Transcript Slayt 1 - Fazli Yildirim

Customer
Satisfaction,
Keeping Existent
Customer,
Customization,
Service Range
Customer Selection
Increase C. Number
Keeping Existent C.
RetentionC.
Functions
Costs &
Benefits
Database
How?
Aim
Customer
Side
Company
Side
Information &
Relational Marketing
Software
Errors
Prediction
or
Description
CRM?
Retention,
Winback &
Acquisition
Theory (Remzi Grocer)
or
Software
Implementing
Crm Systems
ETL
RFM
Primary Key
Granularity
Data Mart
Olap Cubes
Fact Tables
Hierarchy
Navigation
Sales Force
Automation
Measuring
Customer
Satisfaction
CRM
System
Segmantation
Targeting
Posititioning
CRM Based
Marketing
Strategy
Datamining
Loyalty
Cust. Pyramid
Loyalty Types
Reason of Loy.
Rel. Management
Trust
Conflict Handling
Commitment
Communication
CRM FUNCTIONS
Customer Selection
Segmentation
Campain Modelling
Brand Management
New Products
Gain Customer
Order Man.
Demand Analysis
Logistic Man.
Complain Man.
Retain Customer
Increasing
Customers
Market Leadership
Necessity Analysis
Analitic CRM
Cross Selling
BENEFITS - COSTS
COMPANY SIDE - CUSTOMER SIDE
Benefits;
Customized Products
More Income
Long Term Income
Cross ‐selling
Up ‐selling
Bundling
Customer Loyalty
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
Costs;
the other companies’ offers)
IT Costs (server, software,
training, security, labor
organization),
Framework change ,
Re-engineering
Resistance by employees
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???
Which Factors Effects the Customer Loyalty?
Before Sales
During Sales
After Sales
Expectations
Performance/Quality
Pleased
Judgements
Performance/Quality
Satisfied
Expectations and
Judgements
Disappointment
CRM BASED STRATEGY
Customer
Data
CRM
SYSTEM
INFORMATION
Marketing Strategy
MANAGER
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
Re-contact
Winback interest
Qualify Leads
Value Estimates
NO
YES
Close
Ask for the sale
Contact Buying Centers
Recognize Key players
Develop Relationship
Develop interest
Negotiate Terms
Longterm View
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
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
Source: Earl D. Honeycutt, Tanya Thelen, Shawn T. Thelen, Shoren T. Hodge(2005);
“Implements to Sales Force Automation”, Industrial Marketing Management, Volume 34, pp.313-322.
SALES FORCE AUTOMATION
TASKS
Contact and Time
Management
Opportunity or
Lead Management
Price Quotes and
Order
Configuration
Analysis and
Reporting Tools
Knowledge
Management
Follow-up
Management
Contact and Time Management
Communication with potential customers and existent customers
(e-mail, 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
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?
E-mail send
Complaint system
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
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
Data Access (1980s)
"What were unit sales in
New England last March?"
Relational databases
Oracle, Sybase,
(RDBMS), Structured
Informix, IBM,
Query Language (SQL),
Microsoft
ODBC
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)
Advanced algorithms,
"What’s likely to happen to
multiprocessor
Boston unit sales next
computers, massive
month? Why?"
databases
Pilot, Lockheed,
IBM, SGI,
numerous startups
(nascent industry)
Prospective,
proactive
information
delivery
IBM, CDC
Retrospective,
static data
delivery
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
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)
Data Mining
Information Discovery Methods;
Decision Trees
Genetic Algorithms
Neural Networks
First Generation
Second Generation
Third Generation
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Data Mining
Problems;






Measurable ?
Data Size (Enormous)
Disordered Data
Data quality
Securing Personal Data
Multimedia Data -Streaming
CUSTOMER CYCLE
RetentionHolding
Gain
Regain
Loyal
Customer
SuspectPotential
Repeat
Customer
Customers’
First Sales
Unactive
Customer
Losy
Customer
CRM SYSTEM
Recognize;
Name &Past
AIM;
One to One
Relation
Gaining by Satisfying
Customers;
Performance & Quality
Develop;
Customer Relation
LOST CUSTOMER
Which Customer is about to leave?
Life Time value of Customer
Lost
Customer
Why he/she is leaving?
Which contact way is the best?
How much time is needed to
activate the customer?
First Conversaton After
Problem With Customer;
Thanks for trusting to our company
Competely Lost Customer;
Thanks for Past support to
our company