Advertisement effect evaluation method and system based on big data
By combining advertising sales data and publicity environmental factors to evaluate the actual effect, the problem of inaccurate advertising performance evaluation is solved, and more accurate and reliable advertising performance evaluation is achieved, and effective strategy adjustment is supported.
Patent Information
- Application Number
- CN202510262228.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-06
- Publication Date
- 2025-07-04
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
In the prior art, advertising effectiveness evaluation relies on single data such as sales volume and conversion rate, resulting in inaccurate evaluation and inability to adapt to differences in different times, regions and media, affecting the effectiveness of advertising strategy adjustment.
By obtaining the sales data and publicity data of the target advertisement, combining the difficulty values of the publicity time, region and media, calculate the basic effect values and publicity difficulty values, comprehensively evaluate the actual effect values, and feedback to the user terminal for plan adjustments.
It improves the accuracy and reliability of advertising performance evaluation, can better adapt to different publicity environments, and provides reliable data to support advertising strategy adjustments.
Smart Images
Figure CN120258903A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of advertising effect evaluation, and particularly relates to an advertising effect evaluation method and system based on big data. Background Art
[0002] With the development of the information age, advertisements are everywhere, and advertisements play a certain role in promoting and publicizing commodities. The advertising effect generally refers to the social influence and effect that can be generated after the advertising information is spread through advertising media. By evaluating the advertising effect, enterprises can understand the dissemination effect of advertisements among the target audience, the impact on consumer behavior, and the accuracy and clarity of the advertising information transmission, etc., so as to more comprehensively understand the actual effect of advertisements. Secondly, advertising effect evaluation is also an important basis for enterprises to formulate and adjust advertising strategies. Through the feedback of evaluation results, enterprises can timely discover the problems and deficiencies in advertisements, and accordingly adjust advertising content, placement channels, budgets, etc., to improve the advertising effect and input-output ratio. However, evaluating the advertising effect based on sales volume and conversion rate cannot fit all situations. Obviously, in different periods and different scenarios, even for the same advertisement, its effect will vary. Simply relying on fixed data such as sales volume and conversion rate for evaluation is likely to result in inaccurate and unrealistic advertising effect evaluation. Summary of the Invention
[0003] The purpose of the present invention is to provide an advertising effect evaluation method and system based on big data to solve the problems raised in the above background art.
[0004] In a first aspect, an advertising effect evaluation method based on big data provided by the present application adopts the following technical solutions: Obtain a target advertisement, extract the promoted product in the target advertisement, obtain the sales data of the promoted product, and obtain the basic effect value of the target advertisement according to the sales data; Obtain the publicity time, publicity region, and publicity medium of the target advertisement, and evaluate the publicity difficulty value of the target advertisement according to the publicity time, publicity region, and publicity medium; Combine the basic effect value and the publicity difficulty value to confirm the actual effect of the target advertisement and obtain the actual effect value; Feed back the actual effect value to the user terminal and adjust the advertising publicity plan according to the actual effect value.
[0005] Preferably, the step of obtaining the target advertisement, extracting the promoted product in the target advertisement, obtaining the sales data of the promoted product, and obtaining the basic effect value of the target advertisement according to the sales data is specifically: Obtain the sales data of the promoted product, and the sales data includes real-time sales volume, real-time consultation volume, and real-time view volume; Obtain the original sales volume and original consultation volume before the target advertisement is launched, calculate the difference between the real-time sales volume and the original sales volume to obtain the sales volume difference; Calculate the difference between the real-time consultation volume and the original consultation volume to obtain the consultation difference, and calculate the ratio of the real-time sales volume to the real-time consultation volume to obtain the consultation conversion rate; Calculate the ratio of the real-time consultation volume to the real-time view volume to obtain the view conversion rate, respectively set the proportionality coefficients of the sales volume difference, consultation difference, consultation conversion rate and view conversion rate, and calculate the basic effect value according to the proportionality coefficients.
[0006] Preferably, the step of obtaining the publicity time, publicity region and publicity medium of the target advertisement and evaluating the publicity difficulty value of the target advertisement according to the publicity time, publicity region and publicity medium is specifically as follows: Obtain the publicity time, publicity region and publicity medium of the target advertisement, and analyze the time publicity difficulty of the target advertisement according to the publicity time; Obtain the targeted region of the promoted product, and analyze the regional publicity difficulty of the target advertisement in combination with the publicity region; Extract the medium information of the publicity medium, and analyze the medium publicity difficulty of the target advertisement according to the medium information; Integrate the time publicity difficulty, regional publicity difficulty and medium publicity difficulty of the target advertisement to obtain the publicity difficulty value of the target advertisement.
[0007] Preferably, the step of analyzing the time publicity difficulty of the target advertisement according to the publicity time is specifically as follows: Obtain the historical sales volume data of the promoted product, calculate the sales volume difference between adjacent times according to the historical sales volume data, and record it as the sales volume fluctuation value; Judge whether the sales volume fluctuation value reaches the preset fluctuation threshold. If it reaches the preset fluctuation threshold, obtain the historical sales volume average value corresponding to the publicity time and record it as the publicity sales volume value; Extract the time period with the highest historical sales volume as the standard time period according to the historical sales volume data, and calculate the historical sales volume average value of the standard time period and record it as the standard sales volume value; Calculate the difference between the publicity sales volume value and the standard sales volume value and record it as the publicity difference, compare the ratio of the publicity difference to the standard sales volume value to obtain the time publicity difficulty; If the sales volume fluctuation value does not reach the preset fluctuation threshold, the time publicity difficulty is 0.
[0008] Preferably, the step of obtaining the targeted region of the promoted product and analyzing the regional publicity difficulty of the target advertisement in combination with the publicity region is specifically as follows: Judge whether the promoted product has a targeted promotion region. If there is a targeted promotion region, record it as the targeted region; Obtain the factor for screening the targeted region of the promoted product and record it as the standard regional factor; Obtain the geographical factors of the same type as the standard geographical factors for the publicity area and record them as real-time geographical factors; Compare the factor similarity between the standard geographical factors and the real-time geographical factors, calculate the average value of all factor similarities, and obtain the geographical similarity; Calculate the difference between the geographical similarity and the 100% similarity to obtain the geographical publicity difficulty of the target advertisement; If there is no targeted promotion area for the promoted product, the geographical publicity difficulty of the target advertisement is 0.
[0009] Preferably, the steps of extracting the media information of the publicity medium and analyzing the media publicity difficulty of the target advertisement according to the media information are specifically as follows: Extract the media information of the publicity medium, and the media information includes the target audience and the media popularity; Judge whether there is a targeted user for the promoted product. If there is a targeted user for the promoted product, then compare the similarity between the targeted user and the target audience to obtain the user similarity; If there is no targeted user for the promoted product, the user similarity is 100%; Obtain the audience information of the target audience, and confirm the trust degree of the target audience in the medium according to the audience information to obtain the media trust degree; Comprehensively combine the user similarity, the media popularity, and the media trust degree to obtain the media publicity difficulty of the target advertisement.
[0010] Preferably, the steps of the media information including the target audience and the media popularity are specifically as follows: Judge whether the condition for the user to view and read the target advertisement is that the user owns the publicity medium. If the condition is that the user owns the publicity medium, then count the number of people who own the publicity medium, and calculate the media occupancy rate according to the number of people who own the publicity medium and the total population; If the condition is not that the user owns the publicity medium, then obtain the publicity range of the publicity medium, and count the total publicity range of the publicity medium according to the publicity range; Obtain the total population range, and obtain the media occupancy rate of the target advertisement according to the ratio of the total publicity range to the total population range; Obtain the average usage duration of the publicity medium, set user characteristics, and count the coverage range of different user characteristics by the target audience to obtain the characteristic coverage range; Overlay the characteristic coverage ranges of all user characteristics to obtain the group coverage range of the target advertisement; Comprehensively combine the media occupancy rate, the average usage duration, and the group coverage range to obtain the media popularity of the publicity medium.
[0011] Preferably, the steps of obtaining the audience information of the target audience, and confirming the trust degree of the target audience in the medium according to the audience information to obtain the media trust degree are specifically as follows: Obtain the audience information of the target audience, where the audience information includes the audience age and the audience education level; Collect the probability of being deceived in the publicity medium for different ages, search for the probability of being deceived corresponding to the audience age and record it as the age deception probability; Statistically analyze the probability of being deceived in the publicity medium for different education levels, search for the probability of being deceived corresponding to the audience education level and record it as the education deception probability; Combine the age deception probability and the education deception probability to obtain the audience caution level of the target audience; Obtain the medium authenticity of the publicity medium, and combine the audience caution level to obtain the medium trust level.
[0012] Preferably, the step of obtaining the medium authenticity of the publicity medium and combining the audience caution level to obtain the medium trust level is specifically as follows: Obtain the review system of the publicity medium, and extract the average review times and the average review duration according to the review system; Obtain the historical publicity data of the publicity medium, and statistically analyze the error rate of the publicity content according to the historical publicity data; Respectively obtain the medium authenticity according to the average review times, the average review duration and the error rate of the publicity content; Respectively set the weight ratios of the medium authenticity and the audience caution level, and calculate the medium trust level according to the weight ratios.
[0013] In a second aspect, an advertising effect evaluation system based on big data provided by the present application adopts the following technical solutions: An advertising effect evaluation system based on big data, comprising: A basic effect module, which obtains a target advertisement, extracts the promoted product in the target advertisement, obtains the sales data of the promoted product, and obtains the basic effect value of the target advertisement according to the sales data; A publicity difficulty module, which obtains the publicity time, publicity region and publicity medium of the target advertisement, and evaluates the publicity difficulty value of the target advertisement according to the publicity time, publicity region and publicity medium; An actual effect module, which combines the basic effect value and the publicity difficulty value to confirm the actual effect of the target advertisement and obtain the actual effect value; A publicity feedback module, which feeds back the actual effect value to the user terminal and adjusts the advertisement publicity plan according to the actual effect value.
[0014] In summary, the present application includes at least one of the following beneficial technical effects: 1. According to the promotion time, promotion region, and promotion medium of the target advertisement, combined with the sales volume of the promoted product and the evaluation of the promotion difficulty value for the target region, and combined with the basic effect value of the target advertisement obtained from the sales data of the promoted product, the actual effect of the target advertisement is comprehensively obtained, which is more in line with the actual promotion effect and improves the accuracy of the advertisement effect evaluation based on big data.
[0015] 2. Different analyses are performed on the judgment result of whether the condition for the user to view and read the target advertisement is that the user owns the promotion medium to obtain the media occupancy rate. The media popularity is obtained by combining the average usage duration and the group coverage range. Then, the media promotion difficulty is evaluated by comprehensively considering the target audience of the medium, providing reliable data for the advertisement effect evaluation and improving the reliability of the advertisement effect evaluation based on big data.
[0016] 3. The probability of being deceived is found by using the age and educational level of the audience of the promotion medium, so as to obtain the caution degree of the audience of the promotion medium. The authenticity of the medium is obtained by using the review system and the error rate of the promotion content of the promotion medium. Then, the trust degree of the medium is obtained by combining the caution degree of the audience and the authenticity of the medium. The trust degree of the medium can reflect the promotion difficulty of the medium, which is more in line with the actual promotion situation table and improves the practicality of the advertisement effect evaluation based on big data. Description of the Drawings
[0017] Figure 1 It is a schematic diagram of the specific steps of an embodiment of a method for evaluating the advertisement effect based on big data according to the present invention.
[0018] Figure 2 It is a schematic diagram of the module connection of an embodiment of a system for evaluating the advertisement effect based on big data according to the present invention. Detailed Embodiment
[0019] The following combines the embodiments and Figure 1 - Figure 2 makes a further detailed description of the present invention, but the implementation manners of the present invention are not limited thereto.
[0020] The present invention discloses a method for evaluating the advertisement effect based on big data, which specifically includes the following steps: Step S1: Obtain the target advertisement, extract the promoted product in the target advertisement, obtain the sales data of the promoted product, and obtain the basic effect value of the target advertisement according to the sales data.
[0021] Step S2: Obtain the promotion time, promotion region, and promotion medium of the target advertisement, and evaluate the promotion difficulty value of the target advertisement according to the promotion time, promotion region, and promotion medium.
[0022] Step S3: Combine the basic effect value and the promotion difficulty value to confirm the actual effect of the target advertisement and obtain the actual effect value.
[0023] Set the weight ratios of the basic effect value and the promotion difficulty value respectively, and calculate the actual effect value of the target advertisement according to the weight ratios.
[0024] Step S4, feedback the actual effect value to the user terminal, and adjust the advertisement promotion plan according to the actual effect value.
[0025] In actual application, the advertisement effect cannot be only judged by sales volume. Under the same sales volume, even for the same promotional advertisement, its advertisement effect is different under different promotion circumstances. Evaluating the effect of promotional advertisements solely based on sales volume is not accurate. For example, it is warm in Kunming all year round, while it is extremely cold in the Northeast region. For the advertisement of the same winter products, it is definitely easier to sell in the Northeast because people need it. In Kunming, because people don't need it, the promotion is more difficult. If the sales volumes in the Northeast and Kunming are the same, then obviously the advertisement promotion effect in Kunming is better because the promotion difficulty is greater. Therefore, evaluating the advertisement effect in combination with the actual promotion difficulty is more in line with the actual situation.
[0026] The steps of obtaining the target advertisement, extracting the promoted product in the target advertisement, obtaining the sales data of the promoted product, and obtaining the basic effect value of the target advertisement according to the sales data are specifically as follows: Step S11, obtain the sales data of the promoted product. The sales data includes the real-time sales volume, real-time consultation volume, and real-time viewing volume.
[0027] Step S12, obtain the original sales volume and original consultation volume before the target advertisement is put on the market, calculate the difference between the real-time sales volume and the original sales volume, and obtain the sales volume difference.
[0028] The sales volume difference can reflect the change in sales volume after the advertisement is put on the market, so as to evaluate whether the advertisement is effective.
[0029] Step S13, calculate the difference between the real-time consultation volume and the original consultation volume to obtain the consultation difference, and calculate the ratio of the real-time sales volume to the real-time consultation volume to obtain the consultation conversion rate.
[0030] The consultation difference can reflect the promotion degree of the advertisement, thus reflecting the advertisement promotion effect. The consultation conversion rate can reflect whether the advertisement is real and whether it can directly guide users to purchase. If users are attracted by the advertisement but do not purchase after consultation, it means that the advertisement effect has not made users make up their minds to purchase.
[0031] Step S14, calculate the ratio of the real-time consultation volume to the real-time viewing volume to obtain the viewing conversion rate, set the proportionality coefficients of the sales volume difference, consultation difference, consultation conversion rate, and viewing conversion rate respectively, and calculate the basic effect value according to the proportionality coefficients.
[0032] In actual application, the sales volume difference and the consultation difference can intuitively reflect whether an advertisement attracts users, and thus reflect the advertising effect. The larger the sales volume difference and the consultation difference are, the greater the advertising attraction is, so the better the advertising effect is. The higher the viewing conversion rate is, the more it shows that the advertisement can make users place orders. Therefore, the advertisement is attractive enough, indicating a good advertising effect. The higher the consultation conversion rate is, the higher the authenticity of the advertisement is, and the points that users care about are written more comprehensively. After consultation and confirmation, users confirm to place orders. When the consultation conversion rate is not high, it means that some points that users care about are not clearly written, and there may be false propaganda, which seriously affects the advertising effect. For example, the price of the product is not stated in the advertisement. Users are attracted by the advertisement and go to confirm the price of the product. The price of the product is too expensive, resulting in users giving up the purchase. In this way, even if users are attracted by the advertisement, but they do not get the product points they want, users will ultimately not purchase and will have a negative impression of the advertisement. For advertisements with unclear descriptions, it will affect users' understanding and thus seriously affect the advertising effect.
[0033] The steps of obtaining the publicity time, publicity region and publicity medium of the target advertisement and evaluating the publicity difficulty value of the target advertisement according to the publicity time, publicity region and publicity medium are specifically as follows: Step S21: Obtain the publicity time, publicity region and publicity medium of the target advertisement, and analyze the time publicity difficulty of the target advertisement according to the publicity time.
[0034] Step S22: Obtain the targeted region of the promoted product, and analyze the regional publicity difficulty of the target advertisement in combination with the publicity region.
[0035] Step S23: Extract the medium information of the publicity medium, and analyze the medium publicity difficulty of the target advertisement according to the medium information.
[0036] Step S24: Synthesize the time publicity difficulty, regional publicity difficulty and medium publicity difficulty of the target advertisement to obtain the publicity difficulty value of the target advertisement.
[0037] In actual application, the weight ratios of the publicity difficulty of time, region, and medium are set respectively, and the publicity difficulty value of the target advertisement is calculated according to the weight ratios. Different publicity times, regions, and media will all affect the publicity difficulty of the advertisement. For example, assume a travel company launches a new travel route advertisement during the Spring Festival. Since people are usually busy with family gatherings and celebrations during the Spring Festival, their attention to travel advertisements may be relatively low, resulting in an increase in publicity difficulty. In contrast, if the travel advertisement is launched during the summer vacation or before a holiday, the audience's participation and attention may be higher, and the publicity difficulty is relatively low. For different regions, when a down jacket brand conducts advertisement publicity in the southern region, it may be restricted by the regional climate. Because the winter in the southern region is relatively warm, consumers' demand for down jackets is low, resulting in an increase in publicity difficulty. While in the northern region, due to the cold winter, consumers' demand for down jackets is high, and the publicity difficulty is relatively low. Moreover, different media have different target audiences, and the publicity difficulty of the advertisement will also change.
[0038] The steps to analyze the time publicity difficulty of the target advertisement according to the publicity time are specifically as follows: Step S211: Obtain the historical sales volume data of the promoted product, calculate the sales volume difference between adjacent times based on the historical sales volume data, and record it as the sales volume fluctuation value.
[0039] The sales volume at different time points will be different, so there is a sales volume difference between different times. For example, the sales volume of Product A in July is 100,000 pieces, the sales volume in August is 50,000 pieces, and the sales volume in September is 10,000 pieces. Therefore, the sales volume fluctuation value between July and August is 50,000 pieces, and the sales volume fluctuation value between August and September is 40,000 pieces.
[0040] Step S212: Determine whether the sales volume fluctuation value reaches the preset fluctuation threshold. If it reaches the preset fluctuation threshold, obtain the historical sales volume average corresponding to the publicity time and record it as the publicity sales volume value.
[0041] If the sales volume fluctuation value reaches the preset fluctuation threshold, it indicates that the sales volume of this product is related to time. For example, the sales volume of clothes in different seasons varies in different seasons, with a large fluctuation, while the sales volume of household appliances such as sockets varies little at each time point, and the fluctuation value is small.
[0042] Step S213: Extract the time period with the highest sales volume as the standard time period according to the historical sales volume data, and calculate the historical sales volume average of the standard time period and record it as the standard sales volume value.
[0043] When the product sales volume is related to time, there are usually fixed time periods with relatively high sales volumes. Take the fixed time period with the highest sales volume as the standard time period, and calculate the average sales volume within the standard time period over the years as the standard sales volume value. For example, the time period with the highest sales volume is from July to August. The sales volume in July - August 2022 was 100,000 pieces, the sales volume in July - August 2023 was 120,000 pieces, and the sales volume in July - August 2024 was 80,000 pieces. Then the standard sales volume value is 100,000 pieces.
[0044] Step S214, calculate the difference between the promotional sales volume value and the standard sales volume value and denote it as the promotional difference. Compare the ratio of the promotional difference to the standard sales volume value to obtain the promotional difficulty at that time.
[0045] For example, the standard sales volume value is 100,000 pieces. When the promotional sales volume in June is 50,000 pieces, the promotional difference is 50,000 pieces, and the promotional difficulty at that time is 5 / 10 = 50%. If the sales volume is 80,000 pieces, then the promotional difficulty at that time is 2 / 10 = 20%. That is to say, the lower the real - time sales volume, the greater the promotional difficulty at that time, because it is more difficult to sell the product during that time.
[0046] Step S215, if the sales volume fluctuation value does not reach the preset fluctuation threshold, the promotional difficulty at that time is 0.
[0047] In actual application, if the sales volume fluctuation value does not reach the preset fluctuation threshold, it means that the sales volume differences at different times are not significant, that is, time does not affect the sale of the product. Therefore, the difficulty of advertising and promoting the product at any time is the same, so the promotional difficulty at that time is set to 0.
[0048] The steps to obtain the targeted region for promoting the product and analyze the regional promotional difficulty of the target advertisement in combination with the promotional region are as follows: Step S221, determine whether the product to be promoted has a targeted promotional region. If there is a targeted promotional region, denote it as the targeted region.
[0049] Some products have specific targeted promotional regions. For example, regions with higher humidity such as the middle and lower reaches of the Yangtze River and the southern coastal areas are the targeted regions for household dehumidifiers. Due to the humid climate in these areas, it is easy to cause the indoor humidity to be too high, and household dehumidifiers can effectively solve this problem.
[0050] Step S222, obtain the factor for screening the targeted region of the product to be promoted and denote it as the standard regional factor.
[0051] For different products to be promoted with targeted regions, there are reasons for targeting. The standard regional factor can be extracted from the reasons for targeting. For example, the targeted region for household dehumidifiers is the region with higher humidity. Therefore, high humidity is the factor for screening the targeted region, that is, the standard regional factor.
[0052] Step S223: Obtain the regional factors of the same type as the standard regional factors in the publicity region and record them as real-time regional factors.
[0053] For example, if the standard regional factor is a humidity of 75%, then the regional factor of the same type is humidity. Search for the situation of this factor in the publicity region to obtain the real-time regional factor. If the humidity in the standard region is 50%, then the real-time regional factor is a humidity of 50%.
[0054] Step S224: Compare the factor similarity between the standard regional factors and the real-time regional factors, calculate the average value of all factor similarities, and obtain the regional similarity.
[0055] Obtain the factor similarity according to the ratio of the standard regional factors to the real-time regional factors. For example, if the standard regional factor is a humidity of 75% and the real-time regional factor is a humidity of 50%, then the ratio is 50% / 75% = 66.66%, so the factor similarity is 66.66%. Calculate the average value of all factor similarities to obtain the regional similarity.
[0056] Step S225: Calculate the difference between the regional similarity and the 100% similarity to obtain the regional publicity difficulty of the target advertisement.
[0057] For example, if the regional similarity is 60%, then the difference from the 100% similarity is 100% - 60% = 40%. The higher the similarity, the lower the regional publicity difficulty.
[0058] Step S226: If there is no targeted publicity region for the promoted product, the regional publicity difficulty of the target advertisement is 0.
[0059] In practical applications, if there is no targeted publicity region for the promoted product, the difficulty of promoting in each region is the same. Setting the regional publicity difficulty of the target advertisement to 0 is conducive to subsequent analysis of the publicity difficulty value of the target advertisement.
[0060] The steps to extract the media information of the publicity medium and analyze the media publicity difficulty of the target advertisement based on the media information are as follows: Step S231: Extract the media information of the publicity medium, where the media information includes the target audience and the media popularity.
[0061] Different media have different audiences, and at the same time, the media popularity is also different. For example, the audiences of radio media are mainly drivers, office workers, and students. These people usually choose to listen to the radio to obtain information or entertainment during commuting or study breaks.
[0062] Step S232: Determine whether the promoted product has a targeted user. If the promoted product has a targeted user, then compare the similarity between the targeted user and the target audience to obtain the user similarity.
[0063] Different products target different users. For example, children's clothing mainly targets parents and children. Based on the targeted users, targeted features for the users can be extracted, and the user similarity can be calculated through methods such as the Pearson correlation coefficient.
[0064] Step S233, if the promoted product does not target a user, the user similarity is 100%.
[0065] Step S234, obtain the audience information of the target audience, and confirm the degree of trust of the target audience in the medium based on the audience information to obtain the medium trust degree.
[0066] Step S235, comprehensively combine the user similarity, medium popularity, and medium trust degree to obtain the medium promotion difficulty of the target advertisement.
[0067] In practical applications, the weight ratios of the user similarity, medium popularity, and medium trust degree are set respectively, and the medium promotion difficulty is calculated based on the weight ratios. When the user similarity is higher, it means that the user has a higher demand for the promoted product and it is easier to promote, so the medium promotion difficulty is lower. And the greater the medium popularity, the greater the probability that the advertisement will be seen and read, so the difficulty of promoting on this promotional medium is smaller. And the higher the medium trust degree, the higher the trust degree of the user in the advertisement, the more willing the user is to believe the advertisement, and the difficulty of promoting through the advertisement will be reduced, so the medium promotion difficulty will be reduced.
[0068] The steps of the medium information including the target audience and medium popularity are as follows: Step S2311, determine whether the condition for the user to view and read the target advertisement is that the user owns the promotional medium. If the condition is that the user owns the promotional medium, count the number of people who own the promotional medium, and calculate the medium occupancy rate based on the number of people who own it and the total population.
[0069] The conditions for viewing advertisements on different media are different. For example, for the advertisement promotion of some APPs, the APP needs to be downloaded to view the advertisement, while for the promotion of some billboards and advertising screens, the user does not need to own the billboard or advertising screen to see the advertisement. If the condition for viewing and reading the advertisement is that the user needs to own the promotional medium, count the number of people who own the promotional medium, and the proportion of the number of people who can see the advertisement can be obtained.
[0070] Step S2312, if the condition is not that the user owns the promotional medium, obtain the promotional range of the promotional medium, and count the total promotional range of the promotional medium based on the promotional range.
[0071] If the advertisement can be seen without occupying the advertising medium, the advertising scope of the advertising medium is counted according to the advertising scope of the advertising medium. The advertising scope of the advertising medium refers to the range within which users can see the advertising medium. For example, the advertising scope of the billboard in the elevator is limited to the elevator area. If the elevator is 3 square meters, the advertising scope is 3 square meters. Obtain the placement quantity of the advertising medium, and count the total advertising scope of the advertising medium according to the placement quantity and the advertising scope.
[0072] Step S2313: Obtain the total population scope, and obtain the media occupancy rate of the target advertisement according to the ratio of the total advertising scope to the total population scope.
[0073] Search for the total range of population activities and record it as the total population scope. Obtain the media occupancy rate according to the ratio of the total advertising scope to the total population scope, which reflects how many people may see the advertisement.
[0074] Step S2314: Obtain the average usage duration of the advertising medium, set user characteristics, and count the coverage scope of different user characteristics of the target audience to obtain the characteristic coverage scope.
[0075] The target audiences of different media are different, and the coverage scopes are also different. For example, if the user characteristic is set as age, then count the age range of the target audience, that is, the characteristic coverage scope. If the user characteristic is set as height, then the height range of the target audience is the characteristic coverage scope.
[0076] Step S2315: Overlay the characteristic coverage scopes of all user characteristics to obtain the group coverage scope of the target advertisement.
[0077] When the group coverage scope is larger, it indicates that more types of users are used. For example, the use of mobile phone APPs almost covers all users. Therefore, the characteristic coverage scope is large, and the group coverage scope is also large. However, the target audiences of magazines and newspapers are very different and tend to cover a certain type of group. Therefore, the group coverage scope is relatively small.
[0078] Step S2316: Synthesize the media occupancy rate, average usage duration, and group coverage scope to obtain the media popularity of the advertising medium.
[0079] In actual application, the proportional coefficients of the media occupancy rate, average usage duration, and group coverage scope are set respectively, and the media popularity of the advertising medium is calculated according to the proportional coefficients. When the media occupancy rate is larger, it indicates that the popularity of the medium is higher. When the average usage duration is larger, it indicates that the usage rate of the medium is relatively high. Therefore, it reflects a higher popularity. When the group coverage scope is wider, more groups are contacted by the medium. Therefore, it also reflects a higher media popularity.
[0080] Obtain the audience information of the target audience, and confirm the degree of trust of the target audience in the medium based on the audience information. The steps to obtain the medium trust degree are as follows: Step S2341: Obtain the audience information of the target audience. The audience information includes the audience age and the audience education level.
[0081] Calculate the average age and the average education level as the audience age and the audience education level through the age information and education information authorized by the user on the medium.
[0082] Step S2342: Collect the probability of being deceived in the promotional medium for different ages, and find the probability of being deceived corresponding to the audience age and record it as the age deception probability.
[0083] Because the probability of being deceived of people of different ages is different.
[0084] Step S2343: Statistically analyze the probability of being deceived in the promotional medium for different education levels, and find the probability of being deceived corresponding to the audience education level and record it as the education deception probability.
[0085] Moreover, the probability of being deceived of groups with different education levels is also different, and the probability of being deceived corresponding to different education levels can be statistically analyzed.
[0086] Step S2344: Combine the age deception probability and the education deception probability to obtain the audience prudence degree of the target audience.
[0087] Respectively set the weight ratios of the age deception probability and the education deception probability, and calculate the audience prudence degree of the target audience according to the weight ratios.
[0088] Step S2345: Obtain the medium authenticity degree of the promotional medium, and combine the audience prudence degree to obtain the medium trust degree.
[0089] In practical applications, when the medium authenticity degree is higher, the audience's trust degree in it will be higher. And when the audience prudence degree is higher, the audience will be vigilant about the medium, so the trust degree in the medium is lower. The medium trust degree also seriously affects the advertising promotion effect. When the medium trust degree is lower, users do not trust the information on the medium, so they also have a certain degree of suspicion about the advertising information, and thus the number of people placing orders for purchase will decrease significantly.
[0090] The steps to obtain the medium authenticity degree of the promotional medium and combine the audience prudence degree to obtain the medium trust degree are as follows: Step S23451: Obtain the review system of the promotional medium, and extract the average review times and the average review duration according to the review system.
[0091] Step S23452: Obtain the historical promotion data of the promotional medium, and statistically analyze the error rate of the promotional content according to the historical promotion data.
[0092] Step S23453: Obtain the media authenticity based on the average review times, average review duration, and error rate of promotional content respectively.
[0093] Set the weight ratios of the average review times, average review duration, and error rate of promotional content respectively, and calculate the media authenticity based on the weight ratios.
[0094] Step S23454: Set the weight ratio of the media authenticity and the audience prudence respectively, and calculate the media trust based on the weight ratio.
[0095] In practical applications, the media authenticity is usually related to the review of the media platform. When the review duration is longer and the review times are more, it indicates that the review is more stringent, and the error rate will be greatly reduced. At the same time, the lower the error rate of the promotional content, the more truthful and reliable its promotional content is. When the authenticity of the media is higher, it is conducive to the target audience trusting the media more, thus believing the advertising content and reducing the advertising difficulty. When users do not trust the media, they will be skeptical of the advertising information on the media and also distrust the advertised products, thus greatly increasing the advertising difficulty.
[0096] An advertising effect evaluation system based on big data, by applying an advertising effect evaluation method based on big data as described above, includes: Basic effect module: Obtain the target advertisement, extract the promoted product in the target advertisement, obtain the sales data of the promoted product, and obtain the basic effect value of the target advertisement according to the sales data.
[0097] Promotion difficulty module: Obtain the promotion time, promotion region, and promotion media of the target advertisement, and evaluate the promotion difficulty value of the target advertisement according to the promotion time, promotion region, and promotion media.
[0098] Actual effect module: Combine the basic effect value and the promotion difficulty value to confirm the actual effect of the target advertisement and obtain the actual effect value.
[0099] Promotion feedback module: Feedback the actual effect value to the user terminal and adjust the advertising promotion plan according to the actual effect value.
[0100] The above are all the preferred embodiments of this application. It does not limit the protection scope of this application accordingly. Therefore, all equivalent changes made according to the structure, shape, and principle of this application should be covered within the protection scope of this application.
Claims
1. An advertising effect evaluation method based on big data, characterized in that, It includes the following steps: Obtain a target advertisement, extract the promoted product in the target advertisement, obtain the sales data of the promoted product, and obtain the basic effect value of the target advertisement according to the sales data; Obtain the publicity time, publicity region, and publicity medium of the target advertisement, and evaluate the publicity difficulty value of the target advertisement according to the publicity time, publicity region, and publicity medium; Combine the basic effect value and the publicity difficulty value to confirm the actual effect of the target advertisement and obtain the actual effect value; Feed back the actual effect value to the user terminal and adjust the advertisement publicity plan according to the actual effect value.
2. The method for evaluating the advertising effect based on big data according to claim 1, wherein The steps of obtaining the target advertisement, extracting the promoted product in the target advertisement, obtaining the sales data of the promoted product, and obtaining the basic effect value of the target advertisement according to the sales data are specifically as follows: Obtain the sales data of the promoted product, and the sales data includes real-time sales volume, real-time consultation volume, and real-time view volume; Obtain the original sales volume and original consultation volume before the target advertisement is put on the market, calculate the difference between the real-time sales volume and the original sales volume, and obtain the sales volume difference; Calculate the difference between the real-time consultation volume and the original consultation volume to obtain the consultation difference, calculate the ratio of the real-time sales volume to the real-time consultation volume to obtain the consultation conversion rate; Calculate the ratio of the real-time consultation volume to the real-time view volume to obtain the view conversion rate, respectively set the proportionality coefficients of the sales volume difference, consultation difference, consultation conversion rate, and view conversion rate, and calculate the basic effect value according to the proportionality coefficients.
3. A method for evaluating the advertising effect based on big data according to claim 1, characterized in that, The steps of obtaining the publicity time, publicity region, and publicity medium of the target advertisement, and evaluating the publicity difficulty value of the target advertisement according to the publicity time, publicity region, and publicity medium are specifically as follows: Obtain the publicity time, publicity region, and publicity medium of the target advertisement, and analyze the time publicity difficulty of the target advertisement according to the publicity time; Obtain the targeted region of the promoted product, and analyze the regional publicity difficulty of the target advertisement in combination with the publicity region; Extract the medium information of the publicity medium, and analyze the medium publicity difficulty of the target advertisement according to the medium information; Integrate the time publicity difficulty, regional publicity difficulty, and medium publicity difficulty of the target advertisement to obtain the publicity difficulty value of the target advertisement.
4. The method for evaluating advertising effect based on big data according to claim 3, wherein, The steps of analyzing the time publicity difficulty of the target advertisement according to the publicity time are specifically as follows: Obtain the historical sales data of the promoted product, calculate the sales volume difference between adjacent times according to the historical sales data, and record it as the sales volume fluctuation value; Judge whether the sales volume fluctuation value reaches the preset fluctuation threshold. If it reaches the preset fluctuation threshold, obtain the historical sales average value corresponding to the publicity time and record it as the publicity sales value; Extract the time period with the highest historical sales volume as the standard time period according to the historical sales data, and calculate the historical sales average value of the standard time period and record it as the standard sales value; Calculate the difference between the publicity sales value and the standard sales value and record it as the publicity difference, compare the ratio of the publicity difference to the standard sales value, and obtain the time publicity difficulty; If the sales volume fluctuation value does not reach the preset fluctuation threshold, the time publicity difficulty is 0.
5. The method for evaluating advertising effects based on big data according to claim 3, wherein, The steps of obtaining the targeted region of the promoted product and analyzing the regional publicity difficulty of the target advertisement in combination with the publicity region are specifically as follows: Judge whether the promoted product has a targeted promotion region. If there is a targeted promotion region, record it as the targeted region; Obtain the factors for the regions targeted by the promoted product and record them as the standard regional factors; Obtain the regional factors of the same type as the standard regional factors for the publicity region and record them as the real-time regional factors; Compare the factor similarity between the standard regional factors and the real-time regional factors, calculate the average value of all factor similarities, and obtain the regional similarity; Calculate the difference between the regional similarity and the 100% similarity to obtain the regional publicity difficulty of the target advertisement; If there is no targeted promotion region for the promoted product, the regional publicity difficulty of the target advertisement is 0.
6. The method for evaluating the advertising effect based on big data according to claim 3, wherein The step of extracting the media information of the publicity medium and analyzing the media publicity difficulty of the target advertisement according to the media information is specifically as follows: Extract the media information of the publicity medium, and the media information includes the target audience and the media popularity; Judge whether the promoted product has a targeted user. If the promoted product has a targeted user, then compare the similarity between the targeted user and the target audience to obtain the user similarity; If the promoted product has no targeted user, the user similarity is 100%; Obtain the audience information of the target audience, and confirm the degree of trust of the target audience in the medium according to the audience information to obtain the media trust degree; Combine the user similarity, the media popularity, and the media trust degree to comprehensively obtain the media publicity difficulty of the target advertisement.
7. The method for evaluating advertising effect based on big data according to claim 6, characterized in that, The step that the media information includes the target audience and the media popularity is specifically as follows: Judge whether the condition for the user to view and read the target advertisement is that the user owns the publicity medium. If the condition is that the user owns the publicity medium, then count the number of people who own the publicity medium, and calculate the media occupancy rate according to the number of people who own the publicity medium and the total population; If the condition is not that the user owns the publicity medium, then obtain the publicity scope of the publicity medium, and count the total publicity scope of the publicity medium according to the publicity scope; Obtain the total population scope, and obtain the media occupancy rate of the target advertisement according to the ratio of the total publicity scope to the total population scope; Obtain the average usage duration of the publicity medium, set user characteristics, and count the coverage range of the target audience for different user characteristics to obtain the characteristic coverage range; Overlay the characteristic coverage ranges of all user characteristics to obtain the group coverage range of the target advertisement; Comprehensively combine the media occupancy rate, the average usage duration, and the group coverage range to obtain the media popularity of the publicity medium.
8. A method for evaluating the advertising effect based on big data according to claim 6, characterized in that, The step of obtaining the audience information of the target audience, and confirming the degree of trust of the target audience in the medium according to the audience information to obtain the media trust degree is specifically as follows: Obtain the audience information of the target audience, and the audience information includes the audience age and the audience education level; Collect the probability of being deceived of different ages in the publicity medium, search for the probability of being deceived corresponding to the audience age and record it as the age deception probability; Statistically calculate the probability of being deceived of different education levels in the publicity medium, search for the probability of being deceived corresponding to the audience education level and record it as the education deception probability; Combine the age deception probability and the education deception probability to obtain the audience caution degree of the target audience; Obtain the media authenticity of the publicity medium, and combine the audience caution degree to obtain the media trust degree.
9. The method for evaluating the advertising effect based on big data according to claim 8, wherein The step of obtaining the media authenticity of the publicity medium, and combining the audience caution degree to obtain the media trust degree is specifically as follows: Obtain the review system of the publicity medium, and extract the average number of reviews and the average review duration according to the review system; Obtain the historical publicity data of the publicity medium, and calculate the error rate of the publicity content based on the historical publicity data; Obtain the medium authenticity respectively according to the average review times, average review duration and error rate of the publicity content; Set the weight ratios of the medium authenticity and the audience caution respectively, and calculate the medium trust based on the weight ratios.
10. An advertising effect evaluation system based on big data, characterized in that, By applying a big data-based advertising effect evaluation method as described in any one of claims 1-9, including: A basic effect module, which obtains a target advertisement, extracts the promoted product in the target advertisement, obtains the sales data of the promoted product, and obtains the basic effect value of the target advertisement according to the sales data; A publicity difficulty module, which obtains the publicity time, publicity region and publicity medium of the target advertisement, and evaluates the publicity difficulty value of the target advertisement according to the publicity time, publicity region and publicity medium; An actual effect module, which combines the basic effect value and the publicity difficulty value to confirm the actual effect of the target advertisement and obtain the actual effect value; A publicity feedback module, which feeds back the actual effect value to the user terminal and adjusts the advertising publicity plan according to the actual effect value.