Two views of paid-for advertising are compared. One is commonly held but unachievable. The other is more realistic. The main aim of advertising is commonly thought to be growth, but this seldom occurs. The more realistic goal is brand maintenance in a highly competitive market. The growth would come from persuading consumers to buy your brand (a strong theory of advertising), but there is little evidence of this. In contrast, brand maintenance works through reinforcement and occasional nudging (a weak theory). Persuasion would work by differentiating brands (added values) to give people reasons for choosing them. The reinforcement view accepts instead that sales differ because a large brand is salient to more people, and not because they see brands as very different. Being salient (e.g. in people's consideration sets, etc.) can be affected by Here I am type of impactful publicity, leaving longer-term memory traces and possible associations for the brand, rather than by making one brand seem preferable or better than another.
The paper is divided into four main sections. The Methodology describes the data upon which the analyses were based and explains the theoretical background to the approach adopted. The Results are then presented to show how large and small drugs differ and the brand performance measures for a specific drug are presented and explained. The Discussion interprets these results in the light of the theory that has been developed in other markets and also discusses the underlying causes of the patterns of brand performance, the individual behaviour of prescribers. The final section looks at some specific Applications of the approach adopted and outlines some practical examples of how managers could use the concepts presented in this paper.
In this paper, we argue that the dominant brand-building perspective on advertising is much too restrictive and leads to most advertising being seen as ineffective. We maintain that a neglected and under-developed alternative - the brand-maintenance perspective - provides a basis for a more realistic and productive approach to advertising problems. The nature of this alternative is indicated and a research programme designed to articulate and develop it is described. Two examples that illustrate the work proposed are discussed. A summary outline of other aspects of the programme is also given.
As background to planning for the multi-channel interactive future we address two linked questions : What is the demand for different type of programmes? How much would viewers be willing to pay directly for their habitual channels? The paper draws on the wide range of well-established, empirical evidence about consumer behaviour in the UK and other television markets. We note the underlying regularity of much of this behaviour, which is reviewed in the broader context of consumer behaviour in markets for other goods and services. Our research on viewers willingness to pay, involving a single-price package, demonstrated a remarkable price inelasticity for UK terrestrial channels, reflecting their high reach and hours viewed. UK (and other) television is currently underpriced. We conclude that rapid, fundamental change is unlikely to occur in the broadcasting as in other markets in response to new technological opportunities, and that UK viewers will continue to want to watch their current range of programme types. Viewers are prepared to pay for quality services they want to watch, including both existing and new channels.
The purpose of this contribution to our seminar on modelling is to make two points: 1. There is usually little point in modelling something if we do not know what it is; 2. Developing the required empirically-based generalisations in marketing is both possible and essential. To illustrate, we summarise an experimental study on pricing carried out in the UK in 1986. Our aim was to establish whether the sales response to a given price change would generalise.
In this paper I discuss how this traditional process can be fruitfully reversed. We assume some target market share, and use our knowledge of the existing market to predict the new brand's penetration and repeat rates, share of requirements, competitive positioning, retail uptake and image, for when the brand has settled down to be part of the established market with the assumed share. We can then use these predictions to evaluate our new brand concepts, promotional planning, pre-test and test market results, and indeed the assumed assumed market share itself. All this is complementary to the traditional approach and mostly very cheap.
Most television programmes can be classified into two main programme types, Information and Entertainment. Information programmes tend to get smaller audiences but higher appreciation scores than do Entertainment programmes. Between these two main programme types, the correlation of audience appreciation with audience size is therefore negative. But for different programmes of the same type the correlation is positive, though low. Higher appreciation scores tend to go to the programmes with the larger audiences. A theoretical interpretation is that the more demanding a pro- gramme is, the more interesting and/or enjoyable it has to be before people will watch it.
Ultimately we need to establish the effects which promotions have on the consumer- i.e. any increased purchasing in the short term, or changes in attitudes and loyalty in the longer term - and to relate this to costs. Where promotions are aimed at the retail trade, retailers can also be regarded as "consumers" in this context. In any case, consumer sales remain the final yard-stick. To learn about the effects of promotions might imply running controlled experiments comparing behaviour or attitudes with promotions arid without promotions. But controlled experiments for evaluating short-term effects in real life situations are difficult and expensive to mount, and virtually impossible in attempting to evaluate longer-term effects. Two other approaches are therefore needed. One is the use of theoretical norms for evaluating real-life marketing situations. The other the use of deliberately artificial or semi-artificial testing procedures. These two approaches will be discussed here.
The paper shows how different versions of factor analysis applied to the same data can lead to different results. In contrast, factor analyses of data which differ can lead to the same results. These are two major limitations of the technique. Two alternative analysis procedures are described. Firstly, any clusters in the data can readily be seen from the correlation matrix if the correlations are rounded to one or two digits and the variables are ordered according to the average size of their correlations. Secondly, since correlations only reflect the strength of a relationship and not its nature, a further alternative is to establish the actual relationships. This shows up the same kinds of clustering as factor or correlational analysis do at their best, but also adds real hut simple quantification. It leads to a depth of understanding and relative ease of communication which seem impressive.
In this article we show how the effects of many marketing actions can now be evaluated in some detail. The basic question considered is not whether there was any positive effect at all (eg on total sales) but what kind of effect it was (eg extra penetration or heavier purchasing from existing customers). To make such evaluations, we need to compare what actually happened with what would have happened without the marketing action. Research in the last decade has facilitated such comparisons without having to run controlled experiments. Instead of having to measure directly what would have happened without the marketing action, it is now possible to predict such norms successfully. The case-history described in this article is one where a controlled experiment could in fact have been mounted, if it based on a study for the J. Walter Thompson Company had been planned in time. The special lesson therefore is to show how an evaluation could actually be carried out after the event, and how ibis was in any case much cheaper. The approach adopted has already been applied in evaluating many marketing situations, such as price-changes, new brands, relaunches, seasonal trends, life-cycle assessments, private label brands, and various kinds of consumer and retail promotions. As a specific example we describe here a case-history which involved a consumer promotion or deal'.
One question which has been raised in the discussion is that of assessing a manufacturer's scope for launching an additional brand in a product-field instead of simply pushing his existing brand. This is in fact one of several kinds of practical application of the results which are already being actively pursued. It links up with the more general topic of studying buyer behaviour for aggregates of brands. This has specific applications not only for judging the scope for additional upper sales limits of existing brands and for assessing the role of house-names, but also provides a link with macro-economics.
The number of people who buy two particular brands in a given time period does not depend on the brands as such but only on the numbers of people who buy each brand and on a general constant. The constant varies by product-field and by the length of the analysis-period, the correlation between buying any two brands being positive in relatively long periods and negative for shorter periods.