System and method for automatically generating optimal messages for each of online and offline customers in multi-campaign environment

Abstract

A system for automatically generating an optimal message for each online customer in a multi-campaign environment, according to one embodiment of the present invention, comprises: an application programming interface (API) service module for receiving an API request in real time; a profiling processing module, which generates a target scenario and content information for each user in response to a request of the API service module so as to provide same to the API service module; a content generation module for receiving the target scenario and the content information for each user from the API service module, and generating scenario data to be actually exposed to each user; and a transmission processing module for transmitting the generated scenario data for each individual and for each channel.

Description

System and method for automatically generating optimal messages for each online and offline customer in a multi-campaign environment

[0001] The present invention relates to a message generation system and method, and more particularly, to a technology related to a system and method for automatically generating and delivering optimal messages to each online and offline customer in a multiple campaign environment.

[0002] Many companies operating e-commerce platforms use email, text messages, KakaoTalk channel messages, and app push notifications for customer relationship management (CRM) purposes to increase conversion rates and average purchase price among existing members. To deliver these messages, campaigns must be set up based on the six principles of W and H.

[0003] For example, sending a message requires setting the target recipient conditions and the date and time for sending the message. Furthermore, sending a message requires setting the delivery channel (e.g., email, text message, messenger (notification talk, friend talk), app push, etc.) and configuring the text, image, button name, and button link included in the message (material). Furthermore, sending a message requires setting a target indicator, specifying the quantitative indicator to be achieved, and setting other conditions, such as the number of messages allowed per person per day.

[0004] Message performance can be assessed by setting all six principles (the "W" and "H" principles), creating a campaign, sending the message, and then measuring four indicators: visit rate, click-through rate, conversion rate, and return on ad spend (ROAS). To further improve performance, A / B testing is often used, with variations on one of the six principles. For example, this can compare the four indicators between Group A and Group B. While A / B testing is a powerful way to optimize message performance, it can be cumbersome, requiring marketers to manually set up, conduct, and analyze each experiment. Furthermore, if the number of messages sent is small, only one variation can be tested at a time, which can lead to significant optimization delays.

[0005] Therefore, there is a need for a method that can create and deliver optimized messages for each customer in a short period of time with just simple settings.

[0006] The present invention aims to provide a system and method for automatically generating optimized messages for each online and offline customer in a multiple campaign environment, which allows a marketer to automatically generate optimized messages with just a few simple settings.

[0007] According to one embodiment of the present invention, a system for automatically generating optimal messages for each online customer in a multiple campaign environment may include an API service module for receiving an API (application programming interface) request in real time; a profiling processing module for generating target scenario and content information for each user in response to a request from the API service module and providing the generated scenario and content information to the API service module; a content generation module for receiving target scenario and content information for each user from the API service module and generating scenario data to be actually displayed to each user; and a transmission processing module for transmitting the generated scenario data for each individual and channel.

[0008] The above profiling processing module may include a subject extraction unit that extracts scenario subjects by scenario subject extraction logic from collected behavioral information and meta information for each user.

[0009] The above profiling processing module may include a scenario generation unit that verifies the past scenario exposure history of each user for the extracted scenario target and generates scenario data for each user based on the verified scenario exposure history.

[0010] The above profiling processing module may include a priority setting unit that checks a behavior log for each user and sets a scenario priority based on a campaign or scenario exposure log checked from the behavior log.

[0011] The above content creation module can apply tracking code for measuring campaign performance to scenario data.

[0012] The above system can collect action logs based on the results of sending processing of personalized messages transmitted according to the sending processing module.

[0013] The above action log may include exposure, click, and close information for each sent content.

[0014] A method for automatically generating optimal messages for each offline customer in a multiple campaign environment according to one embodiment of the present invention may include: a batch processing module that performs a batch job set according to time triggering; a profiling processing module that generates target scenario and content information for each user in response to a request from the batch processing module; a priority setting module that sorts multiple scenario data based on priority information based on past campaign performance of the client company; a content generation module that receives target scenario and content information for each user and generates scenario data to be actually displayed to each user; and a transmission processing module that transmits the generated scenario data to each individual and channel.

[0015] The above profiling processing module may include a subject extraction unit that extracts scenario subjects by scenario subject extraction logic from collected behavioral information and meta information for each user.

[0016] The above profiling processing module may include a scenario generation unit that verifies the past scenario exposure history of each user for the extracted scenario target and generates scenario data for each user based on the verified scenario exposure history.

[0017] The above profiling processing module may include a channel information verification unit that checks whether the user is online and which channels are reachable based on channel status information for each user.

[0018] The above profiling processing module may include a user response verification unit that verifies a behavior log for each user and verifies a channel-specific response for each user based on an action message log verified from the behavior log.

[0019] The above content creation module can apply tracking code for measuring campaign performance to scenario data.

[0020] The above system can collect action logs based on the results of sending processing of personalized messages transmitted according to the sending processing module.

[0021] The above action log may include exposure, click, and close information for each sent content.

[0022] According to the present invention, there is an advantage in that a marketer can automatically create and deliver an optimized message with only a few simple settings, without having to experiment, measure, judge, and adjust all of the elements corresponding to the six principles described above.

[0023] For example, there is an advantage in that a marketing manager can input simple settings to automatically create and send materials (e.g., images, text, etc.) based on the product interests of each member.

[0024] FIG. 1 is a block diagram showing the detailed configuration of a system for automatically generating optimal messages for each customer in a multiple campaign environment according to one embodiment of the present invention.

[0025] Figure 2 is a block diagram showing a detailed configuration of a scenario processing module according to one embodiment of the present invention.

[0026] FIG. 3 is a block diagram showing a detailed configuration of a scenario selection module according to one embodiment of the present invention.

[0027] FIG. 4 is a flowchart illustrating a method for automatically generating optimal messages for each customer in a multiple campaign environment according to one embodiment of the present invention.

[0028] FIG. 5 is a block diagram showing a detailed configuration of an online customer-specific automatic optimal message generation system in a multiple campaign environment according to one embodiment of the present invention.

[0029] Figure 6 is a block diagram showing a detailed configuration of a profiling processing module according to one embodiment of the present invention.

[0030] FIG. 7 is a block diagram showing a detailed configuration of an offline customer-specific automatic optimal message generation system in a multiple campaign environment according to one embodiment of the present invention.

[0031] Figure 8 is a block diagram showing a detailed configuration of a profiling processing module according to one embodiment of the present invention.

[0032] FIG. 9 is a diagram illustrating the concept of profiling generation according to one embodiment of the present invention.

[0033] FIG. 10 is a block diagram illustrating a system for automatically generating optimal messages for each customer in a multiple campaign environment according to one embodiment of the present invention.

[0034] Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings and the contents described in the attached drawings, but the present invention is not limited or restricted by the embodiments.

[0035] The terminology used herein is for the purpose of describing embodiments only and is not intended to limit the present invention. In this specification, the singular also includes the plural unless the context clearly dictates otherwise. As used herein, the terms "comprises" and / or "comprising" do not exclude the presence or addition of one or more other components, steps, operations, and / or elements.

[0036] The terms “embodiment,” “example,” “aspect,” and “example” used herein are not to be construed as implying that any aspect or design described is better or advantageous over other aspects or designs.

[0037] Also, the term 'or' means 'inclusive or' rather than 'exclusive or'. That is, unless stated otherwise or clear from context, the expression 'x utilizes a or b' means any one of the natural inclusive permutations.

[0038] Additionally, as used in this specification and claims, the singular forms “a” or “an” should generally be construed to mean “one or more” unless otherwise indicated or clear from the context to be in the singular form.

[0039] Additionally, while the terms "first," "second," etc., used in this specification and claims may be used to describe various components, these components should not be limited by these terms. These terms are used solely to distinguish one component from another.

[0040] Unless otherwise defined, all terms (including technical and scientific terms) used herein may be used in their common sense to those of ordinary skill in the art to which the present invention pertains. Furthermore, terms defined in commonly used dictionaries are not to be interpreted ideally or excessively unless explicitly and specifically defined otherwise.

[0041] Meanwhile, when describing the present invention, if a detailed description of a related known function or configuration is judged to unnecessarily obscure the gist of the present invention, such detailed description will be omitted. Furthermore, the terminology used in this specification is intended to appropriately express embodiments of the present invention and may vary depending on the intent of the user or operator, or the practices of the field to which the present invention pertains. Therefore, the definitions of these terms should be based on the contents throughout this specification.

[0042] In the various embodiments described below, a campaign may be a concept that includes advertisements, but is not limited to specific advertisement data. In one embodiment, campaign information may be referred to as scenario data, and the scenario data may include at least one of text, images, videos, and animations.

[0043] FIG. 1 is a block diagram showing the detailed configuration of a system for automatically generating optimal messages for each customer in a multiple campaign environment according to one embodiment of the present invention.

[0044] Referring to FIG. 1, a system for automatically generating optimal messages for each customer in a multiple campaign environment according to one embodiment of the present invention may include a profiling processing module (10), a scenario processing module (20), a scenario selection module (30), a sending processing module (40), and a performance measurement module (50).

[0045] The profiling processing module (10) may generate profiling based on behavioral data on a browser and metadata of the customer. For example, the behavioral data on the browser may include at least one of a page URL (uniform resource locator), the number of item exposures, shopping cart information, purchase information, and scroll information. The customer metadata may include at least one of purchase history, member information, and promotional information. The profiling processing module (10) may calculate profiling based on information of the customer itself (e.g., customer metadata) and behavioral information for each customer (e.g., behavioral data on a browser). According to one embodiment, the profiling may include at least one of interest in a specific item, interest in a specific category, purchase probability, and revisit probability. The profiling may be calculated according to a known calculation method.

[0046] The profiling processing module (10) may generate profiling result data according to the profiling generation process. At this time, the profiling result data may include goal-oriented profiling data. For example, the goal-oriented profiling data may be automatically tuned and generated using profiling parameters based on marketing actions and their performance. The profiling results may be generated by date and / or time. The profiling results may include individual profiling data and may further include targets and information for subsequent marketing actions.

[0047] According to one embodiment, the scenario processing module (20) can generate a plurality of scenario data based on the result data of profiling generated by the profiling processing module (10).

[0048] Hereinafter, the scenario processing module (20) will be described in detail with reference to FIG. 2.

[0049] Figure 2 is a block diagram showing a detailed configuration of a scenario processing module according to one embodiment of the present invention.

[0050] Referring to FIG. 2, a scenario processing module (20) according to one embodiment may include a triggering unit (21), a scenario matching unit (22), a scenario generation unit (23), and an additional information processing unit (24).

[0051] In one embodiment, the triggering unit (21) may be triggered to simultaneously process batch data generation and real-time requests for scenario data. To this end, the triggering unit (21) may have a dual architecture to simultaneously process batch data generation operations and real-time requests.

[0052] The scenario matching unit (22) can select target scenarios based on the client's campaign execution status and personal profiling and performance data. For example, the client's campaign execution status may include activated marketing channels or set times. The personal profiling and performance data may include data reflecting the previous exposure status for each campaign period or the individual's intention (e.g., turning off exposure).

[0053] The above scenario generation unit (23) can generate multiple scenario data for each individual. For example, since scenario data assigned to each individual can be selectively dropped in the future, the above scenario generation unit (23) can generate multiple scenario data.

[0054] The above-mentioned additional information processing unit (24) can additionally generate additional information that is essential to be included in the campaign. The additional information generated by the above-mentioned additional information processing unit (24) can be attached to each of the plurality of scenario data generated by the above-mentioned scenario generation unit (23).

[0055] Referring again to FIG. 1, according to one embodiment, the scenario selection module (30) can select individual final data from among the plurality of scenario data generated by the scenario processing module (20).

[0056] Hereinafter, the scenario selection module (30) will be described in detail with reference to FIG. 3.

[0057] FIG. 3 is a block diagram showing a detailed configuration of a scenario selection module according to one embodiment of the present invention.

[0058] Referring to FIG. 3, the scenario selection module (30) may include a priority evaluation unit (31), a channel filtering unit (32), and a content selection unit (33).

[0059] In one embodiment, the priority evaluation unit (31) can sort multiple scenario data based on priority information derived from the client's past campaign performance. For example, the priority evaluation unit (31) can select and set multiple indicators, such as open rate, click-through rate, and ROAS (Return of Ad Spend), according to the campaign's purpose. The priority evaluation unit (31) may further include response logic for new campaigns (cold starts).

[0060] In one embodiment, the channel filtering unit (32) can filter out unnecessary data (e.g., scenario data) from among the plurality of scenario data according to settings / policies such as channel status and cost control for each customer, thereby eliminating such unnecessary data. In this way, by eliminating unnecessary data from among the plurality of scenario data, charging can be controlled, and erroneous charges and incorrect transmissions can be prevented in advance.

[0061] In one embodiment, the content selection unit (33) may select materials (e.g., scenario data) to be actually exposed to customers and generate final scenario data. The content selection unit (33) may generate personalized scenario data based on previously received customer-specific campaign data. In this case, the content selection unit (33) may employ a tracking means for measuring campaign performance.

[0062] Referring back to FIG. 1, according to one embodiment, the transmission processing module (40) can transmit and process the final scenario data selected by the scenario selection module (30) for each individual and channel. For example, the transmission processing module (40) can transmit and process the final scenario data selected by the scenario selection module (30) by at least one of battery, email, SMS, MMS, notification talk, channel talk, talk provided by a portal site, and app push. At this time, the transmission processing module (4) can transmit a personalized message (e.g., scenario data) in real time or at a preset time. The transmission processing module (40) can check the channel health of the site by collecting indicators of the transmission itself, such as transmission success or exposure success.

[0063] In one embodiment, the performance measurement module (50) can measure the performance of a campaign. For example, the performance measurement module (50) can collect different feedback data according to the characteristics of each channel. In this case, the performance measurement module (50) can collect direct response data from the recipient customer based on the user's open or click behavior. In addition, the performance measurement module (50) can link the on-site behavior data after the recipient customer's response. In addition, the performance measurement module (50) can configure a feedback loop to reflect the performance measurement results back into the customer's profiling. Accordingly, the aforementioned profiling processing module (10) can regenerate the customer's profiling based on the performance measurement results fed back from the performance measurement module (50).

[0064] FIG. 4 is a flowchart illustrating a method for automatically generating optimal messages for each customer in a multiple campaign environment according to one embodiment of the present invention.

[0065] Referring to FIG. 4, according to one embodiment, a system for automatically generating optimal messages for each customer in a multiple campaign environment may first collect behavioral data and metadata of the customer company on a browser (S410). Then, the system for automatically generating optimal messages for each customer in the multiple campaign environment may perform a step of generating profiling based on the collected behavioral data and metadata (S420).

[0066] Next, the system for automatically generating optimal messages for each customer in the above multiple campaign environment can generate multiple scenario data based on the result data of the above generated profiling. (S430)

[0067] Next, the system for automatically generating optimal messages for each customer in the above multiple campaign environment can select individual final data from among the multiple scenario data. (S440)

[0068] Next, the system for automatically generating optimal messages for each customer in the above multiple campaign environment can deliver the selected final data to each individual and channel (S450).

[0069] Finally, the system for automatically generating optimal messages for each customer in the aforementioned multi-campaign environment can measure campaign performance based on feedback data tailored to channel characteristics (S460). Furthermore, a feedback loop can be configured to reflect the campaign performance measurement results back into customer profiling. Accordingly, the performance measurement results from step S460 can be fed back to regenerate profiling in step S420.

[0070] FIG. 5 is a block diagram showing a detailed configuration of an online customer-specific automatic optimal message generation system in a multiple campaign environment according to one embodiment of the present invention.

[0071] Referring to FIG. 5, an online customer-specific automatic optimal message generation system in a multiple campaign environment according to one embodiment of the present invention may include a profiling processing module (510), an API (application programming interface) service module (520), a content generation module (530), a transmission processing module (540), and an information collection module (550).

[0072] The above API service module (520) can receive API requests in real time. The API service module (520) can request profiling processing from the profiling processing module (510) according to real-time API requests.

[0073] The profiling processing module (510) can generate user-specific target scenario and content information in response to a request from the API service module (520). The profiling processing module (510) can receive behavioral information and meta information for each user to extract scenario targets and check past scenario exposure history information. The profiling processing module (510) can generate user-specific scenario data based on the past scenario exposure history of the scenario targets. In addition, the profiling processing module (510) can receive behavioral logs and check campaign or scenario exposure logs (e.g., action banner logs) through the behavioral logs. The profiling processing module (510) can set scenario priorities based on the confirmed campaign or scenario exposure logs (e.g., action banner logs).

[0074] Hereinafter, the profiling processing module (510) will be described in detail with reference to FIG. 6.

[0075] Figure 6 is a block diagram showing a detailed configuration of a profiling processing module according to one embodiment of the present invention.

[0076] Referring to FIG. 6, the profiling processing module (510) may include a target extraction unit (511), a scenario generation unit (512), and a priority setting unit (513).

[0077] The above target extraction unit (511) can extract scenario targets from the collected behavioral information and meta information for each user by using scenario target extraction logic.

[0078] The above scenario generation unit (512) can check the past scenario exposure history for each user for the extracted scenario target, and generate scenario data for each user based on the confirmed scenario exposure history.

[0079] The priority setting unit (513) can check the action log for each user and check the campaign or scenario exposure log (e.g., action banner log) from the action log. The priority setting unit (513) can set the scenario priority based on the checked campaign or scenario exposure log (e.g., action banner log).

[0080] Referring back to FIG. 5, the API service module (520) can receive target scenario and content information for each user from the profiling processing module (510) as a result of a profiling processing request to the profiling processing module (510). The API service module (520) can transmit the target scenario and content information for each user received from the profiling processing module (510) to the content creation module (530).

[0081] In one embodiment, the content creation module (530) may select materials (e.g., scenario data) to be actually exposed to customers and perform the task of generating final scenario data. The content creation module (530) may generate personalized scenario data based on previously received customer-specific campaign data and template information. At this time, the content creation module (530) may apply a tracking means (or tracking code) for measuring campaign performance.

[0082] According to one embodiment, the transmission processing module (540) may transmit final scenario data for each individual and channel based on the content selected by the content generation module (530) and the transmission request data list. For example, the transmission processing module (540) may transmit the final scenario data generated by the content generation module (530) using a banner or a JavaScript function (js function). In this case, the transmission processing module (540) may transmit personalized messages (e.g., scenario data) in real time or at a preset time. The transmission processing module (540) may check the channel health of the site by collecting indicators of the transmission itself, such as transmission success or exposure success.

[0083] According to one embodiment, the information collection module (550) may collect, as a behavior log, the results of the transmission processing of personalized messages transmitted according to the transmission processing module (540), and the exposure, click, and close information of each transmitted content. The information collection module (550) may transmit the collected behavior log to the profiling processing module (510). That is, the information collection module (550) may configure a feedback loop to reflect the collected behavior log back into the customer's profiling. Accordingly, the above-described profiling processing module (510) may regenerate the customer's profiling based on the performance measurement results fed back from the information collection module (550).

[0084] FIG. 7 is a block diagram showing a detailed configuration of an offline customer-specific automatic optimal message generation system in a multiple campaign environment according to one embodiment of the present invention.

[0085] Referring to FIG. 7, an offline customer-specific automatic optimal message generation system in a multiple campaign environment according to one embodiment of the present invention may include a profiling processing module (710), a priority setting module (720), a content generation module (730), a sending processing module (740), and a batch processing module (750).

[0086] The batch processing module (750) can perform batch jobs set according to time triggering. For example, the batch processing module (750) can request profiling processing from the profiling processing module (710) according to the set batch jobs.

[0087] The above profiling processing module (710) can generate user-specific target scenario and content information in response to a request from the batch processing module (750).

[0088] Hereinafter, the profiling processing module (710) will be described in detail with reference to FIG. 8.

[0089] Figure 8 is a block diagram showing a detailed configuration of a profiling processing module according to one embodiment of the present invention.

[0090] Referring to FIG. 8, the profiling processing module (710) may include a target extraction unit (711), a scenario generation unit (712), a channel information verification unit (713), and a user response verification unit (714).

[0091] The above target extraction unit (711) can extract scenario targets from the collected behavioral information and meta information for each user through the scenario target extraction logic.

[0092] The above scenario generation unit (712) can check the past scenario exposure history for each user for the extracted scenario target, and generate scenario data for each user based on the confirmed scenario exposure history.

[0093] The above channel information verification unit (713) can check whether the user is online and which channels are reachable based on channel status information for each user.

[0094] The user response verification unit (714) can verify the action log for each user and check the action message log from the action log. The user response verification unit (714) can verify the response of each user for each channel based on the verified action message log.

[0095] Referring back to FIG. 7, the profiling processing module (710) may generate profiling result data according to the profiling generation process. At this time, the profiling result data may include goal-oriented profiling data. For example, the goal-oriented profiling data may be automatically tuned and generated using profiling parameters based on marketing actions and their performance. The profiling results may be generated by date and / or time. The profiling results may include individual profiling data and may further include targets and information for subsequent marketing actions.

[0096] In one embodiment, the priority setting module (720) can sort multiple scenario data based on priority information derived from the client's past campaign performance. For example, the priority setting module (720) can select and set multiple indicators, such as open rate, click-through rate, and ROAS (Return of Ad Spend), according to the campaign's objectives. The priority setting module (720) may further include response logic for new campaigns (cold starts).

[0097] In one embodiment, the content creation module (730) may select materials (e.g., scenario data) to be actually exposed to customers and perform the task of generating final scenario data. The content creation module (730) may generate personalized scenario data based on previously received customer-specific campaign data and template information. At this time, the content creation module (730) may apply a tracking means for measuring campaign performance.

[0098] According to one embodiment, the transmission processing module (740) can transmit and process the final scenario data generated by the content generation module (730) for each individual and channel. For example, the transmission processing module (740) can transmit and process the final scenario data generated by the content generation module (730) by at least one of email, SMS, MMS, notification talk, channel talk, talk provided by a portal site, and app push. In this case, the transmission processing module (740) can transmit a personalized message (e.g., scenario data) in real time or at a preset time. The transmission processing module (740) can generate behavior logs such as transmission success, arrival, open, and click and feed them back to the profiling processing module (710). For example, the above-described profiling processing module (710) can regenerate the profiling of the corresponding customer based on the fed-back behavior log.

[0099] FIG. 9 is a diagram illustrating the concept of profiling generation according to one embodiment of the present invention.

[0100] Referring to Figure 9, a user can perform various actions over time from visiting a service to completing a purchase. The collected information may include information about the click area, page URL, and inflow channel.

[0101] In one embodiment, analysis can be performed in the reverse direction of the time flow to analyze a user's profile. For example, a purchase completion profile, as illustrated in FIG. 9, can be generated based on information collected from a user who has completed a purchase. The method illustrated in FIG. 9 may be referred to as an ad hoc target-responsive profiling method, but is not limited to this term.

[0102] To generate the above profiling, behaviors can first be tokenized. That is, activities generated by users (i.e., customers) can be defined and converted into unique token values. For example, all detectable behaviors, such as visits to the first page found on a browser, access to the shopping cart page, clicks, and visit times, can be tokenized and stored.

[0103] Next, you can select a token that corresponds to your goal. Any action can be designated as a goal. For example, you can select a token that corresponds to a purchase completion goal, a visit to a product detail page, or a purchase of 100,000 won or more.

[0104] Next, initial parameters can be set based on relative values. That is, parameters can be set for target behaviors found in the behavioral sequence for each customer. These target behaviors can be defined as various features, such as whether they occur (yes or no) or how often they occur (0 to x) in a customer session. Furthermore, customers can be divided into as many clusters as necessary based on the presence or absence of target behaviors, and relative values ​​between token features, such as token occurrence and frequency, can be calculated for each cluster.

[0105] Next, parameters can be optimized through test validation. That is, parameter optimization can be performed by applying initial parameters to a test data set and comparing them. This test validation can utilize a test data set divided by a certain percentage during the initial parameter setting, or a data set divided by time, optimizing to the latest values.

[0106] Finally, profiling can be performed by applying new data. By applying the optimal parameters obtained in the above steps to new customer data, the probability of occurrence of a target token can be calculated. In other words, the probability of triggering a target action can be calculated based on behaviors that previously occurred within a single session. For example, as a result of this profiling, it is possible to identify high-purchase probability targets, high-churn groups, those interested in specific categories, and long-term non-visitors.

[0107] FIG. 10 is a block diagram illustrating a system for automatically generating optimal messages for each customer in a multiple campaign environment according to one embodiment of the present invention.

[0108] Referring to FIG. 10, a system for automatically generating optimal messages for each customer in a multiple campaign environment according to one embodiment may include a communication unit (110), a display (120), a memory (130), a user input unit (140), and a processor (150).

[0109] According to one embodiment, the communication unit (110) may receive browser-based behavioral data and customer metadata input to the profiling processing module (10, 510, 710) from an external server. The browser-based behavioral data and customer metadata collected through the communication unit (110) may be provided to the processor (150). The memory (130) may store the browser-based behavioral data and customer metadata collected through the communication unit (110).

[0110] According to one embodiment, the processor (150) may process functions performed in the profiling processing module (10, 510, 710) based on data collected through the communication unit (110). For example, the processor (150) may perform the functions of each module illustrated in FIGS. 1, 5, and 7.

[0111] According to one embodiment, the processor (150) can transmit selected final data (e.g., scenario data) to each individual and channel through the communication unit (110).

[0112] In one embodiment, the user input unit (140) may receive a scenario triggering request (e.g., a batch data generation request and / or a real-time request) from a user. The display (120) may display data input or generated during the scenario data generation process on the screen. In addition, the display (120) may display performance measurement results measured by the performance measurement module (50) on the screen after the personalized scenario message is delivered.

[0113] The devices described above may be implemented as hardware components, software components, and / or a combination of hardware components and software components. For example, the devices and components described in the embodiments may be implemented using one or more general-purpose computers or special-purpose computers, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable array (FPA), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing instructions and responding to them. The processing device may execute an operating system (OS) and one or more software applications running on the operating system. The processing device may also access, store, manipulate, process, and generate data in response to the execution of the software. For ease of understanding, the processing device is sometimes described as being used alone; however, one of ordinary skill in the art will recognize that the processing device may include multiple processing elements and / or multiple types of processing elements. For example, a processing unit may include multiple processors, or a processor and a controller. Other processing configurations, such as parallel processors, are also possible.

[0114] Software may include a computer program, code, instructions, or a combination of one or more of these, which may configure a processing device to perform a desired operation or may, independently or collectively, command the processing device. The software and / or data may be permanently or temporarily embodied in any type of machine, component, physical device, virtual equipment, computer storage medium or device, or transmitted signal wave, for interpretation by the processing device or for providing instructions or data to the processing device. The software may also be distributed over networked computer systems and stored or executed in a distributed manner. The software and data may be stored on one or more computer-readable recording media.

[0115] The method according to the embodiment may be implemented in the form of program commands that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program commands, data files, data structures, etc., alone or in combination. The program commands recorded on the medium may be those specially designed and configured for the embodiment or may be those known and available to those skilled in the art of computer software. Examples of the computer-readable recording medium include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs and DVDs, magneto-optical media such as floptical disks, and hardware devices specially configured to store and execute program commands, such as ROMs, RAMs, and flash memories. Examples of the program commands include not only machine language codes generated by a compiler, but also high-level language codes that can be executed by a computer using an interpreter, etc. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiment, and vice versa.

[0116] Although the embodiments described above have been described by way of limited examples and drawings, those skilled in the art will appreciate that various modifications and variations can be made based on the above teachings. For example, appropriate results can still be achieved even if the described techniques are performed in a different order than described, and / or components of the described systems, structures, devices, circuits, etc. are combined or combined in a different manner than described, or are replaced or substituted with other components or equivalents.

[0117] Therefore, other implementations, other embodiments, and equivalents to the claims also fall within the scope of the claims described below.

Claims

1. In a system for automatically generating optimal messages for each online customer in a multiple campaign environment, API service module that receives API (application programming interface) requests in real time; A profiling processing module that generates user-specific target scenario and content information in response to a request from the above API service module and provides the same to the above API service module; A content generation module that receives target scenario and content information for each user from the above API service module and generates scenario data to be actually exposed to each user; and An online customer-specific automatic optimal message generation system in a multiple campaign environment, comprising a sending processing module that transmits the generated scenario data to each individual and channel.

2. In paragraph 1, the profiling processing module, An online customer-specific automatic optimal message generation system in a multiple campaign environment, comprising a target extraction unit that extracts scenario targets by scenario target extraction logic from collected user-specific behavioral information and meta information.

3. In paragraph 1, the profiling processing module, An online customer-specific automatic optimal message generation system in a multiple campaign environment, comprising a scenario generation unit that verifies the past scenario exposure history of each user for each extracted scenario target and generates scenario data for each user based on the verified scenario exposure history.

4. In paragraph 1, the profiling processing module, An online customer-specific automatic optimal message generation system in a multiple campaign environment, comprising a priority setting unit that checks an action log for each user and sets a scenario priority based on a campaign or scenario exposure log confirmed from the action log.

5. In paragraph 1, the content creation module, An online customer-specific automatic optimal message generation system in a multi-campaign environment that applies tracking codes to scenario data for campaign performance measurement.

6. In paragraph 1, the system, An online customer-specific automatic optimal message generation system in a multiple campaign environment that collects behavior logs based on the results of sending and processing personalized messages delivered according to the above sending processing module.

7. In paragraph 6, the action log is: An automated optimal message generation system for each online customer in a multi-campaign environment, including exposure, click, and close information for each sent content.

8. In a system for automatically generating optimal messages for each offline customer in a multiple campaign environment, A batch processing module that performs batch jobs set according to time triggering; A profiling processing module that generates user-specific target scenario and content information in response to a request from the above batch processing module; A priority setting module that sorts multiple scenario data based on priority information based on the client's past campaign performance; A content generation module that receives target scenario and content information for each user and generates scenario data to be actually exposed to each user; and An offline customer-specific automatic optimal message generation system in a multiple campaign environment, comprising a sending processing module that transmits the generated scenario data to each individual and channel.

9. In paragraph 8, the profiling processing module, An offline customer-specific automatic optimal message generation system in a multiple campaign environment, comprising a target extraction unit that extracts scenario targets by scenario target extraction logic from collected user-specific behavioral information and meta information.

10. In paragraph 8, the profiling processing module, An offline customer-specific automatic optimal message generation system in a multiple campaign environment, comprising a scenario generation unit that verifies the past scenario exposure history of each user for each extracted scenario target and generates scenario data for each user based on the verified scenario exposure history.

11. In paragraph 8, the profiling processing module, An offline customer-specific automatic optimal message generation system in a multiple campaign environment, comprising a channel information verification unit that checks whether the user is online and which channels are reachable based on channel status information of the user.

12. In paragraph 8, the profiling processing module, An offline customer-specific automatic optimal message generation system in a multiple campaign environment, comprising a user response verification unit that verifies an action log for each user and verifies a channel-specific response for each user based on an action message log verified from the action log.

13. In paragraph 8, the content creation module, An offline customer-specific automatic optimal message generation system in a multi-campaign environment that applies tracking codes to scenario data for campaign performance measurement.

14. In paragraph 8, the system, An offline customer-specific automatic optimal message generation system in a multiple campaign environment that collects behavior logs based on the results of sending and processing personalized messages delivered according to the above sending processing module.

15. In paragraph 14, the action log is: An automatic optimal message generation system for each offline customer in a multi-campaign environment, including exposure, click, and close information for each sent content.

Images