Chapter 4 Secondary Data

Report
Chapter Four
Secondary Data
Chapter Objectives
• Compare the advantages of secondary data
and primary data
• Identify the limitations of secondary data in
terms of their relevance and accuracy
• Distinguish between (1) original and secondhand sources of secondary data and (2)
internal and external sources of secondary
data
Copyright © Houghton Mifflin Company. All rights reserved.
4|2
Chapter Objectives (Cont’d)
• Explain why secondary data management is
increasingly important
• Define marketing information system and
describe its basic components
Copyright © Houghton Mifflin Company. All rights reserved.
4|3
What Do These Companies
Have in Common ?
Pure and Persil detergent
Cadbury Chocolates
Huggies Diapers
Birds Eye Fish Sticks
• Different products, different companies, one
common database
Copyright © Houghton Mifflin Company. All rights reserved.
4|4
Secondary Data
• Data collected for a purpose other than the
research situation at hand
• Advantages
–
–
–
–
Cost and time
Availability
Less expensive
Less time intensive
Copyright © Houghton Mifflin Company. All rights reserved.
4|5
Using Secondary Data: Advantages
• Readily available
–
–
–
–
Whirlpool warranty card
Nielsen/Net Ratings
U.S. Census Bureau
Statistics
Copyright © Houghton Mifflin Company. All rights reserved.
4|6
Disadvantages of Secondary Data
• Relevance: may not match the data needs of
a given project.
– Measurement units
– Differences in category definitions
– Time Period
Copyright © Houghton Mifflin Company. All rights reserved.
4|7
Secondary Data:
Small Business Application
• Market Research for a small business: You
want to start a pool and spa cleaning and
repair service
• How do you find out about market size and
competition?
Copyright © Houghton Mifflin Company. All rights reserved.
4|8
Secondary Data Relevance:
Measurement Units
• Carpets Unlimited manufactures a variety of
carpets
• Sentinel Corporation produces a line of
smoke detectors
• U.S. Census of Population and Housing Data
can be used to estimate the total residential
market potential for their products in different
sections of the country
Copyright © Houghton Mifflin Company. All rights reserved.
4|9
Secondary Data Relevance:
Measurement Units (Cont’d)
• Carpets Unlimited requires size data
expressed in square feet
• Sentinel Corporation requires size data
expressed in number of rooms per household
• U.S. Census of Population and Housing data
– Useful to Sentinel Corporation but not useful
for Carpets Unlimited
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 10
Digital BabySitter
Digital BabySitter.com
website
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 11
Digital BabySitter (Cont’d)
• Specializes in making digital baby monitor
devices
• Wants to expand beyond the United States
– Based on birthrates provided by the United
Nations (www.un.org), the company decided
to target China and India
– Obtained information on computer penetration
in urban areas and chose urban populations
as its target market
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 12
Digital BabySitter (Cont’d)
• Secondary Data Analysis is not meaningful in
China and India because children are either
with their extended families or at school
– Children are almost never alone
– Secondary data is not always relevant!!!
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 13
Secondary Data Is Not Always Reliable
• GOJO launched Purell as an "instant hand sanitizer"
– Walgreen’s positioned it as a skin care/first aid product
(cleans without water)
– Nielsen and Information Resources Inc. (IRI)
categorized it as liquid soap
– Sales varied by location
• Is it a liquid soap or hand sanitizer? What is it?
• Category mismatches make the secondary data not
always reliable
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 14
Problems with Census Data
• Category mismatch
• Changes in category definition
• The time period during which secondary data
were collected
• Using data that are too old
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 15
The Numbers Game
• THE SHOCKING TRUTH IS THAT
STATISTICS ARE ONLY AS CREDIBLE AS
THE SOURCES THAT PRODUCE THEM!
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 16
Spam Projections Which Numbers to Use?
2002
2004
19%
84%
Brightmail
39
65
Postini
60
78
Frontbridge
40
82
Message Labs
Copyright © Houghton Mifflin Company. All rights reserved.
Many accept the
above projections
without questioning
their validity, even
when the
projections differ
by billions of
dollars across the
competing studies
4 | 17
Secondary Data Limitations
• Accuracy
– Who collected the data?
– Why was the data collected?
– How was the data collected?
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 18
Types and Sources of Secondary Data
• Internal Sources
– Company held information
• External Sources
–
–
–
–
Government
Syndicated Sources
Trade Associations
Miscellaneous Sources
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 19
Exhibit 4.1 Flow Diagram
for Conducting a
Data Search
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 20
Secondary Data: Internal vs. External
• Manager of McDonald's wants to know the
effect of the company's tie-in with movies like
Shark Tales
• Should the manager purchase this syndicated
service from the marketing research firm?
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 21
Internal Data
• Internal data can often be obtained with less time,
effort, and expense than external secondary data
• May have relevance to the research being conducted
• Examples include
– A firm’s historical record of sales
– A public service association’s list of donors
– Public opinion polls conducted in the past by a political
candidate’s campaign office
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 22
External Data: Government Sources
• Collects extensive data about people, firms, markets,
and foreign countries; more than any other secondary
data source
• Data collected is readily available on Internet sites
• Documents published are in the form of summary
reports based on the raw data collected
• The raw data is often available for a fee
– Public-Use Microdata files
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 23
Syndicated Sources
• Syndicated services offered by marketing
research firms
– Nielsen Retail Index
• Fees are required but they are more cost
effective than collecting primary data
• Focus directly on the needs of decision
makers
• Updated more frequently than government
data
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 24
Syndicated Sources (Cont’d)
• Often allows for customization
– Roper reports
• Supermarkets are also a valuable source for
secondary data
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 25
Trade Associations
• Very numerous and diverse
• Many collect data relevant to and about their
members
• Also collect competitively sensitive data about
members that may not be available to
industry outsiders
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 26
Competitive Intelligence:
FIND/SVP Helps Clients
• Industrial products and services company facing a
worldwide market decline
• Approached FIND/SVP (a leading knowledge
services company) to compare its plant
manufacturing strategy and costs with those of
competitors
• FIND/SVP
– Undertook a market scan of published information on
competitors’ plants
– Obtained Environmental Protection Agency (EPA)
documents
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 27
Competitive Intelligence:
FIND/SVP Helps Clients (Cont’d)
• Based on FIND/SVP's analysis, the industrial
products and services company was able to
assess cost structures of its competitors and
develop benchmarks for quality, employee
performance, and utility costs
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 28
Competitive Intelligence:
Burger King Corp
• Burger King
– Maintains a brand research library and subscribes to
analyst reports that provide a detailed view of
competitors' financial and long-term plans
– Gathers syndicated reports that provide sales and cost
data and describe the competition's growth plans
– Insights about the restaurant business can be flushed
out from interviews with restaurant business leaders,
published routinely in these trade journals
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 29
Managing Secondary Data
• Merely keeping abreast of all the available
data without being overwhelmed is a
challenge
• Effective secondary-data management is
necessary in this "information explosion" age
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 30
Ad Hoc Research Projects
• Discrete, situation specific projects that are
initiated and completed in response to a
particular question, or set of related
questions, raised by a decision maker
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 31
Evolution of MkIS
Ad Hoc
Marketing
Research
Copyright © Houghton Mifflin Company. All rights reserved.
Stage 1
Marketing
Information System
4 | 32
Full-fledged Marketing
Information Systems
• Data warehouse information storage and
retrieval system
• Marketing decision support systems
– Data Mining
– Data Modeling
• Expert systems
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 33
Exhibit 4.2 A Hotel
Chain’s Marketing
Information System
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 34
Marketing Information Systems (MkIS)
• A continuing and interacting structure of
people, equipment, and procedures designed
to gather, sort, analyze, evaluate, and
distribute pertinent, timely, and accurate
information to marketing decision makers
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 35
Data Warehousing
• A centralized database, which consolidates
enterprise-wide data from a variety of internal
and external sources
• An architecture, which allows individuals to
query and generate ad hoc reports in order to
perform an in depth analysis
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 36
Exhibit 4.4 A Typical Data
Warehouse Operation
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 37
Exhibit 4.5 Database Model
(Dimensional Model)
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 38
7-Eleven's Information System
Helps in Forecasting
• 7-Eleven Inc. installed an inventory
management/sales data system in all of its
5,600 franchisee and company-owned stores
nationwide
• The system provides item-by-item sales data
allowing managers to determine which of the
2,500 products they carry are selling well
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 39
7-Eleven's Information System
Helps in Forecasting (Cont’d)
• The system also alerts managers about
upcoming events and news that could affect
which items will be in demand
• Information system thus helps 7-Eleven in
sales forecasting and in collaborative product
development with suppliers
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 40
Cover Concepts: Database
• A producer of book jackets with corporate
advertising on the cover
• Cover Concepts covered schools' books with
free jackets carrying advertisements and
interesting messages that appealed to kids,
providing national advertisers with a costeffective way to reach the 6-to-18-year-old
market
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 41
Cover Concepts: Database (Cont’d)
• Company's database has grown from 55 Boston-area
schools in 1989 to 31,000 schools (out of a total of
85,000) and more than 21 million kids nationwide
• Cover Concepts gathers the database's extensive
demographic information, which it updates yearly,
from the elementary, junior high, and high schools
themselves, as well as from the Census Bureau,
private database companies, and other sources
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 42
Evolution of MkIS
Ad Hoc
Marketing
Research
Stage 1
Marketing Information
System
Stage 2
Decision Support
System
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 43
Marketing Decision Support System
(MDSS)
• Definition: An MkIS that permits managers to
request special types of data analyses or
reports on an as-needed basis
– Interactively generates “What if...” scenarios
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 44
Data Mining
• The process of digging deep into immense
amounts of data to extract valuable and
statistically valid information
– IBM Intelligent Miner
– Angoss Software’s Knowledge STUDIO
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 45
Applications of Data Mining
• Companies -Telecommunications
• Benefits
– Segmentation of prospective customers to
increase new customer accounts at the same
time reducing cost per account
– Understanding individual customer
preferences and needs to deliver relevant long
distance products and services
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 46
Applications of Data Mining (Cont’d)
• Companies - Insurance
• Benefits
– Improving profitability through timely valuation
of insurance products
– Effective financial data management by
balancing market, regulatory, and insurance
pressures to provide superior customer/patient
care
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 47
Applications of Data Mining (Cont’d)
• Company - High Tech Design
• Benefits
– Profitability analysis and product life cycle
planning leading to increased focus on non
traditional customer segments thereby
expanding the market
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 48
Applications of Data Mining (Cont’d)
• Companies - Retail
• Benefits
– Demographic analysis, financial planning, and
forecasting, leading to precise buying, merchandising
and marketing
– Improving profitability through optimal shelf space
allocation
– Tighter end-to-end integration of internal as well as
vendor systems, leading to better inventory and
merchandise management
– Reducing returns and thereby improving margins
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 49
Applications of Data Mining (Cont’d)
• Companies - Banking
• Benefits
– Consumer intelligence helps create new
products and manage collections while
containing delinquency rates
– Profitability analysis by customer segments
– Market penetration through personalized
promotion strategies
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 50
Marketing Decision Support Systems:
Models
• A marketing response function is a mathematical
model that represents the relationship between
marketing input and output variables
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 51
MDSSs: Retail Databases
• Scanner-based databases allow retailers and
packaged goods manufacturers to monitor
and analyze sales trends:
– Changes in brand shares
– Shifts in consumer preferences
• Information Resources, Inc.’s BehaviorScan
and Nielsen’s Scantrack capture scanner
data from many retailers
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 52
Exhibit 4.7 Data Captured in a
Single Source Data Base
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 53
Evolution of MkIS
Ad Hoc
Marketing
Research
Marketing Information
System
Stage 2
Stage 3
Decision Support
System
Expert System
Copyright © Houghton Mifflin Company. All rights reserved.
Stage 1
4 | 54
Expert System (ES)
• An MDSS that proactively makes managers
aware of market situations warranting their
attention
• An MDSS can recommend appropriate
courses of action
– Artificial intelligence is utilized
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 55
Expert System (ES) (Cont’d)
• 7 - Eleven Maximizes Space and Selection
– Alerts store managers and suggests how to reallocate
shelf space to maximize profits from nutritional snack
bar sales
– Uses its expert system to determine the best allocation
of shelf space among the various products it sells
– Analyzing sales, cost, and promotional data, the
system translates the results into “Plan-a-Grams,”
printouts that show store managers, shelf by shelf,
exactly where to place their stock to maximize profit
Copyright © Houghton Mifflin Company. All rights reserved.
4 | 56

similar documents