Transcript 0273794469_berman_ch_08 12e

CHAPTER 8:
INFORMATION
GATHERING AND
PROCESSING IN
RETAILING
1
Chapter Objectives
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To discuss how information flows in a
retail distribution channel
To show why retailers should avoid
strategies based on inadequate
information
To look at the retail information system,
its components, and recent advances
To describe the marketing research
process
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Figure 8-2: How Information Flows in a
Retail Distribution Channel
Information
and the
Supplier
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Information
and the
Retailer
Information
and the
Consumer
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Suppliers Need To Know
From the Retailer From the Customer
• Estimates of
• Attitudes toward
category sales
styles and models
• Inventory turnover • Extent of brand
rates
loyalty
• Feedback on
• Willingness to pay a
competitors
premium for
superior quality
• Level of customer
returns
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Retailers Need To Know
From the Supplier From the Customer
• Advance notice of • Why people shop
new models and
there
model changes
• Customers’ likes
• Training materials
and dislikes
• Sales forecasts
• Where else people
shop
• Justifications for
price changes
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Consumers Need To Know
From the Supplier From the Retailer
• Assembly and
• Where specific
operating
merchandise is
instructions
stocked in the store
• Extent of warranty • Methods of payment
coverage
acceptable
• Where to send a • Rain check and other
complaint
policies
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Retail Information System (RIS)
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Anticipates the information
needs of retail managers
Collects, organizes, and stores
relevant data on a continuous
basis
Directs the flow of information to
the proper decision makers
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Figure 8-3: A Retail Information System
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Data-Base Management
• A major element in an RIS
• System gathers, integrates, applies, and
stores information in related subject
areas
• Used for
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Loyalty program management
Customer analysis
Promotion evaluation
Inventory planning
Trading area analysis
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Five Steps to Approaching
Data-Base Management
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Plan the particular data base and its
components and determine information needs
Acquire the necessary information
Retain the information in a usable and
accessible format
Update the data base regularly to reflect
changing demographics, recent purchases,
etc.
Analyze the data base to determine strengths
and weaknesses
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Figure 8-5: Data-Base Management
in Action
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Components of a Data Warehouse
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Physical storage location for data –
the warehouse
Software to copy original
databases and transfer them to
warehouse
Interactive software to allow
processing of inquiries
A directory for the categories of
information kept in the warehouse
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Data Mining and Micromarketing
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Data mining is the in-depth analysis of
information to gain specific insights
about customers, product categories,
vendors, etc.
Micromarketing is an application of
data mining whereby retailers use
differentiated marketing and develop
focused retail strategy mixes for
specific customer segments
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Data Mining Example:
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Using traditional statistical methods, an retail
analyst would ask “Are higher-income people
prone to be more loyal to a warehouse club
than those with lower income levels?”
Data mining, on the other hand, could
potentially provide more insight by pointing out
other factors contributing to store loyalty.
Data mining might group customers who have a
warehouse club’s credit cards, who live within
10 miles of the club, who own more than one
car, and who have a separate freezer.
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Figure 8-6: Applying UPC Technology
to Gain Better Information
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Figure 8-7: The Marketing Research Process
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Marketing Research in Retailing
The collection and analysis of
information relating to specific
issues or problems facing a
retailer
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Secondary Data
Advantages
Disadvantages
• Inexpensive
• May not suit current
study
• Fast
• Several sources and • May be incomplete
perspectives
• May be dated
• Generally credible
• May not be accurate
or credible
• Provides
background
• May suffer from poor
information
collection techniques
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Secondary Data Sources
Internal
• Sales reports
• Billing reports
• Inventory
records
• Performance
reports
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External
• Data bases
• Academic Search
Premier
• Government
• U.S. Census of
Retail Trade
• Statistical Abstract
of the U.S.
• Public records
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Primary Data
Advantages
• Collected for
specific purpose
• Current
• Relevant
• Known and
controlled
source
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Disadvantages
• May be more
expensive
• Tends to be more
time consuming
• Information may
not be acquired
• Limited
perspectives
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Primary Data Decisions
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In-house or outsource?
Sampling method?
• Probability
• Non-probability
Data collection method?
• Survey
• Observation
• Experiment
• Simulation
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Survey Methods
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In person
Over the
telephone
By mail
Online
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Disguised
Nondisguised
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Figure 8-9: A Semantic Differential
for Two Furniture Stores
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Mystery Shoppers
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Retailers hire people to pose as
customers in order to evaluate
aspects of the store environment
(e.g. sales presentations, display
maintenance, and service calls)
Often sales encounter based.
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Experiments
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An experiment is a research method
in which one or more elements of a
retail strategy mix are manipulated
under controlled conditions.
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An element may be a price, a shelf
display, store hours, etc.
If a retailer wants to find out the effects
of a price change on a brand’s sales,
only the price of that brand is varied.
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Simulation
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A simulation is a type of experiment
whereby a computer program is
used to manipulate the elements of
a retail strategy mix rather than test
them in a real-life setting.
Two simulation types are now being
applied in retail settings: those
based on mathematical models and
those involving “virtual reality.”
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