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.
This is nonsense, pseudo-science. For some brands, sales (i.e. behavior) strongly affects perceptions, for other brands, perceptions strongly affect sales, for some we see dual causality. Thanks for challenging me a few years ago to show 1 example of a brand perceptions driving sales – which got me to this larger finding. Why did you block me afterwards and appear unwilling to hold up your excellent points to scientific scrutiny? I believe the truth is better served by investigating the relative importance of distribution, ad spending, ad creative,…. and its brand/category moderators than by shouting ‘absolute’ claims like this blog post.
I don’t think you meant to say that it’s as simple as for some brands (which?) sales affects perceptions and for other brands it’s the other way around.
The powerful effect of behaviour (usage) on brand perceptions is well documented. Small deviations from this pattern have also been documented, and appear to be largely for more descriptive, less attitudinal brand associations. This is the extent of our scientific (well documented, replicated) knowledge. Leaving managers who try to interpret brand image data with only intuition and guesswork. That’s the point of my cautionary post.
For the record….
I certainly didn’t block Pauwels to avoid debate, see https://wordpress.com/post/byronsharp.wordpress.com/1530
Both Professor Pauwels and I agree that consumer perceptions affect their behaviour (and vice versa). Unsurprisingly we both agree that mental availability affects sales.
We also agree that scientific knowledge regarding what small image shifts might mean for the future of a brand is currently very limited (in spite of decades of research). By ‘scientific knowledge’ I mean knowing what a particular image shift in a particular situation/context (eg the brand, the product category, size of brand, season etc) means for the future of the brand (e.g. market share next year).
I think we disagree in our confidence in the use of multivariate time series analysis to work out what brand perceptions drive future sales. I’m far less confident because the predictive/forecasting track record of such attempts has been shown to be poor.
Hi Byron, Excellent article as always. My colleague and I at our consultancy use many of your insights for discussions we have clients. We even play a game to see who can drop the words “memory structures” first haha…but it definitely resonates with them once they get their head around it. Thanks again and we loved your new book! Cheers, Matt, 3Fold.
Thanks for those kind words Matt. I’m glad the research has proved useful to you.
Very interesting, and hard to disagree with, of course.
But doesn’t the same apply for mental availability?
We don’t really know the value of – to stick to your example – a larger number of people associating ‘low prices’ / ‘good for when I don’t want to spend a lot of money’ with a supermarket, on actual penetration?
We assume that higher mental market share drives higher penetration but surveys being surveys they can only ever be a proxy for our probabilistic performance in actual consumer contexts.
What’s the alternative?
How else do we diagnose we’re on the right path to growing the brand?
Good questions. My article is a cautionary note. I hope it causes many to realise that they are using intuition/theory/guess like medieval doctors, and so to instead question and seek answers/evidence (or save money). I don’t think “what’s the alternative” is justification for using something, that’s exactly what medieval doctors might have said about bleeding.
Good question. I think we are pretty safe ground that a general increase in mental availability (interacts with physical availability) to grow market share. The very important point being that mental availability measures what evokes the brand, whereas brand trackers tend to focus on what does the brand evoke.
“The very important point being that mental availability measures what evokes the brand, whereas brand trackers tend to focus on what does the brand evoke.”
That is a fantastic line, very helpful both for my understanding, and to trot out to clients.
thanks for the interactions and update, Byron!