About ByronSharp

Byron Sharp is Professor of Marketing Science, and director of the Ehrenberg-Bass Institute, University of South Australia

What is a Chief Growth Officer?

Marketing Week reports that a number of companies  have appointed Chief Growth Officers, e.g. Coty, Colgate-Palmolive, and Coca-Cola.  So what is a Chief Growth Officer?  Well, there are (at least) 3 options.

  1. It can be a new title for Chief Marketing Officer (CMO).  Maybe it’s a better title, maybe not – I suspect it all depends on the person.  Here, the role is to enhance the company’s marketing capability, to make the marketing department better, wiser, less wasteful, more effective.  And to make the marketing function be seen as capable of contributing to growth and being accountable for growth.  This is a tremendously important role, a never-ending one, where success depends substantially on bringing scientific evidence into the minds (and hearts) of the marketing team.  I wrote about this role previously.
  2. It can be the same role as CMO, but with the additional responsibility of the sales team.  Is this a better model?  I don’t know,  I suspect it depends a lot on the implementation.  The idea of marketing and sales reporting to one boss looks attractive, it might help them work together for the good of the brand(s).  Then again, this may be simply too big a job for one person.
  3. The Chief Growth Officer could be a role distinct from CMO.  Marketing capability is at the heart of the competitive performance of many corporations, as they work in increasingly competitive markets.  Mental and physical availability underpin the value of such companies, so the CMO’s role is vital….But, even with excellent marketing, company growth will be stymied if the company isn’t playing in the growing categories, in the growing markets/countries, in the growing distribution channels.  The job of the Chief Growth Officer can be to make the company better at making these investment decisions.  In this case, the CGO and CMO work side-by-side; the CMO builds a better marketing capability, while the CGO works to make the organisation better at deciding where to apply this capability (and resources).

All of the companies listed above are sponsors of the Ehrenberg-Bass Institute, a tribute to how they take marketing and business growth seriously.

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Some inconvenient truths about brand image perceptions

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.

Mistaking statistical modelling for science

Marketing isn’t the only discipline to have been seduced by the idea that modelling can somehow bypass the hard work of developing empirical laws.  Few seem to realise how heroic the assumption is that teasing out a few weak correlations can quantify precisely how much [something of interest eg sales] will change in the future when [various other things, eg media choices] are altered.

Added to this is the ‘Big Data fallacy’ that adding together bunches of weak correlations will lead to more and more accurate predictions – “once we have enough data, a clever programmer, and a powerful enough computer, we’ll be able to predict everything we want”.  It’s as if chaos theory taught us nothing at all.

The basic work of science is making empirical observations, looking for patterns, and then…. once you have found one, looking to see where it holds and where it doesn’t.  This requires lots of replications/extensions over different conditions (eg countries, product categories, and so on).  This is how scientific laws are developed, that give us the ability to make predictions.  These replications/extensions also tell us what conditions don’t affect the law, and maybe some that do.  This leads to deep understanding of how the world works.  Experiments can be used to tease out the causal directions and magnitude, what really affects the pattern and how much.  Again these experiments need to be done carefully, across a range of conditions that might matter.

Yes, this doesn’t sound very glamorous, it takes much time and effort (1% inspiration, 99% perspiration).  Sometimes we get lucky, but generally many many studies are required.  By independent teams, using creatively different approaches – so we can be sure that the empirical phenomenon really does generalise, that it isn’t a fragile result (or a mistake) that only exists in one team’s laboratory.

Unsurprisingly the idea that a computer model could bypass much of this hard work is seductively attractive.

Terribly complicated, yet naive, modelling seems to be everywhere.  In population health statistical correlations deliver precise estimates that if people eat particular foods (or amounts of fat/sugar/alcohol, or sitting around) then their risk of dying early will be such and such.  There is nothing wrong with this, so long as we recognise the weakness of the method.  Unfortunately these correlations often get handed over to engineers who, with a spreadsheet and a few heroic assumptions about causality, produce model predictions that if the government taxed this, or regulated that, then x million lives would be saved, and x $billion saved in hospital bills.  These predictions need to be treated with a high degree of skepticism.  We need tests before legislation is changed and money spent.

In climate science, a rather new, and until recently very small discipline, modellers now seem to dominate.  In the 1970s a short period of cooling led to worry about global cooling, but then temperatures turned around to rising again, and climate scientists started to become seriously concerned about the role of rising CO2 levels.  They rushed to develop models and in the early 1990s they gave their predictions for CO2 emissions to lift global temperature, along with accompanying predictions of oceans rising, ice retreating, polar bears disappearing and so on.  25 years later they are confronted by the overwhelming predictive failures of these models, that is, the models substantially over-predicted the warming that was supposed to occur (given that the CO2 levels have risen – the IPCC, even though they are ‘marking their own homework’, admit this in their assessment).  The modellers are now starting the work to figure out why.  Meanwhile the forecasting scientists who criticised the climate scientists’ forecasting methods, and predicted this result, have been vindicated.

Models that show wonderful fit to historic data routinely fail in their predictions*.  That’s why we revere scientific laws (and the theories built on them) because they have made predictions that have come to pass, over and over.

 

* *See also Dawes, J. G. 2004. ‘Price changes and defection levels in a subscription-type market: can an estimation model really predict defection levels?‘ The Journal of Services Marketing, 18:1, 35-44.

No wonder marketers aren’t respected – even marketers hate marketers it seems

Professor Byron Sharp says it’s time for marketing to stand up and be confident. We have much to be proud of.

Recently campaigns that feature a “save the world” angle have done extraordinarily well in the Cannes Lions creativity awards. Any submission for a charity seems to enjoy a special inside track to winning an award. As do campaigns that link brands to social causes (brand purpose).

As Rory Sutherland, former vice-chairman of Ogilvy Group UK, cheekily observed:

“there’s an aspect to Cannes that slightly irritates me, it’s a little bit of a liberal, worthy wankfest at times. I’d kind of like to see a nice campaign for the National Rifle Association once every two years as there’s a little bit of that self congratulatory ‘mmm, yes, we’re saving the world’ stuff which, frankly, sticks in the throat a little bit.”

“What’s to worry about?” you ask, “isn’t it good that these worthy causes have become so popular with marketers?” But there is plenty to be worried about, let me explain…

First, there is the obvious point that it means that the Lions awards aren’t fair, they aren’t truly awards for creative excellence when they muddle in political correctness. A submission for the NRA would have to be truly outstanding to win an award, indeed perhaps it could never win no matter how good it was? So the festival organisers have allowed their awards to be corrupted – they need to fix this or the awards will lose their value.

More importantly though this trend says something is rotten in the world of advertising and marketing. There is an awful cringe – many people seem to hate the fact that they work in marketing, especially that they promote brands that are popular with billions of consumers and therefore sold by big businesses. This is an awful situation. That we have people prostituting themselves working to market brands when they think commerce is grubby, that big business is immoral, and that the world would be better off without the brands they promote. This cultural cringe is seen in the numbers of marketers who, once they have accumulated a small fortune, leave their agency or company to go work for a charity (or if they have accumulated a large fortune they set themselves up as philanthropists to somehow atone for their sins (or buy their way into heaven?)). If this is the example we set how will we attract ethical young people into our profession?

The loathing of big business over small is odd because it’s big businesses with big brands that are far more likely to be environmentally responsible, non-discriminatory employers. They have a reputation to keep, unlike many small businesses who are more worried about whether they will be still be in business next year.

Brands should be good corporate citizens, but the idea of turning them into saints is nuts. It’s also unimaginative. These are the sort of marketing campaigns that high school students come up with for their term papers. Showing the brand saving the world is sweet, but naive, and hardly original. An adult, Mark Ritson, wrote recently: “Patently, the whole concept of brand purpose is moronic. I do not want Starbucks telling me about race relations and world peace – I want it to serve me a decent coffee in pleasant locations. I care about race equality, deeply, but I do not trust a giant corporation with an extremely spotty reputation for paying its taxes telling me what to think.”

There is also a deep ethical issue of whether it is right to take share-holders money and spend it on your favourite cause. This is other people’s money (the pension savings of millions of people) and these individuals each have their own charitable causes.

The irony of marketing’s brand purpose fashion is that anyone familiar with statistics on human development knows that we are living in extraordinary times. Violence, malnutrition, illiteracy, child labour and infant mortality are falling faster than at any other time in human history. The world has become a drastically better place, and is continuing to get better still – and this is largely due to trade and the value it generates, which allows for investment in scientific discovery, which in turn further accelerates the gains brought about by trade. It was the trading revolution that started 10,000 years ago that brought about the specialisation that would in turn create the scientific revolution. Commerce and science together are changing the world improving lifting millions out of poverty, at a rate never seen before in the entire history of humanity. In the past century extreme poverty (which for most of history was the norm) has dropped to less than 10% of the world population, and that statistic is in free-fall.

Life expectancy has been improving dramatically throughout the world, largely as infant mortality is being eliminated. Vaccination rates throughout the developing world are typically around 90%, higher even than some wealthy, but deluded, suburbs in California. Violence is declining at a similarly dramatic rate, education levels rising, and the moral progress that started during ‘the Enlightenment’ now means that the rights of animals and children are firmly on the global agenda, when only a hundred years ago most people would have thought such notions were absurd.

Last century we saw oppressive regimes fall when they failed to deliver product choice and abundance, banned advertising, and denied their populations brand choice. Their failure to deliver economic progress made these leaders paranoid and oppressive (killers). Democracy needs markets and property rights. Today we still have modern reminders of the dangers of anti-capitalist movements in the starvation economies of North Korea and Venezuela.

Perhaps too many marketers learnt their economic history in arts school?

So at a time when the world should be celebrating the benefits of global trade, many marketers are acting not just as if they are ignorant of its benefits, but that they are genuinely misinformed, i.e. they think it is harmful. This is very odd, a parallel would be doctors opposing medical research (of course there are homeopathic and naturopath quacks who do). Marketers should be the most vocal supporters of trade, of advertising, of brands. They should be standing up proudly for the astonishing amount of choice that the modern market economy (yes, that’s capitalism) delivers. If we of all people don’t, who will?