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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. 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