Packaging—Influence on Expectations
Deliza (1996) also explored the way in which packaging may influ-
ence the consumer’s expectations with an unfamiliar product. Follow-
ing preliminary trials to establish which were the salient attributes of the
unfamiliar product (consumers who had never tasted passion fruit juice
were recruited for this study), a large-scale consumer trial was con-
ducted. Consumers were first asked to evaluate the expected attributes
(sweetness, sourness and refreshingness) and liking. They were then
given passion fruit juices and asked to rate the actual attributes having
been told that the actual attributes they were rating were from the pack-
aging they had been shown. The results indicated that the features of the
packaging contributed to establishing the expectation relating to the sen-
sory attributes and liking for passion fruit juice. The manipulations ap-
peared to increase the expected “freshness” of the product, most notable
of these were the use of a white background color as opposed to a or-
ange background color and lots of information on the packaging; using
a major brand name and representing the passion fruit with a drawing
as opposed to a photograph had a smaller effect. Packaging that con-
tained lots of information increased the expected “naturalness” of the
product while no information had the opposite effect. The effect of in-
formation on the packaging also had a marked effect on the expected
“pureness” of the product. Again, lots of information on the package in-
creased the effect of expected “pureness” while no information decreased
the effect.
INDIVIDUAL DIFFERENCES ANALYSIS—
MODELS THAT EXPLAIN SEGMENTATION
Another factor that we should take into account when considering re-
search using consumers is that of individual differences. This area of re-
search is too large to bring into this chapter and merits a chapter of its
own. Instead we wish to highlight three measurement techniques: the
Elaboration Likelihood Model, the Private Body Consciousness test and
the Need for Cognition test.
The Elaboration Likelihood Model
The Elaboration Likelihood Model (ELM) is used to explain attitude
change after information has been processed (Petty and Cacioppo, 1986).