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©2006 Prentice Hall 6-1 E-Marketing 4/E Judy Strauss, Adel I. El-Ansary, and Raymond Frost Chapter 6: Marketing Knowledge

©2006 Prentice Hall6-1 E-Marketing 4/E Judy Strauss, Adel I. El-Ansary, and Raymond Frost Chapter 6: Marketing Knowledge

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©2006 Prentice Hall 6-1

E-Marketing 4/EJudy Strauss, Adel I. El-Ansary, and Raymond Frost

Chapter 6: Marketing Knowledge

©2006 Prentice Hall

Question???

• Define the following• Data• Information• Knowledge• Understanding• Wisdom

©2006 Prentice Hall 6-2

Chapter 6 Objectives

• After reading Chapter 6 you will be able to:• Identify the three main sources of data that e-

marketers 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 e-marketers can apply to data warehouse information.

©2006 Prentice Hall 6-3

• 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?

The Purina Story

©2006 Prentice Hall 6-4

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?

©2006 Prentice Hall 6-5

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.

©2006 Prentice Hall

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-and-

mortar points of purchase, and all other customer touch points.

©2006 Prentice Hall

Data Drives Strategy

• What to do with all the data?

• Purina marketers built a roadmap for their Internet advertising strategy: 1. Data are collected from a myriad of sources, 2. Filtered into databases, 3. Turned into marketing knowledge, 4. Used to create marketing strategy.

©2006 Prentice Hall

Performance

Metrics

S

D

S

Internal Data Secondary Data Primary Data Information: consumer behavior, competitive intelligence

Product Database

Customer/ Prospect Base

Other Data/ Information

*Marketing Knowledge*

Tier 2 Marketing Mix CRM

Tier 1 Segmentation Targeting Differentiation Positioning

From Sources to Databases to Strategy (SDS Model)

©2006 Prentice Hall

Segmentation

Targeting

Value

Differentiation

CRM/PRM

Positioning

Communication

Distribution

Offer

E-MarketingStrategy

Tier 2tasks

Tier 1tasks

Exhibit 3 - 1 Formulating E-Marketing Strategy in Two Tiers

©2006 Prentice Hall 6-6

Terabytes of Corporate Data

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1,600,000

1,800,000

2,000,000

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.

©2006 Prentice Hall 6-7

From Data to Decision: Purina

Knowledge

Information

Data

Decision

Let’s put banner ads on about.com

Dog owners who see ads online are likely to buy Purina ONE. We know the sites they visit: about.com, www.petsmart.com. 1. Purina buyers are 20% more likely to visit about.com. 2. 36% of dog owners who see Purina ads would buy the brand. 016030102 (Buyer 1 bought Purina puppy chow on March 1)

©2006 Prentice Hall 6-8

• 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.

Marketing Knowledge Management

©2006 Prentice Hall 6-9

Uses of Knowledge ManagementUse in the Telecom Industry Representative Firm

Scanner Check-Out Data AnalysisCall Volume AnalysisEquipment Sales AnalysisCustomer Profitability AnalysisCost and Inventory AnalysisPurchasing Leverage with SuppliersFrequent-Buyer Program Management

AT&TAmeritechBelgacomBritish TelecomTelestra AustraliaTelecom IrelandTelecom Italia

Use in the Retail Industry Representative Firm

Scanner Check-Out Data AnalysisSales Promotion TrackingInventory Analysis and DeploymentPrice Reduction ModelingNegotiating Leverage with SuppliersFrequent-Buyer Program Management Profitability AnalysisProduct Selection for Markets

Wal-MartKmartSearsOsco/Savon DrugsCasino SupermarketsW. H. Smith BooksOtto Versand Mail OrderAmazon.com

©2006 Prentice Hall

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.

©2006 Prentice Hall

The Learning Organization

• Benefits from:

• 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.

©2006 Prentice Hall

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.

©2006 Prentice Hall 6-10

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.

©2006 Prentice Hall 6-11

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

©2006 Prentice Hall

Customer Database

1) Customer orders 10 new computers.

2) Customer calls company

Where is the %@#& “on”

switch?

Sales rep

Customer service rep

Hmmm, 21% of customers can’t find “on” switch.

4) Redesign computer switch

3) database trends

E-Marketers Learn From CustomersSource: Adaptation of ideas from Brian Caulfield (2001), “Facing up to CRM” at www.business2.com

A hypothetical scenario for a computer company that is learning from its customers as a whole and using the information to improve products.

©2006 Prentice Hall 6-12

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.

©2006 Prentice Hall 6-13

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:• Competitors, • Consumers, • The economic environment, • Political and legal factors, • Technological forces, • Other factors in the macro-environment affecting an organization.

©2006 Prentice Hall

Web site Information

Stat-USAwww.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 Austinadvweb.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. Censuswww.census.gov

Provides statistics and trends about the U.S. population.

Public Sources of Data in the U.S.

©2006 Prentice Hall

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 Onlinewww.hoovers.com

Business descriptions, financial overviews, and news about major companies worldwide.

Sampling of Sources of Privately Generated Data in the U.S.

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

©2006 Prentice Hall

©2006 Prentice Hall

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.

©2006 Prentice Hall

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 server-

side 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-and-

mortar retail stores, computer entry by customer service reps while talking on the telephone with customers.

©2006 Prentice Hall 6-15

Firms Using Online Primary Research

0%10%20%30%40%50%60%70%80%90%

100%

Onlinesurveys

E-mailsurveys

Onlinefocus

groups

Bulletinboard focus

groups

Web siteuse

measures

Pro

po

rtio

n U

sin

g

©2006 Prentice Hall

Research Problem

Research Plan

Data Collection

Data Analysis

DistributeResults

Primary Research Steps

5 Steps for Primary Research

©2006 Prentice Hall

Primary Research Steps

1. Research problem. Specificity is vital.

2. Research plan.

• 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.

©2006 Prentice Hall

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.

©2006 Prentice Hall

Online Retailers Web Sites

Improve online merchandisingForecast product demandTest new productsTest various price pointsTest co-brand and partnership effectivenessMeasure affiliate program effectiveness

Pages viewed most oftenIncrease site “stickiness” (stay longer)Test site icons and organizationPath users take through the site—is it efficient?Site visit overall satisfaction

Customers and Prospects Promotions

Identify new market segmentsTest shopping satisfactionProfile current customersTest site customization techniques

Test advertising copyTest new promotionsCheck coupon effectivenessMeasure banner ad click-through

Typical Research Problems for E-Marketers

Some typical e-marketing research problems that electronic data can help solve.

©2006 Prentice Hall 6-17

• 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.

Online Research Advantages & Disadvantages

©2006 Prentice Hall 6-18

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.

©2006 Prentice Hall 6-19

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.• Data Mining• Customer Profiling• Recency, Frequency, Monetary (RFM) Analysis• Report Generating

©2006 Prentice Hall

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.

©2006 Prentice Hall

Customer Database

Data Warehouse

Product Database

Transaction Database

UPC Scanner

Real-Space Data Collection and Storage Example

©2006 Prentice Hall

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.

©2006 Prentice Hall

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.

©2006 Prentice Hall

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.

©2006 Prentice Hall

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.