Transcript E-Marketing 4/E Judy Strauss, Adel I. El

E-Marketing 4/E
Judy Strauss, Adel I. El-Ansary, and Raymond Frost
Chapter 6: Marketing Knowledge
©2006 Prentice Hall
6-1
Question???
• Define the following
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Data
Information
Knowledge
Understanding
Wisdom
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Chapter 6 Objectives
• After reading Chapter 6 you will be able to:
• Identify the three main sources of data that emarketers use to address research problems.
• Discuss how and why e-marketers need to check
the quality of research data gathered online.
• Explain why the Internet is used as a contact
method for primary research and describe the main
Internet-based approaches to primary research.
• Contrast client-side, server-side, and real-space
approaches to data collection.
• Highlight four important methods of analysis that emarketers can apply to data warehouse information.
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The Purina Story
• Nestle Purina PetCare Company wanted to
know whether their web sites and online
advertising increased off-line behavior.
• Nestle developed 3 research questions:
• Are our buyers using our branded Web sites?
• Should we invest in other Web sites?
• If so, where should we place the advertising?
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The Purina Story, cont.
• They combined online and off-line shopping
panel data and found that:
• Banner clickthrough was low (0.06%).
• 31% of subjects who were exposed to both online
and off-line advertising mentioned Purina.
• The high exposure group mentioned Purina more
than the low exposure group.
• Home/health and living sites received the most
visits from their customers.
• Would you also have selected petsmart.com
and about.com for Purina PetCare ads?
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6-4
Data Drives Strategy
• Organizations are drowning in data.
• Marketing insight occurs somewhere between
information and knowledge.
• Purina, for example, sorts through hundreds of
millions of pieces of data about 21.5 million
consumers to make decisions.
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6-5
Data Drives Strategy
• Current problem for marketing decision makers
= Information overload.
• Origin of data:
• Survey results, product sales information, secondary
data about competitors, and much more
• Automated data gathering at Web sites, brick-andmortar points of purchase, and all other customer touch
points.
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Data Drives Strategy
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What to do with all the data?
• Purina marketers built a roadmap for their
Internet advertising strategy:
1.
2.
3.
4.
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Data are collected from a myriad of sources,
Filtered into databases,
Turned into marketing knowledge,
Used to create marketing strategy.
S
D
Internal Data
Secondary Data
Primary Data
Information: consumer behavior, competitive intelligence
Product
Database
Customer/
Prospect Base
Other Data/
Information
*Marketing Knowledge*
S
Tier 1
Segmentation
Targeting
Differentiation
Positioning
Tier 2
Marketing
Mix
CRM
From Sources to Databases to Strategy (SDS Model)
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Performance
Metrics
Differentiation
Tier 1
tasks
Tier 2
tasks
Segmentation
Positioning
Targeting
E-Marketing
Strategy
Offer
CRM/PRM
Communication
Value
Distribution
Exhibit 3 - 1 Formulating E-Marketing Strategy in Two Tiers
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Terabytes of Corporate Data
2,000,000
1,800,000
1,600,000
1,400,000
1,200,000
1,000,000
800,000
600,000
400,000
200,000
0
1999
2000
2001
2002
2003
One Terabyte = 1,099,511,627,776 bytes
The U.S. Library of Congress has claimed it contains approximately 20 terabytes of text.
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6-6
From Data to Decision: Purina
Decision
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Let’s put banner ads on about.com
Knowledge
Dog owners who see ads online are likely to
buy Purina ONE. We know the sites they
visit: about.com, www.petsmart.com.
Information
1. Purina buyers are 20% more likely to visit
about.com.
2. 36% of dog owners who see Purina ads would
buy the brand.
Data
016030102
(Buyer 1 bought Purina puppy chow on March 1)
6-7
Marketing Knowledge Management
• Knowledge management is the process of managing
the creation, use and dissemination of knowledge.
• Data is the lubricant for a learning organization, and
organizations are drowning in it.
• This is an information technology manager’s problem,
and e-marketers must determine how to glean insights
from these billions of bytes.
• Marketing insight occurs somewhere between
information and knowledge:
• Knowledge is more than a collection of information, but
resides in the user,
• People, not the Internet or computers, create knowledge;
computers are simply learning enablers.
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6-8
Uses of Knowledge Management
Use in the Telecom Industry
Representative Firm
Scanner Check-Out Data Analysis
Call Volume Analysis
Equipment Sales Analysis
Customer Profitability Analysis
Cost and Inventory Analysis
Purchasing Leverage with Suppliers
Frequent-Buyer Program Management
AT&T
Ameritech
Belgacom
British Telecom
Telestra Australia
Telecom Ireland
Telecom Italia
Use in the Retail Industry
Representative Firm
Scanner Check-Out Data Analysis
Sales Promotion Tracking
Inventory Analysis and Deployment
Price Reduction Modeling
Negotiating Leverage with Suppliers
Frequent-Buyer Program Management
Profitability Analysis
Product Selection for Markets
Wal-Mart
Kmart
Sears
Osco/Savon Drugs
Casino Supermarkets
W. H. Smith Books
Otto Versand Mail Order
Amazon.com
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6-9
The Learning Organization
• Uses internal and external data to:
• Quickly adapt to its changing environment
• Creating organizational change to improve
competitive position + employee satisfaction.
• Recognizes the importance of:
• Employee empowerment and development,
• Cross-functional teams for brainstorming
• Risk-taking for breakthrough ideas.
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The Learning Organization
• Benefits from:
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Improved product quality and innovation,
Better customer relations,
Shared visioning,
Process breakthrough improvements,
Stronger competitiveness through team effort.
• Is a key concept in an organization because of information
technology advances and the rapid growth of the Internet.
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The Learning Organization
• One of the most important area in marketing learning
= the learning relationship.
 The more marketers can learn about their customers, the better they
can serve them with appropriate marketing mixes needs.
• Example:
• An American Airlines frequent flier can receive a short text
message on her cell phone two hours before a flight with all flight
information.
• A step further = Would you like us to notify you this way for each
flight you book with us?
 American would be learning what the customer wants, confirming
it, and then delivering it automatically.
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The Marketing Information System
• Marketers manage knowledge through a
marketing information system (MIS).
• Many firms store data in databases and data
warehouses.
• The Internet and other technologies have
facilitated data collection.
• Secondary data provides information about
competitors, consumers, the economic
environment, etc.
• Marketers use the Net and other technologies to
collect primary data about consumers.
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Sources of data: Internal records
• Accounting, finance, production and marketing
personnel collect and analyze data.
• Nonmarketing data, such as sales and advertising
spending
• Sales force data
• Customer characteristics and behavior
• Universal product codes (bar code)
• Tracking of user movements through web pages
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1) Customer orders 10
new co mputers.
3) database trends
Sales rep
Where is the
%@#& “on”
switch?
Hmmm, 21% of
customers can’t
find “on” switch.
Customer
Database
4) Redesign computer
switch
2) Customer calls
co mpany
Customer service rep
A hypothetical scenario for a computer company that is learning from its
customers as a whole and using the information to improve products.
E-Marketers Learn From Customers
Source: Adaptation of ideas from Brian Caulfield (2001), “Facing up to CRM” at www.business2.com
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Secondary data
• Can be collected more quickly and less expensively
than primary data.
• Common sources of secondary data for social science
include censuses, large surveys, and organizational
records.
• Secondary data may not meet e-marketer’s
information needs.
• Data were gathered for a different purpose.
• Quality of secondary data may be unknown.
• Data may be old.
• Marketers continually gather business intelligence by
scanning the macro-environment.
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6-12
Public and Private Data Sources
• Publicly generated data
• U.S. Patent Office
• American Marketing Association
• Privately generated data
• Forrester Research
• Nielsen/NetRatings
• Online databases
• Secondary data help marketers understand:
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Competitors,
Consumers,
The economic environment,
Political and legal factors,
Technological forces,
Other factors in the macro-environment affecting an organization.
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6-13
Public Sources of Data in the U.S.
Web site
Information
Stat-USA
www.stat-usa.gov
U.S. Department of Commerce source of international
trade data.
U.S. Patent Office
www.uspto.gov
Provides Trademark and Patent Data for Businesses.
World Trade Organization
www.wto.org
World Trade Data.
International Monetary Fund
www.imf.org
Provides information on many social issues and
projects.
Securities and Exchange Commission
www.sec.gov
Edgar database provides financial data on U.S. public
corporations.
Small Business Administration
www.sbaonline.gov
Features information and links for small business
owners.
University of Texas at Austin
advweb.cocomm.utexas.edu/world
Ad World with lots of links in the ad industry.
Federal Trade Commission
www.ftc.gov
Shows regulations and decisions related to consumer
protection and anti-trust laws.
U.S. Census
www.census.gov
Provides statistics and trends about the U.S. population.
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Sampling of Sources of Privately Generated Data in the U.S.
Web site
Information
AC Nielsen Corporation
www.acnielsen.com
Television audience, supermarket scanner data and more.
The Gartner Group
www.gartnergroup.com
Specializes in e-business and usually presents highlights of its
latest findings on the Web site.
Information Resources, Inc.
www.infores.com
Supermarket scanner data and new product purchasing data.
Arbitron www.arbitron.com
Local-market and Internet radio audience data.
The Commerce Business Daily
www.cbd.savvy.com
Lists of government requests for proposals online.
Simmons Market Research Bureau
www.smrb.com
Media and ad spending data.
Dun & Bradstreet
www.dnb.com
Database on more than 50 million companies worldwide.
Dialog
library.dialog.com
Access to ABI/INFORM, a database of articles from 800+
publications.
Hoovers Online
www.hoovers.com
Business descriptions, financial overviews, and news about
major companies worldwide.
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Public source of data in Viet Nam
Website
Information
http://www.vienkinhte.hochiminhcity.gov.vn
Provides information on HCM’s economy, HCM
library of economy
http://www.gso.gov.vn/
Vietnamese General Statistics Office provides
censuses, survey findings and statistics on various
economic areas
http://www.luatvietnam.vn/
Provides information on Vietnamese Law and
Regulations
http://www.tcvn.gov.vn/
Vietnamese Directorate for Standards and Quality
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Primary Data
• Primary data = information gathered for the first time to solve a
particular problem.
• When secondary data are not available managers may decide to collect
their own information.
• They are more expensive and time-consuming to gather than secondary
data.
• They are current and more relevant to the marketer’s specific problem.
• They are proprietary = unavailable to competitors.
• Each primary data collection method can provide important information,
as long as e-marketers understand the limitations. Remember that
Internet research can only collect information from people who use the
Internet, which leaves out a huge portion of the population.
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Source 3: Primary Data
Electronic sources of primary data collection:
• The Internet:
 Focus groups, observation, in-depth interviews (IDI), and survey
research.
 Online panels: popular survey research method _ single-source
research.
 Real-time profiling at Web sites and computer client-side or serverside automated data collection.
• The real-space
 Refers to technology-enabled approaches to gather information offline
that is subsequently stored and used in marketing databases.
 Techniques = bar code scanners and credit card terminals at brick-andmortar retail stores, computer entry by customer service reps while
talking on the telephone with customers.
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Proportio n Using
Firms Using Online Primary Research
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Online
surveys
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E-mail
surveys
Online
focus
groups
6-15
Bulletin
Web site
board focus
use
groups
measures
5 Steps for Primary Research
Research
Problem
Primary Research Steps
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Research
Plan
Data
Collection
Data
Analysis
Distribute
Results
Primary Research Steps
1.
Research problem. Specificity is vital.
2.
Research plan.
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Research approach. Choose from experiments, focus
groups, observation techniques, in-depth interviews,
and survey research, or nontraditional real-time and
real-space techniques.
Sample design. Select the sample source and number
of desired respondents.
Contact method. Telephone, mail, in person, via the
Internet.
Instrument design. For survey = a questionnaire. For
other methods = a protocol to guide the data collection.
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Primary Research Steps
3.
Data collection. Gather the information according to
plan.
4.
Data analysis: Analyze the results in light of the original
problem. Use statistical software packages for traditional
survey data analysis or data mining to find patterns and
other information in databases.
5.
Distribute finding / add to the MIS. Research data
might be placed in the MIS database and be presented in
written or oral form to marketing managers.
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Some typical e-marketing research problems
that electronic data can help solve.
Online Retailers
Web Sites
Improve online merchandising
Forecast product demand
Test new products
Test various price points
Test co-brand and partnership effectiveness
Measure affiliate program effectiveness
Pages viewed most often
Increase site “stickiness” (stay longer)
Test site icons and organization
Path users take through the site—is it
efficient?
Site visit overall satisfaction
Customers and Prospects
Promotions
Identify new market segments
Test shopping satisfaction
Profile current customers
Test site customization techniques
Test advertising copy
Test new promotions
Check coupon effectiveness
Measure banner ad click-through
Typical Research Problems for E-Marketers
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Online Research Advantages &
Disadvantages
• Advantages
• Can be fast and inexpensive.
• Surveys may reduce data entry errors.
• Respondents may answer more honestly and openly.
• Disadvantages
• Sample representativeness.
• Measurement validity.
• Respondent authenticity.
• Researchers are using online panels to combat
sampling and response problems.
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6-17
Other Technology-Enabled Approaches
• Client-side Data Collection
• Cookies
• Use PC meter with panel of users to track the user
clickstream.
• Server-side Data Collection
• Data log software
• Real-time profiling tracks users’ movements
through a web site.
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6-18
Real-Space Data Collection, Storage,
and Analysis
• Offline data collection may be combined with
online data.
• Transaction processing databases move data
from other databases to a data warehouse.
• Data collected can be analyzed to help make
marketing decisions.
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Data Mining
Customer Profiling
Recency, Frequency, Monetary (RFM) Analysis
Report Generating
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Marketing Databases and
Data Warehouses
• Regardless of whether data are collected online or offline, they
are moved to various marketing databases.
• Product databases = product features, prices, and inventory
levels.
• Customer databases = customer characteristics and behavior.
• Transaction processing databases are important for moving
data from other databases into a data warehouse.
• Data warehouses:
• Store entire organization’s historical data.
• Designed specifically to support analyses necessary for
decision making.
• The data in a warehouse are separated into more specific
subject areas (called data marts) and indexed for easy use.
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UPC Scanner
Product Database
Transaction Database
Data Warehouse
Customer Database
Real-Space Data Collection and Storage Example
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Data Analysis and Distribution
• Data collected from all customer touch points are:
• Stored in the data warehouse,
• Available for analysis and distribution to marketing
decision makers.
• Analysis for marketing decision making:
• Data mining = extraction of hidden predictive
information in large databases through statistical
analysis. Here, marketers don’t need to approach the
database with any hypotheses other than an interest in
finding patterns among the data.
 Patterns uncovered by marketers help them to:
 Refine marketing mix strategies,
 Identify new product opportunities,
 Predict consumer behavior.
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Data Analysis and Distribution
• Customer profiling = uses data warehouse information to help
marketers understand the characteristics and behavior of specific
target groups.
 Understand who buys particular products,
 How customers react to promotional offers and pricing changes,
 Select target groups for promotional appeals,
 Find and keep customers with a higher lifetime value to the firm,
 Understand the important characteristics of heavy product users,
 Direct cross-selling activities to appropriate customers;
 Reduce direct mailing costs by targeting high-response customers.
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Data Analysis and Distribution
• RFM analysis (recency, frequency, monetary) = scans the database
for three criteria.
 When did the customer last purchase (recency)?
 How often has the customer purchased products (frequency)?
 How much has the customer spent on product purchases (monetary
value)?
=> Allows firms to target offers to the customers who are most
responsive, saving promotional costs and increasing sales.
• Report generators:
 automatically create easy-to-read, high-quality reports from data
warehouse information on a regular basis.
 Possible to specify information that should appear in these
automatic reports and the time intervals for distribution.
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Knowledge Management Metrics
• Marketing research is not cheap:
• Need to weigh the cost of gaining additional information against the
value of potential opportunities or the risk of possible errors from
decisions made with incomplete information.
• Storage cost of all those terabytes of data coming from the Web.
• Two metrics are currently in widespread use:
• ROI. Companies want to know:
• Why they should save all those data.
• How will they be used, and will the benefits in additional revenues or
lowered costs return an acceptable rate on the storage space
investment?
• Total Cost of Ownership (TCO). Includes:
• Cost of hardware, software, and labor for data storage.
• Cost savings by reducing Web server downtime and reduced labor
requirements.
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