System and method for automatically allocating customers on basis of target indicators for multiple campaigns

Abstract

The system for automatically allocating customers on the basis of target indicators for multiple campaigns, according to an embodiment of the present invention, includes: a memory for storing information on a plurality of campaigns and information on a plurality of customers; a communication unit for processing the transmission of at least one campaign among the plurality of campaigns to the plurality of customers; and a processor, wherein the processor may: identify target customers for each of the plurality of campaigns stored in the memory; check whether transmission overlap is allowed for each of the plurality of campaigns; calculate a score for each of the plurality of target customers if, as a result of the checking, at least one campaign is set to be not allowed for transmission overlap; allocate each target customer to a specific campaign among the plurality of campaigns on the basis of the calculated score; and process the transmission of the allocated specific campaign to each target customer through the communication unit.

Description

System and method for automatic target allocation based on target indicators for multiple campaigns

[0001] The present invention relates to a system and method for automatically assigning targets, and more particularly, to a technology for a system and method for automatically assigning targets based on target indicators for multiple campaigns.

[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] Additionally, there is a need for a distribution method that allows sending only specific campaigns when the recipient of the message does not allow duplicate sending to multiple campaigns.

[0007] The present invention aims to provide a system and method for automatic target allocation based on target indicators for multiple campaigns, which allows a marketer to automatically generate optimized messages with only a few simple settings.

[0008] In addition, the present invention aims to provide a system and method for automatic target allocation based on target indicators for multiple campaigns, which can send only specific campaigns according to preset rules when the target recipient of the message does not allow duplicate sending for multiple campaigns.

[0009] According to one embodiment of the present invention, a system for automatic target allocation based on target indicators for multiple campaigns includes: a memory for storing information on multiple campaigns and information on multiple customers; a communication unit for sending and processing at least one campaign among the multiple campaigns to the multiple customers; and a processor, wherein the processor identifies a customer target for each of the multiple campaigns stored in the memory, determines whether duplicate sending is allowed for each of the multiple campaigns, and, if at least one campaign is set as not to allow duplicate sending as a result of the checking of whether duplicate sending is allowed, calculates a score for each of the multiple customer targets, and, based on the calculated score, sets each customer target to a specific campaign among the multiple campaigns, and transmits and processes the set specific campaign to each of the customer targets through the communication unit.

[0010] The above score can be calculated based on visit rate, purchase conversion rate, and target indicators that can be calculated from data.

[0011] The processor can identify a transmission target channel for each of the plurality of customer targets and transmit the specific campaign through the identified transmission target channel.

[0012] The above processor can select at least one transmission target channel based on the performance superiority between channels for each customer target and the performance superiority for each campaign.

[0013] The processor may assign a minimum number of guaranteed recipients to each of the plurality of campaigns, and set a specific campaign for each customer target based on the assigned minimum number of guaranteed recipients.

[0014] The processor may set a maximum score for at least one new campaign among the plurality of campaigns, and set a specific campaign for each customer target based on the set maximum score.

[0015] The above processor can, if there are multiple new campaigns, process the multiple customer targets to be evenly distributed among the multiple new campaigns.

[0016] The above new campaign can respond to campaigns that have no sending history during the previously set period.

[0017] A method for automatically allocating target audiences based on target indicators for multiple campaigns according to one embodiment of the present invention may include: storing information about multiple campaigns and information about multiple customers; identifying a target audience for each of the multiple campaigns stored in the memory; identifying whether duplicate sending is allowed for each of the multiple campaigns; calculating a score for each of the multiple customer audiences when at least one campaign is set to not allow duplicate sending as a result of the identifying whether duplicate sending is allowed; setting each customer audience to a specific campaign among the multiple campaigns based on the calculated score; and transmitting the set specific campaign to each of the multiple customer audiences through a communication unit.

[0018] The above score can be calculated based on visit rate, purchase conversion rate, and target indicators that can be calculated from data.

[0019] The method may include the steps of: identifying a transmission target channel for each of the plurality of customer targets; and transmitting the specific campaign through the identified transmission target channel.

[0020] The above method can select at least one transmission target channel based on the performance superiority between channels for each customer target and the performance superiority for each campaign.

[0021] The method may include the steps of assigning a minimum number of guaranteed recipients to each of the plurality of campaigns; and setting a specific campaign for each customer target based on the assigned minimum number of guaranteed recipients.

[0022] The above method can set a maximum score for at least one new campaign among the plurality of campaigns, and set a specific campaign for each customer target based on the set maximum score.

[0023] The above method can be used to evenly distribute the plurality of customer targets to the plurality of new campaigns when there are multiple new campaigns.

[0024] 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.

[0025] The present invention offers the advantage of enabling marketers to automatically generate optimized messages with just a few simple settings. For example, with just a few simple settings, marketers can automatically generate and send content (e.g., images, text, etc.) based on estimated product interests for each member.

[0026] In addition, according to the present invention, there is an advantage in that only a specific campaign can be sent according to a preset rule when the recipient of the message does not allow duplicate sending of multiple campaigns.

[0027] 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.

[0028] Figure 2 is a block diagram showing a detailed configuration of a scenario processing module according to one embodiment of the present invention.

[0029] FIG. 3 is a block diagram showing a detailed configuration of a scenario selection module according to one embodiment of the present invention.

[0030] 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.

[0031] FIG. 5 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.

[0032] FIG. 6 is a diagram illustrating a concept of automatic target allocation based on target indicators for multiple campaigns according to one embodiment of the present invention.

[0033] FIG. 7 is a diagram illustrating a concept of automatic target allocation based on target indicators for multiple campaigns according to one embodiment of the present invention.

[0034] FIG. 8 is a flowchart illustrating a method for automatically assigning targets based on target indicators for multiple campaigns according to one embodiment of the present invention.

[0035]

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] 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.

[0042] 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.

[0043] 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.

[0044] 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.

[0045] 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.

[0046] 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).

[0047] 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.

[0048] 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.

[0049] 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).

[0050] Hereinafter, the scenario processing module (20) will be described in detail with reference to FIG. 2.

[0051] Figure 2 is a block diagram showing a detailed configuration of a scenario processing module according to one embodiment of the present invention.

[0052] 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).

[0053] 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.

[0054] 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).

[0055] 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.

[0056] 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).

[0057] 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).

[0058] Hereinafter, the scenario selection module (30) will be described in detail with reference to FIG. 3.

[0059] FIG. 3 is a block diagram showing a detailed configuration of a scenario selection module according to one embodiment of the present invention.

[0060] 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).

[0061] 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).

[0062] 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.

[0063] 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.

[0064] 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.

[0065] 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).

[0066] 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.

[0067] 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).

[0068] 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)

[0069] 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)

[0070] 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).

[0071] 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.

[0072] FIG. 5 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.

[0073] Referring to FIG. 5, 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).

[0074] According to one embodiment, the communication unit (110) may receive browser-based behavioral data and customer metadata input to the profiling processing module (10) 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).

[0075] According to one embodiment, the processor (150) may process functions performed in the profiling processing module (10) based on data collected through the communication unit (110). For example, the processor (150) may perform the functions of each module illustrated in FIG. 1.

[0076] 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).

[0077] 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.

[0078] Hereinafter, with reference to FIGS. 6 to 8, a system and method for automatic target allocation based on target indicators for multiple campaigns will be described.

[0079] FIG. 6 and FIG. 7 are diagrams illustrating a concept of automatic target allocation based on target indicators for multiple campaigns according to one embodiment of the present invention.

[0080] Referring to FIG. 6, at least some of the targets of Campaign A may overlap with at least some of the targets of Campaign B. For example, a target corresponding to area (a) of FIG. 6 may be a target of both Campaign A and Campaign B. In this case, the targets corresponding to area (a) may be sent messages to both Campaign A and Campaign B. In this case, the targets may be distinguished by user ID.

[0081] Meanwhile, if there is no campaign that allows duplicate sending among Campaign A or Campaign B, the preset campaign selection rules must be controlled so that only one campaign is sent per day.

[0082] Referring to FIG. 7, if there is no campaign that allows duplicate sending as described above, the target corresponding to (a) can be set as a target of campaign A or campaign B according to a preset rule.

[0083] Hereinafter, with reference to FIG. 8, a method for automatically assigning targets based on target indicators for the above multiple campaigns will be described in detail.

[0084] FIG. 8 is a flowchart illustrating a method for automatically assigning targets based on target indicators for multiple campaigns according to one embodiment of the present invention.

[0085] For convenience, the following description exemplifies two campaigns as examples of multiple campaigns. However, the same or similar methods can be applied to three or more campaigns. Furthermore, the methods described below can be performed by the customer-specific automatic optimal message generation system of FIG. 5, described above, in the multiple campaign environment. For example, each operation of the methods described below can be performed by the processor (150) of FIG. 5.

[0086] Referring to FIG. 8, the processor can first identify targets for multiple campaigns (S810). For example, targets for Campaign A and targets for Campaign B can be identified. Meanwhile, as illustrated in FIG. 6, a specific target may simultaneously correspond to targets for both Campaign A and Campaign B.

[0087] Next, the processor can check whether campaign transmission duplication is allowed. (S820) For example, if Campaign A and Campaign B are set to allow duplication, Campaign A may be sent to the target of Campaign A, and Campaign B may be sent to the target of Campaign B. Accordingly, a target who is simultaneously a target of Campaign A and a target of Campaign B may receive both Campaign A and Campaign B.

[0088] Meanwhile, if neither Campaign A nor Campaign B is set to allow duplicate sending, the campaigns should be distributed so that each target receives only one campaign. That is, since by default, each customer is set to receive only one Friend Talk message per day, customers in Area (A) who are targeted by multiple campaigns on a single day should be distributed so that they belong to only one campaign, as illustrated in Figure 7.

[0089] In one embodiment, the processor may calculate a campaign-specific score for each customer (S830). In one embodiment, the score may be calculated based on each user's visitation rate, purchase conversion rate, and target indicator settings that can be calculated from data. For example, the processor may calculate scores for Campaign A and Campaign B for each of the first and second users, as shown in Table 1 below.

[0090] Campaign ACampaign BUser 10.34567890.01234567User 20.00123450.01234567

[0091] For example, referring to the above , the first user and the second user may correspond to both Campaign A and Campaign B. In this case, the first user may be allocated to Campaign A because the score for Campaign A (0.3456789) is greater than the score for Campaign B (0.01234567). The second user may be allocated to Campaign B because the score for Campaign B (0.01234567) is greater than the score for Campaign A (0.0012345). According to one embodiment, the processor may perform a correction for the campaign selection for each case set after the campaign selection for each user. (S840) For example, if the targets of Campaign A and Campaign B are both the same (e.g., 100% overlap), the processor may correct so that not all targets are assigned to either campaign. In addition, if either Campaign A or Campaign B is a new campaign, the processor may process so that all overlapping targets are assigned to the new campaign. At this time, if the number of new campaigns is N, duplicate targets can be divided equally by 1 / N. The new campaign can be set as a campaign with no sending history in the previous 30 days, but is not limited to this.

[0092] In one embodiment, the processor may select a transmission target channel for each user (S850). For example, if multiple channels are configured for a specific user, the processor may select a specific channel based on established rules. Additionally, if a specific channel for a specific user is inactive, the processor may select an active channel to transmit the campaign.

[0093] According to one embodiment, the processor can deliver personalized messages for each customer and each channel according to the selected transmission target channel. (S860)

[0094] In one embodiment, if the audiences of two or more campaigns completely overlap, the audience of the low-performing campaign (i.e., the campaign with a relatively low score) may be set to 0. For example, if sufficient existing data exists, the ratio of audiences may vary depending on the performance (e.g., score) of the campaigns. In particular, if performance differs significantly, the audience of a specific low-performing campaign may be set to 0. In such a case, the low-performing campaign may become unable to update its performance, potentially leading to an irreversible situation. In one embodiment, in such a case, a minimum number of audiences can be guaranteed to ensure that all campaigns perform appropriate exploration within each execution period. The minimum guaranteed number of audiences can be assigned to a parameter that is statistically significant within the set time period. This minimum number of guaranteed audiences should be set to be lower than the parameter of the relatively superior-performing campaign.

[0095] Meanwhile, since new campaigns lack existing data (the cold start problem), there may be no basis for competition between campaigns. Therefore, to ensure competition converges within a short period of time, the new campaign can be assigned the highest score and the maximum number of parameters. If multiple new campaigns (e.g., n new campaigns) are created simultaneously, they can be assigned the same highest score and have targets assigned at a frequency of 1 / n.

[0096] In one embodiment, the processor can adjust the target audience through competition between contact channels. For example, if a customer has multiple direct contact channels, such as email, text message, and app push notifications, sending a single piece of content to all channels is likely to cause inconvenience to the customer. Conversely, omni-marketing across multiple channels may be more effective. Therefore, since these preferences may vary across customers, the processor calculates boundaries for channel preferences and communication frequency for each customer and selects at least one (e.g., 1 to n) target channel based on the customer's performance advantage across channels and the performance advantage of each campaign.

[0097] 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.

[0098] 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.

[0099] 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.

[0100] 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.

[0101] Therefore, other implementations, other embodiments, and equivalents to the claims also fall within the scope of the claims described below.

Claims

1. In the automatic target allocation system based on target indicators for multiple campaigns, A memory that stores information about multiple campaigns and information about multiple customers; A communication unit that processes and sends at least one campaign among the plurality of campaigns to the plurality of customers; and Contains a processor, The above processor, Check the customer target for each of the multiple campaigns stored in the above memory, Check whether duplicate sending is allowed for each of the above multiple campaigns. As a result of the above duplicate allowance check, if at least one campaign is set to not allow duplicate sending, calculate a score for each of the multiple customer targets, Based on the calculated score above, each customer target is set to a specific campaign among the multiple campaigns above, A target index-based automatic target allocation system for multiple campaigns, which transmits and processes the above-mentioned specific campaign set for each of the above-mentioned customer targets through the above-mentioned communication unit.

2. In paragraph 1, the score is, An automatic target allocation system based on target metrics for multiple campaigns, calculated based on visit rate, conversion rate, and other data-based target metrics.

3. In paragraph 1, the processor, Check the transmission target channel for each of the above multiple customer targets, An automatic target allocation system based on target indicators for multiple campaigns, which processes and transmits the specific campaign through the above-mentioned confirmed transmission target channel.

4. In the third paragraph, the processor, An automatic target allocation system based on target metrics for multiple campaigns, which selects at least one delivery target channel based on the performance superiority between channels for each customer target and the performance superiority for each campaign.

5. In the first paragraph, the processor, Allocate a minimum number of guaranteed beneficiaries for each of the above multiple campaigns, An automatic target allocation system based on target indicators for multiple campaigns, which sets a specific campaign for each customer target based on the minimum number of guaranteed targets allocated above.

6. In paragraph 1, the processor, Set a maximum score for at least one new campaign among the above multiple campaigns, A target metric-based automatic target allocation system for multiple campaigns, which sets a specific campaign for each customer target based on the maximum score set above.

7. In the 6th paragraph, the processor, A target index-based automatic target allocation system for multiple campaigns, which evenly distributes multiple customer targets to the multiple new campaigns when there are multiple new campaigns.

8. In paragraph 7, the new campaign, An automatic target allocation system based on target metrics for multiple campaigns, responding to campaigns that have not been sent during a previously set period.

9. In the automatic target allocation method based on target indicators for multiple campaigns, A step of storing information about multiple campaigns and information about multiple customers; A step of confirming customer targets for each of the multiple campaigns stored in the above memory; A step for checking whether duplicate sending is allowed for each of the above multiple campaigns; A step of calculating a score for each of the plurality of customer targets, if at least one campaign is set to not allow duplicate sending as a result of the above duplicate allowance check; A step of setting each customer target to a specific campaign among the plurality of campaigns based on the calculated score; and A method for automatic target allocation based on target indicators for multiple campaigns, comprising the step of transmitting the above-mentioned specific campaign set for each of the above-mentioned customer targets through a communication unit.

10. In paragraph 9, the score is, A method for automatic target allocation based on target metrics for multiple campaigns, calculated based on visit rate, conversion rate, and other target metrics that can be calculated from data.

11. In paragraph 9, the method, A step of confirming a transmission target channel for each of the above multiple customer targets; and A method for automatic target allocation based on target indicators for multiple campaigns, comprising the step of transmitting the specific campaign through the above-mentioned confirmed transmission target channel.

12. In the 11th paragraph, the method, A method for automatic target allocation based on target indicators for multiple campaigns, which selects at least one delivery target channel based on the performance superiority between channels for each customer target and the performance superiority for each campaign.

13. In paragraph 9, the method, A step of allocating a minimum number of guaranteed recipients for each of the above multiple campaigns; and A method for automatic target allocation based on target indicators for multiple campaigns, comprising the step of setting a specific campaign for each customer target based on the minimum number of guaranteed targets allocated above.

14. In paragraph 9, the method, Set a maximum score for at least one new campaign among the above multiple campaigns, A method for automatic target allocation based on target indicators for multiple campaigns, which sets a specific campaign for each customer target based on the maximum score set above.

15. In paragraph 14, the method, A method for automatically allocating targets based on target indicators for multiple campaigns, which processes multiple customer targets to be evenly distributed among the multiple new campaigns when there are multiple new campaigns.

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