Method, device and equipment for improving message reach rate and medium

Abstract

The invention relates to the technical field of medical treatment and data processing, and discloses a method, a device, equipment and a medium for improving the message reach rate, and the method comprises the steps: obtaining different sending targets of a message, and carrying out the information lower layer of the different sending targets of the message; confirming a unique user corresponding to the message according to information lower-layer results of different sending targets of the message; associating different sending targets of the message with the unique user, and establishing a unique user information association model; and confirming an optimal message arriving mode in historical interaction, and sending the message to the unique user through the unique user information association model according to the optimal message arriving mode. The effective message reaching rate is increased, the unnecessary message reaching cost can be reduced, and the stickiness and comfort of a user are improved.

Description

Technical Field

[0001] The present invention relates to the fields of medical technology and data processing technology, and in particular to a method, device, equipment and medium for improving message reach. Background Art

[0002] In today's society, information is complex and different users prefer different ways of obtaining news. In addition, many users block or ignore various messages in order not to be disturbed, resulting in very low efficiency in reaching actual customers.

[0003] In order to optimize the contact method and improve the actual contact efficiency, the existing technology classifies users according to the contact scenarios, and confirms the contact method of users according to different classifications. However, the business scenarios of the contact method are not fixed, the contact methods are scattered, and the contact methods corresponding to fixed scenarios are also fixed, resulting in no significant improvement in contact efficiency, low actual contact efficiency, and increased costs. Summary of the invention

[0004] The present invention provides a method, device, computer equipment and medium for improving message reach rate, so as to solve the technical problems in the prior art that the business scenarios of the reach methods are not fixed, the reach methods are dispersed, resulting in low reach efficiency and low actual reach efficiency.

[0005] In a first aspect, a method for improving message reach is provided, including:

[0006] Obtain different sending targets of the message and perform information sharing on different sending targets of the message;

[0007] According to the information lower-level results of different sending targets of the message, confirm the unique user corresponding to the message;

[0008] Associate different message delivery targets with unique users and establish a unique user information association model;

[0009] Determine the optimal message delivery method in historical interactions, and deliver the message to the unique user through the unique user information association model based on the optimal message delivery method.

[0010] In a second aspect, a device for improving message reach is provided, including:

[0011] The acquisition module is used to acquire different sending targets of the message and perform information downloading on the different sending targets of the message;

[0012] A confirmation module is used to confirm the unique user corresponding to the message according to the lower-level information results of different sending targets of the message;

[0013] An association module is used to associate different sending targets of messages with unique users and establish a unique user information association model;

[0014] The optimal method application module is used to confirm the optimal message delivery method in historical interactions, and deliver the message to the unique user through the unique user information association model based on the optimal message delivery method.

[0015] In a third aspect, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned method for improving message reach rate when executing the computer program.

[0016] In a fourth aspect, a computer-readable storage medium is provided, which stores a computer program. When the computer program is executed by a processor, the steps of the method for improving the message reach rate are implemented.

[0017] In the scheme implemented by the above-mentioned method, device, computer equipment and storage medium for improving the message reach rate, different sending targets of the message can be obtained, and information can be lowered for different sending targets of the message. Then, based on the information lowering results of different sending targets of the message, the unique user corresponding to the message can be confirmed, and then the different sending targets of the message can be associated with the unique user, and a unique user information association model can be established. Finally, the optimal message reach method in the historical interaction can be confirmed, and the message can be sent to the unique user through the unique user information association model according to the optimal message reach method. All user-derived information can be processed uniformly, and user processing can be uniquely confirmed in different systems to reduce repeated message triggering. It can also timely determine the optimal message type for the current message to reach, increase the effective message reach rate, reduce unnecessary message reach costs, and increase user stickiness and comfort. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0019] Figure 1 This is a schematic diagram of an application environment of a method for improving message reach in one embodiment of the present invention;

[0020] Figure 2 It is a flow chart of a method for improving message reach rate in one embodiment of the present invention;

[0021] Figure 3 yes Figure 2 A schematic flow chart of a specific implementation of step S40;

[0022] Figure 4yes Figure 3 A schematic flow chart of a specific implementation of step S410;

[0023] Figure 5 is a flow chart of a method for improving message reach in another embodiment of the present invention;

[0024] Figure 6 It is a structural schematic diagram of a device for improving message reach rate in one embodiment of the present invention;

[0025] Figure 7 is a schematic diagram of a structure of a computer device in one embodiment of the present invention;

[0026] Figure 8 It is another structural schematic diagram of a computer device in one embodiment of the present invention. DETAILED DESCRIPTION

[0027] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0028] The method for improving message reach provided by the embodiment of the present invention can be applied in the following aspects: Figure 1 In the application environment, the client communicates with the server through the network. The server can obtain different sending targets of the message through the client, and perform information lowering on the different sending targets of the message, and then confirm the unique user corresponding to the message according to the information lowering results of the different sending targets of the message, and then associate the different sending targets of the message with the unique user, and establish a unique user information association model, and finally confirm the optimal message reaching method in the historical interaction, and send the message to the unique user through the unique user information association model according to the optimal message reaching method. In the present invention, for complex message reaching situations such as medical business, all user-derived information is processed uniformly, and user processing is uniquely confirmed in different systems, reducing repeated message triggering, and timely determining the optimal message type of the current message, increasing the effective message reaching rate, and reducing unnecessary message reaching costs, increasing user stickiness and comfort. Among them, the client can be but not limited to various personal computers, laptops, smart phones, tablet computers and portable wearable devices. The server can be implemented with an independent server or a server cluster consisting of multiple servers. The present invention is described in detail below through specific embodiments.

[0029] See also Figure 2 As shown, Figure 2A flow chart of a method for improving message reach provided by an embodiment of the present invention includes the following steps:

[0030] S10: obtaining different sending targets of the message, and performing information sharing on the different sending targets of the message;

[0031] The method for improving the message reach rate provided by the present invention can be applied to the outgoing and receiving messages of smart devices in various application scenarios, especially in the medical field. Message generation and sending are usually realized by the system end, and the system end can receive data fed back by the user end in real time. The user end is used to receive the reached messages. Usually, after the message is sent by the system end, it is successfully reached to the user end after the message is screened and the reach rate is improved by the present invention. For example, in the field of medical applications, the system end sends the user's medical message, and the method of improving the message reach rate allows the medical message to successfully reach the user end, avoiding users from blocking or ignoring the medical message, so as to improve the message reach efficiency, wherein the medical message is the type of message that users mark and view on a daily basis.

[0032] The different sending targets of the message are specifically different social accounts of the user, such as mobile phone number, social platform membership number, email name, social platform OpenID, etc. The sending target is determined, and the message is sent to the sending target. The social account corresponding to the sending target receives the message. Among them, the different sending targets of the message are information-downloaded before the message is sent.

[0033] The lower layer of information for the target refers to the data query of each social account type such as mobile phone number, social platform membership number, email name, social platform OpenID to the social account user itself, where information can be divided into multiple levels, usually including data collection layer (lower layer), processing layer and application layer, "information lower layer" refers to the part of original data collection and storage. For example, Ping An Smart Medical Platform account, medical cloud account, mobile phone number, Ping An Insurance Platform account, email name, query the data collection layer of the account in the above platform, and query the identity authentication user of the above account in the data collection layer.

[0034] S20: confirming the unique user corresponding to the message according to the lower-level information results of different sending targets of the message;

[0035] The data of each social account type, such as mobile phone number, social platform membership number, email name, social platform OpenID, etc., is queried to the user using the social account itself, and the user using the social account itself is set as the only user. For example, the Ping An Smart Medical Platform account, medical cloud account, mobile phone number, Ping An Insurance Platform account, and email name are downloaded to the data collection layer, and the data collection layer is queried for the account in the above platform. The identity authentication user of the above account is queried in the data collection layer as the same identity authenticator Xiao Ming, then Xiao Ming is set as the only user after the information is downloaded.

[0036] It should be noted that a unique user may have multiple social accounts on the same platform. In this case, the information of multiple social accounts is also downloaded, and the data collection layer of multiple social accounts in the platform is queried. Multiple social accounts with the same identity authentication are queried, and the multiple social accounts are identified as the same identity authenticated person, that is, the same unique user. This embodiment can achieve that messages in any scenario and any contact method can correspond to a unique user.

[0037] S30: Associating different sending targets of the message with a unique user, and establishing a unique user information association model;

[0038] Different sending targets are associated with a unique user, wherein the different sending targets include social accounts on different platforms and multiple social accounts on the same platform are associated with the unique user.

[0039] When the user conversion relationship corresponding to each information layer is identified according to the information layer results of different message sending targets; the unique user in the user conversion relationship is determined. That is, when a unique user may have multiple social accounts on the same platform, when performing information layering, it is confirmed that the multiple social accounts on the platform are the same identity authenticator, and then the user conversion relationship of multiple social accounts is converted into a unique user, which is convenient for subsequent association and model establishment. The user conversion relationship refers to the migration association behavior between multiple social accounts of users on the platform, which is convenient for unifying the user's information layer data.

[0040] Different sending targets, including social accounts on different platforms and multiple social accounts on the same platform, are associated with a unique user to establish a unique user information association model. When subsequent messages are sent to the sending targets, they can reach the unique user based on the unique user information association model, thereby improving the efficiency of message reach.

[0041] Based on the above solution, this step realizes the unified processing of different message sending targets, breaking the traditional situation where messages are sent to different targets separately. For the same user, no matter what message type is triggered, what purpose is reached, or what social system is reached, as long as the user is logged in to the social account and the user is determined, the unique user information and message content can be obtained from the unique user information association model.

[0042] S40: Determine the optimal message delivery method in historical interactions, and deliver the message to the unique user through the unique user information association model according to the optimal message delivery method.

[0043] It should be noted that if Figure 3 As shown in the figure, the optimal message delivery method in historical interaction is confirmed as follows:

[0044] S410: Acquire the message reaching data of the unique user within the target time period, and determine the message reaching type and actual message reaching situation of the unique user;

[0045] S420: Determine the reach efficiency of different message reach types according to the message reach type and the actual reach situation of the message;

[0046] S430: Confirm the optimal message delivery method in historical interactions based on the delivery efficiency.

[0047] For the analysis of S410 to S430, in the historical interaction behavior of the unique user, the reach data of the message reaching the unique user within the target time period is intercepted, where the message reach data includes the data sent from the system, the message content, the message reach method, and the message reach effect, so as to determine the message reach type and the actual message reach situation of the unique user. Among them, message reach refers to the process of the message being transmitted from the sender to the receiver, and the result of the message being finally received and perceived by the receiver. It is mainly used to describe whether the message successfully reaches the unique user in the information dissemination, push, marketing or notification system.

[0048] The reach efficiency is calculated based on the message reach effect and the data sent by the system. The reach efficiency is an indicator to measure the actual effect of the message on the unique user. Specifically, it refers to the proportion of messages that are effectively received or trigger expected behaviors after successfully reaching the unique user.

[0049] Reach efficiency = (number of effective reach messages / number of message reach) × 100%

[0050] Message reach: the total number of messages actually received by unique users; effective reach: the number of unique users who perform expected actions after receiving messages (such as clicks, opens, reads, purchases, etc.). For example, if a unique user reaches 100 messages and only clicks on 10 of them, then reach efficiency = (10 / 100) × 100% = 10%.

[0051] In another embodiment, after the message reaches, the message that the unique user has viewed is marked, and the message reach efficiency is determined based on the marking mark; after the message reaches, the message that the unique user has not viewed is marked, and the invalid reach rate of the message is determined based on the marking mark. Breaking the traditional message reach end, it is impossible to obtain the user's actual message viewing situation, and by marking the message and other methods to obtain whether the user has read the message, etc., the actual user reach efficiency of different reached messages can be obtained, which can provide reliable data for subsequent analysis of user portraits.

[0052] By calculating the reach efficiency, sorting according to the reach efficiency, selecting the message reach data with the highest reach efficiency, querying the message reach type and message reach method of the message reach data, and confirming it as the optimal message reach method in the historical interaction, in order to optimize the effectiveness of subsequent message reach. In order to improve the specific method of reach efficiency, this embodiment uses user portrait analysis, historical data mining, and exclusion of invalid users. Specifically, user portrait analysis: data analysis, understanding users' interests, behavioral habits and preferences, and building user portraits; grouping and pushing different content to ensure that each user receives messages related to their needs. Historical data mining: Use users' historical interaction behavior data (such as browsing history, purchase history) for accurate recommendations. Exclude invalid users: Eliminate inactive users or users who send messages repeatedly to reduce resource waste.

[0053] Among them, Figure 4 As shown, S410 specifically includes the following steps S411-S414:

[0054] S411: Analyze and determine the user profile based on the actual message reach;

[0055] S412: Determine the habitual contact type of the unique user based on the user portrait;

[0056] S413: Determine the reach efficiency of different message reach types according to the message reach type, the customary reach type, and the actual reach of the message;

[0057] S414: Confirm the optimal message delivery method in historical interactions based on the delivery efficiency.

[0058] User portrait analysis builds a "user portrait" by collecting and analyzing user data to establish a comprehensive understanding of the characteristics, needs and behaviors of unique users. Usually, user portraits are composed of the following dimensions: Demographic characteristics: including basic information such as age, gender, occupation, income level, education, marital status, location, etc. Behavioral characteristics: user operation behavior on the platform, such as browsing history, purchasing habits, active time periods, visit frequency, etc. Interest preferences: the type of content that users pay attention to, and the types of goods or services they are interested in. Psychological characteristics: including the user's personality, values, lifestyle, consumption attitudes, etc. Device and channel preferences: the type of device used by the user (such as mobile phones, computers), operating systems (such as iOS, Android), and access channels (such as APP, Web, social media). Life cycle stage: the stage of the user in the product or service (new users, active users, lost users, loyal users).

[0059] The user portrait analysis method includes the following steps: Data source: platform-owned data (such as user registration information, consumption records); data purchased through external agencies (such as advertising platform data). Data type: structured data: such as age, gender, purchase amount, etc.; unstructured data: such as comment content, social media dynamics, etc. Data cleaning: processing duplicate, incomplete or erroneous data to ensure the accuracy of the analysis results. Data grouping: classify or group users according to specific dimensions (such as age, region, behavior). Data modeling: use machine learning or statistical models to analyze data and explore potential user characteristics and behavioral patterns. Build user portraits: convert the analysis results into a visual user portrait report to intuitively present the characteristics and preferences of the target users.

[0060] After judging the user portrait, the habitual contact type of the unique user is judged according to the user portrait. Specifically, the message type that the user is interested in is inferred according to the user portrait, and the habitual contact type of the unique user is determined according to the message type of interest; the contact efficiency of different message contact types is determined according to the message contact type, the habitual contact type and the actual message contact situation, and then the contact efficiency of the message of the habitual contact type is obtained, and the optimal message contact method in the historical interaction is confirmed based on the contact efficiency. After the optimal contact type model is issued in different scenarios to obtain the user portrait according to the contact rate of the actual contact method, the optimal contact method can be used to contact the user, which increases the effectiveness of the user's actual message contact and reduces some contacts with low contact efficiency and high cost. Statistics are made for the portraits of effective user contact, and different activities can be promoted for this to increase user stickiness and comfort. Reduce the risk of complaints from users' ineffective contact. The selection of the optimal message contact method refers to the analysis of S410 to S430 above, which will not be repeated in this embodiment.

[0061] After step S40, Figure 5 As shown, this embodiment includes:

[0062] S50: Collect the message reaches within a preset time period, and set the reach tracking points in the reached messages;

[0063] S60: Collect the real-time reach efficiency of different message types according to the reach points, and regularly update the reach data of different message reach types.

[0064] For the analysis of S50-S60, collect the message reach within the preset time period, and set the reach tracking point in the reach message. Among them, the reach tracking point refers to the use of tracking technology to record the user's behavior data after receiving the reach information in the product, system or service, so as to analyze the reach effect and optimize the subsequent strategy. The tracking method is as follows: code tracking: developers add tracking code in the message reach link and user operation key nodes; no tracking solution: automatically capture user behavior through tools (such as Mixpanel, GrowingIO); hybrid tracking: combining code tracking and no tracking methods to ensure accurate data collection and improve efficiency.

[0065] Steps for tracking points: Clarify tracking goals: Clarify the tracking effects (such as click-through rate, conversion rate) and key behavior nodes that need to be monitored. Design tracking plan: Determine the tracking location (such as message opening, link clicking); design the tracking data structure (such as event name, attributes, timestamp). Technical implementation: Implement the tracking code on the message sending system and user side, test the tracking function, and ensure normal data collection. Data collection and storage: Collect tracking data and store it in a data warehouse or log system. Data analysis: Use data analysis tools (such as Tableau, Power BI) or programming languages ​​(such as Python, R) to analyze tracking data and evaluate the reach effect. Optimization strategy: Optimize message content, channels, and time strategies based on tracking data feedback.

[0066] In this embodiment, by setting the reach points, the real-time reach efficiency of different message types is collected in real time according to the reach points, and the reach data of different message reach types is updated regularly. By scientifically designing the reach point solution, accurately collecting and analyzing data, the reach effect can be evaluated, the user experience can be optimized, and the reach efficiency can be improved.

[0067] Finally, in order to timely feedback the reach data and regularly update the cloud database, the effectiveness of actual reach and the accuracy of the optimal message reach method are regularly obtained; the effectiveness of actual reach and the accuracy of the optimal message reach method are updated and uploaded to the cloud database. The effectiveness of actual reach and the accuracy of the optimal reach judgment can be regularly obtained, and the result data before and after the optimal reach can be regularly synchronized by configuring an email or a social account to obtain the effectiveness and cost information of the message reach after the optimal reach.

[0068] It can be seen that in the above scheme, for complex message reach situations such as medical business, first obtain the different sending targets of the message, and perform information simplification on the different sending targets of the message, and then confirm the unique user corresponding to the message based on the information simplification results of the different sending targets of the message, and then associate the different sending targets of the message with the unique user, and establish a unique user information association model, and finally confirm the optimal message reach method in the historical interaction, and send the message to the unique user through the unique user information association model according to the optimal message reach method. All user-derived information is processed uniformly, and user processing is uniquely confirmed in different systems, reducing repeated message triggering, and timely determining the optimal message type for the current message, increasing the effective message reach rate, and reducing unnecessary message reach costs, increasing user stickiness and comfort.

[0069] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0070] In one embodiment, a device for improving message reach is provided, and the device for improving message reach corresponds to the method for improving message reach in the above embodiment. Figure 6 As shown, the device for improving message reach rate includes an acquisition module 101, a confirmation module 102, an association module 103, and an optimal method application module 104. Each functional module is described in detail as follows:

[0071] The acquisition module 101 is used to acquire different sending targets of the message and perform information downloading on the different sending targets of the message;

[0072] Confirmation module 102, used to confirm the unique user corresponding to the message according to the information lower-level results of different sending targets of the message;

[0073] The association module 103 is used to associate different sending targets of the message with a unique user and establish a unique user information association model;

[0074] The optimal method application module 104 is used to confirm the optimal message delivery method in historical interactions, and deliver the message to the unique user through the unique user information association model according to the optimal message delivery method.

[0075] In one embodiment, the optimal method application module 104 is specifically used to:

[0076] Obtain the message reach data for a unique user during the target time period, and determine the message reach type and actual message reach status of the unique user;

[0077] Determine the reach efficiency of different message reach types based on the message reach type and the actual message reach situation;

[0078] Based on the reach efficiency, determine the optimal message delivery method in historical interactions.

[0079] In one embodiment, the optimal mode application module 104 is further configured to:

[0080] Analyze and determine user profiles based on the actual reach of messages;

[0081] Determine the habitual contact type of a unique user based on the user portrait;

[0082] Determine the reach efficiency of different message reach types based on message reach types, customary reach types, and actual message reach situations;

[0083] Based on the reach efficiency, determine the optimal message delivery method in historical interactions.

[0084] In one embodiment, the apparatus further comprises:

[0085] The collection module is used to collect the message reaches within a preset time period and set the reach tracking points in the reached messages;

[0086] The first update module is used to collect the real-time reach efficiency of different message types according to the reach points, and regularly update the reach data of different message reach types.

[0087] In one embodiment, the apparatus further comprises:

[0088] The timing acquisition module is used to regularly obtain the effectiveness of actual reach and the accuracy of the optimal message reach method;

[0089] The second update module is used to update and upload the effectiveness of actual reach and the accuracy of the optimal message reach method to the cloud database.

[0090] In one embodiment, the apparatus further comprises:

[0091] The marking module is used to mark the messages that have been viewed by unique users after the messages are reached, and determine the message reach efficiency based on the marking marks; when the messages are reached, mark the messages that have not been viewed by unique users, and determine the message invalid reach rate based on the marking marks.

[0092] In one embodiment, the association module 103 is specifically configured to:

[0093] Identify the user conversion relationship corresponding to each information layer according to the information layer results of different message sending targets;

[0094] Identify unique users in a user conversion relationship.

[0095] The present invention provides a device for improving the message reach rate, which first obtains different sending targets of the message, and performs information layering on the different sending targets of the message, and then confirms the unique user corresponding to the message according to the information layering results of the different sending targets of the message, and then associates the different sending targets of the message with the unique user, and establishes a unique user information association model, and finally confirms the optimal message reach method in the historical interaction, and sends the message to the unique user through the unique user information association model according to the optimal message reach method. All user-derived information is processed uniformly, and user processing is uniquely confirmed in different systems, which reduces repeated triggering of messages, and can also timely determine the optimal message type for the current message, increase the effective message reach rate, reduce unnecessary message reach costs, and increase user stickiness and comfort.

[0096] For the specific limitations of the device for improving the message reach rate, please refer to the limitations of the method for improving the message reach rate above, which will not be repeated here. Each module in the above-mentioned device for improving the message reach rate can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0097] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 7 As shown. The computer device includes a processor, a memory, a network interface and a database connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile and / or volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external client via a network connection. When the computer program is executed by the processor, it implements the functions or steps on the service side of a method for improving message reach.

[0098] In one embodiment, a computer device is provided. The computer device may be a client, and its internal structure diagram may be as follows: Figure 8As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external server via a network connection. When the computer program is executed by the processor, the client-side functions or steps of a method for improving message reach are implemented.

[0099] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0100] By obtaining different sending targets of the message and performing information sub-layering on different sending targets of the message;

[0101] According to the information lower-level results of different sending targets of the message, confirm the unique user corresponding to the message;

[0102] Associate different message delivery targets with unique users and establish a unique user information association model;

[0103] Determine the optimal message delivery method in historical interactions, and deliver the message to the unique user through the unique user information association model based on the optimal message delivery method.

[0104] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0105] By obtaining different sending targets of the message and performing information sub-layering on different sending targets of the message;

[0106] According to the information lower-level results of different sending targets of the message, confirm the unique user corresponding to the message;

[0107] Associate different message delivery targets with unique users and establish a unique user information association model;

[0108] Determine the optimal message delivery method in historical interactions, and deliver the message to the unique user through the unique user information association model based on the optimal message delivery method.

[0109] It should be noted that the above functions or steps that can be implemented by the computer-readable storage medium or computer device can refer to the relevant descriptions on the server side and the client side in the aforementioned method embodiment. To avoid repetition, they will not be described one by one here.

[0110] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0111] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0112] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for improving message reach, characterized in that: include: Obtain different sending targets of the message and perform information sharing on different sending targets of the message; According to the information lower-level results of different sending targets of the message, confirm the unique user corresponding to the message; Associate different message delivery targets with unique users and establish a unique user information association model; Determine the optimal message delivery method in historical interactions, and deliver the message to the unique user through the unique user information association model based on the optimal message delivery method.

2. The method for improving message reach as claimed in claim 1, characterized in that: The step of confirming the optimal message delivery method in the historical interaction includes: Obtain the message reach data for a unique user during the target time period, and determine the message reach type and actual message reach status of the unique user; Determine the reach efficiency of different message reach types based on the message reach type and the actual message reach situation; Based on the reach efficiency, determine the optimal message delivery method in historical interactions.

3. The method for improving message reach as claimed in claim 2, characterized in that: After the step of obtaining the message reaching data of the unique user within the target time period and determining the message reaching type and the actual reaching situation of the unique user, the following steps are further included: Analyze and determine user profiles based on the actual reach of messages; Determine the habitual contact type of a unique user based on the user portrait; Determine the reach efficiency of different message reach types based on message reach types, customary reach types, and actual message reach situations; Based on the reach efficiency, determine the optimal message delivery method in historical interactions.

4. The method for improving message reach as claimed in claim 3, characterized in that: The step of confirming the optimal message reaching method in the historical interaction and delivering the message to the unique user through the unique user information association model according to the optimal message reaching method includes: Collect messages that have been received within a preset time period and set up tracking points in the messages that have been received. According to the reach points, the real-time reach efficiency of different message types is collected in real time, and the reach data of different message reach types is updated regularly.

5. The method for improving message reach as claimed in claim 4, characterized in that: After the step of confirming the optimal message reaching mode in the historical interaction and delivering the message to the unique user through the unique user information association model according to the optimal message reaching mode, the method further includes: Regularly obtain the effectiveness of actual reach and the accuracy of the optimal message reach method; Update and upload the effectiveness of actual reach and the accuracy of the optimal message reach method to the cloud database.

6. The method for improving message reach as claimed in claim 5, characterized in that: After the step of confirming the optimal message reaching mode in the historical interaction and delivering the message to the unique user through the unique user information association model according to the optimal message reaching mode, the method further includes: When the message reaches the target user, it is marked as the message that the unique user has viewed, and the message reach efficiency is determined based on the marked message. When the message reaches the target user, it is marked with a tag that indicates the message has not been viewed by the unique user, and the invalid reach rate of the message is determined based on the tag.

7. The method for improving message reach as claimed in claim 1, characterized in that: The step of confirming the unique user corresponding to the message according to the information lower-level results of different sending targets of the message includes: Identify the user conversion relationship corresponding to each information layer according to the information layer results of different message sending targets; Identify unique users in a user conversion relationship.

8. A device for improving message reach, characterized in that: include: The acquisition module is used to acquire different sending targets of the message and perform information downloading on the different sending targets of the message; A confirmation module is used to confirm the unique user corresponding to the message according to the lower-level information results of different sending targets of the message; An association module is used to associate different sending targets of messages with unique users and establish a unique user information association model; The optimal method application module is used to confirm the optimal message delivery method in historical interactions, and deliver the message to the unique user through the unique user information association model based on the optimal message delivery method.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method for improving the message reach rate as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for improving message reach rate as described in any one of claims 1 to 7 are implemented.

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