Audience segmentation
Lecture 4
COMT 492/592
Overview
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Determine target audience
Determine what you need to know
Audience research
Interpreting results
Determining the target audience
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Primary audience: Clients
Secondary audience:
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People who influence your primary audience (peers;
social referents)
Tertiary audience:
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Policymakers
Media professionals
Supervisors, boards of directors
Your employees
What is a target audience?
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People whose behavior you wish to affect.
Potential customers or consumers
considering whether to adopt the “product”
you are promoting.
People most at risk for the problem you
are addressing.
Potential segmentation bases
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A priori
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Determined in advance (sex, race, age, residential
status)
Objective (can be observed/measured)
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Inferred (assessed thru questionnaire)
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General or behavioral
General or behavioral
Self-selection bases
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Segments define themselves thru response to
campaign
Rarely indicates why response occurred
Bases to segment by:
Objective general data – often
available thru 2ndary data
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Age
Income
Sex
Residence
Race
Family size
Inferred general:
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Inferred behavioral:
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Obj. Behavioral
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Access to health care
Past behaviors
Distance to sources
Behavior of peer group/village/family
Hours watching different media
Personality
Lifestyle
Risk preferences
Media preferences
Self-confidence
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Self-efficacy
Perceived benefits/costs
Stage of behavior change
Social norms
Perceived risk
Perceived severity
Audiences not homogenous
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Even within an audience subgroup, there may
be many important differences with respect to
the behavior you are promoting.
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E.g., an STD prevention program won’t use the same
appeals for boys and girls, or older and younger
teens.
Segmenting by demographics (age, sex,
education, etc.) may NOT be as important as
segmenting by risk-level or personality.
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E.g., those who know they’re at risk may react
differently to those who feel invulnerable.
Theory & Method in
Segmentation
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What criteria are properly used to segment
an audience or market?
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Smorgasboard of techniques and strategies
Little direction for preferred strategy
What’s needed: Identify subgroups that
have common similar determinants of
behavior in question
Slater, M.D. (1996). Theory and Method in Health Audience
Segmentation. J of Health Comm, vol. 1: 267-283.
Behavior Determinants
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1) Identify from research the known
determinants of KAP with respect to goal
behavior
2) Identify audience segments on basis of
distinctive patterns of determinants
HOWEVER…How do you identify these
patterns?
Segmentation Methods
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VALS – Values and Lifestyles dataset for
commercial use
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more art than science?
SES – Crude segmentation by demographics
(education, race, income, gender, geography)
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Easy to measure, but not that informative
Many sub-differences w/in demographic groups
overlooked
Segmentation Methods (cont’d)
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Psychosocial variables – Self-efficacy; peer
support; etc.
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Harder to measure
More informative
Can start w/ demographic sub-groups and then
further subdivide by psychosocial
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But…Assumes there are a few key variables
Assumes one has correctly identified them
May miss subtle distinctions w/in segments
Social Science & Typology
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Segmentation process usually stops there
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Need for parsimony…the fewest possible
variables to explain audience variance
Statistical models are cumbersome when
overloaded with too many variables
Descriptive vs. predictive models
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To best guide channel selection & intervention
design, segments should be predictive of
distinctive patterns of media use
Define Target Audience,
Focus Message & Choose Media
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Start with audience
Define who they are:
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sociodemographic variables
personal identity - what they care about
risk level - stage of behavior change
Gear message to fit
Choose appropriate media
Media diets vary by race &
gender
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Not all teenagers tune into the same kind
of media
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Girls prefer softer music and soap operas
Boys prefer action flicks and harder, louder
music
African-Americans and children from singleparent households watch more TV
Steele JR, Brown JD. Adolescent room culture: Studying media in the
context of everyday life. J Adolesc Hth 1995; 24(5).
Media diet varies by personal
identity, too
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Even within race & class categories,
teenagers’ media use vary dramatically
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Teens define themselves by their identities
Girls’ sense of selves may be particularly
transitory & vulnerable to media influence
Pipher M. Reviving Ophelia. New York: Ballantine Books, 1994.
Thompson S. Going All the Way. New York: Hill and Wang, 1995.
Identity associated with
behavior
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Speaking to teen identities may be key to
influencing behavior
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Identity -- a person’s self-perception & tastes in
fashion, music & friends -- may determine sexual
risk practice
Related to subjective beliefs about what’s
important
Identity attributes may be more amenable to
change than basic sociodemographic
variables
Prochaska J, Redding C, Harlow L, et al. The transtheoretical model of
change and HIV prevention: A review. Hth Ed Qaurt 1994; 21(4):471-86.
Adolescent girls can be
segmented by identities
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Categories of girls’
relationship behavior
(Thompson, 1995)
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Shy girls
Romantic idealists
Hell-raisers
Fast-track girls
Having the baby
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How girls use sexual
media (Steele & Brown,
1995)
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Disinterested
Intrigued/Conformers
Resisters
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Segmenting by risk level:
Stages of Change Model
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Behavior change is not a one-step process
Different messages are needed for each
stage
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Precontemplation
Contemplation
Ready for action
Action
Maintenance
Stages of Behavior Change:
Operationalization
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Pre-contemplation:
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Contemplation:
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Intends to use condoms from now on
Action:
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Intends to use condoms in next 6 months
Ready-for-action:
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No intention to use condoms
Every time condom use for less than 6 months
Maintenance:
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Condoms used every time for at least 6 months
Prochaska J, et al. The transtheoretical model of change and HIV prevention: A
review. Hth Ed Qaurt 1994; 21(4):471-86. Schnell DJ, et al. Measuring the
adoption of consistent use of condoms using the stages of change model. Public
Health Reports 1996;111(suppl 1):59-68.
Segmenting by risk level:
Results
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Campaigns that target audience by risk
level are more effective than nontargeted campaigns
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-- in smoking cessation, exercise adoption,
dietary fat reduction & mammography
screening
Results of a smoking campaign
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People who progress from one stage to next
early in campaign are more likely to ultimately
change behavior
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3% pre-contemplators quit smoking
7% pre-contemplators who moved to contemplation in
1st month quit smoking
20% contemplators took action
41% contemplators who moved to ready-for-action in
1st month took action
Prochaska JO, et al. In search of how people change. American
Psychologist 1992;47(9):1102-14.
Segmenting by risk level:
Condom campaign
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CDC’s Role Model Stories Campaign,
San Francisco, 1992-94
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to change women’s HIV risk behavior &
community norms, using narrative
pamphlets
Target audience:
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Welfare mothers ages 17-54
Different stories developed for
each risk category
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Contemplation:
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Ready-for Action:
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Kizzy says she’ll “seriously try” to use condoms
Mayeisha decides to use condoms with her next man
Action:
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Champagne uses condoms, but not every time
Kinght K, et al. This is my story: A descriptive analysis of a peer education
HIV/STD risk reduction program. Presented at American Public Health
Association, New York City, November, 1996.
Segmenting by demographics:
Project ACTION
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Social marketing campaign to promote
teenage condom use in Portland, Oregon by
Population Services International 1992-94
 Community mobilization
 Condom vending machines
 Peer skill-building workshops
 Motivational media campaign
 Evaluation research
Project ACTION:
Tailoring the message
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Target audience:
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Audience segments:
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At-risk teens ages 12-21
Caucasian boys; Caucasian girls; African-American
boys & girls
Different PSAs designed to match sexual scripts
of each subgroup
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PSA for girls: romantic flowers
PSA for boys: pretty girls
PSA for African-Americans: passionate glance
PSAs promote condoms in
Portland, Oregon 1992-94
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Teens who used condoms in last month
increased from 32% to 40%
Teens who used condoms with casual
partners rose from 72% to 90%
Teens who planned to discuss condoms
with next partners rose from 53% to 80%
Blair J. PSI/Project ACTION: Improving Teen Risk Reduction. Washington:
Population Services International, 1995.
Allocating resources:
Indexing and weighting
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Incidence, severity, defenselessness, etc.
– 1= average; > 1=worse
Average scores + Multiply by population
size for segment (IAP)
Add IAP’s together = total IAP
Convert each segment’s score to a % of
total IAP
See example
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