Our critics have been few, and rather kind (nothing of substance has been raised).
Now and then a marketing guru issues a thinly disguised advertisement for their consulting services that tries to have a go at the laws and strategy conclusions in How Brands Grow. They usually say something like:
“Our data confirms that larger market share brands have much higher market penetration BUT our whizz-bang proprietary metric also correlates with market share, and this proves that it drives sales growth, profits, share price, and whether or not you will be promoted to CMO”.
Often some obscure statistical analysis is vaguely mentioned, along with colourful charts, and buzzwords like:
And sexy sounding (but meaningless) metrics along the lines of:
All of this should raise warning bells amongst all but the most gullible.
Let me explain the common mistakes….
Ehrenberg-Bass say brands grow only by acquiring new customers.
These critics somehow missed the word “double” in Double Jeopardy. Larger brands have higher penetration, and all their loyalty metrics are a bit higher too, including any attitudinal metrics like satisfaction, trust, bonding… you name it.
Brands with more sales in any time period, are bought by more people in that time period. So if you want to grow you must increase this penetration level. In subscription markets (like home loans, insurance, some medicines) where each buyer has a repertoire of around 1, then penetration growth comes entirely from recruiting new customers to the brand. In repertoire markets penetration growth comes from recruitment and increasing the buying frequency of the many extremely light customers who don’t buy you every period.
The “double” in Double Jeopardy tells us that some of the sales growth also comes from existing customers becoming a little more frequent, a little more brand loyal. Also their attitudes towards the brand will improve a bit, as attitudes follow behaviour.
Improved mental and physical availability across the whole market are the main real world causes of the changes in these metrics. The brand has become easier to buy for many of the buyers in the market, it is more regularly in their eyesight to be chosen, and more regularly present in their subconscious, ready to be recalled at the moment of choice.
Why does it matter anyway? Can’t we just build loyalty AND penetration?
Yes, that’s what Double Jeopardy says will happen if you grow.
Loyalty and penetration metrics are intrinsically linked. They reflect the buying propensities of people in the market – propensities that follow the NBD-Dirichlet distribution and Ehrenberg’s law of buying frequencies. Growth comes from nudging everyone’s propensity up just a little bit. Because the vast majority of buyers in the market are very light buyers of your brand this nudge in propensities is seen largely among this group – a lot go from buying you zero times in the period to buying you once, so your penetration metric moves upwards (as do all other metrics, including attitudes).
For a typical brand hitting even modest sales/share targets requires doubling or tripling quarterly penetration, while only lifting average purchase rate by a fraction of one purchase occasion. That tells us that we need to seriously reach out beyond ‘loyalists’, indeed beyond current customers, if we are to grow.
When budgets are limited (i.e. always) it’s tempting to think small and go for low reach, but this isn’t a recipe for growth, or even maintenance.
A focus on penetration ignores emotional decision making.
This is odd logic. A focus on mental and physical availability explicitly realises that consumers are quick emotional decision makers, who make fast largely unthinking decisions to buy, but who if asked will then rationalise their decision afterwards.
Ehrenberg-Bass say there is no loyalty.
Really?! On page 92 of “How Brands Grow” we write:
“Brand loyalty – a natural part of buying behaviour. Brand loyalty is part of every market”.
On page 38 of our textbook “Marketing: theory, evidence, practice” we write:
“Loyalty is everywhere. We observe loyal behaviour in all categories” followed by extensive discussion of this natural behaviour.
In FMCG categories, buyers are regularly and measurably loyal – but to a repertoire of brands, not to a single brand. And they are more loyal to the brands they see a bit more regularly, and buy a bit more regularly.
All brands enjoy loyalty, bigger brands enjoy a little bit more.
Ehrenberg-Bass analysis was only cross-sectional.
Actually, we published our first longitudinal analysis way back in 2003 (McDonald & Ehrenberg) titled “What happens when brands lose or gain share?”. This showed, unsurprisingly, that brands that grew or lost share mainly experienced large change in their penetration. This report also analysed which rival brands these customers were lost to or gained from.
In 2012 Charles Graham undertook probably the largest longitudinal analysis ever of buying behaviour, examining more than six years of changes in individual-level buying that accompanied brand growth and decline. This highlighted the sales importance of extremely light buyers.
In 2014 we published a landmark article in the Journal of Business Research showing that sales and profit growth/decline was largely due to over or under performance in customer acquisition, not performance in retaining customers. Far earlier we had explained that US car manufacturers did not experience a collapse in their customer retention when Japanese brands arrived, they each suffered a collapse in their customer acquisition rates.
But if we can change attitudes then surely that will unlock growth?
It’s rare that it’s a perceptual problem holding a brand back. Few buyers reject any particular brand (and even most of these can be converted without changing their minds first). The big impediment to growth is usually that most buyers seldom notice or think of our brand, and that the brand’s physical presence is less than ideal.
For more on “Marketing’s Attitude Problem” see chapter 2 of “Marketing: theory, evidence, practice” (Oxford University Press, 2013.
Attitudes can predict (some) behaviour change. Light buyers with strong brand attitude were more likely to increase their buying next year. And heavy buyers with weak brand attitude were more likely to decrease their buying next year.
This is a mistaken interpretation, something that has tripped up a few researchers. I’ll explain….
First, understand that a snapshot of buying behaviour (even a year) misclassifies quite a few people: some of the lights are normally heavier but were light that particular year; some of the heavies were just heavy that year (kids party, friends visited, someone dropped a bottle) and next year revert closer to their normal behaviour. Note: for many product categories just a couple of purchases is needed to move someone into, or out of, the heavy buyer group.
Second, we must remember that attitudes tend to reflect any buyer’s longer-term norm.
So someone who is oddly heavy in buying this year will tend to be less attitudinally loyal to the brand than ‘regular’ heavies. Someone who is oddly light this year will tend to be more attitudinally loyal to the brand. Next year, odds are, these people’s buying moves closer to their norm and their expressed attitude. It looks like the attitude caused a shift in behaviour, but it’s an illusion.
This statistical ‘regression to the mean’ is not real longer-term change in behaviour of the kind marketers try to create. Nor does this show that attitudes cause behaviour – their real influence is very weak, while the effect of behaviour on attitudes is much stronger.
Ehrenberg-Bass analysis is very linear reductionist, whereas we take a quadratic holistic approach.
Really not sure what these critics are talking about, nor perhaps do they. This is pseudo-science.
I have a super large, super special data set.
Please put the data in the public domain, or at least show the world some easy-to-understand tables of data. If you want us to consider your claims seriously then please don’t hide behind obscure statistics and jargon.
I have data that shows Ehrenberg-Bass are wrong, but can’t show it.
What do you make of certain ad agencies advocating the need for brands to be purposeful over and above their utility if that makes sense.
To help brand loyalty / increase trust, they need to give back to society and market the fact they do? They seem to show studies that talk about attitudes of consumers but very little on behaviour / evidence of increase in sales.
Wishful thinking… fashion. Ignored by most consumers, and of those that notice they do so only occasionally. Of course firms have to be good corporate citizens but this is not really something for the marketing dept.
It seems that your message about ‘Brand Loyalty’ needs to be constantly repeated. Eventually people will or won’t accept it.
Should it always be a goal for Brands to grow in this manner? Getting as many unique buyers in as fast as possible could potentially ‘blow up’ the brand and make it less meaningfull. A Fad if you will.
Helmer, that’s interesting speculation, but I know of no data to support such an apocalyptic view. Brands that grow mental and physical availability attract more users and enjoy higher share – and become more valuable, they don’t “blow up”.
Wasn’t there a case where a fashion brand forbid (through a lawsuit) actors in a series to wear their clothes? I think it was Hollister and the show was Jersey Shore. I can just imagine that the growth path you look for as a brand can differ and therefore mental and physical availability should be well targeted. Because what is my Gucci bag worth if everybody has one. Shareholder value will rise on the short run of course, but what happens to consumer value?
It will also be different by category I presume. Categories where the brand as such are actually still meaningful (fashion for example) are different from categories like utility companies, insurance companies and FMCG.
And yes, it is just an hypothesis. Don’t have the means to further examine this.
This luxury brand hypothesis is investigated in How Brands Grow part 2.
Great post and great books, but I do think you’re glossing over one of the challenges.
You rightly say that there is evidence that brand attitudes can predict some behaviour change. This seems to me to be a very important result. I agree that it is perfectly likely that many (perhaps even all – although that is less likely) of the light buyers with strong brand attitudes were heavy purchasers historically, but nonetheless they are not regressing to the “mean” when they go back to being heavy buyers – they are by definition going above mean. So, this is not simple “regression to the mean”. Attitudes are allowing us to pick who is more likely to repeat or upweight their purchases in future from a group whose purchase behaviour has been the same for the last 12 months. What is it that makes those heavier purchasers return to their previous purchase weight? You avoid that question above by suggesting that this heavier purchase weight is just a natural state of some sort for these people, but what is it that means these people have a general propensity to purchase more? It’s not mental availability (because our data finds that is less able to pick the switchers than attitudes such as liking the brand). So, surely it is their attitude towards the brand that makes them return to heavy buying? Surely then attitude does play some part in causing some purchase behaviour?
Of course purchase also feed attitude very heavily. But in our data we see that the average level of attitudinal commitment towards brands per purchase made in last 12 months, varies massively across brands and doesn’t correlate with brand size. By this I mean some brands have very strong attitudinal commitment per purchase, whilst others have much weaker (this as for the above comment is when looking at survey data for shopper panelists). That means attitude, although related to brand size, is not a predictable outcome of purchase behaviour. How strongly they relate varies a lot by brand. Some brands build attitudinal commitment much more effectively per purchase than others. This could be because some products are much better than others, but it also seems very likely that it is the result of brand marketing helping to frame and enhance the usage experience (shampoo brands that have basically the same stuff in the bottle see big differences, so unlikely to be just product).
Put those two points together, and it means that brand attitude does contribute to purchase choice and it can be influenced by marketing (if slowly and usually only via usage).
That in turn is why we see over the long-term (eg 2-5 years), that brands with relatively stronger attitudinal commitment than expected for their brand size in year 1 (the ones that generate more attitudinal commitment per purchase), tend to grow faster and get a better market share return on salience increases and effective share of voice over the coming years than brands that start with weaker attitudinal commitment.
I don’t see any of this as contradicting the purchase behavioural relationships of double jeopardy. It doesn’t mean brands grow by building purchase frequency without building penetration. It just means that brands that “enhance” the product experience through marketing that emphasises their product benefits and / or suggests potential higher order benefits of using them get a greater return (both in terms of penetration and purchase frequency) on increases in mental availability brought about by that advertising.
One more challenge. If attitudes don’t drive purchase behaviour at all. How does negative word of mouth cause a reduced propensity to purchase (as per p139 – 141 of HBG2). i agree -ve WOM is a minor influence on brand building, but it’s an instructive influence to study, because it’s the one case where mental availability and attitude are likely to move independently for those exposed to the -ve WOM (mental availability.is likely to stay static or rise slightly – hearing about the brand recently is unlikely to stop it coming to mind even in purchase situations. But positive brand attitude is likely to decline, which is what causes people to dismiss the option when it comes to mind or is presented to them and reduces propensity to purchase, no?).
Josh, There is now decades of evidence to say that marketers are wasting their time/money in tracking attitudes thinking that they will tell them where their brand is going, or how to unlock growth potential. I suspect you are seeing what you would like to see. But until the data is put into the public domain we’ll never know.
Regression to the mean really is regression to the mean (and it refers to the whole sample). If you look at more than 2 years of data you’ll get a better appreciation.
Attitudes can affect buying, certainly for individuals even if they are a small story at brand level, but their effect is usually weak and erratic/idiosyncratic. See “Marketing: theory, evidence, practice” (Oxford University Press) for deeper explanation.
Thanks for replying, but I still don’t understand how attitudes picking those who’ll up and down weight their purchases in the next period doesn’t give you more pause for thought.
Yes, I agree regression to the mean happens. On average a certain proportion of every buyer group will switch to another in the next time period, even when no macro-change occurs.
But the point here is that current attitudinal measures allow us to pre-determine those who will buy more and those who will buy less in the next period.
I am not saying that means that some event has changed their attitudes in the last year and then their behaviour follows (although in some cases that is probably true, as you say need to extend the data over many years, to be certain). My point is that this observation is instructive to understand the influences on an individual’s purchasing. It strongly suggests that attitudes as recorded in these survey questions influence behaviour (regardless of whether they are stable over a long period and influenced by past behaviour from many years and purchase cycles ago).
Certainly it suggests attitudes are more than just the post rationalisation of purchase behaviour (it would be odd to be post rationalising behaviour from 18 months ago, no).
On the broader point about what evidence is out there. You’re right we both see the evidence of the last few decades differently on this specific point. Where you see evidence of attitudes following behaviour, I see a evidence of a cycle of attitudes feeding behaviour and behaviour feeding attitudes, with a clear indications that marketing and brands can enhance that virtuous circle (creating a preferential feedback loop), which is why over the long-term the brands that achieve more than their expected share of attitudinal predisposition tend to grow faster..
Josh, it means we have some limited ability to predict people on the edges, people who were unusually light or heavy this year, and so will return closer to the mean next year. But this is of little practical value because to do it we have to survey everyone. We can already predict the percentages that will change from light to heavy and vice versa using the NBD-Dirichlet (without needing to survey).
Please note that the ability to correctly tag individuals is limited by the fact that people change their attitudinal responses from survey to survey (even if only minutes between) (see Dall’Olmo Riley, 1997 and many others).
PS no it would not be odd to be describing the last 18 months or more of behaviour when giving an attitudinal response, this is largely what people do when asked for an attitude (see Bem 1967) but with stochastic variation (see sentence above).
Josh – Buying Behavior and the NBD Dirichlet support some elements of consumer attitude. Simulation of the NBD at the individual level requires the use of penetration and purchase frequency to create a distribution of preference probability. An individual’s purchase probability, if held constant, shows how purchasing can vary over time and give the appearance of changing loyalty. The idea of reverting to the mean purchase probability applies at the individual level. Nicely, aggregating buying behavior across the simulated population produces patterns of behavior that have repeatedly been shown to match data in purchase panels. To your point, what happens at the individual level when preference changes over time would be thought to validate the idea of equity and attitude tracking. Unfortunately, surveys suffer from point in time claims that haven’t been proven to match well with actual purchase behavior. Physical availability of a large brand cause it to be purchased by “reluctant” consumers. Consumers who proclaim in surveys that they “love” a small brand will be seen to buy popular brands because they are easy to buy. Equity studies, and sentiment analysis of “big data” have difficulty explaining the position of brands in a category. I have seen many attitudinal measures climb and dive while the brand share holds steady. Is there merit to tracking attitudes? If the attitude tracked is specific to product performance you might find some level of explanatory power. A brand that stops delivering the benefits of a changing category will show declining preference and declining share. I don’t believe that a measure of emotion or attitude is the same as a measure of product performance. The NBD distribution of preference shares is the power behind Repeat Buying as explained by Ehrenberg.
Thanks John. Interesting points. I do understand the individual level reversion to the mean. As you suggest, the point I am making is that attitudinal survey measures can help you determine the underlying purchase propensity of an individual (which explains why attitudinal measures can predict who will “revert to the mean” and who won’t in the following period).
As such, these attitudes are more than just a post-rationalisation of the last couple of purchases, they are a measure of the predisposition for the next purchase (as well).
It is not that this underlying attitudinal predisposition moves quickly, always pre-empting short-term growth. In general it progresses very slowly over several purchase cycles (with attitude feeding purchase choice and usage feeding back to attitude). But it is a driver of purchase (not just a result of past purchase). We know this because different brands create very different levels of attitudinal commitment per purchase (meaning attitude doesn’t just result from purchase in a predictable way regardless of brand). Indeed we find that the brands that achieve higher attitudinal commitment per purchase grow faster in the long-term (and achieve a better market share growth return from salience growth).
Therefore over the long-term building this attitudinal predisposition should be a goal for the marketer. And that in turn means they need to understand what drives it for their brand, try to affect that and track success against that.
I agree that the most effective way to build it will often be through product benefits. But it is important to note that marketing plays a critical role in framing usage experience to highlight certain product benefits (which is how some brands achieve higher attitudinal equity per purchase than others). So, products don’t just drive perception of product benefits through a better product, they maximise it by highlighting their superiority in their marketing (to positively frame usage experience). (as an extreme example of this, think of all the private label brands with very high penetration, made in the same factory with the same ingredient as their branded competitors, but with far weaker scores on perceived product benefits and other attitudes).
All this by the way, should be hand in hand with building mental availability (not instead).
I’m aware that this comment board is not the best place for this discussion. In fact, my last post (which Byron chose not to put up, I guess it was a little vanilla), said I’d try to resist prolonging the debate. But I enjoyed your comment and couldn’t resist a lengthy reply. Hope that’s ok.
Reblogged this on PilipBlog and commented:
I’m as guilty as many marketers for taking certain key marketing assumptions as truisms, without doing the proper research to see if those strategic assumptions are based on data or mere belief.
One belief that I never accepted, however, was the old saw “it costs X times to acquire a customer as to retain one.” I knew from my years of experimentation as a continuity marketer that it wasn’t true. Acquisition was the entire key to growth.
This is a great post by Professor Byron Sharp, where he addresses criticisms of his fantastic textbook “Why Brands Grow.” And if you haven’t purchased the book yet and read it, please do so now.
Recently i read this book “The power of Habit”. it talks about an interesting framework – Cue, Routine. Reward and how habit gets formed. Brands which can get into habit loop will grow.
Does this framework fit into ‘increasing Mental and physical availability’ ?
If we make the brand distinct in consumers mind, how will it help in forming the habit loop ?
Will be helpful if you can give me some pointers to explore.
Availability encourages the habit to form and makes it easier for us to act on habits. Habit is just a word for the loyal behaviour.
Professor, Thanks for your reply. The book ‘Power of Habit’ discusses P&G case study on Febreze. It says that consumers become defensive when you try to market product that neutralizes odour of a consumer.
The P&G team supposedly changed their communication showing a different routine and reward and hence sales soared.
This particular action does not fit into “increasing Mental and physical availability” framework unless consumers started identifying the brand for refreshing scents instead of neutralizing odour.
Am I missing something in my understanding here ? Is the need gap of refreshing scents is greater than need gap of neutralizing odour and hence the Category entry point should be framed accordingly in the communication ? So the brand assets should be built towards refreshing scent and not towards neutralizing odour ?
It’s difficult to know, as these sorts of case studies are just stories, told after the event. They are not reliable evidence of anything.