1. CRM Based Marketing Strategy Functions
ETL
RFM
Primary Key
Granularity
Data Mart
Olap Cubes
Fact Tables
Hierarchy
Navigation
Customer Side
Company Side
Customer Selection
Increase C. Number
Keeping Existent C.
RetentionC.
Customer Satisfaction,
Keeping Existent Customer, Customization,
Service Range
Segmantation
Targeting Posititioning
Costs & Benefits
CRM Based Marketing Strategy
Functions
Database
How?
Software Errors
Aim
Information & Relational Marketing
Datamining
Prediction or
Description
CRM?
Loyalty
Retention, Winback &
Acquisition
Theory (Remzi Grocer) or
Software
Cust. Pyramid
Loyalty Types
Reason of Loy.
Rel. Management
CRM System
Sales Force Automation
Implementing Crm Systems
Trust
Conflict Handling
Commitment
Communication
Measuring Customer Satisfaction

2. CRM FUNCTIONS Customer Selection Segmentation Campain Modelling
Brand Management
New Products
Gain Customer
Order Man.
Demand Analysis
Logistic Man.
Complain Man.
Retain Customer
Market Leadership
Necessity Analysis
Increasing Customers
Analitic CRM
Cross Selling

3. COMPANY SIDE - CUSTOMER SIDE
BENEFITS - COSTS
COMPANY SIDE - CUSTOMER SIDE
Benefits;
Customized Products
More Income
Long Term Income
Cross ‐selling
Up ‐selling
Bundling
Customer Loyalty
Costs;
IT Costs (server, software, training, security, labor organization),
Framework change ,
Re-engineering
Resistance by employees
Benefits;
Regularity (Barber - no risk)
Touch point (Banks - ques )
Customized product or service
Enhances service (Holiday Inn)
Costs;
Sharing your personal informations
Opportunity costs(Underestimating the other companies’ offers)

4. LOYALTY – Customer Pyramid
Potential Customer; There is a possiblity to be Customer of the company in the future
Customer;Who bought servise or product from the company
Regular Customers;Who buy servie or product in regular time interval
Supporting Customers;Regular customer but do not recommend the company to other customer
Loyal Customers;Regular customers and recommend companys’ product or services to other customers
Behavioral Brand Loyalty:
Undivided Loyalty :A,A,A,A,A
Divided Loyalty :A,B,A,B,A,B
Switched Loyalty:A,A,A,B,B,B
Indifference Loyalty:A,B,C,D,E,F,G,H
Which Factors Effects the Customer Loyalty???

5. Which Factors Effects the Customer Loyalty?
Before Sales
During Sales
After Sales
Expectations
Performance/Quality
Judgements
Expectations and Judgements
Pleased
Satisfied
Disappointment

6. CRM BASED STRATEGY Marketing Strategy CRM SYSTEM Customer Data
INFORMATION
MANAGER
Marketing Strategy

7. SALES FORCE AUTOMATION
“The application of digital and wireless technologies to personal selling” is known as SFA.
Sfa software; organizes and manages data about sales touch points and customer’s history with company.
SFA may use data mining to integrate the pipeline data with other CRM data and make suggestions to sales representative.
Automation tools describe where prospects /customer are in the sales cycle. “EXPEDIA EXAMPLE”
SFA tools have risks and costs.???
Identfy Leads
Suspected interest
Qualify Leads
Value Estimates
Contact Buying Centers Recognize Key players
Re-contact
Winback interest
Develop Relationship
Develop interest
Negotiate Terms
Longterm View
Close
Ask for the sale NO
YES

8. SALES FORCE AUTOMATION TASKS
Benefits of SFA :
Increase sales productivity and efficiency.
Offers high quality customer service.
Increase customer satisfaction.
Creates customer loyalty.
SFA PROBLEMS:
Planning
Communication
Measurement
Source: Earl D. Honeycutt, Tanya Thelen, Shawn T. Thelen, Shoren T. Hodge(2005);
“Implements to Sales Force Automation”, Industrial Marketing Management, Volume 34, pp
Definition state - aim
Collecting feedback
Connection errors between different departments
Lack of sales person education
Focusing on organizational profits - sales person?
Resistance to downsizing - automation
Lack of process definitions
Reward mechanisms

9. SALES FORCE AUTOMATION TASKS
Contact and Time Management
Opportunity or Lead Management
Knowledge Management
Price Quotes and Order Configuration
Follow-up Management
Analysis and Reporting Tools

10. Contact and Time Management Opportunity or Lead Management
Communication with potential customers and existent customers
( , sms availability)
Date update and integration
customer name, address, phone number and etc
organization chart, decision tree
Providing information to sales representatives about customer data
(birthday, hobies, interests,location maps)
Sharing information between departments and sales team members
Time management tool, meeting arrangements
Opportunity or Lead Management
Determine potential customers of the company
Product focus service
Correct order control
Purchasing precisely
Defining correct communication point with customers
Opportunity management = Leadership + Process and information management
Sales Forecast
Customer Value Calculation
Future sale forecast

11. Price Quotes and Order Configuration
Knowledge Management
Easy managing, managing organizational information
Intranet, network inside the company
Extranet, sharing information, B2B - suppliers
Ordering effectively
Administrative facilities
Price Quotes and Order Configuration
Price lists,discount forms, price quotes information
Product configuration is important for sales represantatives
Decreases offering time
Cross-selling
Establishing self service with Extranet support – e-commerce
Follow-up Management
Communication is a part of Management
Organization of communication and delay follow-up
Product delivered on time?
send
Complaint system

12. Analysis and Reporting Tools
Providing access to call and sales reports iformations
Providing Analysis for sales managers
Time –customer - location based
Providing information for Managers
Ratios, percantage information about the sales
Call Centers
Direct access to customers
Classical call center hyergy:
Menu options
Waiting customer representative
Identication process
Providing iformation about customer to customer represenatative
Problem definition
Informing customer about his/her problem result
Call Routing
Interactive Voice Response
Caller ID Systems
Automatic Distribution System
Trouble ticket
Caller Note

13. Description or Prediction ??? Enabling Technologies
Data Mining
Description or Prediction ???
Automated prediction of trends and behaviors.
Automated discovery of previously unknown patterns.
Evolutionary Step
Business Question
Enabling Technologies
Product Providers
Characteristics
Data Collection (1960s)
"What was my total revenue in the last five years?"
Computers, tapes, disks
IBM, CDC
Retrospective, static data delivery
Data Access (1980s)
"What were unit sales in New England last March?"
Relational databases (RDBMS), Structured Query Language (SQL), ODBC
Oracle, Sybase, Informix, IBM, Microsoft
Retrospective, dynamic data delivery at record level
Data Warehousing & Decision Support
(1990s)
"What were unit sales in New England last March? Drill down to Boston."
On-line analytic processing (OLAP), multidimensional databases, data warehouses
Pilot, Comshare, Arbor, Cognos, Microstrategy
Retrospective, dynamic data delivery at multiple levels
Data Mining (Emerging Today)
"What’s likely to happen to Boston unit sales next month? Why?"
Advanced algorithms, multiprocessor computers, massive databases
Pilot, Lockheed, IBM, SGI, numerous startups (nascent industry)
Prospective, proactive information delivery

14. Data Mining Decision Support Systems Functions:
Churn Analyse: Which customer will switch – To which rival
Cross-Selling: Which customer – Which product
Fraud-Detection: Which customer is planning to cheat (assurance)
Risk Management: Crediy card apply –Yes or No
Customer Segmentation: Who are my customers?
Targeted ads: Which advertising? To which customer?
Sales Forecast: How many products will be sold in the next month

15. Description or Prediction ???
Data Mining
Description or Prediction ???
RFM (Recency, Frequency, Monetary)
Functions;
Classification – Modelling – fuction- test set (Predictive)
Clustering (Descriptive)
Association Rule (Descriptive)
Regression (Predictive)
Deviation Detection (Predictive)
Sequential Pattern Discovery (Descriptive)

16. Data Mining Information Discovery Methods; Decision Trees
Genetic Algorithms
Neural Networks 1 ad 12
ads 25 31
First Generation 6 15 22 28
Second Generation 11 16 19
Third Generation

17. Data Mining Problems; Measurable ? Data Size (Enormous)
Disordered Data
Data quality
Securing Personal Data
Multimedia Data -Streaming

18. Customers’First Sales
CUSTOMER CYCLE
Retention-Holding
Gain
Regain
Suspect-Potential
Loyal Customer
Repeat Customer
Customers’First Sales
Unactive Customer
Losy Customer

19. Gaining by Satisfying Customers;
CRM SYSTEM
Recognize;
Name &Past
Gaining by Satisfying Customers;
Performance & Quality
AIM;
One to One Relation
Result;
Customer Loyalty
Develop;
Customer Relation

20. LOST CUSTOMER Lost Customer Which Customer is about to leave?
Life Time value of Customer
Why he/she is leaving?
Which contact way is the best?
How much time is needed to activate the customer?
Lost Customer
First Conversaton After
Problem With Customer;
Thanks for trusting to our company
Competely Lost Customer;
Thanks for Past support to our company