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Transcript
Building Databases, Selecting Customers,
and Managing Relationships
Chapter 2
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Please Note:
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Opening Vignette
Tidewater
Exterminating
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Customer Database Defined
A customer database is a list of customer
names to which the marketer has
added additional information in a
systematic fashion.
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
A Customer Database is…


The heart of all direct
and interactive
marketing activities.
The key to developing
strong customer
relationships and
retaining customers.
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Primary Objectives of a
Customer Database
1)
2)
3)
4)
5)
6)
To get to know customers better
To sell different products or services to
existing customers
To introduce new products or services
To distribute information about an
upcoming event or sale
To introduce new employees
To keep customers satisfied and happy
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Highly satisfied customers


Tend to be more loyal customers
Generate more profits over their
lifetime of patronage
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
The Reasons Why Loyal
Customers Generate More Profits
Loyal Customers …
1.
Increase their spending over time
2.
Cost less to serve than new customers
3.
Generate word-of-mouth advertising
or referrals
4.
Are less price sensitive than new
customers
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
An Example of How Loyalty Programs
Are Driven by Customer Databases
McDonald Garden Center
Garden Rewards Program
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Types of Source Data To Collect
To Build A Customer Database







Customer’s Name
Address
Telephone Number
E-Mail Address
Demographics
Psychographics
Past Purchases (Transaction Data)
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Database RFM Analysis:
Recency/Frequency/Monetary

Evaluates customers with respect to their
transactions over time
*20 points per each variable
*weights will vary
*See example in text
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Database Maintenance:
Creating Match Codes

An abbreviated name/address record

Allows each record to be matched with other records

A match code is generated for each name on the list
Example Address
Ann Stafford
9330 West Arlington Rd
Alexandria, VA 22301
Derived Match Code
82301SAF9330ALI8A3
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Database Maintenance:
Merge/Purge




A process using match codes to identify and
delete duplicate names and addresses
Keeps house lists from being duplicated
Can remove names that requested no
solicitations
Can identify “multibuyers”
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
The Need for Database
Maintenance




Lists are perishable
Constant control and maintenance is
required
Includes identifying and eliminating any
duplicate records
Three categories of database
maintenance activities are needed
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
3 Categories of
Database Maintenance Activities
1. Change of address investigations
2. Nixie removal
3. Record status updates
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Change of Address


Should be requested through the U.S.
Postal Service (National Change of
Address Service - NCOA)
Promotions that are mailed out to
improper addresses may result in a
financial lost
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Nixie Removal
Defined – mail that has been returned by the
Postal Service because it is undeliverable as
addressed
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Record Status Updates



Transaction data
Marital status
Deaths
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Database Security



Information Privacy
Proper Database Storage
List Marking – “salting” or “seeding”

Direct Marketers must safeguard their
customer database and discourage theft.
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Common Uses of a Customer
Database
1.
2.
3.
4.
5.
6.
7.
8.
Profile Customers
Retain Best Customers
Thank Customers For Their Patronage
Capitalize on Cross-Selling/Continuity Selling
Develop A Customer Communication Program
Perform Marketing Research
Generate New Customers
Send Customized Offers
…and MORE!!
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Example of a Customized Offer
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Performing Database Analytics

Data Mining


Defined: The process of using statistical
and mathematical techniques to extract
customer information from the customer
database to draw inferences about an
individual customer’s needs and predict
future behavior.
Online Analytical Processing (OLAP)
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
What’s the Secret to Database
Analytics?
For Marketers to…
1.
2.
Be able to identify their “most” and
“least” valuable customers;
Clarify demographic and behavioral
statistics that apply to each
population.
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Database Enhancement
Defined – Refers to adding and overlaying
information to customer records to
better understand and describe the
customer
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Reasons To
Enhance a Database
1. Learn more about the customer
2. Increase the effectiveness of future
promotional activities targeted to
current customers
3. To better prospect for new customers
who are similar to current customers
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Common Data Collected for Data
Enhancement
External
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
Geographic Address
Telephone Number
Gender of Head of Household
Length of Residence
Number of Adults at Residence
Number of Children at Residence
Income
Occupation
Marital Status
Make of Automobiles Owned
Internal
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
Age
Gender
Income
Marital Status
Family Composition
Street Address
E-Mail Address
Length of Residence
Size of Household
Type of Housing
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Customer Relationship
Management



Defined: A business strategy designed to
identify and maximize customer value.
To identify “touch points” between the
business (company) and its customers and
prospective customers.
To target customer needs to maximize the
customer’s experience and overall customer
satisfaction.
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Full-Circle Marketing (Kurt Ruf)
Full Circle Marketing
Marketing in the New Economy
External Data Providers
Demographic Data
Lifestyle Data
Prospect Lists
Demand Data
On-line/Off-line Data
Data Mining
Data Cleansing
Postal Processing
Campaign Mgmt.
Database Mgmt.
Data Analysis
c
ar
se
Re
Channels
an
Pl
h
Back office apps.
Central
Marketing/
Relationship
Database
Te
st
Customer
Internal/Web
Front office apps.
lid
Va
ate
Client Interfaces
Mail House
Tele-marketer
e-mail engine
CRM
e-mail
Fax
Phone
Direct Mail
OLAP tools, report tools, data transfer
Direct
Wireless
Client
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Customer Value

Customers should be viewed as an investment

Without customers there is no business

If a marketing effort results in the acquisition of
new customers who will generate value over time
the action is desirable
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Customer Value Hierarchy
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Lifetime Value of A Customer
(LTV)


Calculated as the discounted stream of
net revenues that a customer will
generate over the period of his or her
lifetime of patronage with a company.
The information needed to calculate
LTV is derived from transactions
recorded in a customer database.
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
One-on-One Personalization

Micro-targeting – is one-on-one
personalized marketing based on
advanced, precise psychographic and
lifestyle data.
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Partner Relationship Marketing
(PRM)


Defined: Where companies work closel
with partners in other companies or
departments to generate greater value
to customers.
Marketers cultivate relationships with
prospective partners just as they do
with prospective customers.
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall
Case Study
Smithfield Foods
Copyright© 2010 Pearson Education, Inc.
Publishing as Prentice Hall