Intelligent marketing management method and system based on AI artificial intelligence

Abstract

The invention discloses a smart marketing management method and system based on AI artificial intelligence. The smart marketing management system comprises a data collection and preprocessing module, a market dynamic prediction module, a competing product analysis module, an advertisement strategy generation module and a strategy execution and feedback module. The intelligent marketing management system collects related data of marketing advertisements on the market, collects market dynamic data, and monitors and updates advertisement strategies and market performance of competitive products in real time; and according to the competitive product analysis result and the real-time advertisement effect data, an advertisement putting strategy is automatically adjusted through an AI artificial intelligence technology. Through introduction of an AI technology, market and competitive product data are analyzed in real time, an advertisement strategy is automatically adjusted, advertisement content and putting channels are optimized, and advertisement budget and time frequency are dynamically adjusted, so that high intelligence and automation are achieved in advertisement decision making, reasonable configuration of marketing resources is achieved through a multi-dimensional optimization strategy, and the marketing efficiency is improved. And the overall effect and the return on investment of the advertisement are obviously improved.

Description

Technical Field

[0001] The present invention relates to the technical field related to smart marketing, and in particular to a smart marketing management method and system based on AI artificial intelligence. Background Art

[0002] In the field of smart marketing, as market competition intensifies, advertisers' demand for precise smart marketing is growing. Existing advertising delivery functions in marketing usually rely on static historical data (historical experience and market data), and it is difficult to quickly adjust advertising strategies according to market dynamics. The multi-dimensional optimization capabilities are insufficient, and there is a lack of real-time response to competitor dynamics and multi-dimensional comprehensive optimization capabilities. This approach often leads to poor advertising results and a decline in the input-output ratio. In addition, it usually only focuses on a single aspect such as budget allocation or advertising content selection, resulting in limited effects of advertising strategy adjustments. At the same time, due to the lack of real-time market competition analysis and dynamic adjustment capabilities, traditional advertising systems are difficult to cope with the dynamic strategy changes of competitors and cannot respond quickly to real-time changes in the market, resulting in missed marketing opportunities and a loss of competitive advantage. Therefore, it needs to be improved. Summary of the invention

[0003] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0004] Therefore, in order to solve the above technical problems, the present invention provides the following technical solutions: an intelligent marketing management method based on AI artificial intelligence, comprising the following specific steps:

[0005] S1: Collect relevant data on marketing advertisements in the market, collect market dynamic data, and monitor and update the advertising strategies and market performance of competitors in real time;

[0006] S2: Based on the results of competitive product analysis and real-time advertising performance data, AI technology is used to automatically adjust advertising strategies, including advertising content selection, advertising channel allocation, dynamic budget adjustment, and optimization of advertising time and frequency.

[0007] As a preferred solution of the AI-based smart marketing management method described in the present invention, it uses web crawler technology and API interface to collect product-related advertising data on the market in real time, including information such as advertising content, delivery channels, delivery time, audience positioning, etc.; the data sources of advertising data include social media platforms, search engine advertising, email advertising, etc.; market dynamics data include external data such as market trends, consumer behavior, and hot events.

[0008] As a preferred solution of the AI-based intelligent marketing management method of the present invention, the advertising content selection strategy is based on a comprehensive analysis of the market popularity and advertising effect of competing advertisements, and is calculated by the following formula:

[0009]

[0010] Among them, A i (t): market popularity of competitor advertising content; S i (t): the degree of innovation and differentiation of advertising content; W i (t): The applicability of the current advertising content in the current market environment; R i (t): the responsiveness of competitor advertisements to the market; α i , β i : Adjust the influence of market popularity and competitor response on the selection of advertising content;

[0011] Formula range: The formula range represents the strategic intensity of optimizing advertising content selection, with lower to higher values ​​representing changes in content innovation and market fit.

[0012] As a preferred solution of the AI-based intelligent marketing management method described in the present invention, the allocation strategy of advertising delivery channels is based on the market potential, advertising effect and delivery saturation of each advertising channel, and is calculated by the following formula:

[0013]

[0014] In the above formula, P k (t): the proportion of advertising in the kth channel at time t; L j (t): market potential of the jth advertising channel; E j (t): advertising effect of the jth channel; D j (t): the saturation of the channel, reflecting the intensity of channel competition; γ j , δ j : To adjust the parameters, we can control the impact of the market potential and saturation of advertising channels on the advertising allocation strategy;

[0015] Formula value range: The value range of this formula is [0,1], which represents the allocation weight of each advertising channel.

[0016] As a preferred solution of the AI-based intelligent marketing management method described in the present invention, the dynamic adjustment strategy of the budget is based on the feedback of the competitor's budget and market performance, and the specific calculation formula is as follows:

[0017]

[0018] B(t): the advertising budget adjustment value at time t; n (t): budget share of competitor advertising, changing over time; V n (t): market performance of competing product advertisements; F n (t): feedback on the effectiveness of the current advertisement; Q n (t): sensitivity of market response to budget; λ n , μ n : Adjust parameters to control the impact of competitor market performance and market response on budget adjustment;

[0019] Formula value range: The formula value range represents the quantitative value of the budget adjustment, and the range is the adjustment range of the baseline budget.

[0020] As a preferred solution of the AI-based intelligent marketing management method described in the present invention, the strategy for adjusting the frequency and time of advertising is calculated by analyzing the advertising time of competing products and market reactions. The specific calculation formula is as follows:

[0021]

[0022] In the above formula, T(f) is the adjustment strategy of advertising delivery time and frequency, which changes with the frequency f; H k (f) The performance of competing ads at frequency f; ω k G: Frequency factor for adjusting the advertising time; k (f): The sensitivity of the market response to the frequency of competitor ads; Z(f): Normalization factor, used to ensure that the total delivery time and frequency are within a reasonable range; v k : Adjust the impact of competitive market response on frequency;

[0023] Formula value range: This formula value range represents the frequency of ad delivery within a certain time period, and a higher value means a more frequent delivery.

[0024] As a preferred solution of the AI-based intelligent marketing management method described in the present invention, the current advertising strategy is analyzed to determine whether the advertising delivery strategy needs to be adjusted. The specific calculation formula is as follows:

[0025]

[0026] In the above formula: L i (t): market potential of advertising channels; E j (t): advertising effect of the channel; D j (t): channel saturation, reflecting the intensity of competition; γ j , δ j: Weight parameters for adjusting the allocation ratio of market potential and channel saturation;

[0027] Formula range: S(t) is a decision function that measures whether the current advertising strategy needs to be adjusted; the larger the value, the greater the possibility that the current strategy needs to be adjusted.

[0028] As a preferred solution of the intelligent marketing management method based on AI artificial intelligence described in the present invention, wherein: θ is set as the adjustment threshold of the advertising strategy, then:

[0029] When S(t)>θ, the effect of the current advertising strategy is in line with expectations, so the existing strategy is maintained without adjustment;

[0030] When S(t)≤θ, the effect of the current advertising strategy is not good, and it is necessary to adjust the strategy according to market feedback to generate a multi-objective optimized advertising strategy; among which the optimization goals include advertising content selection, advertising budget, advertising delivery channels, and advertising delivery frequency and time.

[0031] As a preferred solution of the intelligent marketing management method based on AI artificial intelligence described in the present invention, when S(t)≤θ, the optimization method of the advertising delivery strategy includes the following specific steps:

[0032] S21: Optimize the selection strategy of advertising content: Start the optimization function of advertising content, re-evaluate the advertising content according to market popularity, competitive product advertising analysis, consumer preferences and other information; use formula C(t) to re-select new advertising content combinations so that the advertisements can better respond to market demand and consumer behavior; the direction of content adjustment may include: changing advertising materials, highlighting specific product features, adjusting advertising copy, etc.;

[0033] S22: Dynamically adjust the advertising distribution ratio in each channel: Analyze the market potential and effect of different advertising channels (for example: social media, search engines, video ads, etc.); k (t) According to the advertising effect and saturation of each channel, reallocate advertising budget, allocate more resources to channels with good effects, and reduce resource investment in inefficient channels to ensure the maximum dissemination effect of advertising;

[0034] S23: Real-time adjustment of advertising budget: The advertising budget is adjusted dynamically according to the competitor's advertising budget and market feedback through formula B(t); the system will re-evaluate the budget allocation strategy and increase or decrease the overall advertising expenditure; the budget allocation can be adjusted according to the market performance of different competitors; for example, if a competitor's advertising in the market invests a large amount of budget in a certain period of time, the advertising budget for that period can be increased accordingly to enhance market competitiveness;

[0035] S24: Analyze the time of competitor ads and market response, and dynamically adjust the frequency and time of ads: The system analyzes the frequency of competitor ads and market response through formula T(f) to determine the optimal time period and frequency of ads. The system adjusts the time and frequency of ads according to the market response speed of competitor ads. For example, if the market response is relatively positive during a certain time period, the system increases ads during this time period.

[0036] S25: After the advertisement is launched, the system continuously monitors market feedback and collects relevant data (such as click-through rate, conversion rate, market share changes, etc.); based on market changes and competitive product dynamics, the system can automatically determine whether the advertising strategy needs to be adjusted again; the adjustment process continues to iterate until S(t)>θ and the advertising effect is stable.

[0037] The present invention also provides the above-mentioned AI-based smart marketing management system, which is characterized in that: the above-mentioned smart marketing management method is implemented based on the system, and the system includes a data collection and preprocessing module, a market dynamics prediction module, a competitive product analysis module, an advertising strategy generation module and a strategy execution and feedback module; the multi-objective optimal advertising delivery strategy generated in the advertising strategy generation module includes: determining the innovation and differentiation of its own advertising content through competitive product advertising content analysis and market feedback; selecting and adjusting advertising delivery channels such as social media, television, outdoor advertising, etc. based on market data; dynamically adjusting the advertising budget according to market feedback and competitive product budget changes to optimize the input-output ratio; optimizing the delivery time and frequency of advertising according to competitive product delivery strategies and market reactions.

[0038] Beneficial effects of the present invention:

[0039] 1. The present invention uses AI technology to automatically monitor and adjust advertising strategies, thereby significantly improving the efficiency and accuracy of marketing decisions. Compared with traditional advertising methods that rely on manual analysis and adjustment, the present invention reduces delays and errors in human participation, and can respond quickly, especially in complex and changing market environments.

[0040] 2. By collecting the advertising strategies and market performance of competitors, the present invention can analyze the actions of competitors in real time and adjust its own advertising strategy accordingly, so that the adjustment of advertising strategy is no longer a passive reaction, but an active adjustment based on the market competition situation, reflecting the in-depth application of AI in advertising management. This real-time function effectively improves the competitiveness of advertising strategies and ensures that advertising delivery always remains in the optimal state.

[0041] 3. The present invention optimizes the advertising content, channels, budget, time, etc. in the advertising strategy of smart marketing in multiple dimensions, integrates these strategy variables through AI technology, takes mathematical models and optimization algorithms as the core, and obtains specific data that determines whether the advertising delivery strategy should be adjusted through comprehensive calculation of these variables. Compared with the technical defects of the prior art that often only focuses on the optimization of a single dimension of advertising (such as budget allocation or time scheduling), the present invention breaks the limitations of the prior art by comprehensively considering multi-dimensional factors, making the advertising strategy more comprehensive and efficient.

[0042] 4. The present invention can adjust elements such as advertising content and channels according to market changes, ensuring that advertising strategies are flexibly adjusted as the market changes, thereby avoiding the market failure problem caused by fixed advertising strategies in the prior art. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0044] Figure 1 This is a workflow diagram of the smart marketing management method of the present invention.

[0045] Figure 2 This is the overall architecture diagram of the smart marketing management system of the present invention. DETAILED DESCRIPTION

[0046] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0047] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0048] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0049] Example 1

[0050] Reference Figures 1-2, which is the first embodiment of the present invention, provides an AI-based intelligent marketing management system, which includes a data collection and preprocessing module, a market dynamics prediction module, a competitive product analysis module, an advertising strategy generation module and a strategy execution and feedback module; the multi-target optimal advertising delivery strategy generated in the advertising strategy generation module includes: determining the innovation and differentiation of its own advertising content through competitive product advertising content analysis and market feedback; selecting and adjusting advertising delivery channels such as social media, television, outdoor advertising, etc. based on market data; dynamically adjusting the advertising budget according to market feedback and competitive product budget changes to optimize the input-output ratio; optimizing the delivery time and frequency of advertising according to competitive product delivery strategies and market reactions.

[0051] The present invention also provides a smart marketing management method based on the above-mentioned smart marketing management system, comprising the following specific steps:

[0052] S1: Collect relevant data on marketing advertisements in the market, collect market dynamic data, and monitor and update the advertising strategies and market performance of competitors in real time;

[0053] Use web crawler technology and API interfaces to collect real-time advertising data related to products on the market, including information such as advertising content, delivery channels, delivery time, and audience positioning; data sources for advertising data include social media platforms, search engine advertising, email advertising, etc.; market dynamics data include external data such as market trends, consumer behavior, and hot events.

[0054] S2: Based on competitive product analysis results and real-time advertising performance data, AI technology is used to automatically adjust advertising delivery strategies, including advertising content selection, advertising channel allocation, dynamic budget adjustment, and optimization of advertising delivery time and frequency;

[0055] The details are as follows:

[0056] The advertising content selection strategy is based on a comprehensive analysis of the market popularity and advertising effectiveness of competing products, and is calculated using the following formula:

[0057]

[0058] Among them, A i (t): market popularity of competitor advertising content; S i (t): the degree of innovation and differentiation of advertising content; W i (t): The applicability of the current advertising content in the current market environment; R i (t): the responsiveness of competitor advertisements to the market; α i , β i : Adjust the influence of market popularity and competitor response on the selection of advertising content;

[0059] Formula Range: The range of this formula represents the strategic strength of optimizing the selection of advertising content, with lower values ​​to higher values ​​representing changes in content innovation and market fit;

[0060] The allocation strategy of advertising channels is based on the market potential, advertising effect and saturation of each advertising channel, and is calculated using the following formula:

[0061]

[0062] In the above formula, P k (t): the proportion of advertising in the kth channel at time t; L j (t): market potential of the jth advertising channel; E j (t): advertising effect of the jth channel; D j (t): the saturation of the channel, reflecting the intensity of channel competition; γ j , δ j : To adjust the parameters, we can control the impact of the market potential and saturation of advertising channels on the advertising allocation strategy;

[0063] Formula value range: The value range of this formula is [0,1], which represents the allocation weight of each advertising channel.

[0064] The dynamic adjustment strategy of the budget is based on the feedback of competitor budgets and market performance. The specific calculation formula is as follows:

[0065]

[0066] B(t): the advertising budget adjustment value at time t; n (t): budget share of competitor advertising, changing over time; V n (t): market performance of competing product advertisements; F n (t): feedback on the effectiveness of the current advertisement; Q n (t): sensitivity of market response to budget; λ n , μ n : Adjust parameters to control the impact of competitor market performance and market response on budget adjustment;

[0067] Formula value range: This formula value range represents the quantitative value of the budget adjustment, and the range is the adjustment range of the baseline budget;

[0068] The strategy for adjusting the frequency and timing of advertising is based on the analysis of the timing of competing advertising and market response. The specific calculation formula is as follows:

[0069]

[0070] In the above formula, T(f) is the adjustment strategy of advertising delivery time and frequency, which changes with the frequency f; H k (f) The performance of competing ads at frequency f; ω k G: Frequency factor for adjusting the advertising time; k (f): The sensitivity of the market response to the frequency of competitor ads; Z(f): Normalization factor, used to ensure that the total delivery time and frequency are within a reasonable range; v k : Adjust the impact of competitive market response on frequency;

[0071] Formula value range: This formula value range represents the frequency of advertisement delivery within a certain time period, and a higher value means a higher delivery frequency;

[0072] Analyze the current advertising strategy to determine whether it is necessary to adjust the advertising strategy. The specific calculation formula is as follows:

[0073]

[0074] In the above formula: L i (t): market potential of advertising channels; E j (t): advertising effect of the channel; D j (t): channel saturation, reflecting the intensity of competition; γ j , δ j : Weight parameters for adjusting the allocation ratio of market potential and channel saturation;

[0075] Formula range: S(t) is a decision function that measures whether the current advertising strategy needs to be adjusted. The larger the value, the greater the possibility that the current strategy needs to be adjusted.

[0076] Set θ as the adjustment threshold of the advertising strategy, then:

[0077] When S(t)>θ, the effect of the current advertising strategy is in line with expectations, so the existing strategy is maintained without adjustment;

[0078] When S(t)≤θ, the effect of the current advertising strategy is not good, and it is necessary to adjust the strategy according to market feedback to generate a multi-objective optimized advertising strategy; the optimization objectives include advertising content selection, advertising budget, advertising delivery channels, and advertising delivery frequency and time; the optimization method of the advertising delivery strategy includes the following specific steps:

[0079] S21: Optimize the selection strategy of advertising content: Start the optimization function of advertising content, re-evaluate the advertising content according to market popularity, competitive product advertising analysis, consumer preferences and other information; use formula C(t) to re-select new advertising content combinations so that the advertisements can better respond to market demand and consumer behavior; the direction of content adjustment may include: changing advertising materials, highlighting specific product features, adjusting advertising copy, etc.;

[0080] S22: Dynamically adjust the advertising distribution ratio in each channel: Analyze the market potential and effect of different advertising channels (for example: social media, search engines, video ads, etc.); k (t) According to the advertising effect and saturation of each channel, reallocate advertising budget, allocate more resources to channels with good effects, and reduce resource investment in inefficient channels to ensure the maximum dissemination effect of advertising;

[0081] S23: Real-time adjustment of advertising budget: The advertising budget is adjusted dynamically according to the competitor's advertising budget and market feedback through formula B(t); the system will re-evaluate the budget allocation strategy and increase or decrease the overall advertising expenditure; the budget allocation can be adjusted according to the market performance of different competitors; for example, if a competitor's advertising in the market invests a large amount of budget in a certain period of time, the advertising budget for that period can be increased accordingly to enhance market competitiveness;

[0082] S24: Analyze the time of competitor ads and market response, and dynamically adjust the frequency and time of ads: Through formula T(f), the system analyzes the frequency of competitor ads and market response, and determines the optimal time period and frequency of ads; according to the market response speed of competitor ads, the system adjusts the time and frequency of ads. For example, if the market response is relatively positive in a certain time period, increase the number of ads during this time period;

[0083] S25: After the advertisement is launched, the system continuously monitors market feedback and collects relevant data (such as click-through rate, conversion rate, market share changes, etc.); according to market changes and competitive product dynamics, the system can automatically determine whether the advertising strategy needs to be adjusted again. The adjustment process continues to iterate until S(t)>θ and the advertising effect is stable.

[0084] The specific application examples of the above-mentioned intelligent marketing management system and method are as follows:

[0085] An online retail platform launched a new product and began to advertise it on multiple channels (such as Facebook ads, Google search ads, YouTube video ads, etc.);

[0086] The system sets an initial threshold θ = 0.7, based on the average click-through rate and conversion rate of past advertising;

[0087] Real-time monitoring and advertising content optimization:

[0088] After the ad went online, the system monitored market data through the AI ​​algorithm and found that the click-through rate and conversion rate of YouTube ads gradually decreased, resulting in S(t) = 0.65, which is lower than the threshold θ;

[0089] The system automatically triggered the advertising content optimization process, re-analyzed consumer preferences, and found that the product display time in the short video ads was too long, which reduced consumer interest; therefore, the advertising content was adjusted to a shorter and more attractive product demonstration video.

[0090] Channel allocation adjustment:

[0091] By analyzing the advertising effects of different channels, the system found that the click-through rate and conversion rate of Facebook ads were significantly higher than those of other channels (S(t) = 0.8). Therefore, it decided to increase the budget for the Facebook channel and reduce the expenditure on Google search ads.

[0092] According to the formula P k (t) After calculation, the channel allocation was adjusted as follows: The budget ratio of Facebook advertising was increased by 20% to ensure that resources were concentrated on efficient channels.

[0093] Dynamic budget adjustment:

[0094] When monitoring competitor ads, the system detected that the main competitor increased its advertising budget during a specific period. In order to maintain market competitiveness, the system decided to increase the advertising budget during the corresponding period to ensure that it does not fall behind competitors;

[0095] After calculation according to formula B(t), the advertising budget strategy is adjusted to: increase the overall budget by 10%.

[0096] Adjustment of advertising frequency and timing:

[0097] By analyzing the market reaction and the release time of competing products, the system finds that the advertising effect is best during the evening period of 21:00-23:00. According to the calculation of formula T(f), the system finds the best combination of advertising frequency and time to ensure the best exposure effect of the advertisement. The specific adjustment strategy of this embodiment is to increase the advertising frequency during this period and reduce the advertising investment in inefficient periods (such as mornings).

[0098] Final result:

[0099] The effect of the adjusted advertising strategy is significantly improved. By recalculating the value of S(t), the system detects that S(t)=0.75, which exceeds the threshold θ. The advertising strategy enters a stable period. The system continuously monitors market performance to ensure continuous optimization of advertising effects.

[0100] The present invention uses AI technology to analyze market and competitive product data in real time, automatically adjust advertising strategies, optimize advertising content and delivery channels, and dynamically adjust advertising budgets and time frequencies, thereby improving advertising effectiveness and return on investment. The present invention is not only highly intelligent and automated in advertising decision-making, but also achieves a reasonable allocation of marketing resources through multi-dimensional optimization strategies, significantly improving the overall effect of advertising delivery.

[0101] Example 2

[0102] This is the second embodiment of the present invention. This embodiment is different from the first embodiment in that in order to verify its beneficial effects, experimental comparison data between the present invention and the prior art are provided.

[0103] This embodiment simulates the advertising strategies and market performance data of two existing competing products on the market. The data of competing products A and B cover the marketing activities of the past 6 months, including the frequency of advertising, content selection, delivery channels, budgets and their corresponding market performance (such as exposure rate, click-through rate, conversion rate, etc.); in addition, through market research and analysis tools, market dynamics data on the simulated market are collected to monitor changes in competing product advertising strategies and fluctuations in market performance in real time.

[0104] Using an AI-based intelligent marketing management system, the system integrates a market data monitoring module, a competitive product strategy analysis module, and an advertising strategy dynamic adjustment module. The system calculates the optimal combination of advertising strategies based on the collected real-time advertising effect data by automatically adjusting the advertising content selection, the proportion of advertising channels, dynamically adjusting the advertising budget, and optimizing the advertising delivery time and frequency.

[0105] The relevant information of the advertising strategy generated according to the above steps is compared with the advertising strategy generated by the prior art, and the specific situation is shown in the following table.

[0106]

[0107] According to the data in the above table, the present invention is significantly superior to the prior art in terms of optimization strategy for advertising placement. By comparing the data of competitor A and competitor B, it can be found that the present invention has significantly improved both exposure rate and conversion rate. For example, in June, the exposure rate of the present invention reached 70%, while that of competitor A was only 55%, and that of competitor B was 50%. This shows that by intelligently and dynamically adjusting the advertising strategy, the present invention can effectively improve the exposure effect of advertising.

[0108] At the same time, the present invention also has advantages in budget optimization and the adjustment of the frequency of delivery time. For example, as the advertising effect gradually improves, the advertising budget has been reasonably allocated and utilized. While increasing from 1 million to 1.25 million, the conversion rate has increased from 2.5% to 4.0%, and the input-output ratio has been significantly optimized. In contrast, the budget investment and effect of competing products have not shown such a significant improvement.

[0109] Through the AI ​​intelligent advertising management system of the present invention, it is possible to respond to market changes and dynamically adjust competing product strategies in real time, thereby optimizing the overall performance of advertising.

[0110] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An intelligent marketing management method based on AI artificial intelligence, characterized by: The specific steps include: S1: Collect relevant data on marketing advertisements in the market, collect market dynamic data, and monitor and update the advertising strategies and market performance of competitors in real time; S2: Based on the results of competitive product analysis and real-time advertising performance data, AI technology is used to automatically adjust advertising strategies, including advertising content selection, advertising channel allocation, dynamic budget adjustment, and optimization of advertising time and frequency.

2. The AI-based intelligent marketing management method according to claim 1, characterized in that: Use web crawler technology and API interfaces to collect real-time advertising data related to products on the market, including advertising content, delivery channels, delivery time, and audience targeting information; data sources for advertising data include social media platforms, search engine advertising, and email advertising; market dynamics data include external data such as market trends, consumer behavior, and hot events.

3. The AI-based intelligent marketing management method according to claim 2, characterized in that: The advertising content selection strategy is based on a comprehensive analysis of the market popularity and advertising effectiveness of competing products, and is calculated using the following formula: Among them, C(t): the adaptability of advertising content under different market conditions, which affects the creativity and expression of advertising; A i (t): market popularity of competitor advertising content; S i (t): the degree of innovation and differentiation of advertising content; W i (t): The applicability of the current advertising content in the current market environment; R i (t): the responsiveness of competitor advertisements to the market; α i , β i : Adjust the influence of market popularity and competitor response on the selection of advertising content; Formula range: The formula range represents the strategic intensity of optimizing advertising content selection, with lower to higher values ​​representing changes in content innovation and market fit.

4. The AI-based intelligent marketing management method according to claim 3, characterized in that: The allocation strategy of advertising channels is based on the market potential, advertising effect and saturation of each advertising channel, and is calculated using the following formula: In the above formula, P k (t): the proportion of advertising in the kth channel at time t; L j (t): market potential of the jth advertising channel; E j (t): advertising effect of the jth channel; D j (t): the saturation of the channel, reflecting the intensity of channel competition; γ j ,δ j : To adjust the parameters, we can control the impact of the market potential and saturation of advertising channels on the advertising allocation strategy; Formula value range: The value range of this formula is [0,1], which represents the allocation weight of each advertising channel.

5. The AI-based intelligent marketing management method according to claim 4, characterized in that: The dynamic adjustment strategy of the budget is based on the feedback of competitor budgets and market performance. The specific calculation formula is as follows: B(t): the advertising budget adjustment value at time t; n (t): budget share of competitor advertising, changing over time; V n (t): market performance of competing product advertisements; F n (t): feedback on the effectiveness of the current advertisement; Q n (t): sensitivity of market response to budget; λ n , μ n : Adjust parameters to control the impact of competitor market performance and market response on budget adjustment; Formula value range: The formula value range represents the quantitative value of the budget adjustment, and the range is the adjustment range of the baseline budget.

6. The AI-based intelligent marketing management method according to claim 5, characterized in that: The strategy for adjusting the frequency and timing of advertising is based on the analysis of the timing of competing advertising and market response. The specific calculation formula is as follows: In the above formula, T(f) is the adjustment strategy of advertising delivery time and frequency, which changes with the frequency f; H k (f) The performance of competing ads at frequency f; ω k G: Frequency factor for adjusting the advertising delivery time; k (f): The sensitivity of the market response to the frequency of competitor ads; Z(f): Normalization factor, used to ensure that the total delivery time and frequency are within a reasonable range; v k : Adjust the impact of competitive market response on frequency; Formula value range: This formula value range represents the frequency of ad delivery within a certain time period, and a higher value means a more frequent delivery.

7. The AI-based intelligent marketing management method according to claim 6, characterized in that: Analyze the current advertising strategy to determine whether it is necessary to adjust the advertising strategy. The specific calculation formula is as follows: In the above formula: L i (t): market potential of advertising channels; E j (t): advertising effect of the channel; D j (t): channel saturation, reflecting the intensity of competition; γ j ,δ j : Weight parameters for adjusting the allocation ratio of market potential and channel saturation; Formula range: S(t) is a decision function that measures whether the current advertising strategy needs to be adjusted; the larger the value, the greater the possibility that the current strategy needs to be adjusted.

8. The AI-based intelligent marketing management method according to claim 7, characterized in that: Set θ as the adjustment threshold of the advertising strategy, then: When S(t)>θ, the effect of the current advertising strategy is in line with expectations, so the existing strategy is maintained without adjustment; When S(t)≤θ, the effect of the current advertising strategy is not good, and it is necessary to adjust the strategy according to market feedback to generate a multi-objective optimized advertising strategy; among which the optimization goals include advertising content selection, advertising budget, advertising delivery channels, and advertising delivery frequency and time.

9. The AI-based intelligent marketing management method according to claim 8, characterized in that: When S(t)≤θ, the optimization method of the advertising delivery strategy includes the following specific steps: S21: Optimize the selection strategy of advertising content: Start the optimization function of advertising content, re-evaluate the advertising content according to market popularity, competitive product advertising analysis, and consumer preference information; use formula C(t) to re-select a new advertising content combination so that the advertising can better respond to market demand and consumer behavior; S22: Dynamically adjust the advertising distribution ratio in each channel: Analyze the market potential and effect of different advertising channels; k (t) According to the advertising effect and saturation of each channel, reallocate advertising budget, allocate more resources to channels with good effects, and reduce resource investment in inefficient channels to ensure the maximum dissemination effect of advertising; S23: Real-time adjustment of advertising budget: Through formula B(t), the advertising budget is dynamically adjusted according to the advertising budget of competing products and market feedback; the system re-evaluates the budget allocation strategy and increases or decreases the overall advertising expenditure; S24: Analyze the time of competitor ads and market response, and dynamically adjust the frequency and time of ads: The system analyzes the frequency of competitor ads and market response through formula T(f) to determine the optimal time period and frequency of ads; the system adjusts the time and frequency of ads according to the market response speed of competitor ads; S25: After the advertisement is launched, the system continuously monitors market feedback and collects relevant data. Based on market changes and competitive product dynamics, the system automatically determines whether the advertising strategy needs to be adjusted again. The adjustment process continues to iterate until S(t)>θ and the advertising effect is stable.

10. The AI-based intelligent marketing management system according to claim 9, characterized in that: The system includes a data collection and preprocessing module, a market dynamics prediction module, a competitive product analysis module, an advertising strategy generation module, and a strategy execution and feedback module.

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