Precision marketing copywriting generation method based on AI

Abstract

The invention discloses an AI-based precision marketing copywriting generation method, and relates to the technical field of electric data analysis, and the method comprises the steps: carrying out the classification processing of to-be-analyzed behavior data based on an intelligent analysis terminal, and determining the user browsing data. The method comprises the following steps: firstly, determining a main product browsing set of a user, a main channel for the user to browse a copywriting, a time length for the user to browse the copywriting and a main browsing time period of the user, then generating a product marketing copywriting according to the main product browsing set of the user and the time length for the user to browse the copywriting, and finally, displaying the product marketing copywriting. And pushing the product marketing copywriting to the main channel of the user browsing the copywriting according to the main browsing time period of the user, thereby not only determining the product favored by the user, but also determining the document which can be accepted by the user for a long time, and enabling the user to observe the product marketing copywriting in the frequently browsing time period, thereby improving the user experience. Therefore, the user can know the characteristics of the product within the duration of the copywriting accepted by the user, so that the interest of the user on the product is aroused, and the sales volume of the product is indirectly improved.

Description

Technical Field

[0001] This invention relates to the field of electronic data analysis technology, specifically to an AI-based method for generating precise marketing copy. Background Technology

[0002] Marketing refers to the process by which a company achieves its business objectives by engaging in a series of activities (such as product development, pricing, promotion, and service) to meet consumer needs. The ultimate goal of marketing is to achieve long-term success and sustainable development for a company by satisfying consumer needs and desires. It helps companies build a strong brand influence, attract and retain customers, and thus gain an advantage in a highly competitive market.

[0003] The existing product marketing copy is designed for the general public and does not analyze the preferences of each individual user. As a result, some users do not become interested in the product after reading the marketing copy, which leads to a decline in the product's sales. Summary of the Invention

[0004] To address the aforementioned technical issues, this solution provides an AI-based method for generating precise marketing copy. This technical solution resolves the problem mentioned in the background that existing product marketing copy designs are geared towards the general public and do not analyze the preferences of individual users. As a result, some users may not be interested in the product after reading the marketing copy, leading to a decline in product sales.

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

[0006] AI-based methods for generating precise marketing copy include:

[0007] Acquire behavioral data to be analyzed, and classify and process the data based on the intelligent analysis terminal to determine user browsing data;

[0008] Based on the intelligent analysis terminal, feature analysis and processing are performed on user browsing data to determine the user's main browsing data;

[0009] Based on the intelligent analysis terminal, data analysis and processing are performed on the user's main browsing data to determine the set of products that the user mainly browses.

[0010] Based on intelligent analysis terminals, information analysis and processing of user browsing data are performed to determine the main channels through which users browse text and the duration of user browsing text.

[0011] Based on the intelligent analysis terminal, information analysis and processing of user browsing data are performed to determine the user's main browsing time period;

[0012] Based on intelligent analytics terminals, product marketing copy is pushed to the main channels through which users browse copy according to their main browsing time periods.

[0013] Preferably, the acquisition of the behavioral data to be analyzed, based on the intelligent analysis terminal, and the classification and processing of the behavioral data to be analyzed to determine the user browsing data specifically includes the following steps:

[0014] Based on the intelligent analysis terminal, historical data from various channels is read and processed to obtain behavioral data to be analyzed; wherein, the various channels include browsers and shopping software;

[0015] Based on the intelligent analysis terminal, the metadata of the behavioral data to be analyzed is extracted and processed to obtain user ID information;

[0016] Based on intelligent analysis terminals, user ID information is used as a feature to classify and process behavioral data to be analyzed, thereby obtaining user browsing data.

[0017] Preferably, the step of performing feature analysis processing on user browsing data based on the intelligent analysis terminal to determine the user's main browsing data specifically includes the following steps:

[0018] Based on the intelligent analysis terminal, information is extracted and processed from the user's browsing data to determine the user's browsing domain information.

[0019] Based on the intelligent analysis terminal, user browsing data is classified and processed according to the user's browsing domain information to obtain the user's browsing data for each domain.

[0020] Based on the intelligent analysis terminal, the user's browsing data in each field is compared and processed to determine the user's main browsing data.

[0021] Preferably, the step of performing data comparison processing on the user's browsing data in each field based on the intelligent analysis terminal to determine the user's main browsing data specifically includes the following steps:

[0022] Based on the intelligent analysis terminal, data extraction and processing are performed on the user's browsing data in each field to obtain the user's browsing time in each field.

[0023] Based on the maximum value function, the browsing time of each user in each field is sorted to obtain a set of browsing time.

[0024] Based on the intelligent analysis terminal, the browsing data corresponding to the first data in the browsing duration set is set as the user's primary browsing data.

[0025] Preferably, the step of analyzing and processing the user's main browsing data based on the intelligent analysis terminal to determine the user's main browsing product set specifically includes the following steps:

[0026] Based on the intelligent analysis terminal, data extraction and processing are performed on the user's main browsing data to obtain the user's browsing product information;

[0027] Based on the intelligent analysis terminal, the user's main browsing data is classified and processed according to the characteristics of the product information browsed by the user, and the data of each product browsed by the user is obtained.

[0028] Based on the intelligent analysis terminal, data analysis and processing are performed on each product data browsed by the user to determine the set of products the user mainly browses.

[0029] Preferably, the step of performing data analysis and processing on the data of each product browsed by the user based on the intelligent analysis terminal to determine the set of products that the user mainly browses specifically includes the following steps:

[0030] Based on the intelligent analysis terminal, the duration of each product data browsed by the user is calculated and processed to obtain the total browsing time of each product by the user.

[0031] Based on the intelligent analysis terminal, the total browsing time of each user's product and the set product browsing time threshold are judged and processed.

[0032] If the total browsing time of a product is greater than or equal to the set product browsing time threshold, the product corresponding to the total browsing time will be set as the user's main browsing product.

[0033] If the total browsing time of a product is less than the set product browsing time threshold, the product corresponding to that total browsing time is not the user's primary browsing product.

[0034] Based on the intelligent analysis terminal, the user's main browsed products are aggregated to obtain the set of products the user mainly browses.

[0035] Preferably, the step of analyzing and processing user browsing data based on an intelligent analysis terminal to determine the main channels through which users browse the text and the duration of user browsing the text specifically includes the following steps:

[0036] Based on the intelligent analysis terminal, the user's browsing data is processed to calculate the total browsing time for each channel.

[0037] Based on the maximum value function, the total browsing time of each user through each channel is sorted to obtain the set of browsing time of each user through each channel;

[0038] Based on the intelligent analysis terminal, the channel corresponding to the first data in the set of user browsing channel durations is set as the main channel for the user to browse the copy.

[0039] Based on the intelligent analysis terminal, data analysis and processing are performed on user browsing data to determine the duration of user browsing of text.

[0040] Preferably, the step of analyzing and processing user browsing data based on an intelligent analysis terminal to determine the duration of user browsing of text specifically includes the following steps:

[0041] Based on the intelligent analysis terminal, data extraction and processing are performed on user browsing data to obtain the browsing time of each piece of text;

[0042] Based on the intelligent analysis terminal, a one-dimensional coordinate system is constructed using browsing duration as a parameter;

[0043] Based on the intelligent analysis terminal, the browsing time of each text is placed in a one-dimensional coordinate system to obtain several sets of browsing time data points; the number of browsing time data points is consistent with the number of texts browsed.

[0044] Based on the intelligent analysis terminal, the dispersion analysis of several sets of browsing time data points in a one-dimensional coordinate system is performed to determine the clustering position of the data points.

[0045] Based on the intelligent analysis terminal, the average value of browsing time data points at data point aggregation locations is calculated to obtain the user's browsing time for the text.

[0046] Preferably, the step of analyzing and processing user browsing data based on an intelligent analysis terminal to determine the user's main browsing time period specifically includes the following steps:

[0047] Based on the intelligent analysis terminal, data extraction and processing are performed on user browsing data to obtain the user's browsing time period;

[0048] Based on the intelligent analysis terminal, the user's browsing time period is counted to determine the number of times the user appears in each browsing time period;

[0049] Based on the maximum value function, the number of times a user appears in each browsing time period is sorted to obtain a sorted set of occurrences;

[0050] Based on the intelligent analysis terminal, the user's browsing time period corresponding to the first data in the current sorted set is set as the user's main browsing time period.

[0051] Preferably, the step of pushing product marketing copy to the main channels through which users browse copy based on the intelligent analysis terminal and the user's main browsing time period specifically includes the following steps:

[0052] Based on the intelligent analysis terminal, a draft of the product marketing copy is generated for the product corresponding to the first data in the user's main browsing product collection.

[0053] Based on the intelligent analysis terminal, the initial draft of the product marketing copy is adjusted according to the time users spend browsing the copy, and the product marketing copy is obtained.

[0054] Based on intelligent analytics terminals, product marketing copy is pushed to the main channels through which users browse copy according to their main browsing time periods.

[0055] Furthermore, an AI-based precision marketing copy generation system is proposed to implement the aforementioned AI-based precision marketing copy generation method, including:

[0056] The intelligent analysis terminal controls various modules to perform data classification, feature analysis, data calculation, and data analysis on the behavioral data to be analyzed, generates product marketing copy, and determines the method of pushing the product marketing copy; the intelligent analysis terminal also controls data transmission and information interaction between various modules.

[0057] The data reading module reads and processes historical data from various channels, behavioral data to be analyzed, user browsing data, user browsing data in each field, and user's main browsing data.

[0058] The data classification module performs data classification processing on the behavioral data to be analyzed, user browsing data, and user's main browsing data respectively.

[0059] The duration data extraction module performs duration data extraction processing on the browsing data of each user in each field and the browsing data of each product of the user.

[0060] The data sorting module sorts the user's browsing time in each field, the user's total browsing time in each channel, and the number of times the user appears in each browsing time period.

[0061] The data calculation module performs calculations on each product data browsed by the user, user browsing data, and browsing duration data points at the data point aggregation positions.

[0062] A coordinate system construction module, which constructs a one-dimensional coordinate system based on browsing duration;

[0063] The data analysis module is used to perform discrete analysis on several sets of browsing time data points in a one-dimensional coordinate system.

[0064] The copy generation module generates product marketing copy based on the user's main browsing product set and the duration of the user's browsing time.

[0065] The copywriting push module pushes product marketing copy to the user's main browsing channels based on the user's main browsing time period.

[0066] Furthermore, a storage medium is proposed that stores a computer program, which, when invoked and executed, performs the AI-based precision marketing copy generation method described above.

[0067] Compared with existing technologies, this invention provides an AI-based method for generating precise marketing copy, which has the following beneficial effects:

[0068] This invention first performs multiple data analyses on the behavioral data to be analyzed, determining the user's primary product set, the main channels through which the user browses the copy, the duration of the user's copy browsing, and the user's primary browsing time period. Then, product marketing copy is generated based on the user's primary product set and copy browsing duration. Finally, product marketing copy is pushed to the user's primary copy browsing channels according to the user's primary browsing time period. This method not only identifies the products that users prefer but also determines how long a user can accept a document. It also allows users to see product marketing copy during their frequently viewed time periods, enabling them to understand the product's features within their acceptable copy reading time, thereby arousing user interest in the product and indirectly increasing product sales. Attached Figure Description

[0069] Figure 1 This is a flowchart illustrating steps S100-S600 in the AI-based precision marketing copy generation method proposed in this invention.

[0070] Figure 2 This is a structural block diagram of the AI-based precision marketing copy generation system proposed in this invention;

[0071] Figure 3 A block diagram of an exemplary electronic device capable of implementing embodiments of the present invention is shown. Detailed Implementation

[0072] The following description is intended to disclose the invention and enable those skilled in the art to implement it. The preferred embodiments described below are merely examples, and other obvious variations will occur to those skilled in the art.

[0073] Reference Figure 1 As shown, the AI-based method for generating precise marketing copy includes:

[0074] S100: Acquire the behavioral data to be analyzed, and classify the behavioral data to be analyzed based on the intelligent analysis terminal to determine the user browsing data.

[0075] S200: Based on the intelligent analysis terminal, perform feature analysis and processing on user browsing data to determine the user's main browsing data;

[0076] S300: Based on the intelligent analysis terminal, perform data analysis and processing on the user's main browsing data to determine the set of products that the user mainly browses.

[0077] S400: Based on the intelligent analysis terminal, the user browsing data is analyzed and processed to determine the main channels through which the user browses the text and the duration of the user's browsing time.

[0078] S500: Based on the intelligent analysis terminal, it performs information analysis and processing on user browsing data to determine the user's main browsing time period.

[0079] S600: Based on the intelligent analysis terminal, push product marketing copy to the main channels through which users browse copy according to the user's main browsing time period.

[0080] Those skilled in the art will understand that existing product marketing copy is targeted at all users without analyzing the browsing data of each individual user. This results in the generated product marketing copy not being accepted by all users, indirectly reducing product sales. Therefore, it is necessary to analyze the browsing data of each user to determine their favorite products. Then, it is necessary to analyze users' browsing habits to determine when and through which channels they browse information. In addition, a second analysis of users' browsing data is needed to determine how much time users can accept in product marketing copy. Finally, based on the user's browsing time and the set of products they mainly browse, product marketing copy that conforms to user habits is generated and pushed to the user's main browsing channels during their main browsing time. This allows users to understand the features of the products they like, indirectly increasing product sales.

[0081] Example 1

[0082] S100. Obtain the behavioral data to be analyzed. Based on the intelligent analysis terminal, classify and process the behavioral data to be analyzed to determine the user browsing data. This includes the following steps:

[0083] S101. Based on the intelligent analysis terminal, historical data from various channels are read and processed to obtain behavioral data to be analyzed; wherein, the various channels include browsers and shopping software;

[0084] S102. Based on the intelligent analysis terminal, perform information extraction and processing on the metadata of the behavioral data to be analyzed to obtain user ID information;

[0085] Understandably, the metadata contains user ID information. In order to determine the browsing data of each user, it is necessary to classify the behavioral data to be analyzed based on the user ID information. Therefore, it is necessary to extract features from the metadata of the behavioral data to be analyzed to obtain the user ID information of each behavioral data to be analyzed.

[0086] S103. Based on the intelligent analysis terminal, the user ID information is used as a feature to classify and process the behavioral data to be analyzed, and to obtain user browsing data.

[0087] It is understandable that users may search for their favorite products through multiple channels. Therefore, in order to obtain more comprehensive user behavior data, it is necessary to read historical data from multiple channels and then categorize this historical data. However, this data may contain browsing records of different users. Therefore, this data is categorized according to user ID to obtain the browsing data of each user.

[0088] Example 2

[0089] S200. Based on the intelligent analysis terminal, the user browsing data is processed by feature analysis to determine the user's main browsing data, specifically including the following steps:

[0090] S201. Based on the intelligent analysis terminal, perform information extraction and processing on the user's browsing data to determine the user's browsing domain information;

[0091] S202. Based on the intelligent analysis terminal, the user browsing data is classified and processed according to the user's browsing domain information to obtain the user's browsing data for each domain.

[0092] S203. Based on the intelligent analysis terminal, perform data comparison processing on the user's browsing data in each field to determine the user's main browsing data;

[0093] It is understandable that when users search for information through different channels, they may search for products in different fields. Therefore, we first need to determine the fields that users browse, and then analyze the user browsing data based on the fields they browse to determine the user's browsing data in each field. For example, mothers may like to browse baby products and daily necessities products, but these two products belong to different fields. In order to determine which field the mother needs, we need to first classify the browsing data according to the browsing fields, and then judge these fields to determine the user's main browsing data.

[0094] Specifically, S203, based on the intelligent analysis terminal, performs data comparison processing on the user's browsing data in each field to determine the user's main browsing data, including the following steps:

[0095] S2031. Based on the intelligent analysis terminal, perform data extraction and processing on the user's browsing data in each field to obtain the user's browsing time in each field.

[0096] S2032. Based on the maximum value function, sort the browsing time of each user in each field to obtain a set of browsing times;

[0097] S2033. Based on the intelligent analysis terminal, set the browsing data corresponding to the first data in the browsing duration set as the user's main browsing data.

[0098] It's understandable that the time users spend browsing in a particular area indicates their need for products in that area. Therefore, it's necessary to first categorize user browsing data based on each area in their browsing history. To determine which areas users frequently browse, the browsing time in these areas is analyzed. Products in the areas with the longest browsing time are the products users need most recently. Subsequent analysis of the data within these areas further identifies which products the user needs. Then, a marketing plan is generated based on this product and pushed to the user to help them better understand the product and increase their desire to purchase.

[0099] Example 3

[0100] S300, based on the intelligent analysis terminal, performs data analysis and processing on the user's main browsing data to determine the user's main browsing product set, specifically including the following steps:

[0101] S301. Based on the intelligent analysis terminal, perform data extraction and processing on the user's main browsing data to obtain the user's browsing product information;

[0102] S302. Based on the intelligent analysis terminal, the user's main browsing data is classified and processed according to the user's browsing of product information as a feature, and the data of each product browsed by the user is obtained.

[0103] S303. Based on the intelligent analysis terminal, perform data analysis and processing on the data of each product browsed by the user to determine the set of products that the user mainly browses.

[0104] It is understandable that users may have multiple products they want to buy within a browsing area. Therefore, selecting these products, generating product marketing copy in sequence, and pushing them to users at different times can help users better understand the features of these products and increase their desire to buy.

[0105] Specifically, S303, based on the intelligent analysis terminal, performs data analysis and processing on the data of each product browsed by the user to determine the set of products mainly browsed by the user, including the following steps:

[0106] S3031. Based on the intelligent analysis terminal, perform duration calculation processing on the data of each product browsed by the user to obtain the total browsing time of each product by the user.

[0107] S3032. Based on the intelligent analysis terminal, the total browsing time of each product by the user and the set product browsing time threshold are judged and processed.

[0108] S3033. If the total browsing time of a product is greater than or equal to the set product browsing time threshold, the product corresponding to the total browsing time shall be set as the user's main browsing product.

[0109] S3034. If the total browsing time of a product is less than the set product browsing time threshold, the product corresponding to the total browsing time is not the user's main browsing product.

[0110] S3035. Based on the intelligent analysis terminal, perform aggregate processing on the user's main browsed products to obtain the user's main browsed product set.

[0111] Understandably, to determine which products users want to buy, the browsing time for these products is assessed. Products with browsing time meeting certain criteria are those users intend to purchase. This is because users typically search for information about a product multiple times before making a purchase, thus increasing the browsing time. However, users sometimes lack a comprehensive understanding of a product's features, preventing them from making an immediate purchase. Therefore, after identifying products users want to buy based on browsing time, product marketing copy is generated to provide users with detailed information about the product, enabling them to fully understand it and increasing their desire to buy.

[0112] Example 4

[0113] S400: Based on the intelligent analysis terminal, the user browsing data is analyzed and processed to determine the main channels through which users browse the text and the duration of user browsing. Specifically, this includes the following steps:

[0114] S401. Based on the intelligent analysis terminal, perform duration calculation processing on user browsing data to determine the total browsing time of the user on each channel;

[0115] S402. Based on the maximum value function, sort the total browsing time of each user's channel to obtain the set of browsing time of each user's channel;

[0116] S403. Based on the intelligent analysis terminal, set the channel corresponding to the first data in the user browsing channel duration set as the main channel for the user browsing the text.

[0117] S404. Based on the intelligent analysis terminal, perform data analysis and processing on user browsing data to determine the duration of user browsing the text.

[0118] Understandably, since each user has different habits, each user will browse products through different channels. For example, some users like to browse products on Taobao, while others prefer to browse products on JD.com. Therefore, by analyzing the total browsing time of users on each channel, we can determine which channel users usually prefer to browse products on. The resulting product marketing copy will then be pushed to that channel so that users can learn about the product in a timely manner and have the desire to buy it.

[0119] Specifically, S404, based on the intelligent analysis terminal, performs data analysis and processing on user browsing data to determine the duration of user browsing of text, including the following steps:

[0120] S4041. Based on the intelligent analysis terminal, perform data extraction and processing on user browsing data to obtain the browsing time of each piece of text;

[0121] S4042. Based on the intelligent analysis terminal, a one-dimensional coordinate system is constructed using browsing duration as a parameter;

[0122] S4043. Based on the intelligent analysis terminal, the browsing time of each document is placed in a one-dimensional coordinate system to obtain several sets of browsing time data points; the number of browsing time data points is consistent with the number of browsing documents.

[0123] S4044. Based on the intelligent analysis terminal, perform dispersion analysis on several sets of browsing time data points in a one-dimensional coordinate system to determine the clustering position of the data points.

[0124] S4045. Based on the intelligent analysis terminal, calculate the average value of browsing time data points at the data point aggregation location to obtain the user's browsing time of the text.

[0125] Understandably, each user has a different tolerance for the length of product marketing copy. For example, some users can accept 5 minutes of product marketing copy, while others can only accept 2 minutes. Therefore, it is necessary to determine the user's acceptable viewing time for the copy. This involves extracting user browsing data to determine the viewing time for each piece of copy, and then performing dispersion analysis on the viewing time of each piece of copy to determine the data's central location. The central location represents the acceptable viewing time for product marketing copy. If a product marketing copy is too long, it might be because the user had other things to do after seeing the copy, leaving the page open indefinitely, thus causing an excessively long viewing time. However, this viewing time does not represent the user's actual viewing time. Therefore, dispersion analysis is used to determine the user's actual viewing time for the copy.

[0126] Example 5

[0127] S500, based on the intelligent analysis terminal, performs information analysis and processing on user browsing data to determine the user's main browsing time periods, specifically including the following steps:

[0128] S501. Based on the intelligent analysis terminal, perform data extraction and processing on user browsing data to obtain the user's browsing time period;

[0129] S502. Based on the intelligent analysis terminal, count the user's browsing time period to determine the number of times the user appears in each browsing time period;

[0130] S503. Based on the maximum value function, sort the number of occurrences for each browsing time period to obtain the sorted set of occurrences;

[0131] S504. Based on the intelligent analysis terminal, the user's browsing time period corresponding to the first data in the sorted set that appears this time is set as the user's main browsing time period.

[0132] It's understandable that each user browses products at different times. For example, office workers typically browse products after get off work or during their breaks. If product marketing copy is pushed to an office worker during their work hours, they may not see it. Therefore, analyzing user browsing data by time can help determine users' primary browsing time periods. The most frequently occurring browsing time periods are the users' main browsing time periods. Subsequently, simply pushing product marketing copy to users during their main browsing time periods can increase the probability of users seeing the product marketing copy, potentially increasing their desire to purchase the product.

[0133] Example 6

[0134] S600, based on intelligent analysis terminals, pushes product marketing copy to the main channels through which users browse copy according to their main browsing time periods. The specific steps include the following:

[0135] S601. Based on the intelligent analysis terminal, generate a draft of product marketing copy for the product corresponding to the first data in the user's main browsing product set.

[0136] S602. Based on the intelligent analysis terminal, adjust the duration of the initial draft of the product marketing copy according to the user's browsing time, and obtain the product marketing copy.

[0137] S603: Based on intelligent analysis terminals, push product marketing copy to the main channels through which users browse copy according to the user's main browsing time period.

[0138] Reference Figure 2 As shown, the AI-based precision marketing copy generation system is used to implement the AI-based precision marketing copy generation method described above, including:

[0139] The intelligent analysis terminal controls various modules to perform data classification, feature analysis, data calculation, and data analysis on the behavioral data to be analyzed, generates product marketing copy, and determines the method of pushing the product marketing copy; the intelligent analysis terminal also controls data transmission and information interaction between various modules.

[0140] The data reading module reads and processes historical data from various channels, behavioral data to be analyzed, user browsing data, user browsing data in each field, and user's main browsing data.

[0141] The data classification module performs data classification processing on the behavioral data to be analyzed, user browsing data, and user's main browsing data respectively.

[0142] The duration data extraction module performs duration data extraction processing on the browsing data of each user in each field and the browsing data of each product of the user.

[0143] The data sorting module sorts the user's browsing time in each field, the user's total browsing time in each channel, and the number of times the user appears in each browsing time period.

[0144] The data calculation module performs calculations on each product data browsed by the user, user browsing data, and browsing duration data points at the data point aggregation positions.

[0145] A coordinate system construction module, which constructs a one-dimensional coordinate system based on browsing duration;

[0146] The data analysis module is used to perform discrete analysis on several sets of browsing time data points in a one-dimensional coordinate system.

[0147] The copy generation module generates product marketing copy based on the user's main browsing product set and the duration of the user's browsing time.

[0148] The copywriting push module pushes product marketing copy to the user's main browsing channels based on the user's main browsing time period.

[0149] Figure 3A schematic block diagram of an electronic device 900 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0150] Electronic device 900 includes a computing unit 901, which can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) 902 or a computer program loaded into random access memory (RAM) 903 from storage unit 908. RAM 903 may also store various programs and data required for the operation of electronic device 900. The computing unit 901, ROM 902, and RAM 903 are interconnected via bus 904. Input / output (I / O) interface 905 is also connected to bus 904.

[0151] Multiple components in electronic device 900 are connected to I / O interface 905, including: input unit 906, such as keyboard, mouse, etc.; output unit 907, such as various types of displays, speakers, etc.; storage unit 908, such as disk, optical disk, etc.; and communication unit 909, such as network card, modem, wireless transceiver, etc. Communication unit 909 allows electronic device 900 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0152] The computing unit 901 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 901 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 901 performs the various methods and processes described above, such as methods S100 to S600. For example, in some embodiments, methods S101 to S103 can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as storage unit 908. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 900 via ROM 902 and / or communication unit 909. When the computer program is loaded into RAM 903 and executed by the computing unit 901, one or more steps of methods S101 to S103 described above can be performed. Alternatively, in other embodiments, the computing unit 901 may be configured to execute methods S101 to S103 by any other suitable means (e.g., by means of firmware).

[0153] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0154] The program code used to implement the methods of the present invention can be written in any combination of one or more programming languages. This program code can be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code can be executed entirely on the machine, partially on the machine, as a standalone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0155] In the context of this invention, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable media can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0156] 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 to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. An AI-based method for generating precise marketing copy, characterized in that: include: Acquire behavioral data to be analyzed, and classify and process the data based on the intelligent analysis terminal to determine user browsing data; Based on the intelligent analysis terminal, feature analysis and processing are performed on user browsing data to determine the user's main browsing data; Based on the intelligent analysis terminal, data analysis and processing are performed on the user's main browsing data to determine the set of products that the user mainly browses. Based on intelligent analysis terminals, information analysis and processing of user browsing data are performed to determine the main channels through which users browse text and the duration of user browsing text. Based on the intelligent analysis terminal, information analysis and processing of user browsing data are performed to determine the user's main browsing time period; Based on intelligent analytics terminals, product marketing copy is pushed to the main channels through which users browse copy according to their main browsing time periods.

2. The AI-based precision marketing copy generation method according to claim 1, characterized in that, The process of acquiring the behavioral data to be analyzed, based on an intelligent analysis terminal, and classifying and processing the behavioral data to determine the user's browsing data specifically includes the following steps: Based on the intelligent analysis terminal, historical data from various channels is read and processed to obtain behavioral data to be analyzed; wherein, the various channels include browsers and shopping software; Based on the intelligent analysis terminal, the metadata of the behavioral data to be analyzed is extracted and processed to obtain user ID information; Based on intelligent analysis terminals, user ID information is used as a feature to classify and process behavioral data to be analyzed, thereby obtaining user browsing data.

3. The AI-based precision marketing copy generation method according to claim 1, characterized in that, The process of performing feature analysis on user browsing data based on an intelligent analysis terminal to determine the user's main browsing data includes the following steps: Based on the intelligent analysis terminal, information is extracted and processed from the user's browsing data to determine the user's browsing domain information. Based on the intelligent analysis terminal, user browsing data is classified and processed according to the user's browsing domain information to obtain the user's browsing data for each domain. Based on the intelligent analysis terminal, the user's browsing data in each field is compared and processed to determine the user's main browsing data.

4. The AI-based precision marketing copy generation method according to claim 3, characterized in that, The process of comparing and processing user browsing data in each area based on the intelligent analysis terminal to determine the user's main browsing data includes the following steps: Based on the intelligent analysis terminal, data extraction and processing are performed on the user's browsing data in each field to obtain the user's browsing time in each field. Based on the maximum value function, the browsing time of each user in each field is sorted to obtain a set of browsing time. Based on the intelligent analysis terminal, the browsing data corresponding to the first data in the browsing duration set is set as the user's primary browsing data.

5. The AI-based precision marketing copy generation method according to claim 1, characterized in that, The process of analyzing and processing user browsing data based on an intelligent analysis terminal to determine the user's primary browsing product set includes the following steps: Based on the intelligent analysis terminal, data extraction and processing are performed on the user's main browsing data to obtain the user's browsing product information; Based on the intelligent analysis terminal, the user's main browsing data is classified and processed according to the characteristics of the product information browsed by the user, and the data of each product browsed by the user is obtained. Based on the intelligent analysis terminal, data analysis and processing are performed on each product data browsed by the user to determine the set of products the user mainly browses.

6. The AI-based precision marketing copy generation method according to claim 5, characterized in that, The process of analyzing and processing data on each product browsed by the user based on the intelligent analysis terminal to determine the user's main set of browsed products includes the following steps: Based on the intelligent analysis terminal, the duration of each product data browsed by the user is calculated and processed to obtain the total browsing time of each product by the user. Based on the intelligent analysis terminal, the total browsing time of each user's product and the set product browsing time threshold are judged and processed. If the total browsing time of a product is greater than or equal to the set product browsing time threshold, the product corresponding to the total browsing time will be set as the user's main browsing product. If the total browsing time of a product is less than the set product browsing time threshold, the product corresponding to that total browsing time is not the user's primary browsing product. Based on the intelligent analysis terminal, the user's main browsed products are aggregated to obtain the set of products the user mainly browses.

7. The AI-based precision marketing copy generation method according to claim 1, characterized in that, The process of analyzing and processing user browsing data based on an intelligent analysis terminal to determine the main channels through which users browse text and the duration of their browsing time specifically includes the following steps: Based on the intelligent analysis terminal, the user's browsing data is processed to calculate the total browsing time for each channel. Based on the maximum value function, the total browsing time of each user through each channel is sorted to obtain the set of browsing time of each user through each channel; Based on the intelligent analysis terminal, the channel corresponding to the first data in the set of user browsing channel durations is set as the main channel for the user to browse the copy. Based on the intelligent analysis terminal, data analysis and processing are performed on user browsing data to determine the duration of user browsing of text.

8. The AI-based precision marketing copy generation method according to claim 7, characterized in that, The process of analyzing and processing user browsing data based on an intelligent analysis terminal to determine the duration of user browsing of text specifically includes the following steps: Based on the intelligent analysis terminal, data extraction and processing are performed on user browsing data to obtain the browsing time of each piece of text; Based on the intelligent analysis terminal, a one-dimensional coordinate system is constructed using browsing duration as a parameter; Based on the intelligent analysis terminal, the browsing time of each text is placed in a one-dimensional coordinate system to obtain several sets of browsing time data points; the number of browsing time data points is consistent with the number of texts browsed. Based on the intelligent analysis terminal, the dispersion analysis of several sets of browsing time data points in a one-dimensional coordinate system is performed to determine the clustering position of the data points. Based on the intelligent analysis terminal, the average value of browsing time data points at data point aggregation locations is calculated to obtain the user's browsing time for the text.

9. The AI-based precision marketing copy generation method according to claim 1, characterized in that, The process of analyzing and processing user browsing data based on an intelligent analysis terminal to determine the user's main browsing time periods includes the following steps: Based on the intelligent analysis terminal, data extraction and processing are performed on user browsing data to obtain the user's browsing time period; Based on the intelligent analysis terminal, the user's browsing time period is counted to determine the number of times the user appears in each browsing time period; Based on the maximum value function, the number of times a user appears in each browsing time period is sorted to obtain a sorted set of occurrences; Based on the intelligent analysis terminal, the user's browsing time period corresponding to the first data in the current sorted set is set as the user's main browsing time period.

10. The AI-based precision marketing copy generation method according to claim 1, characterized in that, The process of pushing product marketing copy to the main channels through which users browse copy based on the intelligent analysis terminal and the user's main browsing time period includes the following steps: Based on the intelligent analysis terminal, a draft of the product marketing copy is generated for the product corresponding to the first data in the user's main browsing product collection. Based on the intelligent analysis terminal, the initial draft of the product marketing copy is adjusted according to the time users spend browsing the copy, and the product marketing copy is obtained. Based on intelligent analytics terminals, product marketing copy is pushed to the main channels through which users browse copy according to their main browsing time periods.

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