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 1. Select all magazines that, according to SRDS, are read by all age groups (thirteen publications identified) 2. Collect all 1989 (most recent full year available at time of study) issues of each magazine 3. 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/(N 1 + N 2 ) M = number of agreed upon measures N i = 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 I r = {[(F 0 / N) – (1/k)][k / (k - 1)]}.5 F 0 = number of items agreed upon N = total number of codings k = number of coding dimensions I r = {[(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