Targeting Research: Segmentation

1. Targeting Research: Segmentation • Birds of a feather flock together, i.e. people with similar characteristics tend to exhibit similar behaviors • Characteristics on which to segment include: • Demographics • Geographics • Psychographics • Attitudes and behaviors relevant to a brand of product category

2. Demographic Segmentation • Age: only useful when appropriate ranges are used to define age group segments • Too broad (18-45) blurs differences between segments • Too narrow (18-20) results in too many small segments • Gender • Household characteristics • Life stage: combination of all of the above (see page 447) • Race and Ethnicity • Social Class: comprised of education, occupation, and income

3. Geographic Segmentation • Region • East, North, West, South • Pacific, Mountain, West North Central, West South Central, East North Central, East South Central, South Atlantic, Middle Atlantic, New England • Population Size • MSA, PMSA, CMSA • Population Density • Climate

4. Psychographic Segmentation • Attitudes and Values • Different attitudinal segments typically require different advertising messages • Different attitudinal segments often have different media habits, requiring different media plans • Motivations • Reasons for purchase, i.e. pregnancy tests • Lifestyle

5. Category and Brand Related Attitudes and Behaviors • Product Usage • Brand usage • Product usage • Quantity of consumption • Situation of consumption • Brand Loyalty • Benefit

6. Performing Segmentation Research (figure 19.2, p. 456) • Determine basis for segmentation and descriptive variables • Segmentation variables are the variables used to create subgroups, or market segments • Descriptive variables are used to describe differences between the subgroups • Identify range of segmentation and descriptive variables • Collect data • Form groups using cluster analysis • Describe each cluster or segment using descriptive variables • Radar charts are very useful for this • Name and describe each segment • Relate segments to particular brand behaviors • Select a segment to target

7. Determine the Basis for Segmentation • Select segmentation variables • Relevant to product category • Related to category, product, or brand related perceptions or behaviors • Have a high likelihood of being causal factors of category , product or brand choice and usage

8. Identify Descriptive Variables • Equivalent of dependent variables • Used to further describe or identify segment members • Necessary to provide an understanding of the internal characteristics of each segment

9. Identify the Range of Segmentation and Descriptive Variables • There are no “Standard” categories or ranges for segmentation variables • Specific to the researchers informational needs • Language use • Use to guide content and form attitude or other scales

10. Sample and Survey the Population • Random or stratified random sampling • Mail or telephone surveys • Typically likert scale questions

11. For groups using cluster analysis • Respondents with similar patterns of response to segmentation variables are placed in the same group • Frequencies (cross tabs) on segmentation variables used to summarize differences between groups • Use a radar chart to present a better descriptor of segments

12. Example Radar Chart from Table 19.5 data (partial)

13. Final Steps • Describe each sentence in narrative, without using the numbers • Describe segments further based on descriptive variables • Relate Segments to Brand specific behaviors • Select a segment

14. Cluster Analysis in SPSS • Identify segmentation variables • Be sure to tell SPSS to save cluster assignments as a variable • SPSS automatically cross-tabulates data on each segmentation variable for each cluster • Identify defining characteristics for each cluster, now called a segment • Compare meaningful descriptive variables across segments

15. Group Practice • Page 479, Exercise #3 • Each group pick three product categories • For each, determine the most important segmentation type • Identify at least four segmentation and descriptive measures • Craft the specific items to measure those variables

16. Q-Methodology • Method of targeting using a large set of statements (q-sample) that respondents are asked to rank based on their agreement with the statements • Factor analysis is used to identify groups • Typically results in groups based on perceptions and attitudes

17. Q-Methodology Process • Develop, Edit, and Select Q-sort statements • Select type of sort • Determine Sample Characteristics • Create Instructions • Administer and Record the Sort • Analyze data • Apply findings to decision

18. Selection of statements • Prior projects • Prior survey research • Responses to open ended, in depth interview questions • Volunteered comments in focus groups • Responses to projective stimuli such as sentence completion and picture projection • Brainstorming or idea-generation sessions

19. Statement Selection • Range of statements • Must be unbiased, i.e. same number of positive, negative and neutral statements • If more than one concept, equal number of statements for each concept • Item appropriateness • Item Clarity • Item independence

20. Types of Q-sorts • Forced • A predetermined number of cards are to be placed on each point of the scale • Unforced • Any number of statements may be placed on any point of the scale • Little agreement about which type is better, so use whichever you prefer

21. Select the sample • Due to the difficult nature of the task, samples tend to be small, yet representative of the population • Number of popluation variables that are important • Number of required replications (between 3-5) • See table 20.1, page 493

22. Create Instructions, Administer Sort • Establish and communicate sorting criteria • “sort the statements to reflect how much you think each is ‘most like my point of view’ or ‘most unlike my point of view’.” • Record placement of each statement using numerical scale position • Depending on the number of statements, you may have anywhere from 7 to as many as 11 points on the scale

23. Analysis of Q-sort data • Variables are individuals, cases are statements • Factor analysis then groups the individuals • Examine attitudinal characteristics by comparing mean scores of individual statements across factors (groups) • Once group attitudes are identified, demographics, brand related behaviors or other salient characteristics of individuals in each group are compared

24. Group Practice • Page 501-502 • Application exercises 1, 2, and 4