Advertisement design project management system

Abstract

The invention discloses an advertisement design project management system, which relates to the technical field of project management, and comprises an information acquisition unit, the information acquisition unit is used for acquiring operation information and feedback information and sending the operation information to an information analysis unit, and the information analysis unit acquires the operation information and extracts a browsing keyword set based on the operation information; the method comprises the following steps: respectively calculating comprehensive demand indexes of browsing keywords and dividing pushing grades of the keywords, acquiring user information by an advertisement distribution unit, carrying out association matching on the user information and a coincident keyword set, and pushing associated keywords to a matched pushing user set, acquiring feedback information by a feedback analysis unit, calculating a comprehensive feedback coefficient, and sending the comprehensive feedback coefficient to the advertisement distribution unit. And a putting adjustment signal is generated. According to the method, by dividing the pushing levels of the keywords, the advertisement pushing accuracy is improved, the project management efficiency is improved, the advertisement putting effect is optimized in real time through feedback adjustment, the advertisement cost can be effectively reduced, and the rate of return on investment is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of project management, and in particular to an advertising design project management system. Background Art

[0002] With the progress of society and the development of the times, online advertising, as a new advertising and marketing model, has greatly promoted the development of the advertising industry. The management of advertising design projects is also very important. Reasonable advertising push can improve the management efficiency of the project. At the same time, it is also crucial to optimize the advertising effect in real time based on feedback information.

[0003] In traditional advertising design project management, advertising delivery and optimization often rely on manual experience, judgment and market research. Although this method can meet the basic needs of advertising delivery to a certain extent, it has obvious shortcomings. First, manual processing of large amounts of data is inefficient and prone to errors. Second, the lack of accurate user portraits and data analysis leads to poor advertising results. Finally, it is impossible to obtain feedback information in real time and adjust the advertising delivery strategy, which affects the conversion rate and return on investment of the advertisement.

[0004] Existing advertising design project management systems often have many limitations. The accuracy of advertising push is insufficient, which reduces the management efficiency of the project. Moreover, the real-time feedback and adjustment capabilities are insufficient, and the advertising delivery effect cannot be optimized in real time.

[0005] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0006] The purpose of the present invention is to propose an advertising design project management system, which not only improves the accuracy of advertising push but also improves the management efficiency of the project by dividing the push levels of keywords. It can effectively reduce advertising costs and improve the return on investment by optimizing the advertising delivery effect in real time through feedback adjustment.

[0007] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: an advertising design project management system, including an information acquisition unit, an information analysis unit, an advertising allocation unit, a feedback analysis unit and an adjustment push unit; The information acquisition unit includes an operation information acquisition module and a feedback information acquisition module. The operation information acquisition module is used to acquire operation information and send the operation information to the information analysis unit and the advertisement allocation unit. The feedback information acquisition module is used to acquire feedback information and send the feedback information to the feedback analysis unit. The information analysis unit is used to obtain and analyze operation information, wherein the operation information includes user information, advertisement information and product information, extract an advertisement keyword set A based on the advertisement information and product information, extract a browsing keyword set B based on the user information, obtain the search count Cs, search frequency Fb and post-search dwell time Tt of all browsing keywords in the browsing keyword set B, and calculate a comprehensive demand index of the browsing keywords; Compare the browsing keyword set B and the advertising keyword set A, extract the overlapping keyword set Aa including the advertising keyword set A from the browsing keyword set B, preset the demand index interval of the overlapping keywords, determine the demand degree of the overlapping keywords according to the preset demand index interval of the overlapping keywords, divide the push levels of the overlapping keywords, and mark all the keywords in the overlapping keyword set as first-category push keywords, second-category push keywords, and third-category push keywords respectively; The advertisement allocation unit is used to obtain and analyze user information, perform association matching based on the user information and the overlapping keyword set, generate an associated keyword set Aag and a push user set, and push the associated keywords in the associated keyword set to the matched push user set; Further, the feedback analysis unit is used to obtain and analyze feedback information, wherein the feedback information includes a click-through rate CT, a conversion rate CV, and a return on investment RI after the advertisement is delivered, and based on the click-through rate CT, the conversion rate CV, and the return on investment RI after the advertisement is delivered, a feedback evaluation index is calculated; The feedback information also includes the dwell time Tt after the advertisement is placed and the advertisement bounce rate Tc. Based on the feedback evaluation index, the dwell time Tt after the advertisement is placed and the advertisement bounce rate Tc, a comprehensive feedback coefficient is calculated, and a comprehensive feedback coefficient threshold is preset. The advertisement placement effect is judged according to the preset comprehensive feedback coefficient threshold, and a placement adjustment signal is generated, and the placement adjustment signal is sent to the adjustment push unit.

[0008] Further, the push adjustment unit receives the delivery adjustment signal, obtains the push frequency Fs of the initial associated keyword, the dwell time Tt after the advertisement delivery, and the advertisement bounce rate Tc, calculates the push frequency correction value Fxo based on the push frequency Fs of the associated keyword, the dwell time Tt after the advertisement delivery, and the advertisement bounce rate Tc, and adjusts the push frequency of the associated keyword based on the push frequency correction value Fxo. .

[0009] Furthermore, the specific process of calculating the comprehensive demand index of browsing keywords is as follows: S101, obtaining product information and advertising information through an e-commerce platform, extracting all advertising keywords from the product information and advertising information and integrating them into an advertising keyword set A; S102, obtaining user information from a user terminal of the e-commerce platform, wherein the user information includes user browsing preferences; S103, the user browsing preference is specifically a user browsing keyword, and the user browsing keywords are integrated into a browsing keyword set B; S104, obtaining the search count Cs, search frequency Fb and post-search dwell time Tt of all browsing keywords in the browsing keyword set B; S105, through the formula: , where Xq is the comprehensive demand index of browsing keywords and d1 is a constant.

[0010] Furthermore, the specific process of classifying the push levels of overlapping keywords is as follows: S201, comparing the browsing keyword set B and the advertising keyword set A, extracting the overlapping keyword set Aa including the advertising keyword set A from the browsing keyword set B; S202, obtaining the demand index Xqc of all overlapping keywords in the overlapping keyword set Aa; S203, presetting the demand index interval of the overlapping keywords to (Xmin, Xmax); If the demand index Xqc of the overlapping keyword is less than or equal to Xmin, the keyword is marked as a first-class push keyword, and the push frequency of the first-class push keyword is Fs1; If the demand index Xqc of the overlapping keyword is greater than Xmin and less than or equal to Xmax, the keyword is marked as a second-category push keyword, and the push frequency of the second-category push keyword is Fs2; If the demand index Xqc of the overlapping keyword is greater than or equal to Xmax, the keyword is marked as a third-category push keyword, and the push frequency of the third-category push keyword is Fs3; Among them, Fs3>Fs2>Fs1.

[0011] Furthermore, the specific process of pushing the associated keywords in the associated keyword set to the matching push user set is as follows: S301, obtaining user information of a user terminal, wherein the user information further includes user gender, user age and user region; S302: construct a user portrait based on the user information, wherein the user portrait includes a user gender portrait, a user age portrait, and a user region portrait; S303, using the user gender portrait, user age portrait and user region portrait in the user portrait as initial matching portraits, respectively, and performing association matching on the overlapping keyword set Aa with the user gender portrait, user age portrait and user region portrait to generate an associated keyword set Aag and a push user set; S304, obtaining the push levels of all associated keywords Ci in the associated keyword set Aag, and if the keyword Ci is a first-class push keyword, pushing the first-class keyword Ci to a matching push user set; If the keyword Ci is a second-class push keyword, the keyword Ci is pushed to the matching push user set; If the keyword Ci is a third-category push keyword, the third-category push of the keyword Ci is sent to a matching push user set.

[0012] Furthermore, the specific process of association matching is as follows: Match the overlapping keyword set Aa with the user gender profile, find out the keywords related to male or female user characteristics, generate the gender keyword set Aag_m, and push the gender keyword set Aag_m to user sets of different genders; Match the overlapping keyword set Aa with the user age profile, find out the keywords related to the user characteristics of different age groups, generate the age keyword set Aag_a, and push the age keyword set Aag_a to the user sets of different ages; Match the overlapping keyword set Aa with the user regional profile, find out the keywords related to the user characteristics in different regions, generate the regional keyword set Aag_i, and push the regional keyword set Aag_i to the user sets in different regions; The gender keyword set Aag_m, the age keyword set Aag_a and the region keyword set Aag_i are integrated into the associated keyword set Aag, and the gender user set, the age user set and the region user set are integrated into the push user set.

[0013] Furthermore, the specific process of generating the delivery adjustment signal is as follows: S401, obtaining feedback information including click-through rate CT, conversion rate CV and return on investment RI after advertisement delivery; S402, through the formula: , where Fk is the feedback evaluation index and D2 is a constant; S403, obtaining the residence time Tt and the ad bounce rate Tc after the advertisement is placed; S404, through the formula: , where Zh is the comprehensive feedback coefficient; S405, presetting the comprehensive feedback coefficient threshold as Zmin, if Zh is greater than or equal to Zmin, no signal is generated; If Zh is less than Zmin, a delivery adjustment signal is generated and sent to the adjustment push unit.

[0014] Furthermore, the specific process of adjusting the push frequency of associated keywords is as follows: S501, obtaining the push frequency Fs of the initial associated keyword, the stay time Tt after the advertisement is placed, and the advertisement bounce rate Tc; S502, through the formula: , where Fxo is the push frequency correction value and E is a constant; S503: If the push frequency is reduced, the formula used is: ; If you want to increase the push frequency, the formula is: ; In the formula, To reduce or increase the push frequency of related keywords, is the push frequency of the initial associated keyword, and Tk is the push frequency control coefficient.

[0015] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: The present invention extracts an advertising keyword set and a browsing keyword set by acquiring operation information, extracts a coincident keyword set including the advertising keyword set from the browsing keyword set, calculates a comprehensive demand index of the browsing keywords, and divides the push levels of the coincident keywords based on the comprehensive demand index of the browsing keywords. By dividing the push levels of the keywords, not only the accuracy of the advertisement push is improved, but also the management efficiency of the project is improved. By performing association matching between user information and the coincident keyword set, an associated keyword set and a push user set are generated, and the associated keywords in the associated keyword set are pushed to the matched push user set. Accurate advertisement push not only improves the conversion rate of advertisements, but also provides advertisers with more accurate market positioning. By analyzing feedback information and calculating a comprehensive feedback coefficient, and judging the advertisement delivery effect according to a preset comprehensive feedback coefficient threshold to generate a delivery adjustment signal, the advertisement delivery effect can be optimized in real time. By calculating a push frequency correction value, the push frequency of the associated keywords is adjusted. Not only a quantitative basis is provided for the evaluation and adjustment of the advertisement delivery effect, but also the advertisement cost can be effectively reduced and the return on investment can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 A flow chart of an advertising design project management system disclosed in the present invention is shown. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] Example: like Figure 1 As shown, it includes an information acquisition unit, an information analysis unit, an advertisement distribution unit, a feedback analysis unit and an adjustment and push unit; The information acquisition unit includes an operation information acquisition module and a feedback information acquisition module. The operation information acquisition module is used to acquire operation information and send the operation information to the information analysis unit and the advertisement allocation unit. The feedback information acquisition module is used to acquire feedback information and send the feedback information to the feedback analysis unit. The information analysis unit is used to obtain and analyze the operation information, the operation information includes user information, advertising information and product information, extract the advertising keyword set A based on the advertising information and product information, extract the browsing keyword set B based on the user information, obtain the search times Cs, search frequency Fb and post-search stay time Tt of all browsing keywords in the browsing keyword set B, and calculate the comprehensive demand index of the browsing keywords; The specific process of calculating the comprehensive demand index of browsing keywords is as follows: S101, obtaining product information and advertising information through an e-commerce platform, extracting all advertising keywords from the product information and advertising information and integrating them into an advertising keyword set A; S102, obtaining user information from the e-commerce platform user terminal, where the user information includes user browsing preferences; S103, the user browsing preference is specifically the user browsing keyword, and the user browsing keywords are integrated into a browsing keyword set B; S104, obtaining the search count Cs, search frequency Fb and post-search dwell time Tt of all browsing keywords in the browsing keyword set B; S105, through the formula: , where Xq is the comprehensive demand index of the browsing keyword, d1 is a constant, and the comprehensive demand index of the browsing keyword is used to evaluate the user's demand for the browsing keyword. The higher the comprehensive demand index, the higher the user's demand for the browsing keyword, and the lower the comprehensive demand index, the lower the user's demand for the browsing keyword; Compare the browsing keyword set B and the advertising keyword set A, extract the overlapping keyword set Aa including the advertising keyword set A from the browsing keyword set B, preset the demand index interval of the overlapping keywords, judge the demand degree of the overlapping keywords according to the preset demand index interval of the overlapping keywords, divide the push levels of the overlapping keywords, mark all the keywords in the overlapping keyword set as first-class push keywords, second-class push keywords and third-class push keywords respectively, and by dividing the push levels of keywords, not only the accuracy of advertising push is improved, but also the management efficiency of the project is improved; The specific process of classifying the push levels of overlapping keywords is as follows: S201, comparing the browsing keyword set B and the advertising keyword set A, extracting the overlapping keyword set Aa including the advertising keyword set A from the browsing keyword set B; S202, obtaining the demand index Xqc of all overlapping keywords in the overlapping keyword set Aa; S203, presetting the demand index interval of the overlapping keywords to (Xmin, Xmax); If the demand index Xqc of the overlapping keyword is less than or equal to Xmin, the keyword is marked as a first-class push keyword, and the push frequency of the first-class push keyword is Fs1; If the demand index Xqc of the overlapping keyword is greater than Xmin and less than or equal to Xmax, the keyword is marked as a second-class push keyword, and the push frequency of the second-class push keyword is Fs2; If the demand index Xqc of the overlapping keyword is greater than or equal to Xmax, the keyword is marked as a third-category push keyword, and the push frequency of the third-category push keyword is Fs3; Among them, Fs3>Fs2>Fs1; The advertisement distribution unit is used to obtain and analyze user information, perform association matching based on user information and overlapping keyword sets, generate an associated keyword set Aag and a push user set, and push the associated keywords in the associated keyword set to the matched push user set. Accurate advertisement push not only improves the conversion rate of advertisements, but also provides advertisers with more accurate market positioning; The specific process of pushing the associated keywords in the associated keyword set to the matching push user set is as follows: S301, obtaining user information of the user terminal, the user information also includes user gender, user age and user region; S302: construct a user portrait based on the user information, where the user portrait includes a user gender portrait, a user age portrait, and a user region portrait; S303, using the user gender portrait, user age portrait and user region portrait in the user portrait as initial matching portraits, respectively, and performing association matching on the overlapping keyword set Aa with the user gender portrait, user age portrait and user region portrait to generate an associated keyword set Aag and a push user set; S304, obtaining the push levels of all associated keywords Ci in the associated keyword set Aag, and if the keyword Ci is a first-class push keyword, pushing the first-class keyword Ci to a matching push user set; If the keyword Ci is a second-class push keyword, the keyword Ci is pushed to the matching push user set; If the keyword Ci is a third-category push keyword, the third-category push of the keyword Ci is sent to the matching push user set; The specific process of association matching is as follows: Match the overlapping keyword set Aa with the user gender profile, find out the keywords related to male or female user characteristics, generate the gender keyword set Aag_m, and push the gender keyword set Aag_m to user sets of different genders; Match the overlapping keyword set Aa with the user age profile, find out the keywords related to the user characteristics of different age groups, generate the age keyword set Aag_a, and push the age keyword set Aag_a to the user sets of different ages; Match the overlapping keyword set Aa with the user regional profile, find out the keywords related to the user characteristics in different regions, generate the regional keyword set Aag_i, and push the regional keyword set Aag_i to the user sets in different regions; Integrate the gender keyword set Aag_m, the age keyword set Aag_a and the region keyword set Aag_i into the associated keyword set Aag, and integrate the gender user set, the age user set and the region user set into the push user set; The feedback analysis unit is used to obtain and analyze feedback information, the feedback information includes the click-through rate CT, conversion rate CV and return on investment RI after the advertisement is released, and the feedback evaluation index is calculated based on the click-through rate CT, conversion rate CV and return on investment RI after the advertisement is released; The feedback information also includes the dwell time Tt after the advertisement is placed and the advertisement bounce rate Tc. Based on the feedback evaluation index, the dwell time Tt after the advertisement is placed and the advertisement bounce rate Tc, a comprehensive feedback coefficient is calculated, and a comprehensive feedback coefficient threshold is preset. The advertisement placement effect is judged according to the preset comprehensive feedback coefficient threshold to generate a placement adjustment signal, and the placement adjustment signal is sent to the adjustment push unit. Real-time acquisition and analysis of feedback information can optimize the advertisement placement effect in real time. The specific process of generating a delivery adjustment signal is as follows: S401, obtaining feedback information including click-through rate CT, conversion rate CV and return on investment RI after advertisement delivery; S402, through the formula: , where Fk is the feedback evaluation index, which is used to reflect the impact of the click-through rate CT, conversion rate CV and return on investment RI after the advertisement is released on the calculation of the comprehensive feedback coefficient, and D2 is a constant; S403, obtaining the residence time Tt and the ad bounce rate Tc after the advertisement is placed; S404, through the formula: , where Zh is the comprehensive feedback coefficient, which is used to reflect the effect of advertising. The higher the comprehensive feedback coefficient, the better the advertising effect, and the lower the comprehensive feedback coefficient, the worse the advertising effect; S405, presetting the comprehensive feedback coefficient threshold as Zmin, if Zh is greater than or equal to Zmin, no signal is generated; If Zh is less than Zmin, a delivery adjustment signal is generated and sent to the adjustment push unit; The push adjustment unit receives the delivery adjustment signal, obtains the push frequency Fs of the initial associated keyword, the stay time Tt after the advertisement delivery, and the ad bounce rate Tc, calculates the push frequency correction value Fxo based on the push frequency Fs of the associated keyword, the stay time Tt after the advertisement delivery, and the ad bounce rate Tc, and adjusts the push frequency of the associated keyword based on the push frequency correction value Fxo , which not only provides a quantitative basis for the evaluation and adjustment of advertising effects, but also effectively reduces advertising costs and improves the return on investment; The specific process of adjusting the push frequency of associated keywords is as follows: S501, obtaining the push frequency Fs of the initial associated keyword, the stay time Tt after the advertisement is placed, and the advertisement bounce rate Tc; S502, through the formula: , where Fxo is the push frequency correction value and E is a constant; S503: If the push frequency is reduced, the formula used is: ; If you want to increase the push frequency, the formula is: ; In the formula, To reduce or increase the push frequency of related keywords, is the push frequency of the initial associated keyword, and Tk is the push frequency control coefficient.

[0019] In summary of the above technical solutions: the present invention extracts an advertising keyword set and a browsing keyword set by acquiring operation information, extracts a set of overlapping keywords including the advertising keyword set from the browsing keyword set, calculates a comprehensive demand index of browsing keywords, and divides the push levels of overlapping keywords based on the comprehensive demand index of browsing keywords. By dividing the push levels of keywords, not only the accuracy of advertising push is improved, but also the management efficiency of the project is improved. By performing association matching between user information and overlapping keyword sets, an associated keyword set and a push user set are generated, and the associated keywords in the associated keyword set are pushed to the matched push user set. Accurate advertising push not only improves the conversion rate of advertising, but also provides advertisers with more accurate market positioning. By analyzing feedback information to calculate a comprehensive feedback coefficient, and judging the advertising delivery effect according to a preset comprehensive feedback coefficient threshold to generate a delivery adjustment signal, the advertising delivery effect can be optimized in real time. By calculating a push frequency correction value, the push frequency of associated keywords is adjusted. Not only a quantitative basis is provided for the evaluation and adjustment of the advertising delivery effect, but also the advertising cost can be effectively reduced and the return on investment can be improved.

[0020] The setting of the threshold and interval size is for the convenience of comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technicians in this field for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value; Those skilled in the art can appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented by a device or a combination of computer software and electronic hardware; whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution; The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An advertising design project management system, characterized in that: It includes an information acquisition unit, an information analysis unit, an advertisement distribution unit, a feedback analysis unit and an adjustment and push unit; The information acquisition unit includes an operation information acquisition module and a feedback information acquisition module. The operation information acquisition module is used to acquire operation information and send the operation information to the information analysis unit and the advertisement allocation unit. The feedback information acquisition module is used to acquire feedback information and send the feedback information to the feedback analysis unit. The information analysis unit is used to obtain and analyze operation information, wherein the operation information includes user information, advertisement information and product information, extract an advertisement keyword set A based on the advertisement information and product information, extract a browsing keyword set B based on the user information, obtain the search count Cs, search frequency Fb and post-search dwell time Tt of all browsing keywords in the browsing keyword set B, and calculate a comprehensive demand index of the browsing keywords; Compare the browsing keyword set B and the advertising keyword set A, extract the overlapping keyword set Aa including the advertising keyword set A from the browsing keyword set B, preset the demand index interval of the overlapping keywords, determine the demand degree of the overlapping keywords according to the preset demand index interval of the overlapping keywords, divide the push levels of the overlapping keywords, and mark all the keywords in the overlapping keyword set as first-category push keywords, second-category push keywords, and third-category push keywords respectively; The advertisement allocation unit is used to obtain and analyze user information, perform association matching based on the user information and the overlapping keyword set, generate an associated keyword set Aag and a push user set, and push the associated keywords in the associated keyword set to the matched push user set.

2. The advertising design project management system according to claim 1, characterized in that: The feedback analysis unit is used to obtain and analyze feedback information, wherein the feedback information includes a click-through rate CT, a conversion rate CV, and a return on investment RI after the advertisement is delivered, and calculate a feedback evaluation index based on the click-through rate CT, the conversion rate CV, and the return on investment RI after the advertisement is delivered; The feedback information also includes the dwell time Tt after the advertisement is placed and the advertisement bounce rate Tc. Based on the feedback evaluation index, the dwell time Tt after the advertisement is placed and the advertisement bounce rate Tc, a comprehensive feedback coefficient is calculated, and a comprehensive feedback coefficient threshold is preset. The advertisement placement effect is judged according to the preset comprehensive feedback coefficient threshold, and a placement adjustment signal is generated, and the placement adjustment signal is sent to the adjustment push unit.

3. The advertising design project management system according to claim 2, characterized in that: The push adjustment unit receives the delivery adjustment signal, obtains the push frequency Fs of the initial associated keyword, the stay time Tt after the advertisement delivery, and the advertisement bounce rate Tc, calculates the push frequency correction value Fxo based on the push frequency Fs of the associated keyword, the stay time Tt after the advertisement delivery, and the advertisement bounce rate Tc, and adjusts the push frequency of the associated keyword based on the push frequency correction value Fxo .

4. The advertising design project management system according to claim 1, characterized in that: The specific process of calculating the comprehensive demand index of browsing keywords is as follows: S101, obtaining product information and advertising information through an e-commerce platform, extracting all advertising keywords from the product information and advertising information and integrating them into an advertising keyword set A; S102, obtaining user information from a user terminal of the e-commerce platform, wherein the user information includes user browsing preferences; S103, the user browsing preference is specifically a user browsing keyword, and the user browsing keywords are integrated into a browsing keyword set B; S104, obtaining the search count Cs, search frequency Fb and post-search dwell time Tt of all browsing keywords in the browsing keyword set B; S105, through the formula: , where Xq is the comprehensive demand index of browsing keywords and d1 is a constant.

5. The advertising design project management system according to claim 1, characterized in that: The specific process of classifying the push levels of overlapping keywords is as follows: S201, comparing the browsing keyword set B and the advertising keyword set A, extracting the overlapping keyword set Aa including the advertising keyword set A from the browsing keyword set B; S202, obtaining demand index Xqc of all overlapping keywords in the overlapping keyword set Aa; S203, presetting the demand index interval of the overlapping keywords to (Xmin, Xmax); If the demand index Xqc of the overlapping keyword is less than or equal to Xmin, the keyword is marked as a first-class push keyword, and the push frequency of the first-class push keyword is Fs1; If the demand index Xqc of the overlapping keyword is greater than Xmin and less than or equal to Xmax, the keyword is marked as a second-category push keyword, and the push frequency of the second-category push keyword is Fs2; If the demand index Xqc of the overlapping keyword is greater than or equal to Xmax, the keyword is marked as a third-category push keyword, and the push frequency of the third-category push keyword is Fs3; Among them, Fs3>Fs2>Fs1.

6. The advertising design project management system according to claim 1, characterized in that: The specific process of pushing the associated keywords in the associated keyword set to the matching push user set is as follows: S301, obtaining user information of a user terminal, wherein the user information further includes user gender, user age and user region; S302: construct a user portrait based on the user information, wherein the user portrait includes a user gender portrait, a user age portrait, and a user region portrait; S303, using the user gender portrait, user age portrait and user region portrait in the user portrait as initial matching portraits, respectively, and performing association matching on the overlapping keyword set Aa with the user gender portrait, user age portrait and user region portrait to generate an associated keyword set Aag and a push user set; S304, obtaining the push levels of all associated keywords Ci in the associated keyword set Aag, and if the keyword Ci is a first-class push keyword, pushing the first-class keyword Ci to a matching push user set; If the keyword Ci is a second-class push keyword, the keyword Ci is pushed to the matching push user set; If the keyword Ci is a third-category push keyword, the third-category push of the keyword Ci is sent to a matching push user set.

7. The advertising design project management system according to claim 6, characterized in that: The specific process of association matching is as follows: Match the overlapping keyword set Aa with the user gender profile, find out the keywords related to male or female user characteristics, generate the gender keyword set Aag_m, and push the gender keyword set Aag_m to user sets of different genders; Match the overlapping keyword set Aa with the user age profile, find out the keywords related to the user characteristics of different age groups, generate the age keyword set Aag_a, and push the age keyword set Aag_a to the user sets of different ages; Match the overlapping keyword set Aa with the user regional profile, find out the keywords related to the user characteristics of different regions, generate the regional keyword set Aag_i, and push the regional keyword set Aag_i to the user sets in different regions; The gender keyword set Aag_m, the age keyword set Aag_a and the region keyword set Aag_i are integrated into the associated keyword set Aag, and the gender user set, the age user set and the region user set are integrated into the push user set.

8. The advertising design project management system according to claim 2, characterized in that: The specific process of generating a delivery adjustment signal is as follows: S401, obtaining feedback information including click-through rate CT, conversion rate CV and return on investment RI after advertisement delivery; S402, through the formula: , where Fk is the feedback evaluation index and D2 is a constant; S403, obtaining the residence time Tt and the ad bounce rate Tc after the advertisement is placed; S404, through the formula: , where Zh is the comprehensive feedback coefficient; S405, presetting the comprehensive feedback coefficient threshold as Zmin, if Zh is greater than or equal to Zmin, no signal is generated; If Zh is less than Zmin, a delivery adjustment signal is generated and sent to the adjustment push unit.

9. The advertising design project management system according to claim 3, characterized in that: The specific process of adjusting the push frequency of associated keywords is as follows: S501, obtaining the push frequency Fs of the initial associated keyword, the stay time Tt after the advertisement is placed, and the advertisement bounce rate Tc; S502, through the formula: , where Fxo is the push frequency correction value and E is a constant; S503: If the push frequency is reduced, the formula used is: ; If you want to increase the push frequency, the formula is: ; In the formula, To reduce or increase the push frequency of related keywords, is the push frequency of the initial associated keyword, and Tk is the push frequency control coefficient.

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