A method for dynamically adjusting advertising delivery strategies based on digital twins

Abstract

This invention discloses a method for dynamically adjusting advertising delivery strategies based on digital twins, relating to the field of advertising delivery technology. The method includes: constructing a three-layer digital twin framework consisting of a touchpoint layer, a path layer, and an experience stage layer; configuring various advertising experience scripts within this framework to generate an advertising experience twin graph; segmenting advertising experience fragments from actual delivery records and marking touchpoints, paths, and experience stages on the advertising experience twin graph to form an experience fragment library; selecting experience fragments from the library that match the target advertising experience script; and rehearsing these fragments in the digital twin environment by replacing materials and placement to generate a strategy-experience response sketch. This invention, by constructing an experience fragment library and selecting advertising experience fragments that match the target advertising experience script, and rehearsing them in the digital twin environment by replacing materials and placement, achieves visualized diagnosis of different touchpoint combinations and material sequences from an experience stage perspective.

Description

Technical Field

[0001] This invention relates to the field of advertising technology, and in particular to a method for dynamically adjusting advertising strategies based on digital twins. Background Technology

[0002] Against the backdrop of the rapid development of multi-touchpoint integrated marketing, programmatic advertising, real-time bidding, and cross-media attribution analytics technologies have matured. Advertisers can aggregate impression, click, and conversion logs based on user identifiers to statistically model typical user journeys and optimize bidding strategies and creative combinations through audience segmentation, A / B testing, and rule engines. With the expanding application of digital twin technology in retail stores, smart parks, and virtual exhibitions, the industry is also beginning to explore the construction of visualized user touchpoint paths, providing a three-dimensional representation of ad touchpoint distribution, browsing paths, and experience stages to assist in developing advertising strategies.

[0003] However, existing technologies mostly remain at the offline analysis level, guided by single indicators such as overall conversion rate and click-through rate. They are unable to segment historical advertising events across multiple media and paths into reusable advertising experience segments within a unified digital twin space, and to map them one-to-one with specific experience stages, path connections, and touchpoint combinations. Existing methods often lack a closed-loop mechanism that automatically generates structured adjustment guidelines from digital twin rehearsal results and rewrites the experience script with verified touchpoint combinations and material order after actual deployment. As a result, when fine-tuning strategies, they still rely on experience-based adjustments, resulting in long feedback cycles, low reusability, and difficulty in supporting dynamic optimization needs under multiple business objectives. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides a method for dynamically adjusting advertising delivery strategies based on digital twins to solve the problem of lacking dynamic adjustment of digital twin closed-loop strategies that are user experience-oriented in multi-touchpoint advertising delivery.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] This invention provides a method for dynamically adjusting advertising delivery strategies based on digital twins, which includes constructing a three-layer digital twin skeleton consisting of a touchpoint layer, a path layer, and an experience stage layer, configuring multiple advertising experience scripts in the three-layer digital twin skeleton, and generating an advertising experience twin graph.

[0008] According to the preset cycle, the advertising experience segments are divided from the actual delivery records, and the touchpoints, paths and experience stages are marked on the advertising experience twin map to form an experience segment library;

[0009] Select experience segments from the experience segment library that match the target ad experience script, replace the materials and placement in the digital twin environment to rehearse, and generate a strategy-experience response sketch;

[0010] Based on the smooth phases and interruption points marked in the strategy-experience response sketch, a structured adjustment guide is generated and the validated touchpoint combinations and creative sequences are written back into the advertising experience twin map.

[0011] As a preferred embodiment of the dynamic adjustment method for advertising delivery strategies based on digital twins described in this invention, the specific steps for generating the advertising experience twin map are as follows:

[0012] Collect media resource information and typical user journey information to establish touchpoint layer, path layer and experience stage layer;

[0013] The nodes and connections of the touchpoint layer, path layer, and experience stage layer are associated and stored as a three-layer digital twin skeleton;

[0014] Multiple advertising experience scripts are configured in a three-layer digital twin skeleton, specifying the experience stages, path connections, touchpoint nodes, corresponding material types and interaction forms involved. Target material types and target placement order are set for each advertising experience script to generate an advertising experience twin graph.

[0015] As a preferred embodiment of the dynamic adjustment method for advertising delivery strategy based on digital twins described in this invention, the specific steps of dividing the advertising experience segments from the actual delivery records according to a preset period are as follows:

[0016] Pre-set the cycle in the advertising twin platform and link it to the business calendar;

[0017] Retrieve exposure records, click records, and conversion records within each preset period, and generate a behavior sequence according to user identification and occurrence time;

[0018] In each behavior sequence, continuous records are combined into a coherent browsing and interaction process based on touchpoint nodes, behavior types, and time intervals, and the corresponding original material identifiers and original placement identifiers are recorded to generate advertising experience segments.

[0019] As a preferred embodiment of the dynamic adjustment method for advertising delivery strategies based on digital twins described in this invention, the specific steps for marking touchpoints, paths, and experience stages on the advertising experience twin graph to form an experience segment library are as follows.

[0020] Import the ad experience clips into the ad twin platform, and mark the start touch point node and end touch point node in the touch point layer of the ad experience twin graph;

[0021] The path of the ad experience segment is determined at the path layer and a path identifier is attached. The experience stage of the ad experience segment is determined at the experience stage layer and an experience stage label is attached.

[0022] Advertising experience segments with touchpoint node identifiers, path identifiers, and experience stage tags are stored hierarchically according to preset cycles and experience stages, and an index relationship is established to form an experience segment library.

[0023] As a preferred embodiment of the dynamic adjustment method for advertising delivery strategy based on digital twins described in this invention, the target advertising experience script includes a set of target experience stages, a set of target paths, and a set of target touchpoints.

[0024] As a preferred embodiment of the dynamic adjustment method for advertising delivery strategies based on digital twins described in this invention, the specific steps for selecting experience segments that match the target advertising experience script from the experience segment library are as follows:

[0025] In the advertising twin platform, receive the target advertising experience script identifier and read the bound target experience stage set, target path set, and target touchpoint set;

[0026] In the experience segment library, candidate ad experience segments are selected whose experience stage belongs to the target experience stage set, whose path belongs to the target path set, and whose touchpoints belong to the target touchpoint set. The path coverage, touchpoint overlap, and experience stage consistency are statistically analyzed and ranked to form an ad experience segment set.

[0027] As a preferred embodiment of the dynamic adjustment method for advertising delivery strategies based on digital twins described in this invention, the specific steps for rehearsing the replacement of materials and placements in the digital twin environment to generate a strategy-experience response sketch are as follows:

[0028] In the digital twin environment of the advertising twin platform, the original material identifiers and original placement identifiers in the set of advertising experience segments are replaced with material identifiers and placement identifiers corresponding to the target material type and target placement order to form advertising experience segments for rehearsal.

[0029] Play the advertising experience segments in the rehearsal according to their time and path order, record the changes in dwell time, path length, and path interruption location at each stage, and organize them with the corresponding touchpoints and material order to generate a strategy experience response sketch.

[0030] As a preferred embodiment of the dynamic adjustment method for advertising delivery strategies based on digital twins described in this invention, the step of generating structured adjustment guidelines based on the smooth phases and easily interrupted positions marked in the strategy-experience response sketch includes the following specific steps.

[0031] Read the smooth phase markers and interruptible location markers from the strategy experience response sketch, and associate them with the corresponding touchpoint combinations and material order;

[0032] Based on the smooth phase markers, select the corresponding touchpoint combinations and material order to form a recommended combination list, and specify the touchpoint priority, material type matching relationship and interaction form configuration for each touchpoint combination;

[0033] Select the corresponding touchpoint combinations and material order based on the easily interrupted location markers to form a list of combinations to be optimized, and specify the adjustment methods for each touchpoint combination, such as reducing duplicate exposure, increasing explanatory materials, and delaying the presentation of promotional materials;

[0034] The recommended combination list and the combination list to be optimized are merged to generate a structured adjustment guide.

[0035] As a preferred embodiment of the dynamic adjustment method for advertising delivery strategies based on digital twins described in this invention, the specific steps for writing back the verified effective touchpoint combinations and creative sequences to the advertising experience twin graph are as follows:

[0036] Submit the structured adjustment guidelines to the advertising platform, execute advertising according to the structured adjustment guidelines within the preset observation period, and record the number of impressions, clicks and conversions corresponding to each touchpoint combination and material order, and compare them with the number of impressions, clicks and conversions before the adjustment under the same experience stage;

[0037] When the number of clicks and conversions are both higher than before the adjustment and the number of impressions is not lower than before the adjustment, the corresponding touchpoint combination and creative order will be written into the ad experience script in the ad experience twin graph and the original touchpoint combination and creative order will be replaced.

[0038] As a preferred embodiment of the dynamic adjustment method for advertising delivery strategy based on digital twins described in this invention, the preset period is a time interval pre-configured in the advertising twin platform according to the business calendar.

[0039] The beneficial effects of this invention are as follows: By constructing an experience segment library according to a preset cycle and selecting advertising experience segments that match the target advertising experience script, the materials and placements are replaced and rehearsed in a digital twin environment to form a strategy-experience response sketch that includes changes in dwell time, path length, and path interruption location. This enables a visual diagnosis of different touchpoint combinations and material sequences from the perspective of the experience stage. Structured adjustment guidelines are automatically generated based on the smooth stage and easily interrupted locations, and real-world performance is collected within a preset observation period. Verified effective touchpoint combinations and material sequences are written back to the advertising experience twin map, allowing the advertising experience script to continuously iterate under the dual constraints of digital twin simulation and actual delivery feedback. This improves the targeting and convergence speed of strategy optimization, reduces trial-and-error costs, and significantly improves the conversion efficiency and user experience continuity of advertising. Attached Figure Description

[0040] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is a flowchart illustrating a method for dynamically adjusting advertising strategies based on digital twins.

[0042] Figure 2 A flowchart for dividing the advertising experience into segments.

[0043] Figure 3 A flowchart for selecting a matching experience segment.

[0044] Figure 4 A flowchart for generating structured adjustment guidelines. Detailed Implementation

[0045] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0046] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0047] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0048] Reference Figures 1-4 As one embodiment of the present invention, this embodiment provides a method for dynamically adjusting advertising delivery strategies based on digital twins, including the following steps:

[0049] S1. Construct a three-layer digital twin skeleton consisting of a touchpoint layer, a path layer, and an experience stage layer, and configure various advertising experience scripts in the three-layer digital twin skeleton to generate an advertising experience twin map.

[0050] S1.1. Read the existing media resource information and typical user journey information of the business in the advertising twin platform, and organize the information such as online ad placement identifiers, offline screen identifiers, display locations, screen sizes, supported material formats, and delivery time periods into a media resource list; organize the information such as the touchpoint sequence, dwell time, and common behavior types that typical users go through from their first contact with the advertisement to completing the target behavior into a typical user journey list.

[0051] It should be noted that typical users refer to a representative group of users who have completed the process from first contact with the advertisement to the target behavior in the historical advertising records, and whose behavior path is stable and whose sample size meets the preset statistical requirements. This is obtained by screening and classifying the historical advertising records.

[0052] The media resource list is traversed, and an advertising touchpoint node is created for each media resource record. The advertising touchpoint node includes attributes such as media resource identifier, media type, display scenario, spatial location, and available material specifications. All advertising touchpoint nodes are mapped to the digital twin space according to a unified coordinate system to form a touchpoint layer digital twin representation describing the distribution of various online advertising positions and offline screens. A one-to-one correspondence is established between the touchpoint layer digital twin representation and the media resource list in the advertising twin platform.

[0053] Traverse the typical user journey list, and based on the touchpoint access order and behavior type in each typical user journey record, establish browsing path connections between advertising touchpoint nodes in the touchpoint layer digital twin representation. Each browsing path connection includes attributes such as starting touchpoint node, target touchpoint node, browsing behavior type, and dwell time statistical interval. Combine all browsing path connections to form a path layer digital twin representation, and establish a reference relationship between the path layer digital twin representation and the typical user journey list in the advertising twin platform.

[0054] S1.2. Based on the path layer digital twin representation, the experience stages of each complete touchpoint sequence are divided. The user journey is divided into the reminder stage, the careful comparison stage, the hesitation and observation stage, and the decision-making stage according to the attention state and decision-making depth. The reminder stage is assigned the "awakening" advertising role label, the careful comparison stage is assigned the "persuasion" advertising role label, the hesitation and observation stage is assigned the "reassurance" advertising role label, and the decision-making stage is assigned the "facilitating decision" advertising role label.

[0055] By binding the experience stage labels with the corresponding path segments in the path layer digital twin representation, an experience stage layer digital twin representation is formed, so that the touch point layer digital twin representation, the path layer digital twin representation, and the experience stage layer digital twin representation cover the same batch of typical user journeys in the digital twin space.

[0056] In the advertising twin platform, a unique touchpoint node identifier is assigned to each advertising touchpoint node in the digital twin representation of the touchpoint layer, a unique path connection identifier is assigned to each browsing path connection in the digital twin representation of the path layer, and the starting touchpoint node identifier and the target touchpoint node identifier are recorded. A unique experience stage identifier is assigned to each experience stage segment in the digital twin representation of the experience stage layer, and the corresponding path connection identifier and the coverage time interval are recorded.

[0057] The touchpoint node identifier, path connection identifier, and experience stage identifier are associated according to one-to-many and many-to-many relationships. In the advertising twin platform, the digital twin representations of the touchpoint layer, path layer, and experience stage layer are uniformly stored in the form of digital twin structured data, forming a three-layer digital twin skeleton consisting of the touchpoint layer, path layer, and experience stage layer.

[0058] S1.3. In the advertising twin platform, establish a business objective list based on business objectives. The business objective list includes types such as new user acquisition objectives, user activation objectives, user retention objectives, and repeat purchase objectives. For each business objective, select the experience stage identifier set, path connection identifier set, and touchpoint node identifier set that match the business objective from the three-layer digital twin skeleton. Use the experience stage identifier set as the target experience stage set, the path connection identifier set as the target path set, and the touchpoint node identifier set as the target touchpoint set.

[0059] When configuring ad experience scripts, each ad experience script is assigned an ad role for different experience stages in the target experience stage set, the order in which ad content is prioritized is specified for each path connection in the target path set, and the expected material type and interaction form are specified for each touchpoint node in the target touchpoint set. Based on the material type and display requirements, the target material type and target placement order are set for each ad experience script. The ad experience scripts are associated with the target experience stage set, target path set, and target touchpoint set in the three-layer digital twin skeleton. All ad experience script configuration results are saved in the ad twin platform in the form of a digital twin scene description, forming an ad experience script set that covers multiple business objectives.

[0060] The three-layer digital twin framework is integrated with the set of advertising experience scripts. The touchpoint nodes involved in each advertising experience script are marked in the touchpoint layer digital twin representation, the path connections involved in each advertising experience script are marked in the path layer digital twin representation, and the experience stages involved in each advertising experience script are marked in the experience stage layer digital twin representation. The target material type and target placement order of each advertising experience script are recorded on the three-layer digital twin framework. All nodes and connections in the three-layer digital twin framework are combined with the configuration relationships of the advertising experience scripts to form an advertising experience twin map.

[0061] S2. According to the preset cycle, divide the advertising experience segments from the actual delivery records and mark the touchpoints, paths and experience stages on the advertising experience twin map to form an experience segment library.

[0062] S2.1. In the advertising twin platform, configure start and end times for short, medium, and long cycles according to the business calendar. Divide each time interval into a preset cycle and establish a digital twin timeline covering all preset cycles. For any preset cycle, number it... The preset period corresponds to the following time length:

[0063] ;

[0064] in, Indicates the preset period number The corresponding time length, Indicates the preset period number The calendar start time, Indicates the preset period number The end time of the calendar.

[0065] It should be noted that in this embodiment, the short cycle is set to 1 day, the medium cycle to 7 days, and the long cycle to 30 days. The start and end times are divided according to the consecutive natural days in the business calendar and are uniformly configured in the advertising twin platform according to settlement and operation habits.

[0066] In the advertising twin platform, for each preset period, exposure records, click records, and conversion records within the corresponding time interval are retrieved from the actual delivery platform. Each actual delivery record is standardized into a delivery event that includes user identifier, occurrence timestamp, touchpoint identifier, behavior type, creative identifier, and placement identifier. Delivery events belonging to the same preset period and with the same user identifier are sorted from earliest to latest according to their occurrence timestamp, forming a set of user behavior sequences within the preset period.

[0067] For any user identifier as The user's behavior sequence obtained by sorting by time within a certain preset period. The time of occurrence of the delivery event is recorded as follows: The time interval between adjacent delivery events is:

[0068] ;

[0069] in, Indicates user identifier as In the user's behavior sequence, the first The event and the first The time interval between delivery events Indicates user identifier as In the user's behavior sequence, the first The timestamp of the delivery event Indicates user identifier as In the user's behavior sequence, the first The timestamps of each event and the time intervals are used to determine whether multiple events belong to the same continuous browsing and interaction process.

[0070] S2.2. In each user behavior sequence, traverse the delivery events in chronological order. When the touchpoints of adjacent delivery events are located between ad touchpoint nodes in the ad experience twin graph that have a direct path connection and the time interval is... When the events are within a preset time interval, consecutive events will be grouped into the same continuous browsing and interaction process.

[0071] It should be noted that the preset time interval range is used to determine whether the touch point dwell time range belongs to the same continuous browsing and interaction process. It is generally selected based on the distribution statistics of the access time difference between adjacent touch points in the historical delivery records. For example, the range of 0 minutes to 30 minutes is used as the preset time interval range.

[0072] When touchpoint identifiers no longer constitute continuous path connections or time intervals in the advertising experience twin graph When the preset time interval is exceeded, the current continuous browsing and interaction process ends and a new continuous browsing and interaction process begins.

[0073] For each continuous browsing and interaction process, the touchpoint identifiers, behavior types, creative identifiers, and placement identifiers of the starting and ending events are recorded in chronological order. Each continuous browsing and interaction process is defined as an advertising experience segment. The total dwell time for the ad experience segments of the campaign was:

[0074] ;

[0075] in, This indicates the total dwell time of an advertising experience segment on the digital twin timeline. Indicates the number of events displayed within the ad experience segment. Indicates user identifier as In the user's behavioral sequence, the first segment of the advertising experience The timestamp of the event.

[0076] For each ad experience segment, the original material identifier and the original placement identifier are recorded synchronously in chronological order to form a collection of ad experience segments with material information and placement information.

[0077] S2.3. Import the set of advertising experience segments into the advertising experience twin graph one by one in the advertising twin platform. In the digital twin representation of the touchpoint layer, find the corresponding advertising touchpoint node and read the touchpoint node identifier based on the touchpoint identifier recorded in the start and end events of the advertising experience segment. Write the start touchpoint node identifier and the end touchpoint node identifier on the advertising experience segment.

[0078] In the path-layer digital twin representation, the path connections that the advertising experience segment traverses in the advertising experience twin graph are determined based on the starting touch node identifier, the ending touch node identifier, and the touch access order within the advertising experience segment. The path identifier of each path connection in the path connection sequence is added to the advertising experience segment, and a correspondence is established between the path direction of the advertising experience segment in the digital twin space and the path-layer digital twin representation.

[0079] In the digital twin representation of the experience stage layer, based on the time range and path connection of the advertising experience segment, the advertising experience segment is matched with the experience stage identifier of the segment covering the same time range and overlapping path segments, and an experience stage label is attached to the advertising experience segment, so that the advertising experience segment has labeling information of touch point dimension, path dimension and experience stage dimension in the digital twin space.

[0080] In the advertising twin platform, advertising experience segments that have completed touchpoint labeling, path labeling, and experience stage labeling are grouped according to preset cycle numbers. Advertising experience segments in the same preset cycle are grouped into the same time level. Within each time level, experience stage sub-levels are further divided according to experience stage tags. Within each experience stage sub-level, an index table is established based on touchpoint node identifiers and path identifiers. The unique identifier of the advertising experience segment is associated with the touchpoint node identifier, path identifier, and experience stage tag and stored, forming an experience segment library that is hierarchically managed according to preset cycles and experience stages.

[0081] S3. Select experience segments from the experience segment library that match the target advertising experience script, replace the materials and placements in the digital twin environment to rehearse, and generate a strategy-experience response sketch.

[0082] S3.1. After receiving the target advertising experience script identifier in the advertising twin platform, read the target experience stage set, target path set, and target touchpoint set bound to the target advertising experience script in the advertising experience twin graph, and use the target experience stage set, target path set, and target touchpoint set as digital twin constraints for selecting advertising experience segments from the experience segment library.

[0083] Read each ad experience segment from the experience segment library, obtain the corresponding experience stage set, path set, and touchpoint set, and calculate the ad experience segment's matching score using the following expression:

[0084] ;

[0085] in, This represents the overall relevance score of the ad experience segment across three dimensions: experience stage, path, and touchpoints. This represents the number of experience stages contained in the intersection of the set of experience stages for advertising experience segments and the set of target experience stages. This indicates the number of experience stages contained in the target experience stage set. This represents the number of paths contained in the intersection of the set of ad experience segment paths and the set of target paths. This indicates the number of paths contained in the target path set. This represents the number of touchpoints contained in the intersection of the set of ad experience touchpoints and the set of target touchpoints. Indicates the number of contacts contained in the target contact set;

[0086] When the matching score is greater than zero and all three intersections are not empty, a set of candidate ad experience segments is generated, and the segments are sorted from high to low according to the matching score. Several ad experience segments with the highest scores (e.g., 100) are selected to form the ad experience segment set.

[0087] S3.2. In the digital twin environment of the advertising twin platform, for each advertising experience segment in the set of advertising experience segments, read the original material identifier and original placement identifier recorded in the advertising experience segment, and search for the target material type and target placement order pre-configured in the advertising experience twin graph. Select the material identifier that matches the material type from the material resource library according to the target material type, determine the placement identifier in the digital twin representation of the touchpoint layer according to the target placement order, replace the original material identifier with the selected material identifier, replace the original placement identifier with the determined placement identifier, generate a set of advertising experience segments for rehearsal, and keep the touchpoint access order and experience stage label of the advertising experience segments unchanged in the digital twin space.

[0088] In the three-dimensional digital twin scene corresponding to the digital twin environment, the rehearsal advertising experience segments are played one by one according to the time order and path order in the set of rehearsal advertising experience segments. At each experience stage, the dwell time, path length and first path interruption position of the original advertising experience segment on the digital twin time axis are recorded. At the same time, the dwell time, path length and first path interruption position of the rehearsal advertising experience segment in the same experience stage are also recorded.

[0089] Based on the difference between the rehearsal dwell time and the original dwell time, the change in dwell time is obtained. Based on the difference in path length before and after rehearsal and the order of the first path interruption position, it is determined whether the path is shortened or lengthened and whether the interruption position is moved forward or backward. The change in dwell time, the change in path length, and the change in path interruption position are archived together with the corresponding touchpoint combination and material order to form an intermediate statistical result set.

[0090] S3.3. Based on the intermediate statistical results set in the advertising twin platform, each experience stage and touchpoint combination is classified and processed. When the change in dwell time is greater than or equal to zero, the path length does not increase, and the first path interruption position does not advance, the corresponding experience stage is marked as a smooth stage in the strategy-experience response sketch, and the touchpoint combination and material order under the smooth stage are recorded. When the change in dwell time is negative, or the path length increases, or the first path interruption position advances, the corresponding experience stage is marked as an easily interrupted position in the strategy-experience response sketch, and the touchpoint combination and material order under the easily interrupted position are recorded. Finally, the strategy-experience response sketch is saved in the digital twin space in a structured marking manner.

[0091] S4. Based on the smooth phases and interruption points marked in the strategy-experience response sketch, generate structured adjustment guidelines and write back the verified touchpoint combinations and creative sequences to the advertising experience twin map.

[0092] S4.1. Read the strategy-experience response sketches stored in the digital twin space in the advertising twin platform, analyze the smooth stage markers and easily interrupted position markers for each experience stage marker, and establish a correlation between each marker item and the corresponding touchpoint combination, material order, and changes in dwell time, path length, and path interruption position recorded in the strategy-experience response sketch to form a detailed set of markers oriented towards the experience stage dimension.

[0093] Based on the detailed set of tags, for each touchpoint combination and material sequence corresponding to the smooth phase tags, a recommended combination list is generated according to the conditions that the change in dwell time is not less than zero, the path length does not increase, and the path interruption position is not advanced. Touchpoint priorities are assigned to each touchpoint combination, and the touchpoint priorities are arranged according to the order of appearance of touchpoints in the digital twin path and the change in dwell time within the smooth phase.

[0094] Based on the target creative types recorded in the advertising experience twin map, the creative type matching relationship is configured for touchpoint combinations. Based on the interaction performance recorded in the strategy-experience response sketch, the interaction form configuration method is configured for touchpoint combinations. Touchpoint priority, creative type matching relationship and interaction form configuration method are used as structured fields for the recommended combination list.

[0095] S4.2. Based on the detailed set of markers, for each touchpoint combination and material sequence corresponding to the easily interrupted location markers, when the change in dwell time is less than zero, the path length increases, or the path interruption position is advanced, a list of combinations to be optimized is generated. Adjustments to reduce repeated exposure are specified for each touchpoint combination, reducing information fatigue by decreasing the number of times the same touchpoint is exposed in a short period of time. Adjustments to add explanatory materials are specified for touchpoint combinations, improving understanding by prioritizing explanatory content at key touchpoints. Adjustments to delay the presentation of promotional materials are specified for touchpoint combinations, reducing early interruptions by placing promotional materials in the later decision-making stage of the experience phase. Finally, a list of combinations to be optimized containing adjustment directions is formed.

[0096] The recommended combination list and the combination list to be optimized are merged according to the experience stage identifier, path connection identifier, and touch point node identifier. The smooth touch point combination and the touch point combination to be optimized under each experience stage, together with the corresponding material type matching relationship, interaction form configuration method, and exposure control and rhythm adjustment method, are organized into a structured adjustment guide.

[0097] S4.3. Submit the structured adjustment guidelines to the advertising platform. Within the preset observation period, configure the touchpoint combinations and creative order according to the structured adjustment guidelines. After the preset observation period is completed, collect the number of impressions, clicks and conversions for each touchpoint combination and creative order in each experience stage from the advertising platform, and compare them one by one with the number of impressions, clicks and conversions recorded in the experience segment library before the adjustment under the same experience stage, the same touchpoint combination and creative order.

[0098] It should be noted that the preset observation period is selected from short, medium and long periods as the observation window by referring to the settlement and operation rhythm of the business calendar in the advertising twin platform. That is, the preset observation period is set to 7 consecutive days. 7 days can cover a complete round of campaign rhythm, ensure the stability of click and conversion statistics, and provide timely feedback on the effects of touchpoint combination and material order adjustment in the digital twin environment.

[0099] In the advertising twin platform, for each touchpoint combination and material order, if the number of clicks recorded within the preset observation period is greater than the number of clicks before adjustment, the number of conversions recorded within the preset observation period is greater than the number of conversions before adjustment, and the number of exposures recorded within the preset observation period is not less than the number of exposures before adjustment, the corresponding touchpoint combination and material order will be determined as a set of valid touchpoint combinations and material orders.

[0100] For verified effective touchpoint combinations and material sequences, locate the corresponding advertising experience script, as well as the corresponding experience stage identifiers, path connection identifiers, and touchpoint node identifiers in the advertising experience twin graph. Replace the original touchpoint combinations and material sequences with the verified effective touchpoint combinations and material sequences, and update the structured record of the advertising experience twin graph in the digital twin space.

[0101] This embodiment also provides a computer device applicable to the dynamic adjustment method of advertising delivery strategy based on digital twin, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the dynamic adjustment method of advertising delivery strategy based on digital twin as proposed in the above embodiment.

[0102] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0103] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements the method for dynamically adjusting advertising delivery strategies based on digital twins as proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0104] In summary, this invention constructs an experience segment library according to a preset cycle, selects advertising experience segments that match the target advertising experience script, and rehearses them in a digital twin environment by replacing materials and placements. This generates a strategy-experience response sketch that includes changes in dwell time, path length, and path interruption locations, enabling visualized diagnosis of different touchpoint combinations and material sequences from the perspective of the experience stage. Structured adjustment guidelines are automatically generated based on smooth stages and easily interrupted locations, and real-world performance is collected within a preset observation period. Verified effective touchpoint combinations and material sequences are written back to the advertising experience twin map, allowing the advertising experience script to continuously iterate under the dual constraints of digital twin simulation and actual delivery feedback. This improves the targeting and convergence speed of strategy optimization, reduces trial-and-error costs, and significantly improves the conversion efficiency and user experience continuity of advertising.

[0105] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for dynamically adjusting an advertising strategy based on digital twinning, characterized in that: include, A three-layer digital twin framework consisting of a touchpoint layer, a path layer, and an experience stage layer is constructed. Multiple advertising experience scripts are configured within this framework to generate an advertising experience twin graph. The specific steps are as follows. Collect media resource information and typical user journey information to establish touchpoint layer, path layer and experience stage layer; The nodes and connections of the touchpoint layer, path layer, and experience stage layer are associated and stored as a three-layer digital twin skeleton; Multiple advertising experience scripts are configured within a three-layer digital twin framework, specifying the experience stages, path connections, touchpoint nodes, corresponding creative types, and interaction formats involved. Target creative types and target placement order are set for each advertising experience script, generating an advertising experience twin graph. According to the preset cycle, the advertising experience segments are divided from the actual delivery records, and the touchpoints, paths and experience stages are marked on the advertising experience twin map to form an experience segment library; Select experience clips from the experience clip library that match the target ad experience script, replace the materials and placement in the digital twin environment to rehearse, and generate a strategy-experience response sketch. The specific steps are as follows. In the digital twin environment of the advertising twin platform, the original material identifiers and original placement identifiers in the set of advertising experience segments are replaced with material identifiers and placement identifiers corresponding to the target material type and target placement order to form advertising experience segments for rehearsal. Play the advertising experience segments in the rehearsal according to the time sequence and path sequence, record the changes in dwell time, path length and path interruption position at each experience stage, and organize them with the corresponding touchpoints and material order to generate a strategy experience response sketch. Based on the smooth phases and interruption-prone locations marked in the strategy-experience response sketch, a structured adjustment guide is generated, and the validated touchpoint combinations and creative sequences are written back into the ad experience twin map. The specific steps are as follows. Read the smooth phase markers and interruptible location markers from the strategy experience response sketch, and associate them with the corresponding touchpoint combinations and material order; Based on the smoothness stage markers, select the corresponding touchpoint combinations and material order to form a recommended combination list, and specify the touchpoint priority, material type matching relationship and interaction form configuration for each touchpoint combination; Select the corresponding touchpoint combinations and material order based on the easily interrupted location markers to form a list of combinations to be optimized, and specify the adjustment methods for each touchpoint combination, such as reducing duplicate exposure, increasing explanatory materials, and delaying the presentation of promotional materials; The recommended combination list and the combination list to be optimized are merged to generate a structured adjustment guide; Submit the structured adjustment guidelines to the advertising platform, execute advertising according to the structured adjustment guidelines within the preset observation period, and record the number of impressions, clicks and conversions corresponding to each touchpoint combination and material order, and compare them with the number of impressions, clicks and conversions before the adjustment under the same experience stage; When the number of clicks and conversions are both higher than before the adjustment and the number of impressions is not lower than before the adjustment, the corresponding touchpoint combination and creative order will be written into the ad experience script in the ad experience twin graph and the original touchpoint combination and creative order will be replaced.

2. The method for dynamically adjusting advertising delivery strategies based on digital twins as described in claim 1, characterized in that: The specific steps for dividing the advertising experience segments from the actual delivery records according to a preset period are as follows. Pre-set the cycle in the advertising twin platform and link it to the business calendar; Retrieve exposure records, click records, and conversion records within each preset period, and generate a behavior sequence according to user identification and occurrence time; In each behavior sequence, continuous records are combined into a coherent browsing and interaction process based on touchpoint nodes, behavior types, and time intervals, and the corresponding original material identifiers and original placement identifiers are recorded to generate advertising experience segments. 3.The method of claim 1, wherein: The specific steps for completing the annotation of touchpoints, paths, and experience stages on the advertising experience twin graph to form an experience segment library are as follows. Import the ad experience clips into the ad twin platform, and mark the start touch point node and end touch point node in the touch point layer of the ad experience twin graph; The path of the ad experience segment is determined at the path layer and a path identifier is attached. The experience stage of the ad experience segment is determined at the experience stage layer and an experience stage label is attached. Advertising experience segments with touchpoint node identifiers, path identifiers, and experience stage tags are stored hierarchically according to preset cycles and experience stages, and an index relationship is established to form an experience segment library. 4.The method of claim 1, wherein: The target advertising experience script includes a set of target experience stages, a set of target paths, and a set of target touchpoints.

5. The digital-twin-based dynamic adjustment method of an advertising placement strategy according to claim 1, characterized in that: The specific steps for selecting an experience segment from the experience segment library that matches the target advertisement experience script are as follows. In the advertising twin platform, receive the target advertising experience script identifier and read the bound target experience stage set, target path set, and target touchpoint set; In the experience segment library, candidate ad experience segments are selected whose experience stage belongs to the target experience stage set, whose path belongs to the target path set, and whose touchpoints belong to the target touchpoint set. The path coverage, touchpoint overlap, and experience stage consistency are statistically analyzed and ranked to form an ad experience segment set.

6. The digital-twin-based dynamic adjustment method of an advertising placement strategy according to claim 1, characterized in that: The preset period is a time interval pre-configured in the advertising twin platform based on the business calendar.

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