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McGraw-Hill/Irwin McGraw-Hill/Irwin Copyright © 2009 by The McGraw-Hill Companies, Inc. All rights reserved.

Chapter 3 Information-Driven Technology and the Research Process

1. Describe how changing technology influences the marketing research process. 2. Discuss how portals help in the problem definition process. 3. Explain how technology influences research designs and data sources. 4. Explain the influence of technology on methods of primary data collection. 5. Know the differences between data warehouses and data marts. 6. Distinguish between pull and push portals for research presentations. Learning Objectives 3-3

How technology is changing the research process... Sampling and Scale Measurements Research Designs and Data Sources Problem Definition Four Major Ways Data Collection, Data Analysis and Communication 3-4

The way research problems are defined and objectives specified. The way research problems are defined and objectives specified. The designs and data sources. The designs and data sources. Sampling and scale measurements. Sampling and scale measurements. Collecting, storing, analyzing and dissemination of data has become more precise and user-friendly. Collecting, storing, analyzing and dissemination of data has become more precise and user-friendly. How technology is changing the research process 3-5

Value of Portals DashboardsDashboards Enterprise Information Portal TypesTypes 3-6

Dashboards Better informed planning decisions More detailed reports Improved problem identification and definition Visual presentation of marketing data BenefitsBenefits 3-7

Types of Customer Data Transactional Customer Data... supports the daily operations of the business.... used to perform analyses that become the basis of managerial decision making. Analytical Customer Data 3-8

Transactional Customer Data Cash withdrawals from an ATM Hotel or airline reservations Purchases from an online store ExamplesExamples 3-9

Transactional Customer Data Primary Uses Generate sales reports Facilitate inventory control Tracking of sales 3-10

ExamplesExamples Market and industry trends Competitor information Macroenvironmental Changes Transactional Customer Data Analytical Customer Data 3-11

Analytical Customer Data Repositioning a current brand Evaluating new distribution methods Moving into new markets Expanding product lines TypicalDecisionsTypicalDecisions 3-12

Web Traffic Analysis Primary objective = to record customer visits, purchases, revenue, service calls generated, traffic reduction, etc. Measures Website traffic using click-stream data. 3-13

1.Number of pages viewed 2.Pattern of websites visited 3.Length of time on the web site 4.Dates and times of visits 5.Number of registrations completed 6.Number of registrations abandoned 7.Demographics of registered visitors 8.Number of customers with shopping carts 9.Number of abandoned shopping carts 1.Number of pages viewed 2.Pattern of websites visited 3.Length of time on the web site 4.Dates and times of visits 5.Number of registrations completed 6.Number of registrations abandoned 7.Demographics of registered visitors 8.Number of customers with shopping carts 9.Number of abandoned shopping carts Examples – Click Stream Metrics 3-14

Technology and Data Enhancement ExamplesExamplesBiometricsBiometricsSmartcardsSmartcards 3-15

Total U.S. population is about 300 million people with 225 million of them over the age of 17. (U.S. Census) Total U.S. population is about 300 million people with 225 million of them over the age of 17. (U.S. Census) There are million Web users in the U.S. (comScore, June 2007) There are million Web users in the U.S. (comScore, June 2007) 71% of all adults are online. ( 71% of all adults are online. ( 87% of 18–24-year-olds, 83% of 30–49-year-olds, 65% of those 50–64 and 32% of those over 65 are online. ( 87% of 18–24-year-olds, 83% of 30–49-year-olds, 65% of those 50–64 and 32% of those over 65 are online. ( 73% of whites, 62% of blacks, and 78% of English-speaking Hispanics are online. ( 73% of whites, 62% of blacks, and 78% of English-speaking Hispanics are online. ( 73% of people living in urban/suburban environments and 60% living in rural areas are online. ( 73% of people living in urban/suburban environments and 60% living in rural areas are online. ( 93% of those earning $75K+, 82% of those earning $50K– $74K, 69% of those earning $30K–$49K and 55% of those earning less than $30K are online. ( 93% of those earning $75K+, 82% of those earning $50K– $74K, 69% of those earning $30K–$49K and 55% of those earning less than $30K are online. ( Total number of U.S. households is million. (U.S. Census) Total number of U.S. households is million. (U.S. Census) Almost 70% of U.S. households have Internet access at home. (Leichtman Research Group Q1 2007) Almost 70% of U.S. households have Internet access at home. (Leichtman Research Group Q1 2007) 53% of U.S. households have high-speed access (Leichtman Research Group Q1 2007) 53% of U.S. households have high-speed access (Leichtman Research Group Q1 2007) Characteristics of U.S. Internet Users 3-16

Impact of Technology on Marketing Research BenefitsBenefits More efficiently collected and reported data. Easier integration of primary and secondary data. 3-17

3-18

Automated dialing for phone surveys Automated dialing for phone surveys Creation and execution of online, phone and paper surveys. Creation and execution of online, phone and paper surveys. Scanning of paper surveys Scanning of paper surveys Managing and manipulating data Managing and manipulating data Creation of tables from local data Creation of tables from local data Interaction with tables on the desktop Interaction with tables on the desktop Translation of surveys and reports Translation of surveys and reports Collection of data via handheld devices Collection of data via handheld devices Data analysis, including data mining Data analysis, including data mining Preparation of reports and presentations Preparation of reports and presentations Data Collection SPSS Dimensions – Tasks 3-19

Technology-Driven Data Analysis Data Mining Data Warehousing Data Marts 3-20

Research Portals Two Types PushPushPullPull 3-21