슬라이드 1

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1 [ CRM Fair 2004 ] CRM

2 1. CRM Trend 2. Customer Single View 3. Marketing Automation 4. ROI Management 5. Conclusion

3 1. CRM Trend

4 1. CRM Trend Operational CRM Analytical CRM Sales Mgt. &Prcs. Legacy System Data Warehouse Sales Automation Customer Activity Data Mart Product Data Mart Data Mining Call Management Campaign management OLAP Vertical App. Call Center Web Sales & Automation Personalization Web Service Management Web Analysis and Marketing Collaborative CRM

5 1. CRM Trend

6 1. CRM Trend Marketing Sales Service CRM Area DW Campaign Management SFA Sales Force Automation Call Center Management Business Rule Management ebpm ecrm Area (Collaboration CRM) OnLine Customer DB Mart Channel Data Management Contents Management Contact point / Mobile Application Web Area Web Service Application (ASP/JSP)

7 1. CRM Trend 2. Customer Single View 3. Marketing Automation 4. ROI Management 5. Conclusion

8 2. Customer Single View Single View ( Message ) Single View ( ) contact Marketing Marketing Contact Call Center Collaboration Management System Visitor Marketing Web /

9 2. Customer Single View CRM DW ecrm Mart

10 2. Customer Single View,, Model, Data,,,,. RealTime ( / )),,,.,. RealTime EMS/ERMS / ( )), ( ) ) ( )),,,,,,.. ( ) ) /,, /,,

11 2. Customer Single View WEB Log Client Contact Point DB Mart WEB Mobile Client Marketing DB Model DB Model Mobile Data / / / Nibbler Server Application Extractor Server Application / Legacy Mapping (, )

12 2. Customer Single View Mart, Process. Channel Channel Process Process Data Data

13 2. Customer Single View Web Business Rule management Call Center

14 1. CRM Trend 2. Customer Single View 3. Marketing Automation 4. ROI Management 5. Conclusion

15 3. Marketing Automation ecrm Framework ecrm ebiz, ROI ebiz,,,,..,,,, Mix.

16 3. Marketing Automation ( ),

17 3. Marketing Automation 20/80 20% CRM ecrm. (ecrm), ( ) / 20% /,,,

18 3. Marketing Automation ( )

19 3. Marketing Automation Event based OnetoOne Marketing /FeedBack Offer

20 3. Marketing Automation

21 3. Marketing Automation

22 3. Marketing Automation

23 3. Marketing Automation 5% 5% 5% 5% Web PopUp PopUp Business Rule Rule

24 3. Marketing Automation : A : ID : mkang 10 : 14 : Message B : ID : 10 : 1 : 1 1 / /

25 3. Marketing Automation (1) (2) (1) (3) (2) (1) (2) (4) (3) (3) (5) (4) (4) (5) Business Rule Manager (5)

26 3. Marketing Automation Multi Wave Marketing Promotion ( ) site 2 Promotion ( Offer ) Thankyou Mail (, A/S )

27 3. Marketing Automation (WEPA) Web/ / App Server ebrother Server Customer Request Page 1 Event Call Tag Event Call Tag Rule Manager Rule Action Reporter Meta DB Manager Reports Event base Message Include 8 1:1 Tag 2 Event Call Tag 7 Insert 1:1 Message 1:1 Tag Rules DB Check Rules 4 ebrother DB 5 Return Result Legacy DB WEPA-Client Return Result 3 6 WEPA-Server

28 1. CRM Trend 2. Customer Single View 3. Marketing Automation 4. ROI Management 5. Conclusion

29 4. ROI Management

30 4. ROI Management

31 4. ROI Management

32 4. ROI Management ebiz, Site Renewal + - -, ( ) , Point, ( ), ( ) - + +, User Visit Page

33 4. ROI Management ROI ROI

34 4. ROI Management

35 4. ROI Management

36 4. ROI Management

37 1. CRM Trend 2. Customer Single View 3. Marketing Automation 4. ROI Management 5. Conclusion

38 6. Conclusion Channel Integration Application Layer RBMS ebpm Data Analysis Layer Web log Management Contact Log Analysis Mobile Log Analysis Channel Layer (WEPA Server) Gatherer Clent Gatherer Clent Gatherer Clent WEPA Clent WEPA Clent WEPA Clent

39 6. Conclusion Technology WEB Log Client WEB Mobile Client Mobile Legacy (, ) Event Marketing Server Event Based Rule Management (Rule Manage Application) (WEPA Server) ERMS ( /faq ) DB Mart DB Model DB Model Nibbler/Extracter Contact Point WEB Client (,,) WEB Moblie Client mobile (Outbound Mail ) / (inbound Mail/FAQ ) ERMS ERMS

6. Conclusion ebrother Nibbler extractor WEPA Clickstream Data / Data Event Based emarketing Function,, Event Rule Base ROI, SYSTEM Application User Application Gatherer Recorder UserMatcher-Server

40 6. Conclusion ebrother Nibbler extractor WEPA Clickstream Data / Data Event Based emarketing Function,, Event Rule Base ROI, SYSTEM Application User Application Gatherer Recorder UserMatcher-Server UserMatcher-Client Recovery Nibbler Admin/reporting extractor Server(Data ) OLAP Model Reporting OLAP (Optional) WEPA Server WEPA Client META Data Adapter Rule Manager Rule Generator Rule Action Reporter

歯CRM개괄_허순영.PDF

歯CRM개괄_허순영.PDF CRM 2000. 8. KAIST CRM CRM CRM CRM :,, KAIST : 50%-60%, 20% 60%-80%. AMR Research 10.. CRM. 5. Harvard Business review 60%, 13%. Michaelson & Associates KAIST CRM? ( ),,, -,,, CRM needs,,, dynamically