2Nature, Scope, and Role of Secondary Data Secondary data: Data not gathered for the immediate study at hand but for some other purposeInternal secondary data: Data collected by the individual company for accounting purposes or marketing activity reportsExternal secondary data: Data collected by outside agencies such as the federal government, web properties, trade associations, or periodicals
3Nature, Scope, and Role of Secondary Data Secondary data research has gained substantial importance in marketing research with:Increased emphasis on business and competitive intelligenceEver-increasing availability of information from online / electronic sourcesUsed to examine marketing problems because of the relative speed and cost-effectiveness of obtaining the data
4Some Sources of Internal Secondary Data Sales invoicesSales activity reportsOnline registrationsWarranty cardsClickstream DataOnline Analytics (i.e. Google Analytics, Tweetdeck, Facebook Insights, etc.)Customer letters/ comments / sSocial Media data (“found data”)Past studiesStore Audits
5Store AuditsExamination of how much of a particular product or brand has sold at retailProduct sales in relation to competitionEffectiveness of shelf space/POP displaysSales at various price pointsEffectiveness of POS and non-POS offersSales by store type, location, channel, etc.
6External Secondary Data Sources Government Studies & Reports (i.e. Census Data)Business sourcesEditors and Publishers Market GuideSource Book of Demographics and Buying Power for Every Zip Code in the USAIDS and Gartner Group (technology)Neilsen/IRI (consumer products & media)
7Consumer Panels Benefits Risks Lower cost than other methods Rapid availability and timelinessCan track trends over time with same (similar) sampleHigh level of specificityRisksSampling error (low minority representation)Response bias – “inbreeding” effects
10What is a Literature Review? A comprehensive examination of available information related to your research topicCan help clarify and define the research problem and research questionsCan suggest research hypotheses to investigateCan identify scales and research methodologies to use in your studyMay provide an answer to your research question(s)!
12Criteria Used to Evaluate Secondary Data Sources Purpose (i.e. why collected?)Accuracy / TimelinessConsistency over time and across units studiedCredibilityMethodology usedBias in findings
13Developing a Conceptual Model Literature reviews can help you conceptualize a useful and empirically accurate model of realityElements required to conceptualize and test a model:VariablesConstructsRelationshipsHypotheses
14Variable Construct Relationships Independent Variable An observable item that is able to be directly measuredEXAMPLES: Gender, Age, Location, Intention to PurchaseConstructAn unobservable concept that is measured by a group of related variables EXAMPLES: Brand Loyalty, Intelligence, SatisfactionRelationshipsAssociations between two or more variables or constructsIndependent VariableThe variable or construct that predicts or explains the outcome (dependent) variable of interestDependent VariableThe outcome variable or construct researchers are seeking to explain
15Hypotheses and ModelsHypotheses: Theoretical statements about relationships between variables or constructsTwo hypotheses formally stated:Hypothesis 1: Higher spending on advertising leads to higher sales.Hypothesis 2: Higher prices lead to lower sales.A set of related hypotheses form a Conceptual ModelHere we are trying to formulate a model of sales
16Relationship TypesPositive relationship: An association between two variables in which they both increase or decrease togetherNegative relationship: An association between two variables in which one increases while the other decreases (and vice-versa)Non-Directional relationship: Does not specify a covariance pattern (i.e. no directional association specified)
17Characteristics of Good Hypotheses Follow from research questionsClearly and simply statedMust be testable (i.e. falsifiable)Must lend themselves to variable identification and “operationalization” of variablesData sources must be available to populate the operationalized model
18Model Conceptualization Development of a model that outlines all relevant variables/constructs and the hypothesized relationships between themInvolves:Identifying the independent and dependent variables for your researchSpecifying relationships between the variablesPreparing a diagram or other conceptual model that represents the relationships you will studyDeveloping or identifying theories that justify those relationshipsSpecifying “Boundary Conditions” for the relationships, if anyIdentifying any control variables (pre-hoc) or confounding variables (post-hoc) that could affect results
20Boundary Conditions, Control Variables and Confounding Variables Boundary Conditions: Conditions under which your hypothesized relationships and research conclusions will hold / not holdControl Variables: Independent Variables (IVs) that affect the Dependent Variable (DV) but which are often not the main focus of the studyConfounding Variables: IVs that affect the DV which are not part of the conceptual model, not “controlled for” and not observable – BIG TROUBLE!
21Hypothesis TestingHypothesis: An empirically testable though yet unproven statement developed in order to explain phenomenaNull hypothesis: No relationship between two variables/constructs.Alternative hypothesis: Suggests that two variables/constructs are somehow relatedNon-directional vs. Directional
22Hypothesis TestingA null or alternate hypothesis refers to a population parameter, not a sample statisticParameter: The true value of a variableSample statistic: The value of a variable that is estimated from a sample
23Examples - Null Hypotheses There is no significant difference between the preferences toward specific banking method exhibited by white-collar customers and blue-collar customers.No significant differences exist in requests for specific medical treatments from emergency walk-in clinics between users and nonusers of annual preventive maintenance health care programs.
24Examples – Alternate Hypotheses, Non-directional There is a significant difference in satisfaction levels reported by Safeway and Lucky shoppers.Significant differences exist between males and females in the number of hours spent online.
25Examples – Alternate Hypotheses, Directional We expect higher satisfaction levels to be reported by Safeway shoppers than Lucky shoppers.We expect to find that males spend significantly more hours online than females.
26Examples – Alternate Hypotheses (positive relationship) More studying is related to higher GPAs.Friendlier salespeople generate higher sales revenues.More frequent advertising is associated with higher sales.
27Examples – Alternate Hypotheses (negative relationship) Students with higher GPAs consume less alcohol than those with lower GPAs.The more pressure to close sales perceived by salespeople, the fewer the number of follow up, “relationship-building” sales calls made.
28ACTIVITY: Formulating Research Objectives and Hypotheses Develop a simple research question (example: What factors drive the adoption of a new technology?)Formulate a simple model for your research question. Specify the following:Independent Variables (several) vs. Dependent Variables (one)The + or – relationship between each IV and the DV.Theory behind the relationshipsAny boundary conditions for the modelAny control variables/factors neededFollow up: How to measure your IVs/DVs?