Method for determining and recommending putting strategy and related equipment

Abstract

The invention provides a method for determining and recommending a putting strategy and related equipment. The method for recommending the delivery strategy comprises the following steps: determining a delivery index and at least two key behaviors; according to the delivery index and the at least two key behaviors, a delivery strategy is determined, the delivery strategy comprises at least two key nodes corresponding to the at least two key behaviors, and the key nodes are selected from a plurality of nodes to be selected according to the delivery index; and outputting the putting strategy.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technologies, and in particular, to a method for determining and recommending a delivery strategy and related devices. Background Art

[0002] Information delivery is the process of sending information to a terminal device. In Internet technologies, information delivery is usually targeted. For example, the target audience of the information is determined, and the information is sent to the target audience to obtain better feedback.

[0003] However, the inventors of the present disclosure have found that in related technologies, more attention is usually paid to the final delivery effect, rather than how the path segments in the entire link are converted. For some users, such a recommendation method has deficiencies. Summary of the Invention

[0004] The present disclosure provides a method for determining and recommending a delivery strategy and related devices to solve or partially solve the above problems.

[0005] In a first aspect of the present disclosure, a method for a recommended delivery strategy is provided, including:

[0006] Determine a delivery metric and at least two key behaviors;

[0007] According to the delivery metric and the at least two key behaviors, determine a delivery strategy, where the delivery strategy includes at least two key nodes corresponding to the at least two key behaviors, and the key nodes are selected from a plurality of candidate nodes according to the delivery metric;

[0008] Output the delivery strategy.

[0009] In a second aspect of the present disclosure, a method for determining a delivery strategy is provided, including:

[0010] Determine a delivery metric and at least two key behaviors;

[0011] According to the delivery metric and the at least two key behaviors, determine at least two key nodes corresponding to the at least two key behaviors from a plurality of candidate nodes;

[0012] According to the at least two key nodes, determine a delivery strategy.

[0013] In a third aspect of the present disclosure, a device for a recommended delivery strategy is provided, including:

[0014] A first determination module configured to: determine a delivery metric and at least two key behaviors;

[0015] A second determination module, configured to: determine a placement strategy according to the placement metrics and the at least two key behaviors, where the placement strategy includes at least two key nodes corresponding to the at least two key behaviors, and the key nodes are selected from a plurality of candidate nodes according to the placement metrics;

[0016] An output module, configured to: output the placement strategy.

[0017] In a fourth aspect of the present disclosure, there is provided a device for determining a placement strategy, including:

[0018] A first determination module, configured to: determine placement metrics and at least two key behaviors;

[0019] A second determination module, configured to: determine at least two key nodes corresponding to the at least two key behaviors from a plurality of candidate nodes according to the placement metrics and the at least two key behaviors;

[0020] A third determination module, configured to: determine a placement strategy according to the at least two key nodes.

[0021] In a fifth aspect of the present disclosure, there is provided a computer device, including one or more processors, a memory; and one or more programs, where the one or more programs are stored in the memory and executed by the one or more processors, and the programs include instructions for executing the method according to the first aspect or the second aspect.

[0022] In a sixth aspect of the present disclosure, there is provided a non-volatile computer-readable storage medium containing a computer program, which when executed by one or more processors, causes the processors to execute the method according to the first aspect or the second aspect.

[0023] In a seventh aspect of the present disclosure, there is provided a computer program product, including computer program instructions, which when run on a computer, cause the computer to execute the method according to the first aspect or the second aspect.

[0024] The method and related devices for determining and recommending a placement strategy provided by the present disclosure can recommend a placement strategy according to placement metrics and at least two key behaviors, so that the placement strategy can be more targeted and better meet the needs of users. Description of the Drawings

[0025] To more clearly illustrate the technical solutions in the present disclosure or related technologies, the following will briefly introduce the drawings required for use in the embodiments or the description of related technologies. Obviously, the drawings in the following description are only embodiments of the present disclosure. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0026] Figure 1 The figure shows a schematic diagram of an exemplary system provided by an embodiment of the present disclosure.

[0027] Figure 2 The figure shows a schematic flowchart of an exemplary method provided by an embodiment of the present disclosure.

[0028] Figure 3A The figure shows a schematic diagram of an exemplary page according to an embodiment of the present disclosure.

[0029] Figure 3B The figure shows another schematic diagram of an exemplary page according to an embodiment of the present disclosure.

[0030] Figure 3C The figure shows another schematic diagram of an exemplary page according to an embodiment of the present disclosure.

[0031] Figure 4 The figure shows a schematic flowchart of another exemplary method provided by an embodiment of the present disclosure.

[0032] Figure 5 The figure shows a schematic diagram of an exemplary device provided by an embodiment of the present disclosure.

[0033] Figure 6 The figure shows a schematic diagram of another exemplary device provided by an embodiment of the present disclosure.

[0034] Figure 7 The figure shows a schematic diagram of the hardware structure of an exemplary computer device provided by an embodiment of the present disclosure. Detailed implementation manners

[0035] To make the purpose, technical solutions and advantages of the present disclosure clearer and more understandable, the following further details the present disclosure in combination with specific embodiments and with reference to the drawings.

[0036] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present disclosure should have the ordinary meanings understood by those of ordinary skill in the field to which the present disclosure belongs. The "first", "second" and similar terms used in the embodiments of the present disclosure do not denote any order, quantity or importance, but are only used to distinguish different components. The terms such as "including" or "comprising" mean that the elements or objects appearing before this word cover the elements or objects listed after this word and their equivalents, without excluding other elements or objects. The terms such as "connected" or "coupled" are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The terms such as "upper", "lower", "left" and "right" are only used to represent relative positional relationships, and when the absolute position of the object being described changes, the relative positional relationship may also change accordingly.

[0037] It can be understood that before using the technical solutions of the various embodiments of the present disclosure, the types, usage scopes, usage scenarios, etc. of the personal information involved will be informed to the user in an appropriate manner, and the user's authorization will be obtained.

[0038] For example, when a user's active request is received, a prompt message is sent to the user to clearly prompt the user that the operation requested to be executed will require obtaining and using the user's personal information. Thus, the user can autonomously choose whether to provide personal information to software or hardware such as an electronic device, an application program, a server, or a storage medium that performs the operations of the technical solutions of the present disclosure according to the prompt message.

[0039] As an optional but non-limiting implementation manner, the manner of sending a prompt message to the user in response to receiving the user's active request may be, for example, in the form of a pop-up window, and the prompt message may be presented in text in the pop-up window. In addition, the pop-up window may also carry selection controls for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0040] It can be understood that the above process of notifying and obtaining the user's authorization is only illustrative and does not limit the implementation manner of the present disclosure, and other manners that meet relevant laws and regulations can also be applied to the implementation manner of the present disclosure.

[0041] Figure 1 FIG. shows a schematic diagram of an exemplary system 100 provided by an embodiment of the present disclosure.

[0042] As Figure 1As shown, the system 100 may include a computer device 102, a terminal device 104, a server 106, and a database server 108. A medium (e.g., a network) providing a communication link may be included between the computer device 102 and the terminal device 104 and the server 106 and the database server 108. The network may include various connection types, such as wired, wireless communication links, or fiber optic cables, etc.

[0043] In an exemplary information delivery scenario, the user 110 may utilize the system 100 to achieve information delivery. As an exemplary scenario, the user 110 may send an information delivery request to the server 106, and the server 106 determines a delivery strategy based on the information delivery request and feeds back the delivery strategy to the user 110. For example, the delivery strategy is displayed through the computer device 102. Then, the user 110 may use the computer device 102 to determine the final delivery strategy according to the delivery strategy provided by the server 106, and then upload the final delivery strategy to the server 106 so that the server 106 completes subsequent information delivery according to the final delivery strategy. The information delivered according to the final delivery strategy can be obtained and displayed by the terminal device 104 of the end user 112.

[0044] Various application programs (APPs) may be installed on the terminal device 104, such as video conferencing application programs, reading application programs, video application programs, social application programs, payment application programs, web browsers, and instant messaging tools, etc. These application programs can all be used to display the delivered information.

[0045] Here, the computer device 102 and the terminal device 104 may be hardware or software. When the computer device 102 and the terminal device 104 are hardware, they may be various electronic devices with a display screen, including but not limited to smart phones, tablet computers, e-book readers, MP3 players, laptop computers, and desktop computers (PCs), etc. When the computer device 102 and the terminal device 104 are software, they can be installed in the above-listed electronic devices. It can be implemented as multiple software or software modules (e.g., used to provide distributed services), or can be implemented as a single software or software module. No specific limitation is made here.

[0046] The server 106 may be a server providing various services, such as a background server supporting various applications displayed on the terminal device 104. The database server 108 may also be a database server providing various services. It can be understood that when the server 106 can implement the related functions of the database server 108, the database server 108 may not be provided in the system 100.

[0047] The server 106 and the database server 108 here can also be either hardware or software. When they are hardware, they can be implemented as a distributed server cluster composed of multiple servers or as a single server. When they are software, they can be implemented as multiple software or software modules (e.g., for providing distributed services) or as a single software or software module. Specific limitations are not made here.

[0048] It should be noted that the method for generating a page provided by the embodiments of the present disclosure can be executed by the computer device 102 and / or the computer device 104. It should be understood that Figure 1 the numbers of computer devices, terminal devices, users, servers, and database servers in

[0049] In the field of information delivery, in order to build a brand image and positioning or to facilitate the purchase of goods by the end user 112, the user 110 (e.g., an advertiser) needs to contact the end user 112 through information delivery or social media operation.

[0050] With the diversity of information delivery means, there are more and more delivery channels to choose from when conducting information delivery. For example, various information can be delivered to the end user 112 through multiple delivery channels such as the home page display of a portal website, a search channel, a video playback platform, an email channel, and a text message channel. In this way, while the user 110 faces the dispersion of channels for contacting the end user 112, the user 110 also needs to make a choice among the various delivery methods provided by various channels (e.g., posting videos on social media, displaying pop-ups on web pages, etc.).

[0051] In such a dilemma, how to choose among multiple channels and delivery methods, or how to cooperate among multiple channels or delivery methods (e.g., how to combine, how to allocate, how to arrange the order) is a common problem faced by the user 110.

[0052] As mentioned above, in the related art, usually more attention is paid to the final delivery effect, rather than caring about how the path segments in the entire link are converted. However, with more in-depth research, the user 110 is no longer limited to only paying attention to the path of the final successful conversion. How to observe the transfer efficiency and transfer path between behaviors and optimize the transfer efficiency based on this has become a difficult problem to overcome in the next step.

[0053] For example, at a certain stage of brand promotion, some users actually care more about how to achieve the conversion at this stage. If the delivery strategy is recommended to such users according to the final conversion effect, it will be difficult to meet the actual current needs of such users.

[0054] In view of this, embodiments of the present disclosure provide a method for recommending a placement strategy, which can recommend a placement strategy based on placement metrics and at least two key behaviors, so that the placement strategy can be more targeted and better meet the needs of users.

[0055] Figure 2 FIG. shows a schematic flowchart of an exemplary method 200 provided by embodiments of the present disclosure.

[0056] This method 200 can be used to recommend a placement strategy to user 110. Optionally, this method 200 can be implemented by Figure 1 computer device 102 and / or server 106. As Figure 2 shown, this method 200 may include the following steps.

[0057] In step 202, determine the placement metrics and at least two key behaviors.

[0058] The placement metrics may be placement metrics selected or input by the user, which can be used to measure the effect of information placement. The information to be placed, for example, may be text, image, video, sound, or any combination of the above.

[0059] Optionally, the placement metrics may include conversion rate, return on investment (ROI), cost per conversion, probability of being clicked, etc., or a combined metric of at least two of the foregoing.

[0060] The key behaviors may refer to behavior classifications divided according to the degree of attention or consideration stage. For example, in the order of increasing depth of interaction, the key behaviors may include key behavior 1 to key behavior 5, and may respectively correspond to attention degree 1 to attention degree 5. According to the classification of key behaviors, behavior data can be clustered, so that quantitative analysis can be performed based on the clustered information.

[0061] In some embodiments, before determining the placement metrics and at least two key behaviors, computer device 102 may provide a page for user 110 to select or input the placement metrics and key behaviors, thereby facilitating the operation of user 110.

[0062] Figure 3A FIG. shows a schematic diagram of an exemplary page 300 according to embodiments of the present disclosure.

[0063] As Figure 3A shown, in some embodiments, user 110 may start computer device 102, enter the website URL for placing information in the browser of computer device 102, and then enter the first page 300.

[0064] The first page 300 may include a first area 302, and various indicators for the user to select may be included in the first area 302. Each indicator corresponds to a selection control 3022. The user 110 selects the corresponding control 3022 to select the corresponding delivery indicator. For example, Figure 3A as shown, the user 110 selects the conversion rate as the delivery indicator. In some embodiments, such as Figure 3A shown, the page 300 may further include a new control 3024, and the user 110 can add a delivery indicator by triggering the new control 3024. For the delivery indicators displayed on the page 300, the user 110 can select one or multiple of them. The system 100 can calculate a comprehensive indicator based on multiple delivery indicators, and then recommend corresponding delivery strategies to the user 110 according to the comprehensive indicator.

[0065] In some embodiments, such as Figure 3A shown, the first page 300 may further include a second area 304, and the second area 304 can be used to display a flow chart. It can be understood that the flow chart can be generated according to the corresponding indicators after the user selects any control 3022, or can be generated based on default indicators (for example, the conversion rate).

[0066] Optionally, as Figure 3A shown, the flow chart can serially connect multiple key behavior icons 3042 in a predetermined order. Optionally, information about the corresponding key behavior can be displayed in the key behavior icon 3042, for example, key behavior 1, key behavior 2, key behavior 3, key behavior 4, key behavior 5.

[0067] In some embodiments, at least one first indicator 3044 corresponding to the key behavior icon 3042 can also be displayed on one side of the key behavior icon 3042.

[0068] As Figure 3A shown, exemplarily, a first indicator 3044 and its value can be correspondingly displayed on one side of each key behavior icon 3042, so that the user 110 can intuitively see the value of the first indicator 3044 of the corresponding key behavior. It can be understood that Figure 3A the first indicator 3044 in

[0069] is the conversion rate. In addition, other delivery indicators or non-delivery indicators can also be displayed. For example, the first indicator 3044 can also be the click probability of the content corresponding to the key behavior, or the number of individuals in the group corresponding to the key behavior.The calculation of the value of the first indicator or the placement indicator can be performed using historical data. In some embodiments, the historical data can be first clustered according to the classification of key behaviors, and then the value of the corresponding indicator can be calculated based on the historical data. Depending on the needs of user 110, the scope of the historical data can be different. For example, if user 110 wants to view industry data analysis, the historical data can be industry historical data. Another example is that if user 110 wants to view the performance data of their own brand, the historical data can be brand historical data. For another example, if user 110 wants to view the performance data of a certain product (the placement object), the historical data can also be product historical data. Specifically, user 110 can set by themselves the level of granularity (industry, brand, product) for analysis, and the setting options can be displayed on the first page 300 (not shown in the figure) to facilitate user 110 to make the setting.

[0070] Taking the calculation of the number of individuals as an example, the behavioral data in the historical data can be clustered according to the classification of key behaviors to obtain the historical data set corresponding to each key behavior. Then, statistical calculations are performed based on the historical data in the historical data set to obtain the number of individuals corresponding to the corresponding data set, thereby obtaining the value of the corresponding indicator. The calculation of other indicators is similar and will not be elaborated here.

[0071] In some embodiments, as Figure 3A shown, the first page 300 further includes at least two first options 3026 for setting a time period; after the first page is displayed, the method 200 may further include the step of generating a corresponding flow chart based on the time period selected by user 110.

[0072] Specifically, in response to receiving a setting instruction for the at least two first options 3026, a first time period and a second time period are determined; then, the first flow chart corresponding to the first time period and the second flow chart of the second time period are displayed side by side on the first page.

[0073] Figure 3B shows a schematic diagram of an exemplary page 310 according to an embodiment of the present disclosure.

[0074] As Figure 3B shown, user 110 has set a first time period (for example, 2022) and a second time period (for example, 2023) in the two first options 3026 respectively.

[0075] In the second region 304, the first flow chart corresponding to the first time period and the second flow chart of the second time period can be displayed side by side. In this way, by comparing the two flow charts, the user 110 can intuitively compare the performance of the two time periods. For example, taking the user's selection to analyze their own brand as an example, the two flow charts can respectively display the performance indicators in 2022 and 2023. In this way, the user 110 can roughly judge how the performance in 2023 compares to that in 2022 based on the comparison of the two flow charts, and then determine in what direction to make breakthroughs next.

[0076] As an alternative embodiment, as Figure 3B shown, in the first flow chart and the second flow chart, the key behavior icons can reflect the values of the corresponding first indicators through their area sizes.

[0077] From Figure 3B it can be seen that, by way of example, the area of the first key behavior icon in the first flow chart is larger than the area of the first key behavior icon in the second flow chart, indicating that for the first indicator corresponding to the first key behavior icon, the performance in the first time period is better than that in the second time period.

[0078] For another example, the area of the fourth key behavior icon in the first flow chart is larger than the area of the fourth key behavior icon in the second flow chart, indicating that for the first indicator corresponding to the fourth key behavior icon, the performance in the second time period is better than that in the first time period.

[0079] Thus, by directly reflecting the values of the indicators through the areas of the key behavior icons, the comparison becomes more intuitive.

[0080] In some embodiments, after displaying the first page, the method 200 further includes: in response to the value of the first indicator being greater than a first threshold or less than a second threshold, highlighting the key behavior icon corresponding to the first indicator whose value is greater than the first threshold or less than the second threshold.

[0081] As Figure 3B shown, by way of example, assuming that the value of the indicator corresponding to key behavior 1 in the second time period is less than the second threshold (for example, the number of individuals is less than the quantity threshold), then the key behavior icon corresponding to key behavior 1 can be highlighted to remind the user 110 to pay attention to the data with relatively poor performance. Similarly, some first thresholds can also be set for the user 110 to pay attention to the data with relatively good performance.

[0082] As an alternative embodiment, for the key behavior icons corresponding to metrics greater than the first threshold and less than the second threshold, different colors can be used for highlighting. For example, for the key behavior icons corresponding to metrics greater than the first threshold, red can be used for highlighting, and for the key behavior icons corresponding to metrics less than the second threshold, green can be used for highlighting.

[0083] In some embodiments, considering that the metrics corresponding to different key behaviors may not be measurable by absolute thresholds, the thresholds for the metrics corresponding to different key behaviors can be set to different values. For example, for key behaviors 1 to 5, their corresponding thresholds can gradually decrease in sequence.

[0084] It can be understood that in Figure 3A In the page 300 shown, when only one flow chart is displayed, the method applicable to a single flow chart in the foregoing embodiments can also be adopted for implementation.

[0085] In some embodiments, determining at least two key behaviors may further include: in response to a trigger operation on at least two key behavior icons in the flow chart, determining at least two key behaviors corresponding to the at least two key behavior icons.

[0086] For example, as Figure 3B shown, since the metric performance corresponding to key behavior 1 is relatively poor, the user can determine key behavior 1 and key behavior 2 by triggering the key behavior icons corresponding to key behavior 1 and key behavior 2.

[0087] In some embodiments, as Figure 3B shown, after user 110 selects the placement metrics and at least two key behaviors, the user can click the confirm button 3030, thereby sending a recommendation request including the placement metrics and at least two key behaviors to the server 106, so that the server 106 determines a placement strategy based on this recommendation request and recommends the placement strategy to the user 110.

[0088] It can be understood that the foregoing method of using the server 106 to recommend a placement strategy is only an example. In some scenarios, the computer device 102 can also complete the recommendation of the placement strategy. Therefore, in this case, the computer device 102 does not need to send the placement metrics to the server 106.

[0089] In some embodiments, as Figure 3AAs shown, the page 300 may further include options for selecting classification by different audience groups and by different scenario features. By checking the controls in front of the corresponding options and clicking the OK button 3026, corresponding group feature information and scenario feature information can be generated, or corresponding group classification requests and scenario classification requests can be generated, so that the delivery strategy can be classified according to different audience groups and / or according to different scenario features.

[0090] In some embodiments, as Figure 3A shown, the page 300 may further include options for selecting the delivery object. By the user 110 selecting a specific delivery object, the system 100 can recommend a delivery strategy based on the delivery object selected by the user. Among them, the delivery object may refer to an object related to the delivered content, etc., for example, a product (such as Figure 3A the cup and bottle shown in Figure 3A ), service, store, etc. The options for the delivery object on the page 300 may be pre-generated. In some embodiments, as

[0091] shown, the user 110 can also add a delivery object through the new control 3028.

[0091] In step 204, according to the delivery metrics and the at least two key behaviors, a delivery strategy is determined. The delivery strategy includes at least two key nodes corresponding to the at least two key behaviors, and the key nodes are selected from a plurality of candidate nodes according to the delivery metrics.

[0092] In step 204, after obtaining the delivery metrics of the user 110 and the at least two key behaviors selected by the user 110, the corresponding delivery strategy can be determined according to the delivery metrics and the at least two key behaviors, so that the delivery strategy can be more matched with the delivery metrics and the at least two key behaviors.

[0093] Optionally, the delivery strategy includes at least two key nodes corresponding to the at least two key behaviors, and the key nodes may be various nodes related to information delivery and having an impact on the delivery effect, such as delivery methods, delivery combinations, delivery times, and so on.

[0094] In some embodiments, the plurality of key nodes may include at least one of a target delivery method (for example, posting a video on a social media, displaying a pop-up window on a web page, etc.), a delivery method combination including the target delivery method, the delivery times and delivery time intervals corresponding to the delivery method combination, the delivery path segment corresponding to the delivery method combination, the complete path including the delivery path segment, tags, and search terms. Thus, after the user 110 sees the delivery strategy including the key nodes, richer recommended content can be obtained, which is beneficial for the user to determine the delivery strategy.

[0095] Optionally, the key node may be selected from multiple candidate nodes according to the delivery metrics. The candidate nodes may be any nodes related to information delivery, and Method 200 is to find, from these candidate nodes, the key node that has a greater impact on the delivery metrics in the path segment containing the at least two key behaviors.

[0096] Therefore, in some embodiments, the system 100 may preprocess historical data to obtain historical values of the delivery metrics corresponding to the candidate nodes, and then may find the key nodes from the candidate nodes based on these historical values.

[0097] When determining the historical values of the delivery metrics corresponding to the candidate nodes, the following takes the contact path between the brand of User 110 and the end-user group as an example for calculation.

[0098] First, the system 100 may first obtain the historical data under the brand of User 110 (e.g., an advertiser), and then determine the corresponding contact path between the brand and the end-user according to the historical data. It can be understood that the contact path here needs to correspond to the transfer process of the at least two key behaviors.

[0099] For example, assuming that Key Behavior 1 is that the content is viewed and Key Behavior 2 is being followed / interacted with, the behavior data can be searched according to Key Behavior 1 and Key Behavior 2 to find the behavior data in the historical data that matches Key Behavior 1 and Key Behavior 2, and then the contact path corresponding to the behavior data link is determined.

[0100] For example, the browsing of social media and the viewing of videos correspond to Key Behavior 1, and the following of the enterprise account corresponds to Key Behavior 2. The corresponding contact points are social media and the enterprise account, and the corresponding contact path can be social media - enterprise account.

[0101] In some embodiments, in addition to the traditional contact points dedicated to information delivery, the contact points may also include more extensive contact points. For example, any form that can contact the end-user 112 can be considered as a contact point in the embodiments of the present disclosure, making the scenario corresponding to the contact path more comprehensive and more in line with the complex user communication form native to the brand side.

[0102] Then, after filtering out the contact paths, the system 100 may, according to the historical data under the brand of User 110, use a clustering algorithm to cluster the historical data with the same or similar contact paths, and then for each category of historical transaction data, it corresponds to a same or similar contact path, so that subsequent delivery strategies can be recommended to users based on this contact path.

[0103] In some embodiments, after clustering to obtain multiple contact paths, the system 100 may calculate the historical values corresponding to each contact path and the placement metrics based on this historical data under the brand of the user 110. For example, conversion rate, return on investment (ROI), cost per conversion, probability of being clicked, and so on. In some embodiments, when the user 110 adds a new placement metric (e.g., by adding the metrics they care about through page 300), the system 100 may also calculate the historical values corresponding to each contact path and the new placement metric based on this historical data under the brand of the user 110.

[0104] As described above, in some embodiments, in addition to including the complete path, the multiple key nodes may further include the target placement method, the placement method combination including the target placement method, the number of placements and the placement time interval corresponding to the placement method combination, and the placement path segment corresponding to the placement method combination. Therefore, in some embodiments, the candidate nodes may include the placement method, the placement method combination, the number of placements and the placement time interval corresponding to the placement method combination, and the placement path segment corresponding to the placement method combination, and the system 100 may pre-calculate the historical values corresponding to these candidate nodes.

[0105] In some embodiments, the contact path can be matched with a specific application scenario, so that the placement strategy can be further segmented to improve the matching degree of the placement strategy with the specific scenario.

[0106] In some embodiments, the system 100 may cluster the audience groups corresponding to the historical data, then further analyze the contact paths according to the group characteristics, and calculate the historical values corresponding to the placement metrics based on these groups respectively for subsequent recommendation of placement strategies.

[0107] At this point, the system 100 has completed the process of matching each candidate node with the placement metric.

[0108] In some embodiments, determining a placement strategy according to the placement metric and the at least two key behaviors includes: selecting at least two key nodes corresponding to the at least two key behaviors from multiple candidate nodes according to the value of the placement metric; wherein, as described above, the value of the placement metric is obtained through a clustering algorithm based on historical data.

[0109] In this way, by using the value of the placement metric that has been calculated, at least two key nodes corresponding to the at least two key behaviors can be screened out from multiple candidate nodes, and these at least two key nodes perform better under the placement metric.

[0110] In some embodiments, the historical data includes industry historical data and brand historical data; according to the value of the delivery index, at least two key nodes corresponding to the at least two key behaviors are selected from multiple nodes to be selected, including: in response to the brand historical data not reaching the quantity threshold, according to the value of the delivery index corresponding to each of the nodes to be selected calculated by a clustering algorithm using the industry historical data, at least two key nodes corresponding to the at least two key behaviors are selected from multiple nodes to be selected.

[0111] The above embodiment is explained by taking the brand's historical data for calculation as an example. However, it is understandable that for some emerging brands, their historical data may not be sufficient for data analysis. In this case, the historical data of the industry corresponding to the brand can be used as analysis data, so as to obtain more objective and more valuable analysis results.

[0112] After obtaining the above key nodes, in step 206, the delivery strategy may be output to the user 110. Optionally, the delivery strategy may be output to the user in various ways, such as by voice broadcast, display on a display screen, and the like.

[0113] In some embodiments, outputting the delivery strategy to the user may include: displaying a second page, wherein the delivery strategy is presented in the first page in the form of connecting the multiple key nodes in series, so that the user 110 can see the delivery strategy more intuitively and can fully understand the determination path of the delivery strategy, which is conducive to the user's selection of the delivery strategy.

[0114] Figure 3C Another schematic diagram of an exemplary page 320 according to an embodiment of the present disclosure is shown.

[0115] like Figure 3C As shown, the second page 320 displays the delivery strategies including each key node and the process of their generation. For example, the target delivery method B is selected first, then the efficient combination A+B+C including the target delivery method B is determined, then the total delivery times of the combination ABC are determined to be 4 times, and then the 4 path segments in the combination ABC are determined (first 2 times A, then 1 time B, and finally 1 time C), and finally a complete path including efficient path segments is obtained.

[0116] In this way, starting from a target delivery method, users can gain insight into other delivery methods that cooperate with the target delivery method, the order of precedence, the number of times each delivery is delivered, and whether other delivery methods are needed to assist (or take over) before (after) the target delivery method in the long chain.

[0117] In some embodiments, Figure 3CAs shown, two placement strategies with better placement metrics can be displayed on the second page 320. Among them, the difference between the two placement strategies lies in the different target placement methods selected (exemplarily, the first placement strategy selects touchpoint B, and the second placement strategy selects touchpoint C). Accordingly, the subsequent key nodes have also changed, so as to provide different ideas for user 110.

[0118] As an alternative embodiment, as Figure 3C shown, the values of the placement metrics corresponding to each key node are also displayed on the second page 320, enabling user 110 to intuitively compare the advantages and disadvantages of the two placement strategies, which is conducive to user 110 making a decision.

[0119] It can be seen from the above embodiments that the method for recommending placement strategies provided by the embodiments of the present disclosure can recommend placement strategies according to placement metrics and at least two key behaviors, making the placement strategies more targeted and better meeting the needs of users.

[0120] In some embodiments, the method for recommending placement strategies provided by the embodiments of the present disclosure, through cross-analysis of key behaviors with touchpoints and touchpaths, can support users to display the transfer touchpoint link between any two key behaviors, truly helping users analyze touchpoints under different purposes and study the connection or triggering relationship between touchpoints and specific key behaviors.

[0121] It should be noted that the method of the embodiments of the present disclosure can be executed by a single device, such as a computer or a server. The method of this embodiment can also be applied to a distributed scenario and completed by multiple devices cooperating with each other. In this case of a distributed scenario, one of the multiple devices can only execute one or more steps of the method of the embodiments of the present disclosure, and these multiple devices will interact with each other to complete the described method.

[0122] It should be noted that some embodiments of the present disclosure have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be executed in a different order from that in the above embodiments and still achieve the desired results. Additionally, the processes depicted in the figures do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0123] The embodiments of the present disclosure also provide a method for determining a placement strategy. Figure 4 The flowchart of an exemplary method 400 provided by the embodiments of the present disclosure is shown. This method 400 can be applied to Figure 1Server 106 and can be implemented by server 106. As Figure 4 shown, the method 400 may further include the following steps.

[0124] In step 402, determine the delivery metrics and at least two key behaviors.

[0125] The delivery metrics can be delivery metrics selected or input by the user and can be used to measure the effect of information delivery. The information to be delivered can be, for example, text, image, video, sound, or any combination of the above.

[0126] Optionally, the delivery metrics may include conversion rate, return on investment (ROI), cost per conversion, probability of being clicked, etc., or a combined metric of at least two of the foregoing.

[0127] The key behaviors can be a classification of behaviors divided according to different degrees of attention or stages of consideration. For example, in the order of increasing depth of interaction, the key behaviors may include key behaviors 1 to 5, and may respectively correspond to degrees of attention 1 to 5. According to the classification of key behaviors, the behavior data can be clustered, so that quantitative analysis can be performed based on the clustered information.

[0128] In some embodiments, as Figure 3B shown, after the user 110 selects the delivery metrics and at least two key behaviors, the user can click the OK button 3030, so as to send a recommendation request including the delivery metrics and at least two key behaviors to the server 106, so that the server 106 can determine the delivery metrics and the at least two key behaviors.

[0129] In step 404, according to the delivery metrics and the at least two key behaviors, determine at least two key nodes corresponding to the at least two key behaviors from a plurality of candidate nodes.

[0130] Optionally, the delivery strategy includes at least two key nodes corresponding to the at least two key behaviors, and the key nodes can be various nodes related to information delivery and having an impact on the delivery effect, such as delivery methods, delivery combinations, delivery times, and so on.

[0131] In some embodiments, the multiple key nodes may include at least one of a target delivery method (e.g., posting a video on a social media, displaying a pop-up window on a web page, etc.), a combination of delivery methods including the target delivery method, the number of deliveries and the delivery time interval corresponding to the combination of delivery methods, the delivery path segment corresponding to the combination of delivery methods, the complete path including the delivery path segment, tags, and search terms. Thus, after user 110 sees the delivery strategy including the key nodes, richer recommended content can be obtained, which is beneficial for the user to determine the delivery strategy.

[0132] Optionally, the key nodes may be selected from multiple candidate nodes according to the delivery metrics. The candidate nodes may be any nodes related to information delivery, and method 200 is to find the key nodes that have a greater impact on the delivery metrics in the path segment including the at least two key behaviors from these candidate nodes.

[0133] Therefore, in some embodiments, system 100 may preprocess historical data to obtain the historical values of the delivery metrics corresponding to the candidate nodes, and then may find the key nodes from the candidate nodes based on these historical values.

[0134] When determining the historical values of the delivery metrics corresponding to the candidate nodes, the following takes the contact path between the brand of user 110 and the end-user group as an example for calculation.

[0135] First, server 106 may first obtain the historical data under the brand of user 110, and then determine the corresponding contact path between the brand and the end user according to the historical data. It can be understood that the contact path here needs to correspond to the transfer process of the at least two key behaviors.

[0136] For example, assuming that key behavior 1 is that the content is viewed and key behavior 2 is being followed / interacted with, the behavior data can be searched according to key behavior 1 and key behavior 2 to find the behavior data in the historical data that matches key behavior 1 and key behavior 2, and then the contact path corresponding to the behavior data link is determined.

[0137] For example, browsing social media and viewing a video correspond to key behavior 1, and following an enterprise account corresponds to key behavior 2. The corresponding contact points are social media and the enterprise account, and the corresponding contact path can be social media - enterprise account.

[0138] In some embodiments, in addition to the traditional contact points dedicated to information delivery, the contact points may further include a broader range of contact points. For example, any form capable of contacting the end user 112 can be considered a contact point in the embodiments of the present disclosure, making the scenarios corresponding to the contact paths more comprehensive and more in line with the complex user communication forms native to the brand side.

[0139] Then, after filtering out the contact paths, the server 106 can cluster the historical data with the same or similar contact paths according to these historical data under the brand of the user 110 through a clustering algorithm. Furthermore, for each category of historical transaction data, there corresponds a same or similar contact path, so that subsequent delivery strategies can be recommended to the user based on this contact path.

[0140] In some embodiments, after clustering multiple contact paths, the server 106 can calculate the historical values corresponding to each contact path and the delivery metrics according to these historical data under the brand of the user 110. For example, conversion rate, return on investment (ROI), cost per conversion, probability of being clicked, and so on. In some embodiments, when the user 110 adds a new delivery metric (e.g., by adding the metrics they care about through page 300), the system 100 can also calculate the historical values corresponding to each contact path and the new delivery metric according to these historical data under the brand of the user 110.

[0141] As mentioned above, in some embodiments, in addition to including the complete path, the multiple key nodes may further include the target delivery method, the delivery method combination including the target delivery method, the number of deliveries and the delivery time interval corresponding to the delivery method combination, and the delivery path segment corresponding to the delivery method combination. Therefore, in some embodiments, the candidate nodes may include the delivery method, the delivery method combination, the number of deliveries and the delivery time interval corresponding to the delivery method combination, and the delivery path segment corresponding to the delivery method combination, and the server 106 can pre-calculate the historical values corresponding to these candidate nodes.

[0142] In some embodiments, the contact path can be matched with the specific application scenario, so that the delivery strategy can be further refined and the matching degree of the delivery strategy with the specific scenario can be improved.

[0143] In some embodiments, the server 106 can cluster the audience groups corresponding to the historical data, then further analyze the contact paths according to the group characteristics, and calculate the historical values corresponding to the delivery metrics based on these groups respectively for subsequent recommendation of delivery strategies.

[0144] So far, the server 106 has completed the process of matching each candidate node with the delivery metric.

[0145] In some embodiments, a delivery strategy is determined based on the delivery indicator and the at least two key behaviors, including: selecting at least two key nodes corresponding to the at least two key behaviors from multiple candidate nodes based on the value of the delivery indicator; wherein, as mentioned above, the value of the delivery indicator is obtained through a clustering algorithm based on historical data.

[0146] In this way, by using the calculated value of the delivery index, at least two key nodes corresponding to the at least two key behaviors can be screened out from multiple candidate nodes, and the at least two key nodes perform better under the delivery index.

[0147] In some embodiments, the historical data includes industry historical data and brand historical data; according to the value of the delivery index, at least two key nodes corresponding to the at least two key behaviors are selected from multiple nodes to be selected, including: in response to the brand historical data not reaching the quantity threshold, according to the value of the delivery index corresponding to each of the nodes to be selected calculated by a clustering algorithm using the industry historical data, at least two key nodes corresponding to the at least two key behaviors are selected from multiple nodes to be selected.

[0148] The above embodiment is explained by taking the brand's historical data for calculation as an example. However, it is understandable that for some emerging brands, their historical data may not be sufficient for data analysis. In this case, the historical data of the industry corresponding to the brand can be used as analysis data, so as to obtain more objective and more valuable analysis results.

[0149] In step 406, a delivery strategy is determined based on the at least two key nodes.

[0150] Figure 3C Another schematic diagram of an exemplary page 320 according to an embodiment of the present disclosure is shown.

[0151] like Figure 3C As shown, the second page 320 displays the delivery strategies including each key node and the process of their generation. For example, the target delivery method B is selected first, then the efficient combination A+B+C including the target delivery method B is determined, then the total delivery times of the combination ABC are determined to be 4 times, and then the 4 path segments in the combination ABC are determined (first 2 times A, then 1 time B, and finally 1 time C), and finally a complete path including efficient path segments is obtained.

[0152] In this way, starting from a target delivery method, users can gain insight into other delivery methods that cooperate with the target delivery method, the order of precedence, the number of times each delivery is delivered, and whether other delivery methods are needed to assist (or take over) before (after) the target delivery method in the long chain.

[0153] In some embodiments, such as Figure 3C shown, the server 106 may provide two placement strategies with better placement metrics performance to the user 110. Among them, the difference between the two placement strategies lies in the different target placement methods selected (exemplarily, the first placement strategy selects the B touchpoint, and the second placement strategy selects the C touchpoint). Accordingly, the subsequent key nodes have also changed, so as to provide different ideas to the user 110.

[0154] As can be seen from the above embodiments, the method for determining a placement strategy provided by the embodiments of the present disclosure can determine a placement strategy according to placement metrics and at least two key behaviors, so that the placement strategy can be more targeted and better meet the needs of users.

[0155] In some embodiments, the method for determining a placement strategy provided by the embodiments of the present disclosure, through cross-analysis of key behaviors with touchpoints and touch paths, can support the user to display the transfer touchpoint link between any two key behaviors, and truly help the user analyze touchpoints under different purposes, and study how to use the connection or triggering relationship between touchpoints and specific key behaviors.

[0156] It should be noted that the method of the embodiments of the present disclosure can be executed by a single device, such as a computer or a server, etc. The method of this embodiment can also be applied to a distributed scenario and completed by multiple devices cooperating with each other. In this case of a distributed scenario, one of the multiple devices can only execute one or more steps of the method of the embodiments of the present disclosure, and these multiple devices will interact with each other to complete the described method.

[0157] It should be noted that some embodiments of the present disclosure are described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the above embodiments and still achieve the desired results. Additionally, the processes depicted in the figures do not necessarily require the particular order or sequential order shown to achieve the desired results. In certain implementations, multitasking and parallel processing are also possible or may be advantageous.

[0158] The embodiments of the present disclosure also provide a device for recommending a placement strategy. Figure 5 The schematic diagram of an exemplary device 500 provided by the embodiments of the present disclosure is shown. As Figure 5 shown, the device 500 can be used to implement the method 200 and may further include the following modules.

[0159] The first determination module 502 is configured to: determine placement metrics and at least two key behaviors;

[0160] The second determination module 504 is configured to: determine a placement strategy according to the placement metrics and the at least two key behaviors, where the placement strategy includes at least two key nodes corresponding to the at least two key behaviors, and the key nodes are selected from multiple candidate nodes according to the placement metrics;

[0161] The output module 506 is configured to: output the placement strategy.

[0162] In some embodiments, before determining the placement metrics and the at least two key behaviors, the method further includes: displaying a first page; where the first page includes a flow chart of multiple key behavior icons, the flow chart serially connects the multiple key behavior icons in a predetermined order, and at least one first metric corresponding to the key behavior icon is displayed on one side of the key behavior icon.

[0163] In some embodiments, the first page further includes at least two first options for setting a time period; after displaying the first page, the method further includes: in response to receiving a setting instruction for the at least two first options, determining a first time period and a second time period; and concurrently displaying a first flow chart corresponding to the first time period and a second flow chart of the second time period in the first page; where the key behavior icons in the first flow chart and the second flow chart reflect the values of the corresponding first metrics through the area size.

[0164] In some embodiments, determining the at least two key behaviors includes: in response to a trigger operation on at least two key behavior icons in the flow chart, determining at least two key behaviors corresponding to the at least two key behavior icons.

[0165] In some embodiments, after displaying the first page, the method further includes: in response to the value of the first metric being greater than a first threshold or less than a second threshold, highlighting the key behavior icon corresponding to the first metric whose value is greater than the first threshold or less than the second threshold.

[0166] In some embodiments, determining the placement strategy according to the placement metrics and the at least two key behaviors includes: selecting at least two key nodes corresponding to the at least two key behaviors from multiple candidate nodes according to the value of the placement metrics; where the value of the placement metrics is obtained through a clustering algorithm based on historical data.

[0167] In some embodiments, the historical data includes industry historical data and brand historical data; selecting at least two key nodes corresponding to the at least two key behaviors from a plurality of candidate nodes according to the value of the placement metric includes: in response to the brand historical data not reaching the quantity threshold, selecting at least two key nodes corresponding to the at least two key behaviors from a plurality of candidate nodes according to the value of the placement metric corresponding to each of the candidate nodes calculated by using the industry historical data through a clustering algorithm.

[0168] In some embodiments, the at least two key nodes include at least one of a target placement method, a placement method combination including the target placement method, the number of placements and the placement time interval corresponding to the placement method combination, a placement path segment corresponding to the placement method combination, a complete path including the placement path segment, a label, and a search term.

[0169] For convenience of description, when describing the above device, it is divided into various modules according to functions for separate description. Of course, when implementing the present disclosure, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0170] The device of the above embodiment is used to implement the corresponding method 200 in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be described herein again.

[0171] The embodiments of the present disclosure further provide a device for determining a placement strategy. Figure 6 The schematic diagram of an exemplary device 600 provided by the embodiments of the present disclosure is shown. As Figure 6 shown, the device 600 can be used to implement the method 400, and can further include the following modules.

[0172] The first determination module 602 is configured to: determine a placement metric and at least two key behaviors;

[0173] The second determination module 604 is configured to: determine at least two key nodes corresponding to the at least two key behaviors from a plurality of candidate nodes according to the placement metric and the at least two key behaviors;

[0174] The third determination module 606 is configured to: determine a placement strategy according to the at least two key nodes.

[0175] For convenience of description, when describing the above device, it is divided into various modules according to functions for separate description. Of course, when implementing the present disclosure, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0176] The device of the above embodiment is used to implement the corresponding method 400 in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be elaborated herein.

[0177] An embodiment of the present disclosure also provides a computer device for implementing the above method 200 or 400. Figure 7 The schematic diagram of the hardware structure of an exemplary computer device 700 provided by an embodiment of the present disclosure is shown. The computer device 700 can be used to implement Figure 1 the computer device 102, and can also be used to implement Figure 1 the terminal device 104. In some scenarios, the computer device 700 can also be used to implement Figure 1 the server 106 and the database server 108.

[0178] As Figure 7 shown, the computer device 700 may include: a processor 702, a memory 704, a network module 706, a peripheral interface 708, and a bus 710. Among them, the processor 702, the memory 704, the network module 706, and the peripheral interface 708 are communicatively connected to each other inside the computer device 700 through the bus 710.

[0179] The processor 702 may be a central processing unit (CPU), an image processor, a neural network processor (NPU), a microcontroller (MCU), a programmable logic device, a digital signal processor (DSP), an application specific integrated circuit (ASIC), or one or more integrated circuits. The processor 702 can be used to execute functions related to the technologies described in the present disclosure. In some embodiments, the processor 702 may further include multiple processors integrated as a single logic component. For example, as Figure 7 shown, the processor 702 may include multiple processors 702a, 702b, and 702c.

[0180] The memory 704 can be configured to store data (such as instructions, computer codes, etc.). As Figure 7As shown, the data stored in the memory 704 may include program instructions (e.g., program instructions for implementing the method 200 or 400 of the embodiments of the present disclosure) and data to be processed (e.g., the memory may store configuration files of other modules, etc.). The processor 702 may also access the program instructions and data stored in the memory 704 and execute the program instructions to operate on the data to be processed. The memory 704 may include a volatile storage device or a non-volatile storage device. In some embodiments, the memory 704 may include a random access memory (RAM), a read-only memory (ROM), an optical disc, a magnetic disk, a hard disk, a solid state drive (SSD), a flash memory, a memory stick, etc.

[0181] The network interface 706 may be configured to provide communication with other external devices to the computer device 700 via a network. The network may be any wired or wireless network capable of transmitting and receiving data. For example, the network may be a wired network, a local wireless network (e.g., Bluetooth, WiFi, near field communication (NFC), etc.), a cellular network, the Internet, or a combination of the above. It can be understood that the type of the network is not limited to the above specific examples.

[0182] The peripheral interface 708 may be configured to connect the computer device 700 to one or more peripheral devices to achieve information input and output. For example, the peripheral devices may include input devices such as a keyboard, a mouse, a touchpad, a touch screen, a microphone, various sensors, etc. and output devices such as a display, a speaker, a vibrator, an indicator light, etc.

[0183] The bus 710 may be configured to transmit information between various components of the computer device 700 (e.g., the processor 702, the memory 704, the network interface 706, and the peripheral interface 708), such as an internal bus (e.g., a processor-memory bus), an external bus (USB port, PCI-E bus), etc.

[0184] It should be noted that although the architecture of the above computer device 700 only shows the processor 702, the memory 704, the network interface 706, the peripheral interface 708, and the bus 710, in the specific implementation process, the architecture of the computer device 700 may also include other components necessary for normal operation. In addition, those skilled in the art can understand that the architecture of the above computer device 700 may also only include the components necessary for implementing the solution of the embodiments of the present disclosure, and does not necessarily include all the components shown in the figure.

[0185] Based on the same inventive concept, corresponding to any of the above embodiment methods, the present disclosure also provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the method 200 or 400 as described in any of the above embodiments.

[0186] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassette tapes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.

[0187] The computer instructions stored in the storage medium of the above embodiment are used to cause the computer to execute the method 200 or 400 described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be elaborated here.

[0188] Based on the same inventive concept, corresponding to the method 200 or 400 in any of the above embodiments, the present disclosure also provides a computer program product, which includes a computer program. In some embodiments, the computer program is executable by one or more processors to cause the processors to execute the method 200 or 400. Corresponding to the execution subjects of each step in the embodiments of the method 200 or 400, the processors that execute the corresponding steps can belong to the corresponding execution subjects.

[0189] The computer program product of the above embodiment is used to cause the processor to execute the method 200 or 400 described in any of the above embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be elaborated here.

[0190] Those of ordinary skill in the art should understand that: the discussion of any of the above embodiments is only exemplary, and is not intended to imply that the scope of the present disclosure (including the claims) is limited to these examples; under the idea of the present disclosure, the technical features in the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations in different aspects of the embodiments of the present disclosure as described above, and they are not provided in detail for the sake of brevity.

[0191] Additionally, for simplicity of explanation and discussion, and so as not to make the embodiments of the present disclosure difficult to understand, well-known power / ground connections to integrated circuit (IC) chips and other components may or may not be shown in the provided drawings. Further, the devices may be shown in block diagram form in order to avoid making the embodiments of the present disclosure difficult to understand, and this also takes into account the fact that details of the implementation of these block diagram devices are highly dependent on the platform on which the embodiments of the present disclosure are to be implemented (i.e., these details should be fully within the understanding of those skilled in the art). In cases where specific details (such as circuits) are set forth to describe exemplary embodiments of the present disclosure, it will be apparent to those skilled in the art that the embodiments of the present disclosure may be practiced without these specific details or with variations of these specific details. Accordingly, these descriptions should be regarded as illustrative rather than restrictive.

[0192] Although the present disclosure has been described in connection with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art based on the foregoing description. For example, other memory architectures (such as dynamic RAM (DRAM)) may be used with the embodiments discussed.

[0193] Embodiments of the present disclosure are intended to cover all such alternatives, modifications, and variations that fall within the broad scope of the appended claims. Accordingly, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of the embodiments of the present disclosure shall be included within the protection scope of the present disclosure.

Claims

1. A method for a recommended delivery strategy, comprising: Determining delivery metrics and at least two key behaviors; Determining a delivery strategy according to the delivery metrics and the at least two key behaviors, the delivery strategy including at least two key nodes corresponding to the at least two key behaviors, and the key nodes being selected from a plurality of candidate nodes according to the delivery metrics; Outputting the delivery strategy.

2. The method according to claim 1, wherein Before determining the delivery metrics and at least two key behaviors, the method further comprises: Displaying a first page; Wherein, the first page includes a flow chart of a plurality of key behavior icons, the flow chart serially connects the plurality of key behavior icons in a predetermined order, and at least one first metric corresponding to the key behavior icon is displayed on one side of the key behavior icon.

3. The method according to claim 2, wherein The first page further includes at least two first options for setting a time period; After displaying the first page, the method further comprises: Responding to a setting instruction received for the at least two first options, and determining a first time period and a second time period; Displaying side by side in the first page a first flow chart corresponding to the first time period and a second flow chart corresponding to the second time period; Wherein, the key behavior icons in the first flow chart and the second flow chart reflect the values of the corresponding first metrics through the area size.

4. The method according to claim 2, wherein Determining at least two key behaviors includes: Responding to a trigger operation on at least two key behavior icons in the flow chart, and determining at least two key behaviors corresponding to the at least two key behavior icons.

5. The method according to claim 2, wherein, After displaying the first page, the method further comprises: Responding to the value of the first metric being greater than a first threshold or less than a second threshold, and highlighting the key behavior icon corresponding to the first metric whose value is greater than the first threshold or less than the second threshold.

6. The method according to claim 1, wherein Determining a delivery strategy according to the delivery metrics and the at least two key behaviors includes: Selecting at least two key nodes corresponding to the at least two key behaviors from a plurality of candidate nodes according to the value of the delivery metrics; Wherein, the value of the delivery metrics is obtained through a clustering algorithm based on historical data.

7. The method according to claim 6, wherein The historical data includes industry historical data and brand historical data; Selecting at least two key nodes corresponding to the at least two key behaviors from a plurality of candidate nodes according to the value of the delivery metrics includes: Responding to the brand historical data not reaching a quantity threshold, and selecting at least two key nodes corresponding to the at least two key behaviors from a plurality of candidate nodes according to the value of the delivery metrics corresponding to each of the candidate nodes calculated by using the industry historical data through a clustering algorithm.

8. The method according to claim 1, wherein The at least two key nodes include at least one of a target delivery method, a delivery method combination including the target delivery method, the number of deliveries and the delivery time interval corresponding to the delivery method combination, a delivery path segment corresponding to the delivery method combination, a complete path including the delivery path segment, a label, and a search term.

9. A method for determining a delivery strategy, comprising: Determining delivery metrics and at least two key behaviors; Determine at least two key nodes corresponding to the at least two key behaviors from multiple candidate nodes according to the delivery metrics and the at least two key behaviors; Determine a delivery strategy according to the at least two key nodes.

10. A device for recommending a delivery strategy, comprising: A first determination module configured to: determine delivery metrics and at least two key behaviors; A second determination module configured to: determine a delivery strategy according to the delivery metrics and the at least two key behaviors, the delivery strategy including at least two key nodes corresponding to the at least two key behaviors, and the key nodes being selected from multiple candidate nodes according to the delivery metrics; An output module configured to: output the delivery strategy.

11. A device for determining a delivery strategy, comprising: A first determination module configured to: determine delivery metrics and at least two key behaviors; A second determination module configured to: determine at least two key nodes corresponding to the at least two key behaviors from multiple candidate nodes according to the delivery metrics and the at least two key behaviors; A third determination module configured to: determine a delivery strategy according to the at least two key nodes.

12. A computer device, comprising one or more processors, a memory; and one or more programs, wherein the one or more programs are stored in the memory and executed by the one or more processors, and the programs include instructions for executing the method according to any one of claims 1-8 or the method according to claim 9.

13. A non-volatile computer-readable storage medium containing a computer program, which when executed by one or more processors, causes the processors to execute the method according to any one of claims 1-8 or the method according to claim 9.

14. A computer program product, comprising computer program instructions, which when run on a computer, cause the computer to execute the method according to any one of claims 1-8 or the method according to claim 9.

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