Table of Contents I OLAP II OLAP CRM
Table of Contents I. OLAP 의 이해 II. OLAP의 CRM 적용 사례 III. 향후 OLAP의 발전 방향 /23
OLAP의 개념 q OLAP is the set of functionality for gaining insight into business data, both for analysis (looking backwards) and planning (looking forwards). q OLAP enable a variety of users – executives, managers, professional analysts, occasional end users – to go beyond the two dimensional views of data found in spreadsheets to more complex, multidimensional views. q The Term “OLAP” was coined by E. F Codd in 1993 to distinguish OLAP from OLTP. Typically, OLAP uses OLTP data as a foundation. q OLAP is used for business intelligence and decision support. It helps users to identify trends in the business, to understand better what has happened and plan for what should happen in the future. (Source : Gartner) /23
OLAP의 위상 (CRM View) Analytical CRM Operational CRM Sales Mgt. &Prcs. Sales Automation Front Office Mobile Office Customer Interaction Data Warehouse Legacy System Closed Loop Processing Back Office Mobile Sales Call Center Automation Field Services Customer Activity Data Mart Vertical App. OLAP Web Sales & Personalization Web Service Product Data Mart Web Configurator Data Mining Campaign Management Web Analysis and Marketing Collaborative CRM Source: Business Week, Feb. 2000 Meta Group /23
OLAP의 위상(Personalization View) Segmented Customer Market Target Customer Segmentation Analysis 고객 정보의 획득 공헌도, 수익성 분석 개인화 서비스 전략 Technology set 추출도구(ETT) OLAP Data Warehouse Data Mining 5 5/23 Personalization
온라인 기업의 e. CRM 구조 Source Data Extraction Data Warehousing Web Log Customer Profile 다차원분석 E-mail Marketing • Reporting • Data Extraction • Filtering & Aggregation • Transform & Loading Data Warehouse 캠페인관리 Call Center Web Comfigurator • Targeting • Scoring • Modeling & Building 개인화 Transaction Data others Web Touch Point • Multi-Dimensional Analysis 데이터 추 출 Other Log ; BBS, Proxy, FTP, WAP, … Analysis & Targeting • Real-time Recommendation Real time log • Contents Personalization Feedback 9 9/23 Advertising & Event Web Sales Guide Personalized Contents
OLAP 적용 사례 : D 사 – ISP/Portal q 기업 개요 l 회원 수 350 만 이상 l 하루 Web Log Size 30 GB l 100 여 개의 제휴 사이트 q 프로젝트 범위 l Dream. X Family l Membership, Web Log, Email, AOD/VOD q 프로젝트의 특징 l l Analytical CRM 구축 Commerce 부문이 없음 대용량 Web Log Processing (초기 2. 5 GB => 현재 30 GB => Next ? ) 제휴 사 공동 활용 : MSP q 프로젝트 이슈 l Performance Tuning 10 10/23
Sample(2) q Causal Dimension Causal 값들의 누계와 Page View (Measure Fact)의 비교 Filtering Dimension 을 통해 선택된 Causal 값과 Measure Fact 의 비교 Factor Analysis 기법을 통해서 영향력이 큰 요인 집중 관리 15 15/23
OLAP 기능의 확장 q Basic Functionality l Slice-and-Dice l Drill-down l Roll-up q Advanced Functionality l l Web-enabling for Mass Deployment What-if analysis: simulation (Write-back) Data Mining (Within DBMS) Specialized Applications => Packaged § Tight integration of tools, technologies, and business rules enabled by the data mart § Balanced Scorecard (Gentia Software Inc & Renaissance Solutions Inc. 결합) § Enterprise Performance Management /23
OLAP 과 Collaborative CRM의 연결 1. Call Center 와의 연결 2. (Web) Personalization 과의 연결 Web Log Transform OLAP e. Commerce Log Analysis Result Traditional CRM Personalizer Segment Analysis Personalized DB Data Warehouse Transform ERP Campaign OLAP Campaign Personalizer Recommendation Engine SCM Call Center Email Server/ Web Server 22 22/23 Web Server
- Slides: 24