Chapter 4: Secondary Data & Big Data Analytics

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Difference between SECONDARY and PRIMARY data
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• Secondary: data that has been previously gathered • Primary: new data gathered to help solve the problem under investigation
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Is SECONDARY data internal or external?
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Both
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Two types of EXTERNAL secondary data: Define each.
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• Scanner research (data generated electronically via point-of-purchase) • Panel research (group of recruits to take part in research sessions over period of time).
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Examples of EXTERNAL secondary data
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• Government publications: – Statistical abstracts – Census data – Federal reserve bulletins • Periodicals and Books – Trade magazines (e.g., Marketing Health Services) • News media articles / internet data • Syndicated/commercial data (Conducted by a market research firm in an area that may be of interest to multiple companies or organizations within a particular industry)
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Advantages of secondary data
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• Helps clarify the problem; • May provide a solution; • Can provide primary research alternatives; • Alerts researcher to other problems; • Provides background information; • Provides sample frame
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Disadvantages of secondary data
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• Lack of availability; • Lacks relevance; • Inaccurate; • Insufficient
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Questions to ask about secondary research:
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• WHO gathered the data? • PURPOSE of the study? • WHAT INFORMATION was collected? • WHEN was the data collected? • HOW was the information collected? • Is the information CONSISTENT with other information?
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Define INTERNAL DATABASE
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• Collection of related information developed from data WITHIN an organization
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Features of INTERNAL DATABASE
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– Creates large computerized files – Includes current, past, or potential customers – Focuses on demographic/purchase behaviors – Develop customer profiles – Generates customer e-mails via buying behaviors – Collects customer info for website – Enables database search queries – Compatible with database software, to enhance analysis
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Define DATABASE MARKETING
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• Marketing relying on the creation of a large computerized file of (potential) customers’ profiles, purchase patterns • Creates a targeted marketing mix
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Define DATA MINING
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• Using statistical data and other advanced software to discover hidden information; • Methods to find information not visible on the surface
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Define the “80/20 rule”
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80% of effects come from 20% of causes
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Example application of PREDICTING DEMAND
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– Using learning experience from Hurricane Charley to PREDICT DEMAND of Hurricane Frances
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Examples of DATA MINING applications
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– Customer acquisition – Customer retention – Customer abandonment – Market based analysis
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Define BEHAVIORAL TARGETING What is its purpose?
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• Use of online and offline data to understand consumer habits, demographics, social networks • Increases effectiveness of online advertising
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Define BIG DATA ANALYTICS What does it offer?
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• The accumulation and analysis of massive quantities of info • Offers: – Deeper insights – Broader insights
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Define GEOGRAPHICAL INFORMATION SYSTEMS What does it visually display?
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• Computer-based system using secondary data to generate maps • Various types of geographical data
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Define DECISION SUPPORT SYSTEMS (DSS) What is its purpose?
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• Interactive, personalized information management system • To give individual decision makers the power to control and initiate
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Example uses of DECISION SUPPORT SYSTEMS (DSS):
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• Conduct sales analysis • Forecast sales • Evaluate advertising • Analyze product lines • Keep tabs on market trends/competitors’ actions
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Key components of DECISION SUPPORT SYSTEMS (DSS):
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• Interactive (quick and live data) • Flexible (manipulate data) • Discovery-oriented • Easy to learn, use

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