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Advertising Content Analysis. A systematic , objective , and quantitative analysis of advertising conducted to infer a pattern of advertising practice or the elements of brands’ advertising strategies such as brand positioning, selling proposition, and creative tone

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Advertising Content Analysis


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    1. Advertising Content Analysis A systematic, objective, and quantitative analysis of advertising conducted to infer a pattern of advertising practice or the elements of brands’ advertising strategies such as brand positioning, selling proposition, and creative tone • If academic in nature, is usually used to identify trends in practice general relationships between ad characteristics and ad effects • If applied in nature, is usually used to identify practice of competitors in terms of positioning, tone, audience, etc.

    2. Defining the Sample Universe • In advertising content analysis (ACA), the units of measurement are advertisements, not people • Clearly define the universe to eliminate all ambiguity and clearly define the terminology used in the definition • Bad: “The content analysis will examine instances of competitive advertising.” • Better: “The content analysis will examine the toothpaste advertising of Crest, Colgate, Arm & Hammer, Mentadent, and Aqua Fresh. The sample universe consists of ads appearing between January 1 and December 31, 1995 in the following media: television, radio, newspapers and magazines.”

    3. Sampling Frame Selection • In applied ACA, often a census is used. No sampling frame is required. • In academic ACA, the sample must be representative of the universe and large enough to enable generalizations about the universe of ads • Multistage selection can be used to identify ads according to multiple criteria • See multistage example, p. 400

    4. Sampling by Peterson • Select all magazines that, according to SRDS, are read by all age groups (thirteen publications identified) • Collect all 1989 (most recent full year available at time of study) issues of each magazine • Select all ads in all magazines that use human models (1673 ads)

    5. Developing Categories • Categories represent the information that will be extracted from the ads • E.g. format, appeal type, message arguments, musical elements, ad style • Each category must have categorical dimensions identified • Format: slice of life, testimonial, celebrity endorsement, etc • Appeal type: humor, fear, sex, cognitive, etc. • Ad style: temporal pacing, formality, etc.

    6. Category Formation Example • In a study relating ad content and design elements to ad outcome measures, Lohtia et. al. devised the following categories • Ad Objective • Offering Type • Design Elements Used • Interactive Elements Used • Communication Cues Used • Appeal Type

    7. Measurement Types in ACA • Nominal • Checklists for elements present, or characteristics existing • Interval (or Ordinal) • Likert or SD scales for measuring perceived characteristics, such as argument strength, friendliness, formality • Ratio • Temporal characteristics, ad size, number of words, etc

    8. Assessing Reliability • Often content analyses utilize multiple coders to measure the same ads, and often many criteria are subjective • Intercoder reliability is a measure of the extent to which independent coders agree with each other • Reliability = 2M/(N1 + N2) • M = number of agreed upon measures • Ni = number of decisions made by coder I • R = 2(80)/200 = 0.8

    9. Other Reliability Assessments • pi index corrects for chance agreement • pi = (% observed agreement - % expected agreement)/(1 - % expected agreement) • pi = (0.8 - 0.5)/(1 – 0.5) = 0.6 OR • Ir = {[(F0 / N) – (1/k)][k / (k - 1)]}.5 • F0 = number of items agreed upon • N = total number of codings • k = number of coding dimensions • Ir = {[(80/100) – (1/6)][6/(6-1)]}.5 • = [(.8 - .167)(6/5)].5 • = .87

    10. Analysis and Interpretation • From this point, provided the reliability is acceptable, analysis can proceed as with any other nominal (descriptives [Peterson tables]), interval or ratio data (inferences [Lohtia Figure 1])

    11. Example ACA (Lohtia, et. al., 2003) • Hypothesized relationships between banner ad content/design and click through rates • Collected 10,000+ banner ads from an online ad agency (sampling frame defined as all banner ads served by the agency during a specific time period; assumed to be representative of all domestic ads served by other agencies) • Generated categories based on research hypotheses (related to content and design) • Defined dimensions within categories • Trained coders on sub sample of ads • Refined categories • Split sample for coding by independent judges • Judges assess and code thousands of ads • Holdout sample used to assess reliability • Analysis and Reporting

    12. Design an ACA Study • From Kassarjian (page 8), design a study to address your assigned issue (1, 2, 3, or 6) • Operationalize Sampling Plan • Develop Categories • Suggest Analysis of Data • Address Issues of Intercoder Reliability

    13. Coding Practice • Find 10 magazine print ads (first full single-page ad from each magazine) • Code the ads using the following categories: • Use of spokesperson • Animal • Common • Famous • Human • Common • Famous • Identified • Not identified • None • Call to action • Direct • Indirect • None • Information Content • Facts • Opinions • Rhetoric • Storytelling • None • Product Shown • Prominently • In background • Not at all