Download Database marketing with the SAS System

Database Marketing
with
Title
theDtaPaper
SAS System
Joanna Crosse - Product Manager
Linda Saul - Sales Support Consultant
Agenda
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What is database marketing?
Why do it?
Where is it going?
How does SAS fit in?
ý Data Warehousing
ý Data Analysis
Who’s doing it?
Conclusion
S
What is database marketing?
Develop
Develop
Test
Modify
Measure
Data
Test
Implement S
Mass Customisation
S
Why do it?
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Database marketing is:
ý Selective
ý Personal
ý Measurable
ý Adaptable
-Forsyth
S
Why do it?
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Database marketing is:
ý Selective
P communication focused
P maximise returns
P tailored to recipients needs
ý Personal
ý Measurable
ý Adaptable
S
Why do it?
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Database marketing is:
ý Selective
ý Personal
P personal details and needs
P preferences
P customer loyalty
ý Measurable
ý Adaptable
S
Why do it?
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Database marketing is:
ý Selective
ý Personal
ý Measurable
P cost, results
P profitability of individuals
ý Adaptable
S
Why do it?
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Database marketing is:
ý Selective
ý Personal
ý Measurable
ý Adaptable
P Modify to reflect experience
P Cycle of improvement
S
Where is it going?
Evolution of Database Marketing
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Three generations of Database
Marketing identified by Gartner:
ý
ý
ý
First Generation - “Enhanced
List Selection Systems”
Second Generation - “Customer
Information Repositories”
Third Generation - “Enterprise
Relationship Management”
S
Evolution of Database Marketing
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First Generation - “Enhanced List
Selection Systems”
ý
ý
ý
single database / bureau /flat
files
limited sharing & combining of
data
limited analysis

S
Evolution of Database Marketing
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Second Generation - “Customer
Information Repositories”
ý
ý
ý
typified by Data Warehouse
initiatives
combine different sources of
customer information
manage relationship with
customer
S
Evolution of Database Marketing
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Third Generation - “Enterprise
Relationship Management”
ý
ý
focus on customer relationships
enterprise-wide
migration towards “Customer
centric” enterprise
S
How does SAS fit in?
- Data Warehousing
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Database marketing uses a variety
of data sources:
ý
Internal sources
ý
External sources
S
How does SAS fit in?
- Data Warehousing
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Database marketing uses a variety
of data sources:
ý
ý
Internal sources - operational
P Customer service records
P Sales order processing
P Campaign results
P ....
External sources
S
How does SAS fit in?
- Data Warehousing
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Database marketing uses a variety
of data sources:
ý
ý
Internal sources
External sources
P Market Research
P Government statistics
P Geodemographic profiles
P ....
S
Data Warehouse for Database Marketing
Census/
Survey
Sales Order
Processing
Database
Marketing
GIS
Access
Data Cleaning
Campaign
Response
Competitive
Information
Integration
Data Mining
Information
Database
Summarisation
Customer
Service
Records
Data Visualisation
Multi-dimensional
Reporting
Organisation
Management
Campaign
Management
Customer
Profiling
Behavioral
Modeling
Strategy
Formulation
Exploitation
S
Benefits of Data Warehouse for
Database Marketing
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Integration of Information sources
ý Maximum information available
for decision making
Fast, easy access to information
ý Timely, appropriate decisions
ý Rapid response to market
changes
Marketing analysts concentrate
skills on exploiting market
intelligence
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How Does SAS fit in?
- Data Analysis
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Response analysis
Customer profiling
Segmentation
Forecasting
Reporting
Developing scoring models
Identifying purchase patterns
S
Segmentation
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Identifying distinct groups of buyers
Market Segmentation
Identify segmentation
variables and segment
the market.
Develop profiles of
resulting segments.
Market Targeting
Evaluate the
attractiveness of
each segment.
Select the target
segment(s).
“Small is
beautiful.
Less is
more.”
Product Positioning
Identify possible positioning
concepts for each target
segment.
Select, develop, and signal the
chosen positioning concept.
S
SAS for Segmentation
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Principal Components
analysis
Cluster analysis
Tree-based models
Data visualisation
Geographical Data
Visualisation
Cross-tabulations
110
100
i
90
80
-20
-10
0
10
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Identifying Purchase Patterns
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Spanish saying: To be a bullfighter
you must first learn to be a bull
analysis of existing customers to
determine patterns, trends and
associations
Product association
Customer behaviour
S
SAS for Identifying Patterns
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Perceptual mapping
Correlation analysis
Graphics
Data visualisation
Cross tabulations
Correspondence
analysis
Neural networks
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Who’s doing it?
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Ellos (Sweden)
Marks & Spencer Financial Services
(UK)
Mondadori (Italy)
Le Groupe Redoute (France)
Swedish Telecom (Sweden)
S
Mondadori Group
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CDE - books by mail order
ý 900,000 members
ý 8 million books sold annually
Mass customisation
Data Warehouse
Analyse customer behaviour
ý recruitment
ý respond to their needs
S
Marks and Spencer Financial
Services
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Subsidiary of leading UK retailer
Problem
ý “data rich but information poor”
Solution
ý Marketing Information
Management System (MIMS)
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Application areas
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Campaign Management
Customer Profiling
Segmentation
S
Application areas
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Campaign Management
ý response analysis
ý performance tracking
P results fed into next campaign
Customer Profiling
Segmentation
S
Application areas
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Campaign Management
Customer Profiling
ý who are best customers for a
mailing?
ý cross-selling
Segmentation
S
Application areas
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Campaign Management
Customer Profiling
Segmentation
ý Ultimate objective - segmenting
“on a one to one basis”
ý “Our aim is to treat customers as
individuals”
S
Benefits
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Single product for Market Research
Do everything at desktop
Help achieving “individually
targeted customer relationships”
S
Conclusion
Database Marketing
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Cost effective means of
communicating with carefully
selected segments and building
profitable long-term relationships
Advantages:
ý selective, personal, measurable,
adaptable
Requirements satisfied by Data
Warehouse strategy
S
Conclusion
Benefits of Database Marketing
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Aids understanding of customer
Helps identify profitable segments/
niche opportunities
Focuses resources to achieve
maximum return on investment
Maximises control
Aids test marketing
Enables treatment of customers as
individuals
S
Thank you for
your attention
DtaPaper Title
The SAS® System for successful decision making
Database Marketing with the SAS System
Joanna Crosse and Linda Saul
SAS Institute
1. Introduction
In the current climate of increased customer expectations and fierce competition, oneto-one marketing is the vision of today's organisations, rather than the traditional mass
marketing approach.
Database marketing facilitates the development and
implementation of such focused knowledge-based marketing campaigns. This results
in a more effective use of limited marketing resources and hence a stronger, more
competitive position in your marketplace.
This paper will define database marketing and discuss the advantages of employing a
database marketing strategy. The techniques and processes available in the SAS
System that enable database marketing will be discussed.
2. The Concept of Database Marketing
There are many definitions of database marketing, ranging from being equivalent to
direct mailing to doing anything that involves a database! One accepted definition is
given by David Shepard Associates as “an information-driven marketing process that
enables marketers to develop, test, implement, measure and appropriately modify
customised marketing programs and strategies”. This means that existing data, for
example, customers’ detailed transaction records, are used to develop a marketing
campaign, which may then be tested on a sub-population. This campaign can be
implemented, with responses being measured and the campaign details being modified
to improve response rates, resulting in a cycle of continuous improvement and
feedback. Thus database marketing is often characterised by a cyclical information
flow, i.e. using information to direct a marketing initiative that is designed to elicit a
response, which in turn provides more information that can be added to the original
database. This paper will adopt this broader definition of database marketing.
The term database marketing originated from the direct mail and catalogue industry,
but it is evolving into an increasingly sophisticated marketing activity, with the aim of
building, maintaining and enhancing customer relationships using the full range of
communications methods, including telephone, newspapers, personal contact and, of
course, direct mail. The exact combination of marketing methods and customer
contact methods is unique to the particular product or service and the market in which
it is sold.
The combination of control over the message purveyed and the degree of
personalisation possible is a key consideration in any marketing activity, see Figure 1
(Forsyth, 1995). Different media are employed depending on the combination of
control and personalisation required, subject, of course, to financial considerations.
For example, TV adverts offer considerable control over message, but almost no
scope for personalisation, whereas telesales can be personalised but the message may
be diluted. One of the key strengths of database marketing is that it facilitates both
control and personalisation. In addition, with decreasing hardware costs and the
increased power of both hardware and software the necessary management,
organisation and exploitation of the database can now be a reality, providing the route
to mass customisation. This is key to the emerging concept of relationship marketing
and long term customer retention. As Peppers & Rogers (1993) comment “instead of
concentrating on one product at a time and trying to sell it to as many customers as
possible during a fiscal period, tomorrow’s share of customer marketeer will
concentrate on one customer at a time and try to sell that customer as many products
as possible over the customer’s lifetime.” As an example, direct marketing techniques
and relationship marketing are central to Club degli Editori, a subsidiary of the Italian
Mondadori Group, selling books by mail order. Ivano Maestri, General Manager of
CDE SpA, says that in order to succeed “we must increase the performance of our
customers, that is to increase their propensity to buy from us” (SAS Communications,
1996).
INCREASING CONTROL OF CONTENT
Direct sales
staff
Telephone
contact
Franchise
operations
Letters/
mail
The
Customer
Agents/
intermediaries
Bills/
statements
Distributors
Inserts
Influencers
PR
TV
INCREASING PERSONAL ELEMENTS
Delivery
staff
Service
staff
Retail /service
outlets
Press
Figure 1: The many ways in which any organisation can contact and influence its customers
(Forsyth, 1995)
From the consumers viewpoint the move towards services, products and marketing
tailored to each individual is the ultimate goal. However, organisations must balance
the benefits against operating costs and often adopt the intermediate strategy of
developing the right segmentation and analytical tools that will support mass
customisation. This can be illustrated by Levi Strauss who have pioneered a service
of offering custom sized jeans to women, thus increasing repeat business from an
appearance conscious segment of the market. Similarly, CDE SpA have adopted a
mass customisation strategy so that rather than producing a single catalogue for
900,000 members, they produce 900,000 catalogues (SAS Communications, 1996).
3. The Advantages of Database Marketing
The objectives of database marketing are, of course, similar to those of any method
designed to promote goods and services. These may include attracting new
customers, retaining existing customers and increasing demand. However, the
advantages that database marketing has over other marketing methods, as described by
Forsyth (1995) are that it is:
Selective: focusing communication on specific groups. For example, credit card
companies can send material to individuals with a specific profile - they may send
details of premium business travel services to gold card holders in a specific age band
whose spending record shows many foreign transactions. Focusing communication in
this way reduces promotional costs whilst maintaining or increasing sales volumes. In
addition, well targeted campaigns reduce the irritation caused by inappropriate junk
mail.
Personal: allowing the customer not only to be addressed by their preferred name and
title, but also to offer services and products relevant to their known lifestyle and
preferences. For example, respecting people’s preferences not to be telephoned at
home, or sending insurance details only when policies are due for renewal.
Measurable: linking responses to actions enables campaign effectiveness and the
resultant financial return to be measured.
Adaptable: the flexibility and individuality underpinning database marketing enables
the format and scale of customer contact to be tested and modified to maximize
returns, leading to the cycle of information flow already discussed. For example, a
loyalty card may be launched using a general campaign to all customers. Following
analysis, a need for customised campaigns for certain segments such as pensioners
and students can be identified and acted on.
These advantages have made database marketing an application employed within a
wide range of organisations, including retail, banking, financial services, insurance,
health care, telecommunications, charities and mail order companies. It is a costeffective means of systematically communicating with many smaller, carefully
selected segments of people, rather than using a mass marketing, shot gun approach.
4. The Evolution of Database Marketing
Database marketing techniques require data from a variety of sources, both
operational and external. This data needs to be accessed, managed, organised and
exploited and is ideally suited to a data warehousing solution. Such a solution
provides a means of gathering together data from a variety of sources, analysing it and
presenting it to the business user in a consistent and accessible manner. The analysis,
or exploitation, for database marketing includes some specialised analytical
techniques, such as data mining, identification of segments and customer profiling.
Both data warehousing and data analysis will be discussed later in this paper.
In a recent report (Peak Performance, March 1996), The Gartner Group reviewed the
current and future prospects for database marketing. They found that enterprises are
now facing increased pressure to respond to global competition, rising customer
expectations and new market opportunities, so database marketing is becoming
critical. Thus posing the question “How will database marketing evolve to meet
changing user requirements and to reflect the changing marketing process?” The
resulting discussion defines the three generations of database marketing as:
The First Generation: Enhanced list-selection Systems
These are characterised by a proprietary database engine optimised for performance.
First-generation strategies typically opt for an external service bureau to manage
customer and marketing information. Whilst often containing a robust set of direct
marketing functions, these systems limit data access to proprietary tools and they often
lack the scalability required to incorporate growing volumes of detailed customer data.
The Second Generation: Customer Information Repositories
These are typified by data warehousing initiatives as the central information
repository. Accompanying the change in technology is an expanded use of customer
information outside of the marketing function.
The Third Generation: Enterprise Relationship Management
These systems must focus on customer relationships enterprise wide, not be limited to
a single function, product or channel view, and can be supported by an enterprise wide
data warehouse. These systems and strategies allow multiple functions outside of the
marketing function to share information and allocate enterprise resources to optimise
long-term profitable customer relationships.
Gartner’s conclusion is that “with rapid technological change, conflicting vendor
claims and a confusing marketplace, enterprises must align their vision, strategies and
goals with the appropriate systems, infrastructure and capabilities. Enterprises with
first-generation database marketing implementations must begin to invest in scalable
systems, developing new metrics, redesigning business processes surrounding the
customer, and gaining senior managers support to enable the migration toward a
customer-centric enterprise”.
5. Database Marketing with the SAS System
The SAS System is the industry standard business intelligence environment. Its
modular approach provides one of the most functionally rich and flexible solutions,
fully supporting all generations of database marketing. Data warehousing and data
analysis are key components of any successful database marketing implementation.
5.1 Data Warehousing
SAS Institute is the leading supplier of data warehousing technology, with over 200
data warehouse implementations in Europe alone. Successful second generation
database marketing applications are invariably based on a data warehousing
architecture, see Figure 2. SAS Institute will continue to provide the platform that
enables organisations to move forward to the third generation.
The SAS Data Warehouse for Database Marketing
Census/
Survey
Sales Order
Processing
Campaign
Response
Competitive
Information
Data Cleaning
GIS
Data Mining
Integration
Information
Database
Data Visualisation
Database
Marketing
Campaign
Management
Customer
Profiling
Consolidation
Multi-dimensional
Reporting
Behavioural
Modelling
Summarisation
Customer
Service
Records
Strategy
Formulation
Management
Organisation
Exploitation
Figure 2: The SAS Data Warehouse for Database Marketing
The key requirement for a successful database marketing strategy is to have the data
readily accessible in a useable form. As the database marketing strategy matures
within an organisation, data may come from a variety of sources including sales order
processing systems, market research, campaign response information, customer
service records, mailing lists and product registrations. External data sources may
include geodemographic profiles, government statistics, news feeds and stock market
information. This is facilitated through the SAS System’s ability to access data from a
vast number of different sources, ranging from flat files and spreadsheets to merchant
databases. Gathering together data on customers from different sources available
within the organisation is of paramount importance when investigating customer
behaviour patterns, characteristics and preferences in order to identify target segments,
customise messages and track responses. The trend is for the amount of data available
to increase. For instance, many major retailers are introducing loyalty schemes and
more sophisticated electronic point of sale (EPOS) systems enabling more detailed
information such as the combination of purchases in a single transaction to be
recorded and acted upon.
Data from multiple sources must be combined and differences in coding methods
must be addressed and anomalous data where possible identified and corrected. For
example, male and female could be coded as 0 and 1 in one data source, and M and F
in another. When performing queries against a SAS data warehouse, the end-user or
marketing analyst need not be concerned with either the original data sources or the
attendant data management issues, nor be dependent on an overworked IT department
to generate the necessary report. They are able to concentrate their skills on exploiting
data orientated to their subject of concern, which will include customers or products.
Reports and analysis are available in a timely manner enabling effective decisions to
be made. Rapid access to information enables fast reaction to changes in the
organisation’s marketing environment such as unexpected threats or opportunities
through external influences (e.g. competitive action or political change) in order to
protect or improve the organisation’s competitive position within the marketplace.
5.2 Data Analysis Techniques
Within the SAS System, the data analysis techniques suitable for database marketing
are constantly expanding in response to customer demand. For example, tree based
models and neural networks have recently been included. Typical requirements might
include customer profiling, forecasting, segmentation, reporting, developing scoring
models and identifying purchase patterns.
Customer profiling: identifying customer characteristics based on attributes stored in
your data warehouse. For example, enabling you to answer questions such as who is
your typical customer? who are your best or most profitable customers? did the
respondents match your original target audience? Sabine Descamps, of the marketing
department of La Redoute Catalogue, France, makes the point that “the most
important selection criteria in direct mail are historical: who has had a catalogue in the
past, how long they have been a customer, and what they have bought by value and
volume” (Inform 7).
Segmentation: dividing a market into distinct groups of buyers who might require
separate products and/or marketing mixes, enabling you to target profitable segments.
Organisations may use a range of analytical techniques to identify the characteristics
of their best customers, or those most receptive to new products and/or services. This
knowledge can then be used to target those most profitable market segments.
Forecasting: forecasting and predicting future trends and patterns. For example,
enabling you to predict response rates, forecast demand and profitability. As well as
traditional techniques, for example discriminant analysis, data mining algorithms such
as neural networks might be utilised to predict long term profitability of customers.
Descamps of La Redoute Catalogue states that “we use the SAS System to analyse our
customers’ past buying behaviour with discriminant analysis techniques. This reveals
the combinations of criteria which correspond to a high order rate and helps us to
predict the probable future behaviour of the client” (Inform 7).
Reporting: producing management and exception reporting. For example enabling
you to identify areas of opportunity or concern, where new products or services could
be offered or how you compare with the competition.
Developing scoring models: attributing a measure or score to individuals. For
example assessment of credit worthiness of individuals allowing you to model the
risk associated with providing services to particular customers; or using behavioural
scores to segment your data. At Credit Lyonnais, a French bank, scoring card
techniques are not only used to accept or refuse an applicant at branch level, but also
to decide who will be offered a product and to identify who is a potential buyer or
non-buyer in a direct marketing campaign ( Inform 5).
Identifying purchase patterns: analysing behaviour of existing customers to determine
patterns, trends or product associations. For example, retailers may perform basket
analysis to look for buying patterns, such as a strong association between barbeque
equipment and sausages. This is illustrated at Printemps, a leading retailer; Norbert
Bachelot, director of computing studies, comments “We want to use the SAS
System’s analysis facilities to identify the links across departments so that we can
successfully gain new customers for, say, the perfumery department by promoting to
customers who buy ladies’ hats” (Inform 7).
Strategy formulation: determining the direction of the organisation based on
information gathered about the market place and environment, for example
competitors, demographic trends and technological advances.
The SAS System is rich in depth and range of functionality available for database
marketing, including:
• ad-hoc querying
• natural language querying
• report generation
• frequency counts
• multi-dimensional reporting
• correlation analysis
• linear and non-linear regression
• discriminant analysis
• factor analysis
• linear programming
• data visualisation
• geographical information systems
• neural networks
• tree based models
• perceptual mapping
• conjoint analysis
• clustering techniques
• econometric time series and forecasting
• pareto analysis
• control charts
and, of course, data mining. A combination of these techniques and the relevant
historical data enable you to predict how a customer, or customer segment will behave
in the near future and over the long term.
6. Summary
Database marketing is for targeting customer populations and profiles of interest. The
advantages of database marketing is that it is selective, personal, measurable and
adaptable. By their nature, database marketing strategies are constantly evolving.
They must be supported by flexible business intelligence systems, implementing data
warehousing and data analysis technology. The SAS System is ideally suited to this
role.
References
David Shepard Associates, The New Direct Marketing: How to Implement a ProfitDriven Database Marketing Strategy, 1995
Forsyth, P, Database Marketing, The Financial Times Handbook of Management,
1995, pp623-631
Gartner Group, Database Marketing, Peak Performance, Q1 1996, pp1-10
Peppers D & Rogers M, The One to One Future, 1993
SAS Institute, Accurate Segmentation, Inform 7 ‘One-Stop Shopping’, pp14-15
SAS Institute, A Closely Guarded Secret, Inform 5 ‘Marketing for Profit’,pp14-15
SAS Institute, Delivering the Goods, Inform 7 ‘One-Stop Shopping’, pp16-17
SAS Institute, The Experience of the Mondadori Group, SAS Communications, Q1
1996, pp36-39
Further Reading
Brown, M. & Bulkley, J., Database Marketing and Business Geographics, SUGI 21,
1996, pp830-835