crm phases
TRANSCRIPT
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Customer Relationship
Management (CRM)by
Abhishek Tatachar
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HighlightsEvolutionofCRMWhat is CRMCRM Phases
Integrated ArchitectureHow does Data Mining help CRMLeading CRM VendorsLimits
Conclusion
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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.
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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.
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Planning
Phase
Plan to approach the customers
Planfor making new campaigns
This phase includes
Marketing tools
Various Softwares
Marketing& Sales personnelareinvolved in thisphase
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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
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Execution
Phase
Customer interaction
Executes campaigns
Track customer feedback
This phase uses
Internet
Callcenters
Directmailsetc.
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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.
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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.
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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
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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.
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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.
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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.
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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
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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
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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
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Leading CRM Vendors
Siebel
mySAP
Oracle
PeopleSoft
Vantive
Clarify
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Screenshots o
fmy
SAP
It supports:
Marketing
Sales
Service
Analytics
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Screenshots o
fmy
SAP
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Screenshots (continued)
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Limits
Expensive
Hard to implement
Time consuming
It requires a lotofmanagement and money
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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.
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References
CRM by Kristin Anderson & Carol Kerr
www.crmguru.com
www.dwreview.comsap.com
The Rushmore Group, LLC
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Thank
You