, initial bill of lading date information, and initial bill of lading customer basic information based on the initial advertising material bill of lading integration information, advertising delivery time bill of lading information, and advertising delivery platform bill of lading information; Generate and fill in the preset bill of lading template based on the initial bill of lading number information, initial bill of lading date information, and initial bill of lading customer basic information.

3. The intelligent robot bill of lading management method based on advertising effect according to claim 1 is characterized by: If there are new customers who need to place advertisements and optimize advertisements, the bill of lading generation process also includes: Obtain information on new customers' bill of lading requirements and the impact of new customers' bill of lading; Generate and fill in a preset new bill of lading template based on new customer bill of lading demand information, new customer bill of lading impact information and advertising platform standard source data; Distribute the preset new bill of lading template to the corresponding advertising delivery optimization platform, and deliver and optimize the corresponding advertising delivery strategy.

4. An intelligent robot bill of lading management system based on the effect of advertising, used to implement the management method according to any one of claims 1 to 3, characterized in that: include: A data collection module, wherein the data collection module is used to collect source data of the advertising delivery platform and perform data preprocessing on the source data of the advertising delivery platform to obtain standard source data of the advertising delivery platform; A data management module, wherein the data management module is used to organize and store the standard source data of the advertising delivery platform according to a preset data architecture to obtain a big data storage database, and to determine whether a bill of lading generation process is required based on an advertising delivery effect index and a dynamic threshold value of the advertising delivery effect index, and to determine whether a secondary optimization is required for the advertising delivery strategy corresponding to the preset bill of lading template of the initial optimization based on the initial optimization quality index; The effect indicator calculation and threshold setting module is used to extract the standard source data of the advertising delivery platform in sequence based on the big data storage database, and determine the advertising delivery effect indicator corresponding to the standard source data of the advertising delivery platform, and obtain the advertising delivery effect indicator dynamic threshold corresponding to the advertising delivery effect indicator according to the standard source data of the advertising delivery platform; The bill of lading tracking module is used to distribute the preset bill of lading template to the corresponding advertising delivery optimization platform, obtain and initially optimize the advertising delivery strategy corresponding to the preset bill of lading template, and at the same time obtain the initial optimization process information, which is used to track the initial optimization process information and record the initial real-time processing information.

5. According to claim 4, an intelligent robot bill of lading management system based on advertising effect is characterized in that: The data management module comprises: A data storage unit, the data storage unit is used to organize and store the standard source data of the advertising delivery platform according to a preset data architecture to obtain a big data storage database; The data judgment unit is used to judge whether it is necessary to perform a bill of lading generation process based on an advertising delivery effect index and a dynamic threshold of the advertising delivery effect index, and to judge whether it is necessary to perform secondary optimization on the advertising delivery strategy corresponding to the initially optimized preset bill of lading template based on an initial optimization quality index.

6. The intelligent robot bill of lading management system based on advertising effect according to claim 4 is characterized in that: The effect index calculation and threshold setting module includes: An effect indicator calculation unit, the effect indicator calculation unit is used to extract the standard source data of the advertising delivery platform in sequence based on the big data storage database, and determine the advertising delivery effect indicator corresponding to the standard source data of the advertising delivery platform; A threshold setting unit, wherein the threshold setting unit is used to obtain a dynamic threshold value of an advertising delivery effect indicator corresponding to the advertising delivery effect indicator according to standard source data of the advertising delivery platform.

7. The intelligent robot bill of lading management system based on advertising effect according to claim 4 is characterized in that: The bill of lading tracking module includes: An advertisement delivery optimization unit, the advertisement delivery optimization unit being used to distribute the preset bill of lading template to the corresponding advertisement delivery optimization platform, obtain and initially optimize the advertisement delivery strategy corresponding to the preset bill of lading template, and simultaneously obtain initial optimization process information; A tracking unit is used to track the initial optimization process information and record the initial real-time processing information.

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