Abstract
Heavy users can be a critical segment for packaged-goods marketers to target. Yet many attempts to profile heavy users have proven to be unsuccessful because of methodological and measurement problems. This article shows the diagnostic shortcomings of the commonly used mean comparison method of heavy-user segmentation, and it presents a clustering method that effectively differentiates different types of heavy users from light users. Characteristics that differentiate heavy users from light users were collected from academic and commercial studies and are shown to relate to five basic lifestyle factors and six personality factors. While providing a key starting point for studying heavy users, they also show the dominant role that personality characteristics (versus lifestyle or demographic characteristics) play in differentiating heavy users from light users.
| Original language | English |
|---|---|
| Pages (from-to) | 61-72 |
| Number of pages | 12 |
| Journal | Journal of Advertising Research |
| Volume | 40 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 2000 Jan 1 |
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All Science Journal Classification (ASJC) codes
- Communication
- Marketing
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Methods and measures that profile heavy users. / Wansink, Brian; Park, Se-Bum.
In: Journal of Advertising Research, Vol. 40, No. 4, 01.01.2000, p. 61-72.Research output: Contribution to journal › Article
TY - JOUR
T1 - Methods and measures that profile heavy users
AU - Wansink, Brian
AU - Park, Se-Bum
PY - 2000/1/1
Y1 - 2000/1/1
N2 - Heavy users can be a critical segment for packaged-goods marketers to target. Yet many attempts to profile heavy users have proven to be unsuccessful because of methodological and measurement problems. This article shows the diagnostic shortcomings of the commonly used mean comparison method of heavy-user segmentation, and it presents a clustering method that effectively differentiates different types of heavy users from light users. Characteristics that differentiate heavy users from light users were collected from academic and commercial studies and are shown to relate to five basic lifestyle factors and six personality factors. While providing a key starting point for studying heavy users, they also show the dominant role that personality characteristics (versus lifestyle or demographic characteristics) play in differentiating heavy users from light users.
AB - Heavy users can be a critical segment for packaged-goods marketers to target. Yet many attempts to profile heavy users have proven to be unsuccessful because of methodological and measurement problems. This article shows the diagnostic shortcomings of the commonly used mean comparison method of heavy-user segmentation, and it presents a clustering method that effectively differentiates different types of heavy users from light users. Characteristics that differentiate heavy users from light users were collected from academic and commercial studies and are shown to relate to five basic lifestyle factors and six personality factors. While providing a key starting point for studying heavy users, they also show the dominant role that personality characteristics (versus lifestyle or demographic characteristics) play in differentiating heavy users from light users.
UR - http://www.scopus.com/inward/record.url?scp=0011637498&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0011637498&partnerID=8YFLogxK
U2 - 10.2501/JAR-40-4-61-72
DO - 10.2501/JAR-40-4-61-72
M3 - Article
VL - 40
SP - 61
EP - 72
JO - Journal of Advertising Research
JF - Journal of Advertising Research
SN - 0021-8499
IS - 4
ER -