8/9/2019 Crm Phases

1/24

Customer Relationship

Management (CRM)by

Abhishek Tatachar

8/9/2019 Crm Phases

2/24

HighlightsEvolutionofCRMWhat is CRMCRM Phases

Integrated ArchitectureHow does Data Mining help CRMLeading CRM VendorsLimits

Conclusion

8/9/2019 Crm Phases

3/24

EvolutionInitially, there were Door-to-Door sales forcesto approach the customers.

Then, Mass marketingreplaced the intimacy

ofa direct sales force.

Later, Targeted marketingevolved. Use ofdirect mail and telemarketing.

Latest is Customer Relationship Management(CRM), the next step inEvolution. A conceptsupported by latest technologies.

8/9/2019 Crm Phases

4/24

What is CRM ?

A Customer-centric business strategy which

Focuses on Managing and optimizing entire customer life cycle.

Demand re-engineering ofwork processes with customer infocus.

It consists of3 phases Planning Phase

Assessment Phase

Execution Phase

LaymanDefinitionof CRM

The process includes collecting customer data, analyzing this data tomake decisions which helps to make new customers and satisfy the

existing ones.

8/9/2019 Crm Phases

5/24

Planning

Phase

Plan to approach the customers

Planfor making new campaigns

This phase includes

Marketing tools

Various Softwares

Marketing& Sales personnelareinvolved in thisphase

8/9/2019 Crm Phases

6/24

Assessment

Phase

Select customer base for analysis

Analyze customer requirements

This phase includes technologies like Datawarehousing

DataMining

Online analytical processing(OLAP)

Acertified personnelsetsupthe CRMpackage while abusinessanalystanalyzesthe data

8/9/2019 Crm Phases

7/24

Execution

Phase

Customer interaction

Executes campaigns

Track customer feedback

This phase uses

Internet

Callcenters

Directmailsetc.

8/9/2019 Crm Phases

8/24

Technology behind AssessmentP

haseDatai i

Dataar s

OLAP

Server

arehousecontainingCustomer data.

ultidimensionalStructurestofacilitate better and fastanalysis ofdata.

Integrates withData arehouse &OLAP to implement intelligentalgorithms to discover patterns.

User analyzes thesepatterns to take decisionssuitablefor his business.

8/9/2019 Crm Phases

9/24

DATAWAREHOUSING

A data warehouse is a copy of transactional data.Data is specifically structured for querying and reportingA data warehouse can be a relational, multidimensional

hierarchical database or a flatfile.

DISTINGUISHABLE FEATURES

Contains historical data Nofrequentupdates Data stored is subjectoriented

TERMINOLOGYData Mart-Contains data about a specific subject.Metadata-Describes the data stored in data warehouse.Data Cleansing-The process ofensuring that allvalues in a dataset

are consistent and correctly recordedETL-Extraction, Transformation and Loading ofData.

8/9/2019 Crm Phases

10/24

ATypical Data Warehouse

Data Warehouse

Detailed Data

Data

Mart

Data

Mart

Data

Mart

Summarized Data

MetaD

ata

Dataaboutdata.

Facilitat

esinf

iringqueries on

detailed data.

Datamarts containdata specific toa

subject.

customer campaign sales

8/9/2019 Crm Phases

11/24

OLAP

Online analyticalprocessing is the name given to database anduser interface tools that allow to quickly navigate within data.

Provides a mechanism to store the data in multidimensionalcubes.

DISTINGUISHABLE FEATURES

Multidimensional Cubes- To store data which are multidimensional innature.

Calculation Intensive- Allows complex calculations on database.

8/9/2019 Crm Phases

12/24

Data Model

OfOLAP

The central table inan OLAP star data

model is called thefact table .

The surroundingtables are called thedimensions

The values offacttable are known asmeasures.

8/9/2019 Crm Phases

13/24

Data Model

OfOLAP

The supervisor that gavethe most discounts.

The quantity shipped ona particular date, month,year or quarter.

Inwhich zip code didproduct A sell the most?

Toobtain answers to the above shownqueries from a data model, OLAP cubes arecreated.

OLAP cubes are not strictly cuboids-it is aname given to the process oflinking datafrom different dimensions.

8/9/2019 Crm Phases

14/24

Interaction b/n Warehouse &

OLAP

Extract Data from

Warehouse

Transform and

Standardize

Data

Import to

OLAP

Database

Build Cubes Produce

Reports

Process of transforming warehouse data

8/9/2019 Crm Phases

15/24

How does

Data Mining help CRM

CRM systems typically collect a great dealofdata

Data Mining is used to search through thisinformation

Identify patterns that can help topredict buyerbehavior

Target specific customers with specific offers

This area ofCRM is referred to as Analytical CRM

8/9/2019 Crm Phases

16/24

With CRM, a business can

Provide better customer service

Make call centers more efficient

Increase customer revenues

Help sales staffclose deals faster

Simplify marketing and sales processes

Discover new customers

8/9/2019 Crm Phases

17/24

Leading CRM Vendors

Siebel

mySAP

Oracle

PeopleSoft

Vantive

Clarify

8/9/2019 Crm Phases

18/24

Screenshots o

fmy

SAP

It supports:

Marketing

Sales

Service

Analytics

8/9/2019 Crm Phases

19/24

Screenshots o

fmy

SAP

8/9/2019 Crm Phases

20/24

Screenshots (continued)

8/9/2019 Crm Phases

21/24

Limits

Expensive

Hard to implement

Time consuming

It requires a lotofmanagement and money

8/9/2019 Crm Phases

22/24

Conclusion

CRM is a concept, implemented with thesupportofvarious technologies.

Supporting technologies include Data

warehousing, Data Mining, OLAPetc.Aproper Data warehouse should be inplacefor any CRM initiative.

Customer needs should be infocus whileimplementing CRM.

8/9/2019 Crm Phases

23/24

References

CRM by Kristin Anderson & Carol Kerr

www.crmguru.com

www.dwreview.comsap.com

The Rushmore Group, LLC

8/9/2019 Crm Phases

24/24

Thank

You