Customer Relationship Management (CRM)

byAbhishek Tatachar

HighlightsEvolution of CRMWhat is CRMCRM PhasesIntegrated ArchitectureHow does Data Mining help CRMLeading CRM VendorsLimitsConclusion

EvolutionInitially, there were Door-to-Door sales forces to approach the customers.Then, Mass marketing replaced the intimacy of a direct sales force.Later, Targeted marketing evolved. Use of direct mail and telemarketing.Latest is Customer Relationship Management (CRM), the next step in Evolution. A concept supported by latest technologies.

What is CRM ?

A Customer-centric business strategy whichFocuses on Managing and optimizing entire customer life cycle.Demand re-engineering of work processes with customer in focus.It consists of 3 phases

Planning Phase Assessment Phase Execution Phase

Layman Definition of CRM

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

Planning Phase

Plan to approach the customersPlan for making new campaignsThis phase includes Marketing tools Various Softwares

Marketing & Sales personnel are involved in this phase

Assessment Phase

Select customer base for analysisAnalyze customer requirements This phase includes technologies like Data warehousing Data Mining Online analytical processing (OLAP)

A certified personnel sets up the CRM package while a business analyst analyzes the data

Execution Phase

Customer interactionExecutes campaignsTrack customer feedbackThis phase uses Internet Call centers Direct mails etc.

Technology behind Assessment Phase

Data Mining

Data Warehouse

OLAP Server

Warehouse containing Customer data.

Multidimensional Structures to facilitate better and fast analysis of data.

Integrates with Data Warehouse & OLAP to implement intelligent algorithms to discover patterns.

User analyzes these patterns to take decisions suitable for his business.

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

hierarchical database or a flat file.

DISTINGUISHABLE FEATURES

• Contains historical data• No frequent updates• Data stored is subject oriented

TERMINOLOGY

Data Mart- Contains data about a specific subject.Metadata- Describes the data stored in data warehouse.Data Cleansing- The process of ensuring that all values in a dataset are consistent and correctly recordedETL- Extraction, Transformation and Loading of Data.

A Typical Data Warehouse

Data Warehouse

Detailed Data

DataMart

DataMart

DataMart

Summarized DataMeta Data

Data about data.Facilitates in firing queries on detailed data.Data marts contain data specific to a subject.

customer campaign sales

OLAP

•Online analytical processing is the name given to database and user interface tools that allow to quickly navigate within data.

•Provides a mechanism to store the data in multidimensional cubes.

DISTINGUISHABLE FEATURES

•Multidimensional Cubes- To store data which are multidimensional in nature.

•Calculation Intensive- Allows complex calculations on database.

Data Model Of OLAP

The central table in an OLAP star data model is called the fact table .The surrounding tables are called the dimensions The values of fact table are known as measures.

Data Model Of OLAPThe supervisor that gave the most discounts. The quantity shipped on a particular date, month, year or quarter. In which zip code did product A sell the most?

To obtain answers to the above shown queries from a data model, OLAP cubes are created.

OLAP cubes are not strictly cuboids-it is a name given to the process of linking data from different dimensions.

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

How does Data Mining help CRM

CRM systems typically collect a great deal of data Data Mining is used to search through this information Identify patterns that can help to predict buyer behavior Target specific customers with specific offers

This area of CRM is referred to as Analytical

CRM

With CRM, a business can …

Provide better customer serviceMake call centers more efficientIncrease customer revenuesHelp sales staff close deals fasterSimplify marketing and sales processes Discover new customers

Leading CRM Vendors

SiebelmySAP Oracle PeopleSoftVantiveClarify

Screenshots of mySAP

It supports:MarketingSalesServiceAnalytics

Screenshots of mySAP

Screenshots (continued)

Limits

ExpensiveHard to implementTime consuming It requires a lot of management and money

Conclusion

CRM is a concept, implemented with the support of various technologies. Supporting technologies include Data warehousing, Data Mining, OLAP etc.A proper Data warehouse should be in place for any CRM initiative.Customer needs should be in focus while implementing CRM.

References

CRM by Kristin Anderson & Carol Kerrwww.crmguru.comwww.dwreview.comsap.comThe Rushmore Group, LLC

ThankYou