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The Contribution of Andrew Ehrenberg to Social and Marketing Research
Abstract
The life-long contribution of Andrew Ehrenberg, now retired, to both the wider science of social research and to marketing science has been notable. A major achievement has been to establish wide-ranging reproducible quantitative relationships in human behaviour in fields in which demonstration of such simple law-like relations had been thought unachievable. The paper gives a brief biography of Andrew Ehrenberg and reviews a few of many publications to illustrate his approach and the results.
... The Dirichlet model is a stochastic preference model, which allows the understanding of the level of competition between brands (or product attributes, such as grape variety, price point, or origin) in a given market. In order to test whether the market observed by the analyst is Dirichlet-like or not, it is recommended to follow the instructions suggested by Bound (2009) in relation to the use of the Dirichlet software (Kearns 2009). If the data show that one is in a Dirichlet-type market, certain patterns occur in that market, summarized as double jeopardy, growth by penetration, the lack of niche or change-of-pace brands, and the occurrence of the Duplication of Purchase Law (Sharp 2010). ...
Wine is complex alcoholic beverage composed of a wide array of sensory and product attributes. Therefore, while wine is an interesting product to research consumer preferences for, there are a series of academic and practical challenges one needs to take into account.
The purpose of this chapter is threefold. First, the chapter explains the reasons why wine is considered a complex product. Second, the chapter illustrates the various quantitative techniques one can use to investigate consumer preferences toward different wines, showing the main advantages and disadvantages of each technique and some notable examples of research conducted with each of these techniques. Third, the chapter provides some practical advice in order to conduct research for wine in an appropriate manner. In particular, the chapter explains what the researcher should keep in mind to set up the objectives of the research and how to apply these to the research approach. The chapter then continues by providing some indications of the costs one should keep in mind based on the approach one intends to use and the advantages and disadvantages of conducting research in-house versus outsourcing it to a research firm.
In this chapter, we build upon the concepts introduced in “Big Little Learnings.” Little learnings initially emerge from individual studies, but with scrutiny across vast datasets, patterns emerge, transforming attention study into a reliable science. The ‘big learnings’ here represent the culmination of research undertaken over the past seven years, dictating our engagement with advertising and what captures attention. Like established marketing laws, each of these ‘Laws of Attention’ has been consistently validated across extensive datasets. The significance of these laws cannot be overstated as the attention category evolves. These interconnected principles should serve as the bedrock for both helping advertisers tackle the challenges of media effectiveness and efficiency, and for the development of attention predicting products.
The Ehrenberg’s law like equation is deemed to fit (within minor error) universally among children aged 11 – 17. This paper adopts this equation to confirm or deny the universal applicability based on selected schools in South-South region in Nigeria which is believed to be environmentally degraded. Data on Age, Sex and anthropometric measures (weight and height) of the cohort in public and private schools were used to fit the model. After the data were pooled from the public and private school, Microsoft Excel Package was used to test how different conditions may influence the fit of the model to the data. The conditions considered were: Gender and Social class (determined by school type), hence there were five different data classifications. Results obtained showed that although the average deviation recorded for female students fell out of the expected limit of ±0.01 although marginally by another +0.01; all other subsets of the data set were found to fit the given equation appropriately. This goes to show that irrespective of gender or social class, provided the students are within the specified age bracket, the Ehrenberg's law like equation will be a good model for use. This is equally verified using the test of significance as well as the test for equality of the regression models.
This review outlines the scientific principles that underpinned Andrew Ehrenberg's working methods, then summarizes his ground-breaking findings in buyer behavior and brand perceptions. It follows on to describe how he applied that knowledge to produce his theory of how advertising works mainly as publicity, now widely if not universally accepted but highly controversial at the time. It concludes with an appreciation of the extraordinary breadth and influence of the body of work, and the inspiration it provides for future scientific study, not least as evidenced in this Special Edition of the Journal of Advertising Research.
A result can be regarded as routinely predictable when it has recurred consistently under a known range of different conditions. This depends on the previous analysis of many sets of data, drawn from different populations. There is no such basis of extensive experience when a prediction is derived from the analysis of only a single set of data. Yet that is what is mainly discussed in our statistical texts. The paper discusses the design and analysis of studies aimed at achieving routinely predictable results. It uses two running case history examples.
Much of what we know in science is as yet confused by uncertainty. But implicit in our observed phenomena are many lawlike relationships saying that if this occurs, so does that. The systematic uncovering of such relationships and their subsequent applications to practical problems are how science and how technology progress. The meaning of a lawlike relationship lies in the variety of empirical conditions under which it is known to hold. Such generalized or lawlike relationships are of course familiar and widely used in practice, but the statistical literature does not give much explicit help in deriving them. The present paper tries to set out some elementary aspects by means of a simple case-history.
In this article Mr Ehrenberg shows how data on purchases of non-durable consumer goods can be fitted by the negative binomial distribution, and discusses applications of this finding. He also considers a simple model for purchases made in different periods of time and some quick and easy methods for calculating standard errors.
Who says that the social sciences are not quantitative? Even in a field supposed to be dominated by people's impulses to buy --- that of marketing --- there are striking regularities.
Two closely related stochastic models are described: The two-parameter NBD or negative binomial distribution model, and the simpler LSD or logarithmic series distribution model.
A variety of exploratory laboratory–style tests compared brand–choices at different controlled prices. This has led to consistent findings across different brands and products (including durables and services) and other conditions.
Price elasticity, rather than being a specific characteristic of a brand, varied consistently with the competitive context, such as proximity to competitors’ prices, brand share, how overt the price change was, and consumer characteristics such as being younger, or a light buyer of the brand. Measurement procedures affected the size of the effects, but the relative patterns persisted.
Such results can provide a grounded base for developing and testing pricing hypotheses.
Description, Prediction and Decision
- A Ehrenberg
Ehrenberg, A., (1964) Description, Prediction and Decision, Journal of the Market Research Society, 13,
14-33.
The discovery and use of laws of Marketing
- A Ehrenberg
Ehrenberg, A. (1969), The discovery and use of laws of Marketing, Journal of Advertising Research, 9,2,
11-17.