Advertisement budget control-based delivery method
By conducting in-depth analysis of advertising channels and user groups, combined with real-time data monitoring and multi-indicator evaluation, and dynamically adjusting the budget, the problems of budget mismatch and resource waste in traditional advertising have been solved, thereby improving the efficiency and effectiveness of advertising.
Patent Information
- Application Number
- CN202510871221.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-26
- Publication Date
- 2025-10-31
AI Technical Summary
Traditional advertising budget control methods are insufficient to meet the needs of enterprises for efficient marketing, resulting in budget mismatch and resource waste. Furthermore, they lack dynamic adjustment mechanisms and are unable to cope with market fluctuations.
By comprehensively analyzing advertising channels and user groups, calculating the initial budget allocation ratio, monitoring advertising data in real time, adopting multi-indicator evaluation methods, dynamically adjusting budget allocation, continuously optimizing advertising strategies, and combining market and user changes.
It achieves precise matching of advertising, reduces costs, improves conversion rates and ROI, ensures reasonable use of budget, and adapts to market changes.
Smart Images
Figure CN120875971A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of advertising placement methods, and in particular to a placement method based on advertising budget control. Background Technology
[0002] In today's digital marketing era, advertising has become a crucial means for businesses to promote their products and services, enhance brand awareness, and increase market share. With the rapid development of internet technology, advertising channels have become increasingly diversified, including search engine advertising, social media advertising, and video platform advertising. However, the advertising process faces numerous challenges, among which effective control of the advertising budget is a key issue.
[0003] In the current advertising landscape, traditional budget control methods and placement models have significant shortcomings, making it difficult to meet the needs of businesses for efficient marketing. Experience-based allocation relies on subjective experience to allocate budgets, ignoring channel characteristics and user differences, leading to budget mismatches and wasting significant resources on inefficient channels. While the goal-oriented approach has a logical framework, its goal setting lacks a dynamic adjustment mechanism, making it unable to flexibly adjust budgets in the face of market fluctuations. Summary of the Invention
[0004] In response to the technical problems mentioned in the background art, the present invention provides a method for advertising placement based on advertising budget control.
[0005] The technical solution adopted in this invention is: a method for advertising placement based on advertising budget control, specifically including the following steps:
[0006] Step 1: Determine the total advertising budget B based on the advertising objectives and the company's marketing strategy;
[0007] Step 2: Conduct a comprehensive analysis of the available advertising channels, including the channel's user base, user activity, user age, gender, geographic distribution, and consumption habits.
[0008] Step 3: Calculate the initial budget allocation ratio for each channel. Based on the user characteristics of the advertising channels and the distribution of the target user group, calculate the initial budget allocation ratio for each channel.
[0009] Step 4: During the advertising campaign, monitor advertising data across all channels in real time, including impressions. i Click count C i Click-through rate (CTR) i Conversion rate CR i Cost per click (CPC) i Cost per conversion (CPA) i ;
[0010] Step 5: During the advertising campaign, a multi-indicator comprehensive evaluation method is adopted, combined with real-time monitored advertising data, to dynamically analyze the advertising effectiveness of each channel.
[0011] Step 6: Based on the advertising performance evaluation results, dynamically adjust the advertising budget allocation for each channel;
[0012] Step 7: During the advertising campaign, continuously collect and analyze advertising data, and analyze the campaign performance based on changes in the market environment, changes in user behavior, and budget adjustments.
[0013] In one embodiment, in step 1, historical ROI data or industry benchmarks are used, through formula B, Work backwards to calculate the budget.
[0014] In one embodiment, in step 2, there are n advertising channels in total. For the i-th channel (i = 1, 2, ..., n), its user scale is U. i User activity level is A i ;
[0015] User scale U i This reflects the number of potential audiences for the channel, and user activity level A. i This indicates the user's level of activity on the channel, which is measured by metrics such as average daily usage time and average monthly usage frequency.
[0016] A comprehensive analysis of available advertising channels is conducted, including the channel's user base, user activity level, user age, and gender.
[0017] There are n advertising channels in total. For the i-th channel (i = 1, 2, ..., n);
[0018] Its user base is U i This reflects the number of potential audiences for the channel;
[0019] User activity level is A i The activity level of users on this channel is measured by metrics such as average daily usage time and average monthly usage frequency.
[0020] The target user group is segmented based on user characteristics into different groups. Let there be m user groups in total. For the j-th group (j = 1, 2, ..., m), the number of users on the i-th channel is U. ij .
[0021] In one embodiment, in step 3, a weighting coefficient w is introduced. ij , indicating the importance of the i-th channel to the j-th user group;
[0022] Among them, the weighting coefficient w ij The value range is [0,1]. The larger the value, the more important the channel is to the user group.
[0023] Based on the user characteristics and target user group distribution of advertising channels, a multidimensional data analysis model is used to calculate the initial budget allocation ratio for each channel, and to calculate the initial budget allocation ratio r for the i-th channel. i The formula is:
[0024]
[0025] Among them, molecules The denominator represents the weighted number of users across all user groups for the i-th channel. r represents the weighted total number of users across all channels targeting all user groups, calculated using this formula. i This reflects the relative importance of each channel in meeting the needs of the target user group, thus determining the initial budget allocation ratio. Therefore, the initial budget B for the i-th channel... i for:
[0026] B i =r i B.
[0027] In one embodiment, in step 4,
[0028] Click-through rate (CTR) i The calculation formula is: This formula is used to measure the attractiveness of an advertisement on the i-th channel;
[0029] Conversion rate CR i The calculation formula is: Among them, O i This represents the number of conversions on the i-th channel;
[0030] Cost per click (CPC) i The calculation formula is: Among them, B ic This represents the click budget already spent on the i-th channel;
[0031] Cost per conversion (CPA) i The calculation formula is: Among them, B it This represents the total budget already spent on the i-th channel.
[0032] In one embodiment, step 5 introduces an effectiveness evaluation index E. i :
[0033]
[0034] Among them, CTR i The click-through rate (CR) represents the ad click-through rate of the i-th channel, reflecting the ad's appeal to users; i CPC represents the conversion rate of the i-th channel, reflecting the ability of advertising to guide users to complete their target behavior. i It is the cost per click for the i-th channel, measuring the cost of acquiring traffic for advertising; CPA i Let be the single conversion cost of the i-th channel, reflecting the actual investment in acquiring effective users; coefficients α1, α2, α3, and α4 are the weight parameters of each indicator, with values ranging from [0,1] and satisfying the following conditions: Where α1, α2, α3, and α4 are weighting coefficients, and α1+α2+α3+α4=1.
[0035] In one embodiment, in step 6, the budget adjustment factor β is calculated. i The formula is:
[0036]
[0037] β i This represents the proportion of the i-th channel in the new budget allocation; based on the budget adjustment factor β i Recalculate the costs for each channel.
[0038] Budget B′ i :B′ i =β i B if B′ i >B i Then increase the budget for the i-th channel, with the increased budget coming from other less effective channels.
[0039] Mixing; if B′ i i If the budget for channel i is reduced, the reduced budget will be allocated to other channels that are performing better.
[0040] In one embodiment, step 7 involves adjusting the content and format of the advertisement based on user feedback, and adjusting the timing and frequency of ad placement based on market competition.
[0041] The beneficial effects of this invention are as follows: Compared with existing technologies, this invention lays a reasonable planning foundation for advertising by clearly defining the target audience and total budget, avoiding waste of funds and the risk of overspending. In-depth analysis of channels and user groups, combined with scientific initial budget allocation calculations, achieves precise matching between advertisements and target users, improving the accuracy of ad placement. Real-time monitoring of placement data and the use of multiple indicators to comprehensively evaluate effectiveness enable a comprehensive and timely understanding of advertising performance. Based on the evaluation results, dynamic adjustments to budget allocation and continuous optimization of placement strategies allow advertising to quickly adapt to market and user changes, allocating budgets to efficient channels, reducing costs, and increasing conversion rates and ROI. Attached Figure Description
[0042] Figure 1 This is a flowchart illustrating the present invention; Detailed Implementation
[0043] In the description of this invention, it should be noted that the terms "front", "up", "down", "left", "right", "vertical", "horizontal", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.
[0044] refer to Figure 1 To address the problems existing in the background technology, this application proposes the following technical solution: a method for ad placement based on advertising budget control, specifically including the following steps:
[0045] Step 1: Determine the total advertising budget B based on the advertising objectives and the company's marketing strategy;
[0046] In step 1, determining the total budget B requires comprehensive consideration of factors such as the company's financial situation, market competition, and expected advertising results.
[0047] First, it is necessary to systematically analyze the advertising objectives. Common objective types include:
[0048] Brand building: Enhance brand awareness (e.g., increase the number of target audience members reached), improve brand image (e.g., enhance reputation through emotional marketing), and strengthen brand memorability (e.g., the reach of advertising slogans);
[0049] Sales conversion metrics: Achieving sales growth for specific products (e.g., a 20% increase in quarterly sales) and driving participation in promotional activities (e.g., the number of limited-time discount coupons claimed).
[0050] Traffic growth strategies: Increase daily website visits, boost app downloads and activations, and promote social media follower growth.
[0051] After clarifying the objectives, and in conjunction with the company's medium- and long-term marketing strategy, a tiered budgeting method was used to determine the total budget B:
[0052] Feasibility analysis: Refer to the company's annual marketing budget as a percentage (it is generally recommended to control it at 3%-15% of revenue) and set a budget ceiling based on cash flow situation;
[0053] Competitive benchmarking research: Analyze competitors' advertising spending through third-party data platforms (such as iResearch and QuestMobile) to develop differentiated budget strategies;
[0054] Performance prediction model: Using historical ROI (Return on Investment) data or industry benchmarks, through formula B: Work backwards to determine a reasonable budget.
[0055] For example, a fast-moving consumer goods brand plans to launch a new product and sets a sales target of 100,000 units within 3 months. Referring to the historical product ROI of 1:5 and considering the average monthly investment of competitors of 500,000 yuan, the total budget B is finally determined to be 800,000 yuan.
[0056] In advertising, defining clear objectives and a total budget is a crucial first step, providing direction and a solid foundation for subsequent strategy development. Clear objectives, such as increasing brand awareness or boosting product sales, allow advertisers to focus on core messages and avoid dispersing resources. Determining the total budget by considering the company's financial situation, market competition, and expected results ensures that the budget meets advertising needs while remaining within the company's budget. This avoids situations where an excessively high budget leads to excessive financial pressure, or an insufficient budget negatively impacts advertising effectiveness. Furthermore, scientifically determining the total budget helps companies rationally plan their marketing resources, allocating funds to the most effective areas for achieving goals, laying a solid foundation for precise targeting and efficient conversions, and improving the overall effectiveness of advertising from the outset.
[0057] Step 2: Conduct a comprehensive analysis of the available advertising channels, including the channel's user base, user activity, user age, gender, geographic distribution, and consumption habits.
[0058] In step 2, suppose there are n advertising channels in total. For the i-th channel (i = 1, 2, ..., n), its user scale is U. i User activity level is A i ;
[0059] User scale U i This reflects the number of potential audiences for the channel, and user activity level A. i This indicates the user's level of activity on the channel, which is measured by metrics such as average daily usage time and average monthly usage frequency.
[0060] A comprehensive analysis of available advertising channels is conducted, including the channel's user base, user activity level, user age, and gender.
[0061] There are n advertising channels in total. For the i-th channel (i = 1, 2, ..., n);
[0062] Its user base is U i This reflects the size of the channel's potential audience. For example, short video platforms, with their large user base, often have a high UoS (User ID) ratio. i Value is a high-quality choice for reaching a wide range of people.
[0063] User activity level is A i User activity levels on a platform are measured by metrics such as average daily usage time and average monthly usage frequency. For example, on social media platforms, if a user's average daily usage time exceeds 60 minutes and their average monthly usage frequency reaches 20 times or more, it indicates that the platform's activity level is high. i A higher level means that ads have more exposure opportunities on this channel. • User profiling: By analyzing user age distribution, the proportion of users in different age groups can be clearly identified. For example, education ads are suitable for channels where young students are concentrated; gender distribution can help vertical categories such as beauty and menswear accurately target their audience; geographic distribution data can help local life service ads focus on specific cities or regions; and consumption habits can be identified through indicators such as purchase frequency and spending amount, allowing for the selection of suitable advertising channels for high-priced goods such as luxury goods and electronics.
[0064] The target user group is segmented based on user characteristics, into different groups such as young and fashionable people, middle-aged business people, etc. Let there be m user groups in total. For the j-th group (j = 1, 2, ..., m), the number of its users on the i-th channel is U. ij .
[0065] This step, through a comprehensive analysis of advertising channels and user groups, significantly improves the accuracy and effectiveness of ad placement. A deep understanding of the user base, activity levels, and demographic characteristics (age, gender, region, etc.) across various channels helps advertisers precisely target their audience. For example, targeting trendy product ads to channels frequented by young, fashionable individuals can significantly enhance ad relevance and appeal. Segmenting the target user group and understanding their distribution across different channels avoids wasting advertising resources. This ensures ads reach potential customers precisely, improving ad exposure efficiency and conversion rates, making each ad impression more valuable, enhancing the alignment between ad placement and user needs, and providing strong support for achieving advertising goals.
[0066] Step 3: Calculate the initial budget allocation ratio for each channel. Based on the user characteristics of the advertising channels and the distribution of the target user group, calculate the initial budget allocation ratio for each channel.
[0067] In step 3, a weighting coefficient w is introduced. ij , indicating the importance of the i-th channel to the j-th user group;
[0068] Among them, the weighting coefficient w ij The value of w ranges from [0,1]. The larger the value, the higher the importance of the channel to this user group; the weighting coefficient w ij The determination can be made through a combination of market research, data analysis, and expert evaluation.
[0069] Based on the user characteristics of advertising channels and the distribution of target user groups, a multi-dimensional data analysis model is used to calculate the initial budget allocation ratio for each channel. The specific steps involved in determining the weighting coefficients are as follows: Market Research: Data on target users' preferences for different advertising channels is directly collected through questionnaires, user interviews, etc. For example, for young consumers, the focus can be on researching their usage frequency and ad acceptance on short video platforms, social media, and other channels. Data Analysis: Based on historical advertising data, regression analysis, cluster analysis, and other methods are used to quantify the conversion effect of each channel on different user groups. For example, analyzing e-commerce platform advertising data clarifies the contribution of each channel to new customer acquisition and repeat purchases from existing customers. Expert Evaluation: An evaluation team composed of advertising industry experts and marketing scholars is invited to score the importance of each channel based on industry trends and practical experience. For example, for emerging metaverse advertising channels, experts can evaluate their value to specific user groups from dimensions such as technological maturity and potential user scale. Through the above multi-dimensional and multi-method comprehensive evaluation system, the weighting coefficient w is ensured. ij It can reflect both objective market laws and adapt to dynamically changing user needs. Calculate the initial budget allocation ratio r for the i-th channel. i The formula is:
[0070]
[0071] Among them, molecules The denominator represents the weighted number of users across all user groups for the i-th channel. r represents the weighted total number of users across all channels targeting all user groups, calculated using this formula. i This reflects the relative importance of each channel in meeting the needs of the target user group, thus determining the initial budget allocation ratio. Therefore, the initial budget B for the i-th channel... i for:
[0072] B i =ri B.
[0073] This approach, based on channel and user group analysis, scientifically calculates the initial budget allocation ratio, effectively solving the problem of unreasonable budget allocation. By introducing weighting coefficients to measure the importance of channels to different user groups, the allocation ratio determined after comprehensively considering multiple factors ensures that the budget is tilted towards channels with greater potential and value. This matches advertisers' investment with the ability of each channel to meet the needs of target users, avoiding blind budget allocation. It ensures that limited budget resources are used to the maximum extent, improving budget efficiency and making advertising on different channels more aligned with expected goals. This provides a guarantee for achieving good advertising results and ROI, improving the scientific and rational nature of advertising placement from the perspective of budget allocation.
[0074] Step 4: During the advertising campaign, monitor advertising data across all channels in real time, including impressions. i Click count C i Click-through rate (CTR) i Conversion rate CR i Cost per click (CPC) i Cost per conversion (CPA) i .
[0075] In step 4,
[0076] Click-through rate (CTR) i The calculation formula is:
[0077] This formula measures the attractiveness of an ad on the i-th channel; a higher click-through rate indicates that the ad is more appealing to users.
[0078] Among them O i This represents the number of conversions (such as the number of orders, registrations, etc.) on the i-th channel. Conversion rate reflects the effectiveness of advertising in guiding users to complete a specific action.
[0079] Cost per click (CPC) i The calculation formula is:
[0080] Among them B ic This represents the click budget already spent on the i-th channel. (CPC) i Used to measure the cost of acquiring each click on this channel.
[0081] Cost per conversion (CPA) i The calculation formula is:
[0082] Among them B it This represents the total budget already spent on the i-th channel. (CPA)i This reflects the cost of achieving each conversion on this channel.
[0083] Real-time monitoring of ad delivery data provides advertisers with timely and accurate feedback, a crucial element for precise ad targeting and effective management. By acquiring multi-dimensional data such as impressions, clicks, and click-through rates (CTR) in real time, advertisers can monitor the dynamics of their ads across various channels. This allows for the timely identification of problems during ad delivery; for example, a low CTR on a particular channel may indicate a need to adjust ad content or delivery strategies. This real-time data also provides objective evidence for subsequent evaluation of ad performance and adjustments to budget allocation, helping advertisers quickly respond to market changes and shifts in user behavior, ensuring ad delivery remains at its optimal state and enhancing the flexibility and adaptability of ad delivery.
[0084] Step 5: During the advertising campaign, a multi-indicator comprehensive evaluation method is adopted, combined with real-time monitored advertising data, to dynamically analyze the advertising effectiveness of each channel.
[0085] In step 5, the effect evaluation index E is introduced. i :
[0086]
[0087] Among them, CTR i The click-through rate (CR) represents the ad click-through rate of the i-th channel, reflecting the ad's appeal to users; i CPC represents the conversion rate of the i-th channel, reflecting the ability of advertising to guide users to complete their target behavior. i It is the cost per click for the i-th channel, measuring the cost of acquiring traffic for advertising; CPA i Let be the single conversion cost of the i-th channel, reflecting the actual investment in acquiring effective users; coefficients α1, α2, α3, and α4 are the weight parameters of each indicator, with values ranging from [0,1] and satisfying the following conditions: It can be flexibly adjusted according to the advertising objectives, such as focusing on CTR for brand promotion. i The conversion rate will increase the CR. i Weighting is used to achieve accurate quantitative evaluation of the effectiveness of advertising channels.
[0088] Here, α1, α2, α3, and α4 are weighting coefficients, and α1 + α2 + α3 + α4 = 1. These weighting coefficients are set according to different advertising objectives. For example, when the advertising objective is to increase brand awareness, the click-through rate (CTR) can be appropriately increased. i The weight α1; when the goal is to increase product sales, it can improve the conversion rate CR. i Cost per conversion (CPA) iThe relevant weights are α2 and α4. E is calculated using this formula. i It can comprehensively reflect the overall performance of each channel in terms of click-through rate, conversion rate, cost, etc., thereby evaluating the effectiveness of advertising.
[0089] The method employs a multi-indicator comprehensive evaluation approach to comprehensively and accurately measure the effectiveness of advertising campaigns, overcoming the limitations of single-indicator evaluation. By comprehensively considering multiple factors such as click-through rate, conversion rate, and cost, and setting corresponding weights based on different advertising campaign objectives, it can more realistically reflect the actual effectiveness of advertising campaigns across various channels.
[0090] Step 6: Based on the advertising performance evaluation results, dynamically adjust the advertising budget allocation for each channel;
[0091] In step 6, the budget adjustment factor β is calculated. i The formula is:
[0092]
[0093] β i This represents the proportion of the i-th channel in the new budget allocation. Based on the budget adjustment factor β... i Recalculate the budget B′ for each channel. i :B′ i =β i B if B′ i >B i If B′, then increase the budget for the i-th channel, and the increased budget should be allocated from other less effective channels; i i If the budget for channel i is reduced, the reduced budget will be allocated to other channels that are performing better.
[0094] Among its features, the dynamic adjustment of budget allocation based on advertising performance evaluation results endows advertising with strong dynamic adaptability. By calculating budget adjustment coefficients, the budget is tilted towards better-performing channels, reducing investment in inefficient channels, thus achieving optimal allocation of budget resources. In the face of constantly changing market environments and user behavior, this dynamic adjustment mechanism allows advertisers to adjust their strategies in a timely manner, ensuring that advertising always aligns with market demands.
[0095] Step 7: During the advertising campaign, continuously collect and analyze advertising data, and analyze the campaign performance based on changes in the market environment, changes in user behavior, and adjustments to the budget.
[0096] In step 7, the content and format of advertisements are adjusted based on user feedback, and the timing and frequency of ad placement are adjusted according to market competition to maximize advertising effectiveness and optimize budget utilization. During the advertising campaign, a real-time data monitoring system needs to be built to achieve dynamic optimization through multi-dimensional indicator analysis. Specifically, big data analytics tools are used to track core data such as click-through rate (CTR), conversion rate (CVR), and average cost per click (CPC) in real time. This data is then combined with user profile tags (such as age, region, and consumption preferences) and market sentiment data to establish an evaluation model for campaign effectiveness.
[0097] In summary, this embodiment lays a solid foundation for rational advertising planning by clearly defining the campaign objectives and total budget, thus avoiding wasted funds and the risk of overspending. In-depth analysis of channels and user groups, combined with scientific initial budget allocation calculations, achieves precise matching between advertisements and target users, improving campaign accuracy. Real-time monitoring of campaign data and the use of multiple indicators to comprehensively evaluate performance allow for a complete and timely understanding of advertising performance. Dynamic adjustments to budget allocation and continuous optimization of campaign strategies based on evaluation results enable advertising to quickly adapt to market and user changes, allocating budgets to efficient channels, reducing costs, and increasing conversion rates and ROI.
[0098] Although embodiments of the invention have been shown and described, the scope of the invention will be defined by the appended claims and their equivalents by those skilled in the art.
Claims
1. A method for ad placement based on advertising budget control, characterized in that, Specifically, the following steps are included: Step 1: Determine the total advertising budget B based on the advertising objectives and the company's marketing strategy; Step 2: Conduct a comprehensive analysis of the available advertising channels, including the channel's user base, user activity, user age, gender, geographic distribution, and consumption habits. Step 3: Calculate the initial budget allocation ratio for each channel. Based on the user characteristics of the advertising channels and the distribution of the target user group, calculate the initial budget allocation ratio for each channel. Step 4: During the advertising campaign, monitor advertising data across all channels in real time, including impressions. i Click count C i Click-through rate (CTR) i Conversion rate CR i Cost per click (CPC) i Cost per conversion (CPA) i ; Step 5: During the advertising campaign, a multi-indicator comprehensive evaluation method is adopted, combined with real-time monitored advertising data, to dynamically analyze the advertising effectiveness of each channel. Step 6: Based on the advertising performance evaluation results, dynamically adjust the advertising budget allocation for each channel; Step 7: During the advertising campaign, continuously collect and analyze advertising data, and analyze the campaign performance based on changes in the market environment, changes in user behavior, and budget adjustments.
2. The advertising budget control-based placement method according to claim 1, characterized in that, In step 1, using historical ROI data or industry benchmarks, through formula B, Work backwards to calculate the budget.
3. The advertising budget control-based placement method according to claim 2, characterized in that, In step 2, suppose there are n advertising channels in total. For the i-th channel (i = 1, 2, ..., n), its user scale is U. i User activity level is A i ; User scale U i This reflects the number of potential audiences for the channel, and user activity level A. i This indicates the user's level of activity on the channel, which is measured by metrics such as average daily usage time and average monthly usage frequency. A comprehensive analysis of available advertising channels is conducted, including the channel's user base, user activity level, user age, and gender. There are n advertising channels in total. For the i-th channel (i = 1, 2, ..., n); Its user base is U i This reflects the number of potential audiences for the channel; User activity level is A i The activity level of users on this channel is measured by metrics such as average daily usage time and average monthly usage frequency. The target user group is segmented based on user characteristics into different groups. Let there be m user groups in total. For the j-th group (j = 1, 2, ..., m), the number of users on the i-th channel is U. ij .
4. The advertising budget control-based placement method according to claim 3, characterized in that, In step 3, a weighting coefficient w is introduced. ij , indicating the importance of the i-th channel to the j-th user group; Among them, the weighting coefficient w ij The value range is [0,1]. The larger the value, the more important the channel is to the user group. Based on the user characteristics and target user group distribution of advertising channels, a multidimensional data analysis model is used to calculate the initial budget allocation ratio for each channel, and to calculate the initial budget allocation ratio r for the i-th channel. i The formula is: Among them, molecules The denominator represents the weighted number of users across all user groups for the i-th channel. r represents the weighted total number of users across all channels targeting all user groups, calculated using this formula. i This reflects the relative importance of each channel in meeting the needs of the target user group, thus determining the initial budget allocation ratio. Therefore, the initial budget B for the i-th channel... i for: B i =r i B。 5. The advertising budget control-based placement method according to claim 4, characterized in that, In step 4, Click-through rate (CTR) i The calculation formula is: This formula is used to measure the attractiveness of an advertisement on the i-th channel; Conversion rate CR i The calculation formula is: Among them, O i This represents the number of conversions on the i-th channel; Cost per click (CPC) i The calculation formula is: Among them, B ic This represents the click budget already spent on the i-th channel; Cost per conversion (CPA) i The calculation formula is: Among them, B it This represents the total budget already spent on the i-th channel.
6. The advertising placement method based on advertising budget control according to claim 5, characterized in that, In step 5, the effect evaluation index E is introduced. i : Among them, CTP i The click-through rate (CR) represents the ad click-through rate of the i-th channel, reflecting the ad's appeal to users; i CPC represents the conversion rate of the i-th channel, reflecting the ability of advertising to guide users to complete their target behavior. i It is the cost per click for the i-th channel, measuring the cost of acquiring traffic for advertising; CPA i Let be the single conversion cost of the i-th channel, reflecting the actual investment in acquiring effective users; coefficients α1, α2, α3, and α4 are the weight parameters of each indicator, with values ranging from [0,1] and satisfying the following conditions: Where α1, α2, α3, and α4 are weighting coefficients, and α1+α2+α3+α4=1.
7. The advertising budget control-based placement method according to claim 6, characterized in that, In step 6, the budget adjustment factor β is calculated. i The formula is: β i This represents the proportion of the i-th channel in the new budget allocation; Based on the budget adjustment factor β i Recalculate the costs for each channel. Budget B′ i :B′ i =β i B if B′ i >B i Then increase the budget for the i-th channel, with the increased budget coming from other less effective channels. Mixing; if B′ i i If the budget for channel i is reduced, the reduced budget will be allocated to other channels that are performing better. 8. The advertising budget control-based placement method according to claim 7, characterized in that, In step 7, the content and format of the advertisements are adjusted based on user feedback, and the timing and frequency of ad placement are adjusted based on market competition.