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Transcript of Operational Data Tools Chapter Eight. Copyright © Houghton Mifflin Company. All rights...
Operational Data Tools
Chapter Eight
Copyright © Houghton Mifflin Company. All rights reserved. 8–2
Chapter Eight Learning Objectives
• To learn database basics and how databases benefit Internet marketing
• To understand how data warehouses and data mining are operational data tools
• To describe privacy-sensitive techniques used to develop consumer profiles
• To recognize the importance of the marketing intelligence process and how it is conducted online
Copyright © Houghton Mifflin Company. All rights reserved. 8–3
Operational Data Tools and Databases
Operational data tools - computer-based techniques used to learn about• Own operations, web site, Internet
activities
• Competitor's online activities
• Environment
• Customers - current, past, potential
Copyright © Houghton Mifflin Company. All rights reserved. 8–4
Operational Data Tools and Databases (cont’d)
• Privacy advocates are incensed that
• Marketers collect masses of data
• Without consumer knowledge or consent
• Do not give consumers opportunity to edit own data
• New data tools used surreptitiously
• Collecting broader, more sensitive data
Copyright © Houghton Mifflin Company. All rights reserved. 8–5
Operational Data Tools and Databases (cont’d)
Should the Internet be …• Opt-in
– No data collected without subject’s approval
– Ask before collect
• Opt-out– Must ask to be excluded from data collection
– Cease collecting only on request
Copyright © Houghton Mifflin Company. All rights reserved. 8–6
Operational Data Tools and Databases (cont’d)
• Databases - collection of data structured for computer retrieval
• Data - sets of text, numbers, other elements input into a database
• Marketing data– Demographic, transaction, lifestyle, behavioral,
technical
Copyright © Houghton Mifflin Company. All rights reserved. 8–7
Operational Data Tools and Databases (cont’d)
• Database - electronic file cabinet, process to retrieve data
• Database construction - involves information technology and marketing
• Relational databases - data stored in linked tables
• In-house databases– Own data
• Compiled databases– Purchased from other sources
Copyright © Houghton Mifflin Company. All rights reserved. 8–8
Data Warehousing and Mining
• Data warehouse - electronic storage, extraction and management system
• Data mining - machine learning, knowledge discovery– Machine-driven methods
– Looking for hidden patterns, relationships in databases and warehouses
– Can answer “what if?” marketing questions
Copyright © Houghton Mifflin Company. All rights reserved. 8–9
Collect and Apply
• Privacy-sensitive tools
• Cookies - small data files placed on user’s computer by web site’s server
• Bugs (beacons) - gif images placed by third-party media and research companies– Allow multi-party tracking
• Server log files
• Web analytics - software and people analyze collected data
Copyright © Houghton Mifflin Company. All rights reserved. 8–10
Collect and Apply (cont’d)
• eCRM
• Electronic customer relationship management
• Broad strategy for applying data-derived knowledge to develop more effective marketing tactics
• Widely promoted; less widely adopted
• Costly, complex, often disappointing
• Dynamic web pages provide personalized content
Copyright © Houghton Mifflin Company. All rights reserved. 8–11
Marketing Intelligence
• Process - system for collecting and transforming data
• Content - knowledge for marketing decision making
• Not espionage!
• Legal, ethical collection of public data
• Focused in-house, externally, both
• Requires timely, relevant, accurate data
Copyright © Houghton Mifflin Company. All rights reserved. 8–12
Figure 8-1:Marketing Intelligence Process