A cautionary note….
Marketers spend quite a lot of money tracking perceptions of the brand. There is some use in gathering this information at least once in a while, because if you know how consumers see your brand you can use this knowledge to craft your advertising (and other things like packaging) to look like you, so it will work more for you and is less likely to mistakenly work for competitors. But this is not how image tracking is usually used. Instead marketers look at small changes in particular brand associations, e.g. we are up a bit on “community minded” but down a bit on “a brand I can trust” and try to infer some significance. What do such shifts mean?
Decades of research has documented how attitudinal perceptions (evaluative ie good or bad) strongly reflect the past buying of the respondents in the survey – so simply our market share (if our survey sample is a good one). Of course attitudes also affect buying but the effect is turns out to be weaker than we used to think it was, while the effect of buying on brand attitudes is very strong. So our brand trackers show attitudes improve, but mostly after we gain market share.
Some descriptive perceptions are reasonably straightforward to understand. If only a third of the population know that we sell men’s as well as women’s shoes then this is going to restrict our men’s shoe sales.
Yet even with these less attitudinal, more descriptive associations, it’s not as clear as we might think, e.g. supermarket chain might worry about their association with “low price”, because they make assumptions that being perceived as having “low prices” drives sales – but how much? It’s not an unreasonable assumption that perceptions of “low prices” probably affects shoppers’ overall attitudes (i.e. a multi-attribute attitudinal model where improvement on this feature nudges the overall attitude (how much?)). Alternatively, it affects them in a probabilistic manner, when they happen to think of low prices, or desire low prices, the particular supermarket chain now has more chance of popping into memory as a suitable choice. But… how often and how much this this affects behaviour isn’t known (isn’t documented over different conditions).
The truth is that we have practically no knowledge of how/where/when much particular perceptions affect behaviour – what is a tiny change worth? Anyone who claims to know is either lying (trying to fool you), or fooling themselves.
Spider graphs, perceptual maps – none of them tell us how much any perception is worth.
Some analysts use regression type analyses to determine which perceptions are “drivers” of other perceptions, or of sales movements. Sadly this is more pseudo-science than science – fitting models of weak correlations to a single set of time series data, something well known to produce useless predictions (see Armstrong 2011, Dawes et al 2018). Sales (i.e. behaviour) strongly affect perceptions, so correlations between the two are largely, if not totally, due to behaviour causing the perception. This powerful causal relationship makes quantifying how particular perceptions drive other perceptions or sales impossible. All you get is a bunch of over-fitted models describing spurious relationships. It’s impossible to tell which model might be useful, not without doing many differentiated ‘replications’, the basic work of science (statistical gymnastics is no shortcut).
But we also don’t know how much these shifts in market research response are merely that – shifts in a particular (non sales) behaviour i.e. response to survey questions. For example, for years Mars used the slogan in Australia for their market leading Mars bar “a Mars a day helps you work, rest, and play”. So any survey that asks “which chocolate bar helps you work” will record many responses for Mars bar. And the more recently that Mars have advertised using this slogan, the higher the response will be. The market really does react to advertising, especially if it is done well – clearly branded, placed in broad reach media. So perceptual shifts may be useful in evaluating advertising (see footnote). But how can we interpret a 3% shift in respondents picking Mars bar for “helps you work”? How much of this is them just parroting back the advertising versus actually believing that Mars bars help you work? And even if they did believe how will this affect their behaviour? We simply don’t know.
While we do know that people can learn things and yet never bring these beliefs into play in purchasing situations.
Another related problem is that people learn things about brands largely for identification, not for helping them evaluate, or even recall. For example, lots of us know that Amazon’s book reader is called Kindle. That we do is good for Amazon, but who has thought about the meaning of the word, actually it was chosen because Amazon liked the “start a fire” connotation, that’s why Kindle Fire has the name it has – I suspect you never even noticed the connection. In the same way that no one wonders why McDonalds has a Scottish name.
My point is that movements in market research surveys are precisely that, and we don’t know what they really tell us about how memories in brand buying situations have changed, let alone how this would affect behaviour/sales.
We have to be humble and realistic about our collective lack of knowledge.
All we have is the qualitative notion along the lines that it’s probably better for a supermarket to improve things like the proportion of people who associate it with “low prices”. So we watch such metrics to check if they start dramatically trending downwards. Though the reality is that this virtually never happens unless our sales collapse (when all perceptions track downwards), or that our prices really fall behind (in both cases it’s unlikely we need market research to alert us!).
Footnote: the Ehrenberg-Bass Institute has done research on how advertising affects image surveys. We show that it does. And that without adjusting scores for changes in behaviour (because of sampling variation and real things going on in the market) the effect of particular messages can be missed or misinterpreted.
Anyone interested in this cautionary note on the interpretation of brand image associations and attitudes can read more in the chapter on “Meaningful Marketing Metrics” in the textbook “Marketing: theory, evidence, practice” 2nd edition, Oxford University Press 2013.
These patterns in image data have been document over decades, and many many brands, categories, countries eg:
Barwise, T. P. & Ehrenberg, A. 1985. ‘Consumer Beliefs and Brand Usage.’ Journal of the Market Research Society, 27:2, 81-93.
Bird, M., Channon, C. & Ehrenberg, A. 1970. ‘Brand image and brand usage.’ Journal of Marketing Research, 7:3, 307-14.
Romaniuk, J. & Gaillard, E. 2007. ‘The relationship between unique brand associations, brand usage and brand performance: Analysis across eight categories.’ Journal of Marketing Management, 23:3, 267-84.
Romaniuk, J., Bogomolova, S. & Dall’Olmo Riley, F. 2012. ‘Brand image and brand usage: Is a forty-year-old empirical generalization still useful?’ Journal of Advertising Research, 52:2, 243-51.