Download Broadening the Empirical Generalisation of the Impact of

Broadening the Empirical Generalisation:
the Impact of Brand Usage on Memories of Advertising
Peter Hammer and Erica Riebe, Ehrenberg-Bass Institute for Marketing Science,
University of South Australia
Abstract
It is well recognised that memories of advertising are affected by the usage of the advertised
brand (Rice and Bennett, 1998; Sharp, et al., 2001; Sharp, et al., 2002). In two exploratory
papers, users of a brand were found to be about twice as likely to recall and recognise
advertising for that brand than non-users. Our paper further tests this empirical generalisation
by using an alternative methodology with a broader range of measures and categories.
Using an experimental methodology, we investigated 431 users and non-users for a range of
brands. Like Sharp, Beal and Romaniuk (2001; 2002), it was found that users of a brand were
more likely (though slightly less than twice as likely) to recall that brand’s advertising than
non-users. We also demonstrated, however, that the magnitude of this difference between
users and non-users varied according to the measure used – that is, unprompted recall for
users was 54% higher, on average, compared to non-users, and only 19% higher for
recognition measures. In addition, we found this to vary based on the market type, with the
difference between users and non-users being greater in FMCG compared to the durable
markets.
Introduction
It is widely held that for an advertisement to be effective, it needs to be remembered (White,
1998). Recall and recognition measures are commonly used in advertising research to
perform this task, however, our understanding and interpretation of these metrics is still
subject to much debate. In two exploratory studies, Sharp, Beal and Romaniuk (2001; 2002)
addressed the influence of brand usage on advertising recall. They made a broad empirical
generalisation that users of brands were more than twice as likely to recall advertising for that
brand when compared to non-users. This research will look to replicate and extend these
initial findings using an alternative experimental methodology in two ways:
Firstly, Sharp, Beal and Romaniuk (2001; 2002) used the term ‘recall’ to describe a range of
measures, from prompted recall and unprompted recall, through to recognition-type measures,
with few conclusions drawn about how their result varied for these different measures. We
therefore consider how users and non-users differ in their ability to recall/recognise
advertising, and do so by considering variation in this relationship across the range of
measures.
Secondly, Sharp, Beal and Romaniuk (2001; 2002) limited their research to three categories
(insurance, banking and international travel), all of which might be considered subscription
rather than repertoire markets (Sharp, et al., 2002). We extend this study by addressing
repertoire markets – FMCG and durable markets – which support different characteristics in
consumer behaviour when compared to the markets studied in Sharp, Beal and Romaniuk
(2001; 2002).
Background
While Sissors and Baron (2002) state that there is no widely-accepted means for assessing
advertising effectiveness, measures of advertising memory (such as recall and recognition)
continue to be widely used in most advertising research (O'Guinn, et al., 2000).
There are two main forms of recall – ‘unprompted’ recall and ‘prompted’ recall. When recall
tests are performed, respondents are exposed to a stimulus (the ad) and then a cue to retrieve
it. This task relies on respondents to reconstruct the stimulus (Bettman, 1979). When only a
temporal cue is used (e.g. “do you recall seeing any advertisements in the program you just
watched?”), the test is known as unprompted recall. If information other than a temporal cue
is provided (e.g. a brand/category) the test is referred to as prompted recall. Different cues
have differing levels of complexity and ad retrieval (Singh and Rothschild, 1983).
While recall tests have minimal cues, recognition tests usually involve respondents being
exposed to the original material (Singh and Rothschild, 1983). This means that there is
usually sufficient information provided in recognition tests to differentiate or discriminate
between choices (Bettman, 1979), providing an effective measure of exposure. As
recognition is more easily achieved than recall (i.e. recognition scores are typically higher
than recall scores), it is has often been criticised as being less sensitive (Krugman, 1977). It is
often suggested that recall and recognition should be used for different purposes. For
example, it is thought that recall is a more important measure of learning for products that
elicit high involvement (Singh and Rothschild, 1983), whereas recognition is thought to be
more appropriate measure of learning for low involvement situations (Singh and Rothschild,
1983). Similarly, Krugman (1977) suggested that recall is a more complex task and is more
of a left-brain activity, whereas recognition is less complex and more of a right-brain activity.
Not surprisingly, these measures are poorly correlated (du Plessis, 1994).
Despite evidence that they might capture different elements of memory, these measures are
commonly used for similar purposes, and so it is important to determine differences and
similarities between them. In particular, it is important to clarify whether the different
measures of memory are related to other variables in the same ways, and in-line with
previously established patterns. One of these known patterns is that between brand usage and
advertising recall. Sharp, Beal and Romaniuk (2001; 2002), in two separate studies found
that brand users were about twice as likely to recall advertising for that brand than non-users.
Research conducted by Rice and Bennett (1998) suggested that, in general, users were more
likely than non-users to notice and like advertising. Similar usage effects were observed by
Bird and Ehrenberg (1970) who found that the proportion of consumers who expressed a
favourable attitudes towards a brand was generally highest among current users, and then
former users, and lowest among those who had never used the brand.
However, in the studies by Sharp, Beal and Romaniuk (2001; 2002), there is no comment on
how the relationship might vary for different types of measures. Arguably, current and
former users of a brand should have (more) established memory structures relating to the
brand, and such, find it easier to recall the advertising with appropriate cues. Whereas
recognition measures are said to represent a more subjective estimate of advertising exposure
(Heath, 2004), and are therefore less likely to be reliant established memories. Thus, we aim
to extend this empirical generalisation by examining the differences between users and nonusers of brands across a range of advertising measures. We also aim to extend the findings of
Sharp, Beal and Romaniuk (2001; 2002), by broadening the range of markets in which the
relationship is observed. Sharp, Beal and Romaniuk (2001; 2002) limited their research to the
insurance, banking and international travel markets. We therefore seek to test whether the
relationship holds with the same magnitude in FMCG markets (including chocolate bars,
alcohol, baby products and cleaning products) and in durables markets (including cars,
televisions and mobile phones).
Sharp, Wright and Goodhardt (2002) identified a clear and radical distinction between
markets based upon their underlying characteristics. They addressed two core market
structures – subscription and repertoire markets – and demonstrated that these markets types
differed considerably in terms of brand performance measures and buyer behaviour. For
instance, subscription markets (such as those studied by Sharp, Beal and Romaniuk (2001;
2002)) are characterised by many sole-loyal buyers who allocate most of their category
requirements to a single brand. By contrast, repertoire markets (such as the FMCG and, to a
lesser extent, durables markets) are characterised by multi-brand buying and minimal sole
brand loyalty. It is expected that there will be some differences in advertising recall and
recognition, based simply upon the nature of these markets. For instance, repertoire markets
are characterised by more regular buying of the product category (Sharp, et al., 2002), and
therefore users in these categories have more recent experience with some brands. We might
therefore expect users in repertoire markets to differ more dramatically from non-users in
their ability to recall and recognise advertising.
Methodology
The data for this study was collected as part of a larger experimental study addressing the
impact of television advertising clutter on advertising effectiveness. A total of 431
respondents were randomly recruited from the Adelaide metropolitan area with the request
that they evaluate a new television program. To ensure that their attention was not drawn to
the advertising component of the experiment, respondents were not told about the true
research interest in the advertising prior to undertaking the study. The research was
conducted in the respondent’s home to induce more realistic viewing behaviours than would
be expected in a laboratory environment.
All respondents were exposed to the same pilot of a US crime series that had not been aired in
Australia. Within this program, a selection of 36 commercials were placed in several
advertisement breaks. While all of the commercials were for brands that were available to
consumers in Australia, none of the commercials had been aired in Australia. It was desirable
to use a program and commercials that had not aired in Australia to ensure that any recall of
the commercials captured was from the experiment, rather than from some previous exposure
over which we would have no control. Following the viewing of the one-hour television
program, respondents were asked to complete a questionnaire. They were asked a range of
questions in relation to their opinions of the program and their memories of advertising that
was placed within the program. In this paper, however, we concentrate upon four main
measures – the brand usage of the included advertisements (whether the respondent had ever
used the brand before), as well as unprompted recall, prompted recall and recognition of the
advertisements. The questions were ordered to ensure that preceding measures would not
artificially inflate subsequent scores (Dallett and Murdock, 1971). As such, respondents were
first asked about their recall of advertising without prompting, then prompted recall (using a
brand prompt) and then their recognition of advertising usual hardcopy screen shots of the
advertisements.
An experimental research design was used for the research, allowing for some control over
factors such as the frequency of advertising exposure, and surrounding programme content. It
also ensured that all respondents were actually exposed to the advertising, rather than falsely
identifying an advertisement based on their experience with the brand, as has been found in
prior studies (Hall, 2002).
Results
The following table represents the average unprompted recall, prompted recall and
recognition levels for users and non-users of the brand across all 36 advertisements. These
results are presented as a percentage of the users or non-users who recalled/recognised the
advertisement. Using percentages rather than raw recall/recognition ensures that the scores of
larger brands (those with more users) are not artificially inflated. On average across the entire
sample, users represented 22% and non-users 78%.
TABLE 1: Average recall/recognition by brand usage (n=431)
Users
(%)
Non-users
(%)
Total
(%)
Difference
Users/Non-Users
(%)
Unprompted Recall
14
9
10
54
Prompted Recall
46
35
39
33
Recognition
61
52
54
19
On average, users provided a higher recall score than non-users of the brand. For example,
users provided an unprompted recall score that was 54% higher than that of non-users (i.e.
14% c.f. 9%). For prompted recall, however, the difference between users and non-users was
less significant, being just 33% higher (46% c.f. 35%). And finally, for recognition the
difference between users and non-users was even less varied, being just 19% higher for users
(61% c.f. 52%). The general rule outlined by Sharp, Beal and Romaniuk (2001; 2002) clearly
varies according to the measure used to capture such data. It would seem that a more
complex retrieval task results in a greater overall difference between users and non-users.
The following table shows the same data split by market type.
TABLE 2: Average recall/recognition by brand usage for FMCG and durables (n=431)
FMCG
DURABLES
Users
(%)
Non-users
(%)
Total
(%)
Differ.
(%)
Users
(%)
Non-users
(%)
Total
(%)
Differ.
(%)
Unprompted Recall
14
8
9
62
14
11
12
29
Prompted Recall
50
37
41
36
37
32
33
17
Recognition
63
53
56
19
58
51
52
14
There is a slight difference between FMCG and durables markets. For durables markets, the
difference between users and non-users in their recall/recognition of advertising is
consistently smaller (more than half the difference in recall for the unprompted and prompted
measures) than the difference between these groups for the FMCG markets. It might reflect
the recency of brand experience that respondents are likely to have had with FMCG brands.
Discussion
Our results broaden the support of the empirical generalisation that users of brands are more
likely to remember advertising for the brands they use than non-users. We achieved this by
replicating earlier studies using an alternative methodology, as well as using additional
measures and a range of brands in two different repertoire market-types (FMCG, durables).
However, the difference between users and non-users were notably smaller than those
observed in the previous study (Sharp, et al., 2001; 2002). While we support the findings
made by Sharp, Beal and Romaniuk (2001; 2002), the methodology was such that advertising
exposure was not guaranteed. In earlier studies, respondents were provided with category
prompts, and may have falsely attributed their own brand for the advertising they recalled (as
in Hall (2002)). No descriptive information relating to ad message/content was captured to
verify exposure, as such may have resulted in the inflation of user scores.
Additionally, the methodology used in this study effectively controlled for decay, as
respondents were asked about their memories almost immediately after exposure. It is
perhaps not surprising that the tracking data used by Sharp, Beal and Romaniuk (2001; 2002)
provided a larger difference between user and non-user recall, and might suggest that nonusers are subject to advertising decay more than users.
Conclusion and Future Research
The results from this study replicate and broaden the empirical generalisation that users of a
brand are more likely to recall and recognise advertising than non-users using an experimental
methodology. The findings also inferred that the difference between users and non-users was
influenced by the research instruments used and the type of market of the advertised brand.
This research is important in building prior knowledge in marketing that researchers can use
to understand and interpret advertising metrics.
Future research should look to further replicate these findings across more categories, using
different methodologies, research instruments and across different media. Additionally, our
datasets showed trends that recent experience with the category is likely to affect the extent to
which advertising is remembered – that is, current users were more likely to recall advertising
than former (or non-recent) users and those who have never used the brand. There was,
however, an insufficient sample to substantiate the finding in this research, and it is urged that
it be addressed in subsequent replications.
References
Bettman, J. R., 1979. Memory factors in consumer choice. Journal of Marketing, 43, 37-53.
Bird, M. and Ehrenberg, A. S. C., 1970. Consumer Attitudes and Brand Usage. Journal of the
Market Research Society 12 (4), 233-247.
Dallett, C. F. and Murdock, B. B., 1971. Effects of Prior Recall Testing on Final Recall and
Recognition. Journal of Experimental Psychology, 62, 361 – 67.
du Plessis, E., 1994. Recognition Versus Recall. Journal of Advertising Research 34 (3,
May/June), 75-91.
Hall, B. F., 2002. A New Model For Measuring Advertising Effectiveness. Journal of
Advertising Research, 42 (2).
Heath, R., 2004. Ah Yes, I remember it well! Admap (450), 36 – 38.
Krugman, H. E., 1977. Memory without recall, exposure without perception. JAR, 17, 7-12.
O'Guinn, T., Allen, C. T. and Semenik, R. J., 2000. Advertising, Southwestern Publishing,
Cincinnati, OH.
Rice, B. and Bennett, R., 1998. The Relationship Between Brand Usage and Advertising
Tracking Measurements: International Findings. Journal of Advertising Research (MayJune), 58-66.
Sharp, B., Beal, V. and Romaniuk, J., 2001. First steps towards a marketing empirical
generalisation: brand usage and subsequent advertising recall. ANZMAC. Albany, New
Zealand.
Sharp, B., Beal, V. and Romaniuk, J., 2002. Quantifying an Empirical Generalisation: Usage
and Advertising Recall in the International Travel Market. ANZMAC. Melbourne, Australia.
Sharp, B., Wright, M. and Goodhardt, G., 2002. Purchase loyalty is polarised into either
repertoire or subscription patterns. Australasian Marketing Journal, 10 (3), 7.
Singh, S. N. and Rothschild, M. L., 1983. Recognition as a Measure of Learning from
Television Commercials. Journal of Marketing Research, 20 (August), 235-248.
Singh, S. N. and Rothschild, M. L., 1983. The effect of recall on recognition: An empirical
investigation of cconsecutive learning measures. Advances in Consumer Research
Sissors, J. Z. and Baron, R. B., 2002. Advertising Media Planning, McGraw-Hill.
White, R., 1998. The Blind Alleys of Recall. Admap (January), 39-41.