CN102163205A - Automatic excavation system for analogous customer groups - Google Patents
Automatic excavation system for analogous customer groups Download PDFInfo
- Publication number
- CN102163205A CN102163205A CN2010102904464A CN201010290446A CN102163205A CN 102163205 A CN102163205 A CN 102163205A CN 2010102904464 A CN2010102904464 A CN 2010102904464A CN 201010290446 A CN201010290446 A CN 201010290446A CN 102163205 A CN102163205 A CN 102163205A
- Authority
- CN
- China
- Prior art keywords
- client
- analyzer
- enterprise
- analysis device
- customer
- 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
Images
Abstract
The invention discloses an automatic excavation system for analogous customer groups, which comprises a data preprocessing and cleaning device, an unstructured information extractor, a fusion search engine, an excavation target generator, a data warehouse, a relevance analyzer, a tendency analyzer, a customer lose analyzer, a classification analyzer, a cluster analyzer, an isolated point analyzer, customer enterprise characteristic analyzer, a commercial activity analyzer, a customer enterprise credit analyzer, a customer enterprise loyalty index analyzer, a customer enterprise attention analyzer, a customer enterprise marketing analyzer and a result summarization and visualization module. With the system, the contracted customer enterprises are taken as cases, and the analogous customer groups are deeply and accurately excavated in real time, so that value-added services of analogous customer enterprise groups can be immediately provided for users according to rules of a case expansion method.
Description
Technical field
The present invention relates to digital signal processing technique field, more particularly, relate to a kind of similar customer group's automatic mining system.
Background technology
Data mining is to find and extract a kind of new technology that is hidden in useful information wherein from data warehouse, it can extract potential, valuable knowledge, model or rule from lot of data, help enterprise to find professional trend, disclose the known fact, the result that prediction is unknown.But, valuable especially case expansion method in the marketing of enterprise market is not had directly corresponding data digging system.
Case is expanded method, promptly duplicate clone's market expansion method as the seed case with the client enterprise that strikes a bargain, because of case truly took place, with a high credibility, cogency is strong, is the favourable guarantee of implementing precision marketing and pattern marketing, but duplicates fresh successful seed case, need very high promptness and accuracy, otherwise can occur counter productive out-of-date or that mislead on the contrary.
Summary of the invention
In view of this, the embodiment of the invention provides a kind of similar customer group's automatic mining system, it is used for initiatively double type marketing for all enterprises, by to the client enterprise that struck a bargain as case, by real-time, tap/dip deep into accurately, expand the method rule according to case, the value-added service of similar client's group of enterprises is provided to the user immediately.
The embodiment of the invention provides a kind of similar customer group's automatic mining system, comprising: data pre-service and washer, the unstructured information withdrawal device, merge search engine, excavate the target maker, data warehouse, the association analysis device, the trend analysis device, the Customer Churn's Analysis device, the classification analysis device, the cluster analysis device, the isolated point analyzer, client's enterprise characteristic analyzer, the commercial activity analyzer, client's corporate credit analysis device, client enterprise loyalty analyzer, client enterprise notice analyzer, client enterprise marketing analyzer, the result gathers and visualization model;
Described data pre-service and washer are used for the rubbish of filtering data, monitor data and the information related with client enterprise;
Described unstructured information withdrawal device is used for the Automatic Extraction unstructured information, and with structurized formal representation;
Described fusion search engine is used for the information of data warehouse under real-time information on the line and the line is searched for and fusion gathers;
Described excavation target maker is used to produce purpose, content and the requirement that follow-up data excavates;
Described data warehouse is used to store the business data and the market information of real-time update;
Described association analysis device is used to understand the buying habit and the preference of client enterprise, generates the bundle sale strategy that characterizes marketing;
Described trend analysis device is used to resolve the market development process of client enterprise in some periods;
Described Customer Churn's Analysis device, be used to understand which client when section why reason run off;
Described classification analysis device is used to predict which client enterprise can respond to which kind of advertisement and marketing tools such as products catalogue, complimentary ticket, and deciding grade and level of client enterprise and bankruptcy prediction;
Described cluster analysis device is used for the market segments, client enterprise is divided into some the segmenting market by the similarity of its behavior or feature mode, and takes marketing strategy targetedly;
Described isolated point analyzer is used to analyze unusual client's behavior, and client or swindle note abnormalities;
Described client's enterprise characteristic analyzer is used to understand client's behavioural habits, according to buying the historical value of discerning the client;
Described commercial activity analyzer is used for utilizing situation by the comprehensive resources of data such as client's distribution of funds situation, flow situation being analyzed the client;
Described client's business standing degree analyzer is used to assess the credit grade of enterprise;
Described client enterprise notice analyzer is used for carrying out comprehensive assessment based on degree of belief, contact frequency, service effectiveness, satisfaction and contract renewed treaty rate to enterprise;
Described client enterprise marketing analyzer is used to carry out client's complaint analysis; Client's consulting analysis; The client advises analyzing; The client contacts evaluation; The customer satisfaction A+E;
Described client enterprise marketing analyzer is used to analyze the marketing process that this client's enterprise practical of contrast takes place and the potential trend of the industry;
Described result gathers and visualization model, is used for similar customer group is divided into similar customers, doubtful customers and non-customers, and with visual graphical representation;
Described communication module is used for linking up immediately with similar customer group and doubtful customer group.
Preferably, to obtain be automatically to the extraction of unstructured information to the client's company information in the described excavation target generative process.
Preferably, the related information search in the described excavation target generative process is concurrent to the search of data warehouse under the search of real-time information on the line and the line, and fusion gathers automatically.
Preferably, there are uninterrupted automatic tracking and renewal automatically in employed data warehouse and internet in the described excavation target generative process.
Preferably, described excavation target comprises that system is carried out the interactive user who controls wishes the region of appointment, the multiplicative parameter that excavation is duplicated.
Preferably, the platform network that presents of described similar client's excavation comprises: internet, LAN (Local Area Network), wireless network, broadcasting and television network, the carrier that presents comprises: computer, mobile phone, PDA.
Compare with prior art, technical scheme provided by the invention produces the system of a plurality of similar client's groups of enterprises based on the integrated information data mining of the client enterprise that strikes a bargain, utilize the client enterprise that has struck a bargain really to have these characteristics of very strong cogency as case, by this fresh successful case is duplicated the clone immediately, accurately, requirements such as the region of setting according to the user, multiplicative parameter, system automatically produces similar client's group of enterprises for the user.The user is as long as adopt the marketing strategy consistent with successful case, can implement more client enterprise apace in similar client's group of enterprises, and the user can be doubled because of quick copy produce achievement on sales achievement.No matter which kind of marketing model the user adopted in the past, as long as the case that will strike a bargain is given this system as seed, system can both produce the achievement of multiplication for it.
Description of drawings
In order to be illustrated more clearly in the technical scheme of the embodiment of the invention, to do to introduce simply to the accompanying drawing of required use in embodiment or the description of the Prior Art below, apparently, accompanying drawing in describing below only is some embodiments of the present invention, for those of ordinary skills, under the prerequisite of not paying creative work, can also obtain other accompanying drawing according to these accompanying drawings.
A kind of similar customer group's that Fig. 1 provides for the embodiment of the invention automatic mining system architecture synoptic diagram.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the invention, the technical scheme in the embodiment of the invention is clearly and completely described, obviously, described embodiment only is the present invention's part embodiment, rather than whole embodiment.Based on the embodiment among the present invention, those of ordinary skills belong to the scope of protection of the invention not making the every other embodiment that is obtained under the creative work prerequisite.
At first the automatic mining system to a kind of similar customer group provided by the invention describes, and with reference to shown in Figure 1, described system comprises:
Excavate the system of a plurality of similar client's groups of enterprises of generation by data pre-service and washer 2 based on the integrated information data (shown in 1) of the client enterprise that strikes a bargain, unstructured information withdrawal device 5, merge search engine 6, excavate target maker 3, data warehouse 4, association analysis device 7, trend analysis device 8, Customer Churn's Analysis device 9, classification analysis device 10, cluster analysis device 11, isolated point analyzer 12, client's enterprise characteristic analyzer 13, commercial activity analyzer 14, client's corporate credit analysis device 15, client enterprise loyalty analyzer 16, client enterprise notice analyzer 17, client enterprise marketing analyzer 18, the result gathers and visualization model 20.
Wherein, merging on 6 pairs of lines of search engine under the real-time information and line the information of data warehouse searches for, structured message withdrawal device 5 will merge the unstructured information in the Search Results, as: webpage neutralizes the related valuable Information Automatic Extraction of this client enterprise with structurized formal representation;
The data pre-service is removed not related rubbish with washer 2, and real-time listening data and the information related with client enterprise, upgrades the stale data and the information of data warehouse 4;
Merge information under the line that search engine 6 then obtains information and the data warehouse from structurized related again actual time line,, merge and pass to and excavate target maker 3 according to excavating the outline formula template that target maker 3 is set up;
Then, excavate target maker 3 and generate final excavation target according to the information such as further feature of the excavation region of customer requirements, multiplicative parameter, client enterprise;
Subsequently, system enriches data warehouse 4 to the complete information that merges, and excavates target maker 3 and passes to association analysis device 7, trend analysis device 8, Customer Churn's Analysis device 9, classification analysis device 10, cluster analysis device 11, isolated point analyzer 12 excavating target.Association analysis device 7 is analyzed the buying habit and the preference of client enterprise, is used to characterize the bundle sale strategy of marketing; Trend analysis device 8 is resolved the market development process in some periods of client enterprise; Which client that Customer Churn's Analysis device 9 is understood client enterprises when section why reason runs off; The classification analysis device 10 which client of prediction can respond to which kind of advertisement and the marketing tools such as products catalogue, complimentary ticket of client enterprise, and client enterprise is defined the level; Cluster analysis device 11 is used for the market segments, and client enterprise is divided into some the segmenting market by the similarity of its behavior or feature mode; Isolated point analyzer 12 is analyzed unusual client's behavior, and client or swindle note abnormalities.Association analysis device 7, trend analysis device 8, Customer Churn's Analysis device 9, classification analysis device 10, cluster analysis device 11, isolated point analyzer 12 in doing above analytic process all with data warehouse 4 interactions.Depth analysis is finished by client's enterprise characteristic analyzer 13, commercial activity analyzer 14, client's corporate credit analysis device 15, client enterprise loyalty analyzer 16, client enterprise notice analyzer 17, client enterprise marketing analyzer 18.Client's enterprise characteristic analyzer 13 is analyzed client's behavioural habits, according to the historical value of discerning the client of buying; Commercial activity analyzer 14 utilizes situation by the comprehensive resources of data such as client's distribution of funds situation, flow situation being analyzed the client; The credit grade of client's business standing degree analyzer 18 assessment enterprises; Client enterprise notice analyzer 17 carries out comprehensive assessment based on degree of belief, contact frequency, service effectiveness, satisfaction and contract renewed treaty rate to enterprise; Client enterprise marketing analyzer 18 is finished: client's complaint analysis, client's consulting analysis, client advise analyzing, the client contacts evaluation, customer satisfaction A+E; Client enterprise marketing analyzer is analyzed the marketing process of this client's enterprise practicals generation of 18 contrasts and the potential trend of the industry; The result gathers with visualization model 20 similar customer group is divided into similar customers 21, doubtful customers 22 and non-customers 23, and with visual graphical representation.Dissatisfied or produce feedback when abnormal conditions take place to system user, and according to feedback information 19 with require to revise automatically whole similar client's group of enterprises and excavate flow process, till system user is satisfied.
This system is prerequisite with the fact, with result is evidence, the client enterprise that setting has struck a bargain is as seed, according to data and information such as the diversity of settings information of this conclusion of the business client enterprise, product feature, scope of business, trading activities, by unstructured information Automatic Extraction, data cleansing and the information fusion related, generate and excavate target with this client enterprise.Then, in the marketing data warehouse of magnanimity, carry out data mining, analysis, obtain knowledge such as deeper client's enterprise characteristic, commercial activity, credit, loyalty and marketing mode.At last, according to this knowledge mate, reasoning and copy in the market similarly client's group of enterprises, allow system user go to open up this similar client's group of enterprises with same marketing strategy, can quick copy and multiplication thereby allow the market expansion become.This system is actual, and what realize is that a kind of case is expanded method, i.e. market expansion method of duplicating as case with the client enterprise that strikes a bargain.Based on the system of case, with a high credibility because of case truly took place, cogency is strong, is the favourable guarantee of implementing precision marketing and pattern marketing.
After adopting native system, the user can duplicate fast and doubles by the case that has struck a bargain, and excavates the potential customers colony in bigger zone rapidly, reaches the initiatively effect of multiplication marketing.As long as given client's case, system just can prize customer group at double.Marketing strategy and words art that system user adopts the conclusion of the business case originally needn't change, and just can be used on the customer group that system copies comes out, and brought more probability of transaction, and sales achievement doubles.After adopting native system, marketing is accelerated, and can shorten the cycle of determining the client greatly, thereby the cost that strikes a bargain is reduced greatly.
After adopting native system, similarly, a given satisfactory commission merchant, system just can bring satisfactory commission merchant colony at double, for the user holds initiative on the marketing channel, and free from trusted to chance and strokes of luck the marketing model of formula in the past, finish the work of setting up bigger regional channel network at short notice beyond one's ability of original enterprise, for enterprise wins the new first market opportunities and opportunity.
This system is an a kind of active marketing system, it is except being used for intelligentized sweeping the building, also have communication function concurrently, precisely send mail, fax, note to similar customer group, automatic batch is called out, and the very first time is sought client's purpose, simultaneously at the purpose client, again self detailed publicity materials of enterprise product or model agreements are provided the accurate purpose client that these have locked, also can be in conjunction with traditional form a visit such as potential customers being paid.Like this, the flow process of whole marketing has just obtained maximum optimization and speed-raising, and the marketing elite has had the sharp weapon that help him to repeat to sign a bill.
System embodiment described above only is schematic, wherein said unit as the separating component explanation can or can not be physically to separate also, the parts that show as the unit can be or can not be physical locations also, promptly can be positioned at a place, perhaps also can be distributed on a plurality of network element.Can select wherein some or all of module to realize the purpose of present embodiment scheme according to the actual needs.Those of ordinary skills promptly can understand and implement under the situation of not paying creative work.
To the above-mentioned explanation of the disclosed embodiments, make this area professional and technical personnel can realize or use the present invention.Multiple modification to these embodiment will be conspicuous concerning those skilled in the art, and defined herein General Principle can realize under the situation of the spirit or scope that do not break away from the embodiment of the invention in other embodiments.Therefore, the embodiment of the invention will can not be restricted to these embodiment shown in this article, but will meet and principle disclosed herein and features of novelty the wideest corresponding to scope.
Claims (6)
1. a similar customer group automatic mining system, it is characterized in that, comprising: data pre-service and washer, the unstructured information withdrawal device, merge search engine, excavate the target maker, data warehouse, the association analysis device, the trend analysis device, the Customer Churn's Analysis device, the classification analysis device, the cluster analysis device, the isolated point analyzer, client's enterprise characteristic analyzer, the commercial activity analyzer, client's corporate credit analysis device, client enterprise loyalty analyzer, client enterprise notice analyzer, client enterprise marketing analyzer, the result gathers and visualization model;
Described data pre-service and washer are used for the rubbish of filtering data, monitor data and the information related with client enterprise;
Described unstructured information withdrawal device is used for the Automatic Extraction unstructured information, and with structurized formal representation;
Described fusion search engine is used for the information of data warehouse under real-time information on the line and the line is searched for and fusion gathers;
Described excavation target maker is used to produce purpose, content and the requirement that follow-up data excavates;
Described data warehouse is used to store the business data and the market information of real-time update;
Described association analysis device is used to understand the buying habit and the preference of client enterprise, generates the bundle sale strategy that characterizes marketing;
Described trend analysis device is used to resolve the market development process of client enterprise in some periods;
Described Customer Churn's Analysis device, be used to understand which client when section why reason run off;
Described classification analysis device is used to predict which client enterprise can respond to which kind of advertisement and marketing tools such as products catalogue, complimentary ticket, and deciding grade and level of client enterprise and bankruptcy prediction;
Described cluster analysis device is used for the market segments, client enterprise is divided into some the segmenting market by the similarity of its behavior or feature mode, and takes marketing strategy targetedly;
Described isolated point analyzer is used to analyze unusual client's behavior, and client or swindle note abnormalities;
Described client's enterprise characteristic analyzer is used to understand client's behavioural habits, according to buying the historical value of discerning the client;
Described commercial activity analyzer is used for utilizing situation by the comprehensive resources of data such as client's distribution of funds situation, flow situation being analyzed the client;
Described client's business standing degree analyzer is used to assess the credit grade of enterprise;
Described client enterprise notice analyzer is used for carrying out comprehensive assessment based on degree of belief, contact frequency, service effectiveness, satisfaction and contract renewed treaty rate to enterprise;
Described client enterprise marketing analyzer is used to carry out client's complaint analysis; Client's consulting analysis; The client advises analyzing; The client contacts evaluation; The customer satisfaction A+E;
Described client enterprise marketing analyzer is used to analyze the marketing process that this client's enterprise practical of contrast takes place and the potential trend of the industry;
Described result gathers and visualization model, is used for similar customer group is divided into similar customers, doubtful customers and non-customers, and with visual graphical representation;
Described communication module is used for linking up immediately with similar customer group and doubtful customer group.
2. similar customer group's according to claim 1 automatic mining system is characterized in that, it is automatic extraction to unstructured information that the client's company information in the described excavation target generative process obtains.
3. similar customer group's according to claim 1 automatic mining system, it is characterized in that, related information search in the described excavation target generative process is concurrent to the search of data warehouse under the search of real-time information on the line and the line, and fusion gathers automatically.
4. similar customer group's according to claim 1 automatic mining system is characterized in that, there are uninterrupted automatic tracking and renewal automatically in employed data warehouse and internet in the described excavation target generative process.
5. similar customer group's according to claim 1 automatic mining system is characterized in that, described excavation target comprises that system is carried out the interactive user who controls wishes the region of appointment, the multiplicative parameter that excavation is duplicated.
6. similar customer group's according to claim 1 automatic mining system, it is characterized in that, the platform network that presents that described similar client excavates comprises: internet, LAN (Local Area Network), wireless network, broadcasting and television network, the carrier that presents comprises: computer, mobile phone, PDA.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN2010102904464A CN102163205A (en) | 2010-02-21 | 2010-09-20 | Automatic excavation system for analogous customer groups |
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201020116276.3 | 2010-02-21 | ||
| CN201020116276 | 2010-02-21 | ||
| CN2010102904464A CN102163205A (en) | 2010-02-21 | 2010-09-20 | Automatic excavation system for analogous customer groups |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN102163205A true CN102163205A (en) | 2011-08-24 |
Family
ID=44464437
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN2010102904464A Pending CN102163205A (en) | 2010-02-21 | 2010-09-20 | Automatic excavation system for analogous customer groups |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102163205A (en) |
Cited By (20)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103164474A (en) * | 2011-12-15 | 2013-06-19 | 中国移动通信集团贵州有限公司 | Method for analyzing data service |
| CN103186555A (en) * | 2011-12-28 | 2013-07-03 | 腾讯科技（深圳）有限公司 | Evaluation information generation method and system |
| CN104036409A (en) * | 2013-03-08 | 2014-09-10 | 姚德明 | Method and system for improving competiveness of e-commerce enterprises |
| CN104809188A (en) * | 2015-04-20 | 2015-07-29 | 广东工业大学 | Enterprise talent drainage data mining analysis method and device |
| CN105243515A (en) * | 2015-11-09 | 2016-01-13 | 浙江中之杰软件技术有限公司 | Enterprise condition management system |
| CN105894372A (en) * | 2016-06-13 | 2016-08-24 | 腾讯科技（深圳）有限公司 | Method and device for predicting group credit |
| CN106033455A (en) * | 2015-03-17 | 2016-10-19 | 阿里巴巴集团控股有限公司 | Method and device for processing user operation information |
| CN106127397A (en) * | 2016-06-30 | 2016-11-16 | 成都生辉电子科技有限公司 | A kind of information classification hierarchical processing method |
| CN106294390A (en) * | 2015-05-20 | 2017-01-04 | 上海纳鑫信息科技有限公司 | A kind of data mining analysis method and system |
| CN106937138A (en) * | 2015-12-31 | 2017-07-07 | 北京国双科技有限公司 | The analysis method and device of television services usage amount anticlimax reason |
| CN106937139A (en) * | 2015-12-31 | 2017-07-07 | 北京国双科技有限公司 | Television services usage amount is uprushed the analysis method and device of reason |
| WO2017181346A1 (en) * | 2016-04-19 | 2017-10-26 | 大连理工大学 | Optimal dividing method for credit grade based on credit similarity maximization |
| CN107527149A (en) * | 2017-08-25 | 2017-12-29 | 前海梧桐（深圳）数据有限公司 | For analyzing the method and system of enterprise's Situation Awareness |
| CN107526780A (en) * | 2017-07-22 | 2017-12-29 | 长沙兔子代跑网络科技有限公司 | A kind of method and device for the intelligent excavating generation race client that drawn a portrait according to user |
| CN107886241A (en) * | 2017-11-10 | 2018-04-06 | 北京三快在线科技有限公司 | Resource analysis method, apparatus, medium and electronic equipment |
| CN107886354A (en) * | 2017-10-31 | 2018-04-06 | 广州云移信息科技有限公司 | A kind of method and system for determining marketing target colony |
| CN109741102A (en) * | 2018-12-28 | 2019-05-10 | 上海德启信息科技有限公司 | A kind of information acquisition method and device |
| CN110717716A (en) * | 2019-10-10 | 2020-01-21 | 安徽九州通智能科技有限公司 | Cloud logistics platform and construction method |
| CN111445276A (en) * | 2019-01-17 | 2020-07-24 | 苏州黑牛新媒体有限公司 | Visual big data retail industry analysis method |
| TWI706356B (en) * | 2017-03-09 | 2020-10-01 | 香港商阿里巴巴集團服務有限公司 | Method and device for business drainage |
-
2010
- 2010-09-20 CN CN2010102904464A patent/CN102163205A/en active Pending
Cited By (26)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103164474B (en) * | 2011-12-15 | 2016-03-30 | 中国移动通信集团贵州有限公司 | A kind of method that data service is analyzed |
| CN103164474A (en) * | 2011-12-15 | 2013-06-19 | 中国移动通信集团贵州有限公司 | Method for analyzing data service |
| CN103186555A (en) * | 2011-12-28 | 2013-07-03 | 腾讯科技（深圳）有限公司 | Evaluation information generation method and system |
| WO2013097603A1 (en) * | 2011-12-28 | 2013-07-04 | 腾讯科技（深圳）有限公司 | Evaluation information generation method and system, and computer storage medium |
| CN103186555B (en) * | 2011-12-28 | 2016-05-11 | 腾讯科技（深圳）有限公司 | Evaluation information generates method and system |
| CN104036409A (en) * | 2013-03-08 | 2014-09-10 | 姚德明 | Method and system for improving competiveness of e-commerce enterprises |
| CN106033455B (en) * | 2015-03-17 | 2020-01-17 | 阿里巴巴集团控股有限公司 | Method and equipment for processing user operation information |
| CN106033455A (en) * | 2015-03-17 | 2016-10-19 | 阿里巴巴集团控股有限公司 | Method and device for processing user operation information |
| CN104809188A (en) * | 2015-04-20 | 2015-07-29 | 广东工业大学 | Enterprise talent drainage data mining analysis method and device |
| CN106294390A (en) * | 2015-05-20 | 2017-01-04 | 上海纳鑫信息科技有限公司 | A kind of data mining analysis method and system |
| CN105243515A (en) * | 2015-11-09 | 2016-01-13 | 浙江中之杰软件技术有限公司 | Enterprise condition management system |
| CN106937138A (en) * | 2015-12-31 | 2017-07-07 | 北京国双科技有限公司 | The analysis method and device of television services usage amount anticlimax reason |
| CN106937139A (en) * | 2015-12-31 | 2017-07-07 | 北京国双科技有限公司 | Television services usage amount is uprushed the analysis method and device of reason |
| WO2017181346A1 (en) * | 2016-04-19 | 2017-10-26 | 大连理工大学 | Optimal dividing method for credit grade based on credit similarity maximization |
| CN105894372A (en) * | 2016-06-13 | 2016-08-24 | 腾讯科技（深圳）有限公司 | Method and device for predicting group credit |
| CN106127397A (en) * | 2016-06-30 | 2016-11-16 | 成都生辉电子科技有限公司 | A kind of information classification hierarchical processing method |
| TWI706356B (en) * | 2017-03-09 | 2020-10-01 | 香港商阿里巴巴集團服務有限公司 | Method and device for business drainage |
| US11062353B2 (en) | 2017-03-09 | 2021-07-13 | Advanced New Technologies Co., Ltd. | Method and apparatus for service diversion in connection with mobile payment transactions |
| US10915925B2 (en) | 2017-03-09 | 2021-02-09 | Alibaba Group Holding Limited | Method and apparatus for guiding service flow |
| CN107526780A (en) * | 2017-07-22 | 2017-12-29 | 长沙兔子代跑网络科技有限公司 | A kind of method and device for the intelligent excavating generation race client that drawn a portrait according to user |
| CN107527149A (en) * | 2017-08-25 | 2017-12-29 | 前海梧桐（深圳）数据有限公司 | For analyzing the method and system of enterprise's Situation Awareness |
| CN107886354A (en) * | 2017-10-31 | 2018-04-06 | 广州云移信息科技有限公司 | A kind of method and system for determining marketing target colony |
| CN107886241A (en) * | 2017-11-10 | 2018-04-06 | 北京三快在线科技有限公司 | Resource analysis method, apparatus, medium and electronic equipment |
| CN109741102A (en) * | 2018-12-28 | 2019-05-10 | 上海德启信息科技有限公司 | A kind of information acquisition method and device |
| CN111445276A (en) * | 2019-01-17 | 2020-07-24 | 苏州黑牛新媒体有限公司 | Visual big data retail industry analysis method |
| CN110717716A (en) * | 2019-10-10 | 2020-01-21 | 安徽九州通智能科技有限公司 | Cloud logistics platform and construction method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102163205A (en) | Automatic excavation system for analogous customer groups | |
| Wang et al. | Analytics in the era of big data: The digital transformations and value creation in industrial marketing | |
| Oklander et al. | Analysis of technological innovations in digital marketing | |
| CN110222272A (en) | A kind of potential customers excavate and recommended method | |
| KR100786795B1 (en) | Internet advertising service system and method thereof | |
| Domegan | The adoption of information technology in customer service | |
| Tupikovskaja-Omovie et al. | Eye tracking technology to audit google analytics: Analysing digital consumer shopping journey in fashion m-retail | |
| Cabena et al. | Intelligent miner for data applications guide | |
| Trnka | Market basket analysis with data mining methods | |
| Mei et al. | Overview of Web mining technology and its application in e-commerce | |
| Scholz et al. | AKEGIS: automatic keyword generation for sponsored search advertising in online retailing | |
| Orogun et al. | Predicting consumer behaviour in digital market: a machine learning approach | |
| CN106326318A (en) | Search method and device | |
| CN104537553A (en) | Application of repeated negative sequence pattern in customer purchase behavior analysis | |
| Ziemba et al. | Dynamic decision support in the internet marketing management | |
| Bulut et al. | Ranking of advertising goals on social network sites by Pythagorean fuzzy hierarchical decision making: Facebook | |
| Cacciolatti et al. | Empirical Evidence for a Relationship between Business Growth and the Use of Structured Marketing Information Amongst Food and Drink SME's | |
| Chen et al. | Customer segmentation in customer relationship management based on data mining | |
| CN117273776A (en) | Marketing operation method based on big data analysis | |
| CN117035826A (en) | Digital marketing method and marketing platform | |
| Bremer et al. | Analysing clickstream data: do paid and organic search affect each other? | |
| Žitkienė et al. | Model of impact of social networks on internet marketing of enterprises | |
| Chopra et al. | E-CRM–A new paradigm for managing customers | |
| Omorogbe | Improving Digital Marketing Strategy: The Impact of Digital Analytics | |
| Karunanithy et al. | An evolution of customer relationship management: a conceptual approach |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C12 | Rejection of a patent application after its publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20110824 |