CN110097388A - A kind of web advertisement data analysing method - Google Patents
A kind of web advertisement data analysing method Download PDFInfo
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- CN110097388A CN110097388A CN201810093961.XA CN201810093961A CN110097388A CN 110097388 A CN110097388 A CN 110097388A CN 201810093961 A CN201810093961 A CN 201810093961A CN 110097388 A CN110097388 A CN 110097388A
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- 238000000034 method Methods 0.000 title claims abstract description 41
- 238000012545 processing Methods 0.000 claims abstract description 32
- 238000002372 labelling Methods 0.000 claims abstract description 22
- 238000013523 data management Methods 0.000 claims abstract description 19
- 238000001914 filtration Methods 0.000 claims abstract description 17
- 238000004140 cleaning Methods 0.000 claims abstract description 12
- 238000010606 normalization Methods 0.000 claims abstract description 11
- 230000002159 abnormal effect Effects 0.000 claims abstract description 5
- 238000007418 data mining Methods 0.000 claims abstract description 5
- 230000013011 mating Effects 0.000 claims description 8
- 230000002123 temporal effect Effects 0.000 claims description 8
- 238000007726 management method Methods 0.000 claims description 4
- 238000013507 mapping Methods 0.000 claims description 4
- 238000010801 machine learning Methods 0.000 abstract description 4
- 230000006399 behavior Effects 0.000 description 28
- 235000020095 red wine Nutrition 0.000 description 18
- 238000007405 data analysis Methods 0.000 description 7
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/10—File systems; File servers
- G06F16/18—File system types
- G06F16/1805—Append-only file systems, e.g. using logs or journals to store data
- G06F16/1815—Journaling file systems
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
- G06F16/215—Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0242—Determining effectiveness of advertisements
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0251—Targeted advertisements
Abstract
It the present invention relates to a kind of web advertisement data analysing method, is run based on server, the business datum, external data when the data of the website or APP that count on when comprising steps of (1) burying advertiser by adding code, advertisement are launched input advertisement log data library；(2) the daily record data information after summarizing in advertisement log data library is issued into data normalization processing module, data filtering cleaning module is sent to after being standardized；(3) valid data are sent to data label processing module by data filtering cleaning module filtering cheating data and abnormal data；(4) data label processing module carries out machine learning and data mining to data according to the label model rule that labeling data management module is sent, and will be sent to labeling data management module after data labelization processing；(5) labeling data management module synchrodata is to external data platform.The present invention uses labeling data mode precise positioning advertisement target group, has the characteristics that precision marketing.
Description
Technical field
The present invention relates to a kind of web advertisement data analysing methods, in particular to one kind being capable of precise positioning advertising objective group
The web advertisement data analysing method of body belongs to web advertisement data analysis field.
Background technique
The characteristics of either deisgn product or daily operation understand the true situation of target user, find their behaviors
With motivation, and it is classified and be layered by certain logic, is the basis of each Marketing group work, also determines them
Audient can be precisely caught, is won victory with differentiated service.The mode for developing extreme shock advertisement and launching of internet, works as tradition
When the method that advertisement is casted net has been unable to satisfy precision marketing demand, hobby and characteristic based on user, which launch advertisement, becomes master
Stream.It arrives at a station outer channel from electric business using the information displaying of the prime locations such as interior banner, as APP is spread its tail patch before advertisement, video
Advertisement etc. instructs advertisement to launch, can not only reduce cost using user's representation data, can also greatly promote clicking rate and
Conversion ratio promotes Integral advertisement and launches effect.
Summary of the invention
Inventive network ad data analysis method discloses new scheme, wide using labeling data mode precise positioning
Target group are accused, solve the problems, such as that existing scheme is unable to satisfy precision marketing demand.
Inventive network ad data analysis method, web advertisement data analysing method are run based on server, server
Including Data Input Interface, advertisement log data library, data normalization processing module, data filtering cleaning module, data label
Change processing module, labeling data management module, data output interface, comprising steps of (1) by advertiser by adding code to bury a little
When the data of website or APP that count on, advertisement business datum when launching, external data by Data Input Interface input extensively
Accuse log database；(2) the daily record data information after summarizing in advertisement log data library is issued into data normalization processing module,
Data normalization processing module is sent to data filtering cleaning module after being standardized to daily record data information；(3) data
Filtering cleaning module cleans data, and valid data are sent to data label by filtering cheating data and abnormal data
Processing module；(4) the label model rule that data label processing module is sent according to labeling data management module to data into
Row machine learning and data mining will be sent to labeling data management module after data labelization processing；(5) labeling data
Management module passes through data output interface synchrodata to external data platform.
Further, in step (1), business datum when advertisement is launched includes exposure, hits to the method for this programme,
External data includes advertiser's customer relation management data, electric business transaction data, third party's data management platform data.
Further, in step (1), Data Input Interface includes receiving number interface, mating interface to the method for this programme, extensively
Accuse the data of the main website or APP counted on when burying by adding code, business datum when advertisement is launched is by receiving number interface
Advertisement log data library is inputted, external data inputs advertisement log data library by mating interface.
Further, the method for this programme in step (1), is used the data in all sources only using User ID mapping table
One ID mark.
Further, the method for this programme step (4) in, label model includes user identity information, user behavior time
Information, user contact point information, user behavior type information, user identity information for distinguish, One-Point Location user, Yong Huhang
It include time point information, time segment information, the time point of time point information identity user behavior, time segment information for temporal information
For identity user in the residence time of contact point, user behavior temporal information determines the decay factor information of label model, user
Contact point information includes web page address information, web page content information, and web page address information determines network address weight information, in webpage
Hold information and determines that model label information, user behavior type information determine user behavior weight information.
Further, the weight of the label model of the method for this programme is decay factor information, user behavior weight information, net
The product of location weight information.
Inventive network ad data analysis method uses labeling data mode precise positioning advertisement target group, has
The characteristics of precision marketing.
Detailed description of the invention
Fig. 1 is the flow chart of inventive network ad data analysis method.
Specific embodiment
Inventive network ad data analysis method, web advertisement data analysing method are run based on server, server
Including Data Input Interface, advertisement log data library, data normalization processing module, data filtering cleaning module, data label
Change processing module, labeling data management module, data output interface, comprising steps of (1) by advertiser by adding code to bury a little
When the data of website or APP that count on, advertisement business datum when launching, external data by Data Input Interface input extensively
Accuse log database；(2) the daily record data information after summarizing in advertisement log data library is issued into data normalization processing module,
Data normalization processing module is sent to data filtering cleaning module after being standardized to daily record data information；(3) data
Filtering cleaning module cleans data, and valid data are sent to data label by filtering cheating data and abnormal data
Processing module；(4) the label model rule that data label processing module is sent according to labeling data management module to data into
Row machine learning and data mining will be sent to labeling data management module after data labelization processing；(5) labeling data
Management module passes through data output interface synchrodata to external data platform.Above scheme is accurate using labeling data mode
Positioning advertising target group reduce the input cost of advertiser.
In order to improve the collection and transmission of data, differentiate the source of data, the method for this programme in step (1), advertisement
Business datum when dispensing includes exposure, hits, and external data includes advertiser's customer relation management data, electric business number of deals
According to, third party's data management platform data.The method of this programme in step (1), Data Input Interface include receive number interface,
Mating interface, the business datum when data of a website or APP that advertiser counts on when being buried by adding code, advertisement are launched are logical
Receipts number interface input advertisement log data library is crossed, external data inputs advertisement log data library by mating interface.This programme
Method in step (1), using User ID mapping table identifies the unique ID of the data in all sources.
In order to realize the labeling of data, the method for this programme step (4) in, label model includes user identifier letter
Breath, user behavior temporal information, user contact point information, user behavior type information, user identity information for distinguish, single-point
Position user, user behavior temporal information includes time point information, time segment information, time point information identity user behavior when
Between point, period message identification user determines declining for label model in the residence time of contact point, user behavior temporal information
Subtracting coefficient information, user contact point information includes web page address information, web page content information, and web page address information determines network address
Weight information, web page content information determine that model label information, user behavior type information determine that user behavior weight is believed
Breath.In order to determine that label weight, the weight of the label model of the method for this programme are decay factor information, user behavior weight letter
The product of breath, network address weight information.
This programme discloses a kind of Internet ad data analysis method, can be realized by following procedure.
Process 1
First party, second party, third party's data are input to subscriber data center (advertisement log data library), comprising: first party
The data of the website or APP that count on when advertiser buries by adding code, second party are transmitted by receiving number by receiving number interface
The external number that business datum (such as exposure, hits) when interface transmission advertisement is launched, third party are transmitted by mating interface
According to (including advertiser's CRM data, electric business transaction data, third party's DMP data etc.).
Process 2
Simultaneously log Log is written in transmitting data information, including receipts number interface and mating interface (input interface) transmit data to log
Arrange storage.It should be noted that user identifier is inconsistent, especially under PC environment since the source that data input is more
Cookie, it is therefore desirable to which User ID mapping table gets through the data in all sources with unique ID.
Process 3
Log management is stored the data information after summarizing (including structural data, semi-structured data and unstructured data)
Issue data processing service.
Process 4
Data processing service (data normalization processing module) is standardized log information, is sent to analysis engine.
Process 5
Analysis engine (data filtering cleaning module) cleans data, and filtering cheating data and other abnormal datas will have
Effect data are sent to algorithm center.
Process 6
Algorithm center (data label processing module) combination tag model rule carries out machine learning and data mining to data,
Tag control platform will be returned to after data labelization processing.
Process 7
Tag control platform (labeling data management module) by data output interface synchrodata to each data application platform,
Such as DSP, PCP, AdX/SSP or other platforms.
The data processed result of this programme is to obtain user's crowd portrayal, and whether user's crowd portrayal is precisely test data
The key index of processing capacity.How the core that model output label, weight are data processings constructed according to user behavior.One
Event model (label model) includes three time, place, personage elements.User behavior is substantially a Random event each time
Part can be described in detail are as follows: what user at what time, what place what has done." what user " key is pair
The mark of user, the purpose of user identifier are to distinguish user, One-Point Location." when ", the time includes two important
Information, timestamp, time span.Timestamp is the time point for identity user behavior, can be as accurate as second or microsecond, usually
Using the timestamp for being accurate to the second.Time span is in order to which identity user is in the residence time of a certain page." what ground
Point " is user contact point (Touch Point), and each user contact point is potential to contain two layers of information, i.e. network address, content.Often
One url link (page/screen) located an internet page address or the specific webpage of some product, can be PC
The page url of certain upper electric business website is also possible to the microblogging on mobile phone, wechat etc. and answers using some function pages, certain product
Specific picture, such as Great Wall red wine single-item page, the wechat subscription page, the page that reaches a standard of certain game etc..Each url network address
Content in (page/screen) can be the relevant information of single-item, such as classification, brand, description, attribute, site information etc..
For example, red wine, Great Wall, extra dry red wine, for each internet contact point, wherein network address determines that weight, content determine label.
Contact point can be network address, be also possible to the specific function interface of some product.For example, same one bottle of mineral water,
Supermarket sells 1 yuan, 3 yuan is sold on train, scenic spot sells 5 yuan.The sale price of commodity does not lie in cost, is more market location.Label
It is mineral water, but the difference of contact point has embodied weight difference.Here weight can be understood as user for mineral water
Desirability it is different, that is, be ready that the price of payment is different.That is label weight: 1//supermarket of mineral water, 3//train of mineral water, mine
5//scenic spot of spring.Similar, user is showed in Jingdone district store browsing red wine information in product still red wine net browsing red wine information
It is also out discrepant to the preference degree of red wine.Here focus is different network address there are weight difference, weight model
Building is needed according to respective business demand.So network address itself characterizes the label preference weight of user, network address is corresponding interior
Appearance embodies label information.
" what " is to say user behavior type, has a following typical behaviour for electric business: browsing, addition shopping cart, search,
It comments on, buy, thumb up, collect.The label information that different behavior types generates the content of contact point has different
Weight.For example, the weight of " purchase " is calculated as 5, the weight of " browsing " is calculated as 1, i.e. red wine 1//browsing red wine, red wine 5//purchase is red
Wine.The data model (label model) of the above analysis, user's portrait may be summarized to be following formula: user identifier+when
Between+behavior type+contact point (network address+content), i.e. user because at what time, what place done can be labeled with phase
The label answered.The weight of user tag may increase at any time and decay, therefore defining the time is decay factor, behavior class
Type, network address determine that weight, content determine label, are further converted into formula: label weight=decay factor × behavior weight
The sub- weight of × network address.It is illustrated below.
User's A yesterday browses the Great Wall Dry Red Wine information of one bottle of 238 yuan of value in product still red wine net.Therefore, label:
Red wine, Great Wall；Time: because being the behavior of yesterday, it is assumed that decay factor are as follows: r=0.95；Behavior type: browsing behavior is denoted as
Weight 1；Place: the sub- weight of network address of product still red wine single-item page is denoted as 0.9.Assuming that user to red wine for really liking, just meeting
The red wine net of profession is gone to choose, without choosing in comprehensive store, then user preference label is red wine, and weight is 0.95 × 0.9 × 1
﹦ 0.855, i.e. user A: red wine 0.855, Great Wall 0.855.The selection of above-mentioned Model Weight value is the algorithm thinking of this programme, tool
The weighted value needs of body carry out two modelings according to business demand, remove building user's portrait model from whole thinking, and then gradually
Refined model.This programme realizes precise positioning and arrives as a result, to promote advertiser's web advertisement investment conversion ratio as primary index
Advertising objective crowd reduces invalid advertisement and launches consumption, reduces the input cost of advertiser.Based on the above feature, we
The web advertisement data analysing method of case has substantive distinguishing features outstanding and significant progress compared to existing scheme.
The web advertisement data analysing method of this programme is not limited to content disclosed in specific embodiment, in embodiment
The technical solution of appearance can the understanding based on those skilled in the art and extend, those skilled in the art combine according to this programme
The simple replacement scheme that common knowledge is made also belongs to the range of this programme.
Claims (6)
1. a kind of web advertisement data analysing method, the web advertisement data analysing method is run based on server, the clothes
Business device includes Data Input Interface, advertisement log data library, data normalization processing module, data filtering cleaning module, data
Labeling processing module, labeling data management module, data output interface, it is characterized in that comprising steps of
(1) business datum when the data of the website or APP that count on when advertiser being buried by adding code, advertisement are launched, outer
Portion's data input advertisement log data library by Data Input Interface；
(2) the daily record data information after summarizing in advertisement log data library is issued into data normalization processing module, data normalization
Processing module is sent to data filtering cleaning module after being standardized to daily record data information；
(3) data filtering cleaning module cleans data, and valid data are sent to by filtering cheating data and abnormal data
Data label processing module；
(4) data label processing module carries out machine to data according to the label model rule that labeling data management module is sent
Device study and data mining will be sent to labeling data management module after data labelization processing；
(5) labeling data management module passes through data output interface synchrodata to external data platform.
2. web advertisement data analysing method according to claim 1, which is characterized in that in step (1), advertisement is launched
When business datum include exposure, hits, external data include advertiser's customer relation management data, electric business transaction data,
Third party's data management platform data.
3. web advertisement data analysing method according to claim 1, which is characterized in that in step (1), data input
Interface includes receiving number interface, mating interface, the data of a website or APP that advertiser counts on when being buried by adding code, advertisement
Business datum when dispensing inputs advertisement log data library by receiving number interface, and external data inputs advertisement day by mating interface
Will database.
4. web advertisement data analysing method according to claim 1, which is characterized in that in step (1), using user
ID mapping table identifies the unique ID of the data in all sources.
5. web advertisement data analysing method according to claim 1, which is characterized in that step (4) in, label model
Including user identity information, user behavior temporal information, user contact point information, user behavior type information, user identifier letter
It ceases for distinguishing, One-Point Location user, user behavior temporal information includes time point information, time segment information, time point information
The time point of identity user behavior, period message identification user determine in the residence time of contact point, user behavior temporal information
Determine the decay factor information of label model, user contact point information includes web page address information, web page content information, webpage
Location information determines network address weight information, and web page content information determines that model label information, user behavior type information determine
User behavior weight information.
6. web advertisement data analysing method according to claim 5, which is characterized in that the weight of label model is decaying
The product of factor information, user behavior weight information, network address weight information.
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| CN110852812A (en) * | 2019-11-20 | 2020-02-28 | 满江(上海)软件科技有限公司 | Advertisement information monitoring system |
| DE202022102520U1 (en) | 2022-05-09 | 2022-05-23 | Yashwant Singh Chouhan | System for analyzing advertising on online video platforms for digital marketing through machine learning to reach wide audiences |
| CN116805255A (en) * | 2023-06-05 | 2023-09-26 | 深圳市瀚力科技有限公司 | Advertisement automatic optimizing throwing system based on user image analysis |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110602533A (en) * | 2019-09-10 | 2019-12-20 | 四川长虹电器股份有限公司 | Intelligent television advertisement recommendation system and method for time-sharing and crowd-sharing |
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| CN116805255A (en) * | 2023-06-05 | 2023-09-26 | 深圳市瀚力科技有限公司 | Advertisement automatic optimizing throwing system based on user image analysis |
| CN116805255B (en) * | 2023-06-05 | 2024-04-23 | 深圳市瀚力科技有限公司 | Advertisement automatic optimizing throwing system based on user image analysis |
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