CN108846034A - A method of about user behavior analysis - Google Patents
A method of about user behavior analysis Download PDFInfo
- Publication number
- CN108846034A CN108846034A CN201810525541.4A CN201810525541A CN108846034A CN 108846034 A CN108846034 A CN 108846034A CN 201810525541 A CN201810525541 A CN 201810525541A CN 108846034 A CN108846034 A CN 108846034A
- Authority
- CN
- China
- Prior art keywords
- user
- data
- behavior
- analysis
- website
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Abstract
The invention discloses a kind of method about user behavior analysis, S1, acquisition user behavior record, all behaviors that acquisition user occurs on website；S2 analyzes user, establishes analysis dimension with humanistic visions such as the region of user, gender, ages with carrying out various dimensions；S3 is adequately counted and is recorded to the consumption information of user；S4 carries out the analysis of emphasis data to the behavior of user；The data information of emphasis is cleaned, is converted, extracted and is calculated by S5.This kind of invention is after periodically obtaining user behavior, after over cleaning, conversion, Macro or mass analysis, finally the good result data of Macro or mass analysis is loaded into corresponding table according to the database model pre-defined, user more intuitive can detect the behavioral statistics record of user, it is convenient for analyzing, simpler, use is more convenient.
Description
Technical field
The present invention relates to information technology field, especially a kind of method about user behavior analysis.
Background technique
User behavior refers to the interbehavior of user Yu product UI, is mainly manifested in Android App, iOS App
In Web page.These interbehaviors, some meetings are communicated with back-end services, and some only causes the variation of front end UI, still
Regardless of behavior, behind invariably accompanies one group of attribute data.For the behavior interacted with rear end, Wo Menke
To take related data from back-end services log, service database；And those are occurred only at the behavior of front end, then
It needs just know by front end active reporting to rear end.User behavior data acquisition system is responsible for from front-end collection institute
The complete user behavior information needed, for data analysis and other business.
User behavior analysis refers in the case where obtaining website visiting amount master data, unites to related data
Meter, analysis therefrom find that user accesses the rule of website, and these rules are combined with net marketing strategy etc., to send out
Now in current network marketing activity there may be the problem of, and provided further to correct or reformulating net marketing strategy
Foundation.This is the user behavior analysis of narrow sense only referred on network.
Currently, with the development of science and technology, the fused many user behavior analysis systems of various industries business model,
However government lacks the software systems of this part.
For above problem, herein it is proposed that a kind of method about user behavior analysis.
Summary of the invention
The present invention provides a kind of method about user behavior analysis for the deficiency in background technique.
The present invention is to solve above-mentioned technical deficiency, using modified technical solution, a kind of side about user behavior analysis
Method, S1, acquisition user behavior record, all behaviors that acquisition user occurs on website；
S2 analyzes user, establishes analysis dimension with humanistic visions such as the region of user, gender, ages with carrying out various dimensions
Degree；
S3 is adequately counted and is recorded to the consumption information of user；
S4 carries out the analysis of emphasis data to the behavior of user；
The data information of emphasis is cleaned, is converted, extracted and is calculated by S5.
As present invention further optimization mode, in step S1, acquire user behavior include including search, browsing,
Marking, comment, part chat record, further include the corelation behaviour on third party website, and such as the rate of exchange see related evaluation and test, participate in
Discussion, the exchange in social media are interacted with good friend.
As present invention further optimization mode, in step S3, consumption information includes the consumption information all to user
It is counted, including whether the past has click, if there is purchase, whether be added that shopping cart is to be paid, the value of the product of purchase,
When the frequency of purchase, the last time are bought, and all consumption information attributes are carried out list data quantization, simultaneously
Information attribute to be consumed is subjected to list data quantization.
As present invention further optimization mode, in step S4, the analysis of emphasis data include user area of source,
Incoming road domain name and the page；User website residence time, jump out rate, return visit person, new visitor, pay a return visit number, pay a return visit be separated by
Number of days；User and nonregistered user are registered, browsing habit between the two is analyzed；Search engine used by a user, key
Word, association keyword and interior keyword of standing；Which type of entry form user selects, and advertisement or web portal link are more
Effectively；Whether user accesses website process, reasonable for analyzing page structure design；Webpage hotspot graph of the user on the page
Distributed data and web overlay data；Amount of access situation of the user in different periods；Font color of the user for website
Fancy grade.
As present invention further optimization mode, the data cleansing include the double typing comparison of data, data merge,
Repetition values are searched, missing values is searched and searches exceptional value, the wherein double typing comparisons of data reach in user data collected
Start after preset specified value, the data, which merge, carries out whole merging for the similar user data of acquisition.
As present invention further optimization mode, the lookup repetition values be will be used for multiple times website or comment or
Purchase information carries out unified record and carries out data reference.
As present invention further optimization mode, it is described search missing values be by user occur zero record information into
Row statistics；The lookup exceptional value is that user classifies beyond normal record data 5-100 multiple as exceptional value
Statistics.
The beneficial effects obtained by the present invention are as follows being：This kind of invention is after periodically obtaining user behavior, through over cleaning, conversion, remittance
After bulk analysis, finally the good result data of Macro or mass analysis is loaded into corresponding table according to the database model pre-defined
Go, user more intuitive can detect user behavioral statistics record, be convenient for analyzing, it is simpler, using compared with
For convenience.
Specific embodiment
Below in conjunction in the embodiment of the present invention, technical solution in the embodiment of the present invention is clearly and completely retouched
It states, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.Based on the present invention
In embodiment, every other implementation obtained by those of ordinary skill in the art without making creative efforts
Example, shall fall within the protection scope of the present invention.
The present invention provides a kind of technical solution：A method of about user behavior analysis, S1, acquisition user behavior note
Record, all behaviors that acquisition user occurs on website；
S2 analyzes user, establishes analysis dimension with humanistic visions such as the region of user, gender, ages with carrying out various dimensions
Degree；
S3 is adequately counted and is recorded to the consumption information of user；
S4 carries out the analysis of emphasis data to the behavior of user；
The data information of emphasis is cleaned, is converted, extracted and is calculated by S5.
In step S1, the behavior for acquiring user includes also wrapping including search, browsing, marking, comment, part chat record
Include the corelation behaviour on third party website, such as the rate of exchange, see it is related evaluate and test, participate in discussion, the exchange in social media, with it is good
Friend's interaction etc..
In step S3, consumption information includes that the consumption information all to user counts, including a little whether the past
It hits, if there is purchase, whether be added that shopping cart is to be paid, the value of the product of purchase, the frequency of purchase, what the last when
Purchase is waited, and all consumption information attributes are subjected to list data quantization, while information attribute to be consumed is subjected to table
Data quantization.
In step S4, the analysis of emphasis data includes area of source, incoming road domain name and the page of user；User is in website
Residence time, jump out rate, return visit person, new visitor, pay a return visit number, pay a return visit be separated by number of days；User and nonregistered user are registered,
The browsing habit of analysis between the two；Search engine, keyword, association keyword and interior keyword of standing used by a user；With
Which type of entry form family selects, and advertisement or web portal link are more effective；User accesses website process, is used to divide
Whether reasonable analyse page structure design；Webpage hotspot graph distributed data and web overlay data of the user on the page；User
In the amount of access situation of different periods；Fancy grade of the user for the font color of website.
The data cleansing includes the double typing comparisons of data, data merging, searches repetition values, searches missing values and lookup
Exceptional value, the wherein double typing comparisons of data start after user data collected reaches preset specified value, the number
The similar user data of acquisition is subjected to whole merging according to merging.
The lookup repetition values are will to carry out unifying to record counting with website or comment is used for multiple times or buys information
According to reference.
The missing values of searching are that the information that user to zero record occurs counts；The lookup exceptional value is will to use
Family carries out statistic of classification as exceptional value beyond normal record data 5-100 multiple.
To sum up state, this kind of invention is after periodically obtaining user behavior, after over cleaning, conversion, Macro or mass analysis, finally according to
The database model pre-defined is loaded into the good result data of Macro or mass analysis in corresponding table, and user can be more
The behavioral statistics record for intuitively detecting user, is convenient for analyzing, simpler, use is more convenient.
The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention, for this field
For technical staff, it is clear that invention is not limited to the details of the above exemplary embodiments, and without departing substantially from spirit of the invention
Or in the case where essential characteristic, the present invention can be realized in other specific forms.It therefore, in all respects, should all
Regard embodiment as exemplary, and be non-limiting, the scope of the present invention by appended claims rather than on
Bright restriction is stated, it is intended that including all changes that fall within the meaning and scope of the equivalent elements of the claims in this
In invention.
In addition, it should be understood that although this specification is described in terms of embodiments, but not each embodiment is only
It contains an independent technical solution, this description of the specification is merely for the sake of clarity, and those skilled in the art answer
When considering the specification as a whole, the technical solutions in the various embodiments may also be suitably combined, forms those skilled in the art
The other embodiments that member is understood that.
Claims (7)
1. a kind of method about user behavior analysis, which is characterized in that S1, acquisition user behavior record acquire user in net
All behaviors occurred on standing；
S2 analyzes user, establishes analysis dimension with humanistic visions such as the region of user, gender, ages with carrying out various dimensions；
S3 is adequately counted and is recorded to the consumption information of user；
S4 carries out the analysis of emphasis data to the behavior of user；
The data information of emphasis is cleaned, is converted, extracted and is calculated by S5.
2. a kind of method about user behavior analysis according to claim 1, which is characterized in that in step S1, acquisition
The behavior of user includes including search, browsing, marking, comment, part chat record, further includes the correlation on third party website
Behavior, such as the rate of exchange, see and related evaluate and test, participate in discussion, the exchange in social media, interacting with good friend.
3. a kind of method about user behavior analysis according to claim 1, which is characterized in that in step S3, consumption
Information includes that the consumption information all to user counts, including whether the past has click, if has purchase, purchase whether is added
Object vehicle is to be paid, the value of the product of purchase, the frequency of purchase, and when the last time is bought, and by all consumption information
Attribute carries out list data quantization, while information attribute to be consumed is carried out list data quantization.
4. a kind of method about user behavior analysis according to claim 1, which is characterized in that in step S4, emphasis
Data analysis includes area of source, incoming road domain name and the page of user；User website residence time, jump out rate, return visit person,
New visitor, return visit number, return visit are separated by number of days；User and nonregistered user are registered, browsing habit between the two is analyzed；With
Search engine, keyword used in family, association keyword and interior keyword of standing；Which type of entry form user selects, extensively
It accuses or web portal link is more effective；Whether user accesses website process, reasonable for analyzing page structure design；User
Webpage hotspot graph distributed data and web overlay data on the page；Amount of access situation of the user in different periods；User
For the fancy grade of the font color of website.
5. a kind of method about user behavior analysis according to claim 1, which is characterized in that the data cleansing packet
Include the double typing comparisons of data, data merge, search repetition values, search missing values and search exceptional value, the wherein double typings pair of data
Than starting after user data collected reaches preset specified value, the data merge the similar number of users of acquisition
According to the whole merging of progress.
6. a kind of method about user behavior analysis according to claim 5, which is characterized in that the lookup repetition values
It is that will carry out unified record progress data reference with website or comment is used for multiple times or buys information.
7. a kind of method about user behavior analysis according to claim 5, which is characterized in that the lookup missing values
It is that the information that user to zero record occurs counts；The lookup exceptional value is by user beyond normal record data 5-
100 multiples carry out statistic of classification as exceptional value.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810525541.4A CN108846034A (en) | 2018-05-28 | 2018-05-28 | A method of about user behavior analysis |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810525541.4A CN108846034A (en) | 2018-05-28 | 2018-05-28 | A method of about user behavior analysis |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108846034A true CN108846034A (en) | 2018-11-20 |
Family
ID=64209909
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810525541.4A Pending CN108846034A (en) | 2018-05-28 | 2018-05-28 | A method of about user behavior analysis |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108846034A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110011759A (en) * | 2019-03-15 | 2019-07-12 | 烽火通信科技股份有限公司 | The data transmission method and system of planisphere in OTN transmission network |
| CN110348365A (en) * | 2019-07-05 | 2019-10-18 | 秒针信息技术有限公司 | The recording method of operation and device |
| CN110516184A (en) * | 2019-05-27 | 2019-11-29 | 广州起妙科技有限公司 | A kind of simulation trial method counting UV quantity |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102346667A (en) * | 2011-09-19 | 2012-02-08 | 北京金和软件股份有限公司 | Realization method for automatically recording behavioral data of user |
| CN102364468A (en) * | 2011-09-29 | 2012-02-29 | 北京亿赞普网络技术有限公司 | User network behavior analysis method, device and system |
| CN106339439A (en) * | 2016-08-22 | 2017-01-18 | 成都众易通科技有限公司 | Big data analysis method |
| CN106779827A (en) * | 2016-12-02 | 2017-05-31 | 上海晶樵网络信息技术有限公司 | A kind of Internet user's behavior collection and the big data method of analysis detection |
| CN107515920A (en) * | 2017-08-22 | 2017-12-26 | 湖北大学 | A kind of image big data analysis method based on dynamic aerial survey |
| US9860200B1 (en) * | 2014-08-27 | 2018-01-02 | Google Llc | Message suggestions |
-
2018
- 2018-05-28 CN CN201810525541.4A patent/CN108846034A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102346667A (en) * | 2011-09-19 | 2012-02-08 | 北京金和软件股份有限公司 | Realization method for automatically recording behavioral data of user |
| CN102364468A (en) * | 2011-09-29 | 2012-02-29 | 北京亿赞普网络技术有限公司 | User network behavior analysis method, device and system |
| US9860200B1 (en) * | 2014-08-27 | 2018-01-02 | Google Llc | Message suggestions |
| CN106339439A (en) * | 2016-08-22 | 2017-01-18 | 成都众易通科技有限公司 | Big data analysis method |
| CN106779827A (en) * | 2016-12-02 | 2017-05-31 | 上海晶樵网络信息技术有限公司 | A kind of Internet user's behavior collection and the big data method of analysis detection |
| CN107515920A (en) * | 2017-08-22 | 2017-12-26 | 湖北大学 | A kind of image big data analysis method based on dynamic aerial survey |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110011759A (en) * | 2019-03-15 | 2019-07-12 | 烽火通信科技股份有限公司 | The data transmission method and system of planisphere in OTN transmission network |
| CN110516184A (en) * | 2019-05-27 | 2019-11-29 | 广州起妙科技有限公司 | A kind of simulation trial method counting UV quantity |
| CN110348365A (en) * | 2019-07-05 | 2019-10-18 | 秒针信息技术有限公司 | The recording method of operation and device |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Fang et al. | Consumer heterogeneity, perceived value, and repurchase decision-making in online shopping: The role of gender, age, and shopping motives | |
| Huang et al. | The impact of price and tobacco control policies on the demand for electronic nicotine delivery systems | |
| Li et al. | Discovering influencers for marketing in the blogosphere | |
| US10268670B2 (en) | System and method detecting hidden connections among phrases | |
| Tang et al. | Ranking user influence in healthcare social media | |
| JP5154975B2 (en) | Interest system graph forming apparatus, interest system graph forming method, and interest system graph forming program | |
| CN108846034A (en) | A method of about user behavior analysis | |
| CN103440259A (en) | Network advertisement push method and device | |
| Dong et al. | Brand purchase prediction based on time‐evolving user behaviors in e‐commerce | |
| Nizar et al. | Impact of digital marketing on consumer purchase behaviour | |
| CN109493113A (en) | A kind of providing method and device of favor information | |
| CN108416627A (en) | A kind of brand influence force monitoring method and system based on internet data | |
| US20130185055A1 (en) | System and Method for Performing Analysis on Information, Such as Social Media | |
| Slof et al. | A competing risks model based on latent Dirichlet Allocation for predicting churn reasons | |
| Su et al. | Detecting Crowdturfing" Add to Favorites" Activities in Online Shopping | |
| CN107025565A (en) | A kind of method and system for improving e-commerce website conversion ratio | |
| Alavi et al. | A trend study on the impact of social media on advertisement | |
| CN106202216A (en) | A kind of data processing method and data handling system | |
| Hamzehei et al. | Topic-based social influence measurement for social networks | |
| CN109409940A (en) | Browse processing method, device, equipment and storage medium based on path | |
| Wu et al. | Enhanced review-based rating prediction by exploiting aside information and user influence | |
| Tao et al. | Micro-behaviour with reinforcement knowledge-aware reasoning for explainable recommendation | |
| Tsuboi et al. | Product purchase prediction based on time series data analysis in social media | |
| Verma et al. | Weighted product taxonomy for mobile-commerce site in recommendation of product based on heuristic approach | |
| Palazuelos et al. | Analysis of social metrics in dynamic networks: measuring the influence with FRINGE |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20181120 |