What’s Not to “Like”? Can a Facebook Fan Base Give a Brand the Advertising Reach it Needs?

Our earned media research article has now been published in the Journal of Advertising Research:

What’s Not to “Like?” Can a Facebook Fan Base Give a Brand the Advertising Reach it Needs?
Karen Nelson-Field, Erica Riebe, and Byron Sharp

Journal of Advertising Research, 2012, June, Volume 52, No.2
A marketer with a Facebook Fan base has at least some ability to advertise to that audience. What quality of reach, however, does this sort of “earned media” deliver? The landmark discovery by Andrew Ehrenberg of the negative binomial distribution (NBD) implies that the most effective advertising requires media that reach across both heavy and light buyers of the brand. This article investigates the buying concentration of the Facebook Fan base of two different brands (both Fast Moving Consumer Goods (FMCG) categories) and compares it to the brands’ actual buying bases. The buyer base of each of
the brands is distributed in the typical NBD, whereas the Fan base delivered by Facebook is skewed in an opposite pattern—skewed toward the heaviest of the brands’ buyers— making the quality of Facebook’s reach appear rather unappealing.

Can you use facebook to stimulate your fans to talk about you?

Since the Advertising Age covered the Ehrenberg-Bass Institute’s analysis of facebook’s ‘talking about’ metric there has been a flurry of internet coverage.

The findings got reduced to a sound bite of “only 1% of facebook fans engage with brands”. Which could easily be misinterpreted. Dr Karen Nelson-Field’s result is actually that around 0.4% (ie less than one percent) of the fans of a brand actually interact with it on facebook in a typical wek.

The interaction is what facebook report as “Talking about’, and includes activity such as to like, comment on or share a Brand Page post (or other content on a page, like photos, videos or albums), post to a Page’s Wall, answer a posted question, liking or sharing a check-in deal, RSVP to an event, mention a Page in a post, phototag a Brand Page…all the activity that facebook measure.

Now 0.4% in a week doesn’t sound so bad. It sounds like it might cumulate to near 25% in a year, but this would be a heroic assumption. In these sorts of social phenomenon we usually see highly skewed distributions. There will be a small percent of fans who do most of the talking every week. So this probably cumulates to something much less than 10% in a year. Karen is investigating.

Even facebook’s own fans don’t talk much about facebook (on facebook)

One of the questions asked of Dr Karen Nelson-Field’s analysis of facebook fans engagement with their brands on facebook is whether the result is simply due to slack social marketing by the brands in question.

Given that Karen analysed the 200 brands with the most facebook fans it seems a bit of a stretch to say that these brands “don’t understand facebook”.

Some have speculated that brands that understand passionate loyalty probably do much better.  But Karen’s analysis included brands such as Old Spice, Harley-Davidson, Ferrari, and Tiffany & co.

Finally, Karen’s analysis included facebook’s own facebook fans.  In a typical week only 0.28% ‘talk about’ facebook on facebook.  Maybe facebook itself doesn’t care much about fan engagement, after all they are clever marketers.

The flawed Stengel Study of Business Growth

Here I describe the ‘Stengel Study of Business Growth’ using quotes from “Grow: How Ideals Power Growth and Profit at the World’s Greatest Companies” by Jim Stengel, published by Crown Business 2011. Along the way I point out the fatal flaws in the research design.

The ‘Stengel Study of Business Growth’ started in 2007 when Procter & Gamble’s CEO A.G. Lafley endorsed Jim’s idea to “commission a study to identify and learn from businesses that were growing even faster than we were, in whatever industry” (p. 24).

Initially the P&G team studied “the fastest growing brands over the previous five years” (p.24) identified in collaboration with market research agency Millward Brown Optimor using their BrandZ database. The team “assembled five-year financial trends on twenty-five businesses that had grown faster than P&G over that period. The teams then dug behind the numbers with additional research, including interviewing business executives, agency leaders, brand experts, and academics at Harvard, Duke and Columbia”. (p.25)

“We went in looking for superior financial growth, and only after that for whatever the top-ranked businesses were doing differently from the competition” (p26). Professor Philip Rosenzweig explains this classic sampling mistake as being like trying to learn about blood pressure by only looking at a small group of patients who all have high blood pressure.

Another very important mistake, that we have learnt about as various strategy researchers have made it over the years, is to look for causes of success by interviewing managers and ‘experts’ for their opinions on firms that have been doing well. Known as “the Halo effect” people tend to say that firms they know are performing well possess all sorts of desirable characteristics in terms of culture, leadership, values and more. No one describes a known winner as having “unfocused strategy”, or “weak leadership”, or “lack of customer focus”, or “lack of ideals”, or whatever the researchers choose to decide to ask opinions about. As Philip Rosensweig shows clearly in his book “many things we commonly claim drive business performance are simply attributions based on past performance”.

“Successful companies will almost always be described in terms of clear strategy, good organization strong corporate culture, and customer focus” (p.87). Rosenzweig dramatically shows how when successful companies falter experts abruptly change their assessment. Suddenly the previously described “strong culture” is now described as “rigid”, their previously declared “promising new initiatives” are now described as “straying”, their “careful planning” now in hindsight turns out to be “slow bureaucracy” and so on. In reality large businesses change very slowly, but opinions about them change quickly and are largely based on current financial performance (which is itself is largely due to environmental and competitor effects).

The Halo Effect is particularly strong for subjective, nebulous concepts such as ‘values’ and ‘ideals’. The ‘Stengel Study’ made no attempt to supplement their judgements with ‘hard’ objective measures.

In the Stengel study they ‘discovered’ that their chosen high-growth firms were ‘ideal driven’. The central finding therefore was that “businesses driven by a higher ideal, a higher purpose, outperform their competition by a wide margin”. Yet there is no mention of any systematic investigation of competitors, perhaps many of these lesser performers were also ‘ideal driven’? What we can expect is that because of the Halo Effect less successful performers would be less likely to have been described by interviewees as having a clear ideals well activated throughout the business – irrespective of reality.

Subjective concepts such as ‘ideals’ almost certainly introduce confirmation bias on the part of researchers – when there are no objective measures it’s near impossible for a researcher to stop themselves seeing what they want to see. The “unexpected discovery” of the causal effect of ideals, says Jim Stengel “corroborated what I had implicitly believed and acted upon throughout my career”. Hmm, of course it did.

With this ‘ideals’ hypothesis now firmly in place the full ‘Stengel Study’ was then done after Jim Stengel left P&G by selecting 50 brands based on their excellent recent financial performance over 10 years. As a whole this group (refered to as “The Stengel 50”) “grew three times faster over the 2000s than their competitors…individually some of the fastest-growing of the Stengal 50, such as Apple and Google, grew as much as ten times faster than their competition from 2001 to 2011.”

Promotional material for Stengel’s book says that “over the 2000s an investment in these companies—“The Stengel 50”—would have been 400 percent more profitable than an investment in the S&P 500”. The implication is that this proves Stengel’s ‘ideals’ thesis – but Stengel picked these companies for their financial growth!

If they have been picked purely based on some, ideally ‘hard’ (or intersubjectively certifiable), measure of being ‘ideals driven’ then correlations with financial performance might mean something. Especially if this were future, not past, performance. But as these companies were picked for their financial performance then their stock price performance over the same period shows nothing.

A team of four second-year MBA students being taught by Jim Stengel and Professor Sanjay Sood made the Stengal Study the subject of their required applied management research thesis; “this team crawled all over the Stengal 50 to test the role of ideals” conducting interviews with executives, academics and consultants”. No one should be surprised that they found what their instructors believed. They and the ‘Stengal Study’ both passed with flying colors reports Jim Stengel (page 34).

There is one addition to the Stengel Study which is different from previous similar (flawed) studies of business success. Stengel arranged his leading brands into “five fields of fundamental human values that improve people’s lives” by (1) eliciting joy, (2) enabling connection, (3) inspiring exploration, (4) evoking pride, or (5) impacting society (sic). Millward Brown then used implicit and explicit association measures and found that the Stengel 50 brands are perceived as more associated with their selected ideals than competitors.

Again this is a staggering piece of circular logic. First analyse a select group of brands for what particular ideals they represent, then take these ideals into market research and viola these brands turn out to be more associated with these particular ideals. This is not a test that these ideals drive performance, it is simply a test of the researchers’ judgement of brand image. It merely shows that the researchers live in the same culture as the market research respondents. Jim Stengel thinks Backberry ‘enables connection’ and so does the market, Jim Stengel thinks Mercedes Benz ‘evokes pride’ and so do normal people.

Now one might reasonably argue that there is advantage in FedEx and Blackberry being more associated with a category benefit such as “enables connection” than their competitors. However, leading brands always show higher associations because they have more users, who use them more often. Behaviour has a powerful effect on attitudes and memory, for evidence see BIRD, M. & EHRENBERG, A. 1972 “Consumer Attitudes and Brand Usage – Some Confirmations”. Journal of the Market Research Society, 14, 57. RIQUIER, C. & SHARP, B. 1997 “Image Measurement and the Problem of Usage Bias” in proceedings of 26th European Marketing Academy Conference, Warwick Business School, U.K., 1067-1083. ROMANIUK, J. & SHARP, B. 2000 “Using Known Patterns in Image Data to Determine Brand Positioning”, International Journal of Market Research, 42, 219-230.

There is no mention of controlling for this effect.


In summary, the ‘Stengel Study’ makes the same or similar mistakes as much earlier flawed studies that claimed to uncover the secret of sustained financial success. Jim Stengel, and none of his team appear to have read Philip Rosenzweig’s “The Halo Effect: … and the Eight Other Business Delusions That Deceive Managers” which turns out to be a great pity. As he writes “if the data aren’t of good quality, it doesn’t matter how much we have gathered or how sophisticated our research methods appear to be”. The Stengel Study is yet another study that is deeply flawed, it tries to look like science, but turns out to be merely a story, one that will appeal to many but tells us nothing reliable (or new) about the world.

A final note: Based on the track record of previous such studies I expect the financial performance of these ‘ideals driven’ companies to fall back in the near future. Some such as Blackberry, HP have already suffered very dramatic reversals of fortune.

Review of Jim Stengel’s disappointing book “Grow”

Research reveals the hidden secret to business success? No, sadly this is pseudoscience – that will only convince the most gullible of minds.

Jim Stengel seems a nice guy, he wants us to be passionate about our business and to feel that there is a greater purpose than simply making money.  Few would disagree.  But he also claims to have discovered the secret to sustained super profits – based on a flawed study dressed up as science.

Stengel is a marketing consultant, a famous one because he was formerly Chief Marketing Officer of Procter & Gamble 2001-08 until he surprisingly ‘retired’ to consult (and write this book). During the decade that Jim mostly presided over marketing at P&G the company was pretty successful, at least in comparison to the 3 year period immediately before he became CMO of unsuccessful restructuring and CEO turnover. However the success of the 2000s has been exaggerated; the reality is that during Jim’s decade P&G’s stock price doubled, though that is a misleading overstatement due to the brief dramatic dip in 2000 (the reasons why are discussed here). Without that dip the year before Jim took over as CMO the stock price only improved 20% over the full decade. That’s less impressive than the previous decade (90s) when stock price had increased 5-fold (or 3 fold when the brief dip of 2000 is considered), similar gains were also made in the prior decade (80s). So P&G’s performance during Jim’s tenure should perhaps more accurately described as a mild turnaround, or partial restoration. This chart shows the full history of the stock price.

In all fairness though, Jim Stengel doesn’t ask us to believe his amazing discovery just because he was (like millions of others) a successful practitioner, his claims are based on what he calls an unprecedented 10-year empirical study of highly successful firms and the brands they own. But his study does have precedent, it joins a growing list of books that claim to have discovered a few simple rules for business that near guarantee profit performance that will beat all rivals. Each of these books are based on severely flawed research that ‘proves’ just what the author wanted to say in the first place (which is the opposite of a surprising discovery). “In Search of Excellence” was one of the first of these books, which was largely discredited when the excellent companies went on to make poor financial returns in the years after the book came out.

Professor Phil Rosenzweig exposes these flaws in his 2007 book “The Halo Effect: … and the Eight Other Business Delusions That Deceive Managers“.

I describe and critique “The Stengel Study”, which is the basis of Stengel’s book, here. A quick summary is that to detect factors that might cause financial success then Stengel should at least compared very carefully matched samples of both successful and unsuccessful firms, and developed hard objective measures of strategy – not relied almost entirely on interviews with experts. Also, to avoid confirmation bias, the researchers who described the firms and their strategies should not have been aware of which were the successful and unsuccessful ones. And finally, any resulting theories should be tested against the future performance of the firms. Otherwise what looks like science turns out to be simply a story.

Tellingly the ‘research’ takes up small portion of Stengel’s book, the rest is a story: anecdote and assertion. Jim tells us what to do, but experienced marketers looking for strategic advice won’t find much new or particularly helpful. It’s pretty much the standard sort of consultant fare such as “deliver a near-ideal customer experience”.

It’s well meaning though, Stengel wants us to all be passionate about our business and to feel that there is a greater purpose than simply making money (even if finding out how to make money was the motivation of his ‘research’).  This is a nice sentiment, however, the success of brands (and the large corporations behind them) is far more complex than Stengel’s book and its predecessors claim.

Zero Moment of Truth – Hype, Nonsense, and PseudoScience

Shock, how amazing – new ‘research’ from Google shows that advertisers should be spending far more of their advertising dollars online with Google.

In a report that insults the intelligence of the marketing community Google tell us that consumers are doing more on-line product research than they did in the past (when they weren’t online). Unless you have been in a coma for the past decade you didn’t need Google to tell you that. But some quantitative insight would be useful – how much are consumers using on-line sources of product information, and what sources? Unfortunately Google’s research and data presentation is so shoddy we can gleam nothing reliable.

They did an online survey (ie biased towards heavier online users) of various subsamples (eg 500 people who had bought an automobile, another 250 who had applied for a new credit card in the past 6 months, and so on).

All the data concerns claimed (recalled) behaviour and the sub-sample results are then often averaged into meaningless metrics.

The report highlights stupid meaningless quotes like “70% of Americans say they look at product reviews before making a purchase”. Is this every purchase ? Or 70% have a least once in their lives looked at a product review ? Actually this quote is sourced from an equally sloppy 2009 study but not by Google – why they chose it when they have their own “new research” puzzles me.

I could spend all day pointing out how meaningless the metrics are in the Google report, but I don’t think there is any need. Only extremely gulliable marketers would rely on such a sloppy blatent piece of self-promotion disguised as research.

In May, Professor Jerry Wind and I are hosting a conference at Wharton. If Google had some meaningful, reliable data on the value of online touchpoints we would be delighted to invite them to present.

More choices increase sales

Early this year I attended an excellent, thought-provoking presentation by the very lovely Professor Sheena Iyengar from Columbia Business School  on her (small-scale) choice experiments.  The results seemed to suggest that consumers could easily experience choice overload.  And the implication for marketers was to beware of offering lots of choices because this can actually depress sales.

It was this last implication that worried me because (a) it seemed to clash with the real-world evidence, and (b) there are good logical reasons why different consumers on different days might notice/want different things, so more choice should satisfy more people.

I asked Prof Jordan Louviere, director of the Centre for the Study of Choice, and one of the world’s top authorities.  He replied bluntly “it’s worthless. These guys do not understand how to run experiments properly and/or how to properly analyse data, so they draw totally inappropriate conclusions about their results.”

Supporting Jordan’s assessment is that replications of Sheena’s experiments by other researchers have failed.

Now the Journal of Consumer Research has published a meta-analysis of 50 different choice-overload experiments (including Sheena Iyengar’s) across categories and countries.  The results show more choice options led to more (not less) consumption, there is no generalised choice-overload effect, and no conditions could identify why different studies get different effects.


No doubt consumers can find choices bewildering at times.  Marketers need to help them out e.g. by giving them signposts.

But the conclusion that offering more choice can easily decrease sales is an incorrect message.  More choices increases sales.

Can There Ever Be Too Many Options? A Meta‐Analytic Review of Choice Overload
Author(s): Benjamin Scheibehenne, Rainer Greifeneder, Peter M. Todd
Journal of Consumer Research, Vol. 37, No. 3 (October 2010), pp. 409-425

You are charging too much

Why is it that marketing theorists tend to blame a brand’s demise on “loss of differentiation” or some such thing when they shoud be saying “it’s too expensive, it’s no longer competitive” ?  (which incidentally means the brand is becoming more not less differentiated).

Why is charging too much seen as a indicator of marketing strength, not weakness or stupidity ?

It annoys me how people keep citing Apple as a company that charges price premiums.  They don’t.  Anyone really familiar with the industry knows of the comparison feature-by-feature breakdowns that show macs are priced competitively they just don’t compete in bargain basement minimal feature area.  Notice how iPad competitors are struggling to even match the iPads pricing.

Back in 2008 Steve Jobs said this during an interview with financial analysts:

Toni Sacconaghi – Sanford Bernstein:

“And then you had also mentioned the price umbrella statement and you said look, certainly to be successful on iPhone, we don’t want to create a price umbrella. I think in response to another question, you also talked about extraordinary feature functionality in terms of your Mac products. Do you have the same philosophy around Mac as you do with iPhone, that you have to be careful not to create an umbrella in each? So I guess the simple question is should we continue to see more affordable price points across the Mac product family and across iPhone going forward?”

Steven P. Jobs:

“Well, I think what we want to do is deliver a lot, an increasing level of value to these customers. There are some customers which we choose not to serve. We don’t know how to make a $500 computer that’s not a piece of junk, and our DNA will not let us ship that. But we can continue to deliver greater and greater value to those customers that we choose to serve and there’s a lot of them. And we’ve seen great success by focusing on certain segments of the market and not trying to be everything to everybody. So I think you can expect us to stick with that winning strategy and continuing to try to add more and more value to those products in those customer bases we choose to serve. Does that make sense to you?”

Share of wallet isn’t enough

In a recent Harvard Business Review article TIm Keiningham et al (Oct 2011) argue that managers should pay attention to “share of wallet”. To grow brands should aim to improve their share of wallet rank.

To do this you obviously have to get customers who currently give you a very small share of their purchasing to give you a greater share – it’s logically impossible to get much more share out of customers who already give you near 100%.

So Tim Keiningham et al have discovered the importance of light customers. Great.

Unfortunately, in their article they then make an unsupported assertion that the way to improve a brand’s share of wallet metric (and hence market share) is to survey customers on their motivations for buying each brand and then whatever it is that they like about a competitor should be improved in your brand. This ignores the very weak link between claimed motivations and behaviour. But is an unsurprising recommendation from someone who works for a market research agency.

Like Reichheld and Sasser (see retention profit myth) they also imply that improving loyalty metrics is easy – just ask people what they are looking for, provide it, and then your share of wallet metric will jump.

They provide (only) a hypothetical example of a supermarket. So let’s look at real data on supermarket loyalty. This is Kantar Worldpanel data (2006) on UK supermarkets (a very vibrant and competitive grocery market), market share is in the left column, penetration next, and share of purchases in the right:



Like all loyalty metrics, share of purchases rises with penetration and market share, in accordance with the Double Jeopardy law. As expected, there is much greater variation in penetration than in the loyalty metric.

In the HBR article’s fictional example the supermarket achieves a 7 percentage point gain in share of wallet (at some unknown cost), the implication is that this is an easy task. But this would be equivalent of Sainsbury’s doubling its market share – that’s a Herculean task!  And, very importantly, Double Jeopardy shows us that Sainsbury can’t do this without also increasing its penetration from an annual 64% to something nearer 80% – in other words it has to gain more customers.

That means the supermarket has to increase its reach (in space or time), e.g. more stores, longer hours.  This vital message is missing from the HBR article.

Professor Byron Sharp

Oct 2011

Correlations are a poor way of assessing predictive ability

Firstly, I’d like to blow away the myth that correlations above 0.5 are spectacular in the social sciences. On pages 32 and 33 of my book “How Brands Grow” I present some car repeat loyalty metrics and market shares for the USA, UK and France. A quick calculation shows a higher than 0.6 correlation between repeat rates and market share. These sorts of correlations between brand performance metrics are the norm.

Secondly I want to highight the misleading claims of consultants peddling special brand health metrics who often claim correlations of say 0.7 between their special score for brands in a category and their sales – they say how amazing this is, and how it is proof of predictive ability.  Well here are my attempts to predict tomorrow’s temperature in Adelaide Australia, each prediction and reading is taken about a month apart starting in Summer and ending in Winter. I get it right that the temperatures go down as Winter arrives (big deal, it’s a bit like predicting that growing brands will increase sales a bit next period) but otherwise my predictions are miserable, they are always wrong, sometimes too high, mostly too low. The correlation however is very near perfect, 0.99 to be precise.

Actual temperature (Celsius) is in the left column, and my hopeless predictions in the right column:

39   43
32   36
24   22
21   18
17   15

r = 0.99

The moral of the story is that correlation is not a good indicator of predictive ability.


Professor Byron Sharp

Satisfaction drives Apple’s growth – or not ?

Apple has again topped the American Customer Satisfaction Index for personal computers (the product and service). Famous satisfaction researcher, Professor Fornell, gushes:

“In the eight years that Apple has led the PC industry in customer satisfaction, its stock price has increased by 2,300%,” remarks Claes Fornell, founder of the ACSI and author of The Satisfied Customer: Winners and Losers in the Battle for Buyer Preference. “Apple’s winning combination of innovation and product diversification—including spinning off technologies into entirely new directions—has kept the company consistently at the leading edge.”

But wait a minute… is he implying that satisfaction with Apple computers is driving this financial performance? I’m sure that many would read it like that. But this is only satisfaction with Apple computers, while Apple’s stellar gains in revenue, profits and market capitalization in recent years have almost entirely come from the iPod, iTunes, iPhone and now iPad. Their computer sales have done well, but they are a shrinking part of their revenue and profits.

What is the story on Apple’s PC satisfaction scores ? Well they have always been good, which isn’t surprising given that they steer clear of offering really low quality, low featured, low price models. Even back in the mid to late 90s when Apple sales were dropping and profits evaporated Apple held its position as number 2 on satisfaction behind Dell. Just as Dell has continued to hold onto a satisfaction score of 77 for the past decade in spite of ups and downs in its fortunes.

Apple’s resurgence begain in 1997 with the return of Steve Jobs. Within a year they posted an astonishing profit turnaround (from losses to profits) and launched the iMac. Satisfaction nudged up in 1999 but was still below their norm for the mid-90s. And it kept on nudging up, which probably reflects that their computers and computer service have been getting better. It may also reflect a halo effect from the iPod, iPhone, iPad, iTunes – that’s a problem with satisfaction scores, they are influenced by other things (like the weather).

But let’s be clear, this rise in satisfaction for Apple computers did not cause Apple’s 2300% rise in share price. Maybe it helped a tiny bit but the heavy lifting was done by sales of other products.

US brands are not losing their loyal customers – even more misleading metrics

Oops they did it again. Catalina Marketing have announced that packaged goods brands in the US have lost about half of their loyalty customers – AGAIN. Oh no how horrific. It’s a wonder they have any customers left. It’s a wonder that major brands aren’t tumbling out of the market. Sell your shares in Kraft, P&G, Unilever, Coke….

Of course it is complete nonsense. There is nothing wrong with the data, just faulty analysis.

This is the 2nd time Catalina Marketing have made this mistake. They are misinterpreting the natural wobble in people’s purchasing histories as real change in their loyalties.

Marketing scientists have know about this wobble for decades, it can actually be quantified using the NBD-Dirichlet. But Catalina in ignorance instead report that brands have lost nearly half their loyal customers. Oh no the sky is falling!!! Nice headline but it is wrong, plain wrong.

A few years ago when they reported this they said it was an unusual event, due to the GFC. Now having noticed it happens each year they say it is just a terrible indictment on marketing.

All of this is wrong, because this would still happen even in perfectly stationary conditions where no brands are growing or declining, and no consumers are changing their propensity to buy the category nor their loyalties to the particular brands in the category.

Let me explain. Each of us has a tendency to buy from the category, some of us are heavy category buyers and most of us are light. On top of this we each have our own particular loyalties so we buy some brands more often than others. These two mixed distributions mean that there is a lot of diversity between consumers of any product category. Diversity which is modelled extremely well by the Dirichlet.

On top of this we don’t buy like robots. I might have a tendency to buy chocolate bars 5 times a year, and have loyalties so that I buy Snickers 30% of the time, so that’s once or twice a year. But some years I’ll buy chocolate bars more than 5 times a year, and some years less – for thousands of random potential reasons. Plus some years I’ll give Snickers more than 30% of my purchasing and some years less.

So even if I don’t make any changes to my tastes, habits and loyalties I could buy zero Snickers in a year or 5+.

If we classify people into “loyals” or “heavies”, or whatever, based on what they do in one year then a lot of people are going to be misclassified. They aren’t really super-loyals it’s just that in that year they were – perhaps they had a party, some friends visited…a thousand potential reasons. Next year they are likely to revert to closer to their normal purchasing. It looks like they have changed when they haven’t. This is behind the phenomenon statisticians call regression to the mean. Catalina Marketing don’t seem to have learnt their basic statistics.

Catalina categorised someone as loyal if they gave 70% of their purchasing to the brand. If they didn’t in the next year they said they were lost. This means it is largely an analysis of lighter category buyers, as heavier buyers are less likely to give one brand such weight. So it’s people who bought the brand once out of one category purchase, 2 out of 2, 3 out of 3, or 3 out of 4, or 4 out of 5. So buying the brand just once less, or buying the category just once more means you get classed as lost, defected, no longer loyal. That’s why they get such a high figures as 50% being ‘lost’.

So It’s all an illusion. I explained this back in 2009. Sad that I have to say it again. I’ll repeat what I said then: Catalina Marketing sell targeted marketing services based on using this loyalty program data – which is a bit odd because this fluctuation seriously undermines the capacity to target consumers based on their past buying.


Professor of Marketing Science

Director, Ehrenberg-Bass Institute

University of South Australia

See the official website for the book “How Brands Grow”

Memories affect noticing – of brands and advertising

Our common-sense model of memory, particularly long-term memory, is that it’s like a reference book or a hard-drive – something that we have to go and consult. We go in order to (try to) retrieve something from memory, a bit like going to the library to borrow a book.

But our memories are being used every second, on the fly, in real time. Your ability to read these words depends on this. When you were very young words looked like boring bits of black scribble (and you noticed the pictures instead), as a child you worked hard to get these letters and then words into your head, now they are there and they can be accessed in a micro-second. You can’t help yourself noticing words, you can’t stop it even if you try, but if you want to notice the font shape, or the ink or the pixels then you have to try so much harder. Some things are incredibly easy to notice, others aren’t.

When someone looks at a shelf of brands, or down a street at a range of different shops, they don’t notice half (or more) of what’s there. Some things are so hard to notice, not because they don’t stand out, but because the viewer doesn’t have the necessary memory structures in their head.

One person sees two trees, the other sees an oak and and elm.

When marketers think about noticing they think of things they can do to try to grab attention. Which is fine. But for many this means bright colours, stunts, something NEW, price discounts and so on. Now there is nothing wrong with trying to grab attention with such devices but we have to also remember that noticing depends on memories. If you want your brand to be noticed then you need to build and refresh consistent brand memory structures. Changing a logo is more likely to get you noticed in the marketing press than on shelf.

It’s the same for advertising. Most ads aren’t noticed, or not noticed sufficiently for them to build or refresh brand memories. You need a clever advertising agency to create content that is attractive, that gains some attention, but if you are only relying on the creativity to drive noticing you will fail – people have to notice your brand not just the creative content of the advertisement. To do that you have to work with what’s already inside their heads. Which means undertaking careful research to document existing memory structures, to understand your brand’s distinctive assets.

Laws of Marketing – to find them we have to look

How Brand Grow” presents almost a dozen scientific laws relating to marketing and buying behaviour. Not laws like the Ries and Trout “thou shalt” laws based on anecdotes, but law-like regularities, relationships that keep on occurring in a wide range of conditions. So we can make predictions based on these laws. In science such laws are the building block of knowledge.

Marketing academia has for too long failed to look for laws, and ignored those that have been discovered. Professor Shelby Hunt, marketing’s most famous student of philosophy of science was a big advocate for laws, yet, to my knowledge he didn’t practice what he preached.

Marketing is awash with ‘theory’ based on speculation or reading non-empirical literature. Theory not based on any empirical laws, much of it in direct ignorance of existing laws, and some in direct conflict with such laws.

Academia should be helping sort this all out, but we (and many other social sciences) are gripped by the model of doing research which says “do some weak theorising largely based on other theoretical literature (not empirical laws) and then conduct a weak empirical test – one that does not rule out many other potential explanations”.

And empirical work in marketing tends to be highly specific. In effect the data sets are tiny slices of the empirical phenomena of interest – one questionnaire, one country, one time.

It’s time we dropped this narrow, and wimpy, model of how to do research.

Professor Byron Sharp.

Purple Cow – where’s the beef ?

There is a small, nay large, industry that makes claims like:

“consumer behaviour has changed radically”
“marketing doesn’t work anymore”

And yet then presents nothing more than a repackaging of the orthodoxy.

For example, Seth Godin’s “Purple Cow” says that marketing is “broken”, that advertising could once turn a sow’s ear into a silk purse but has lost its effectiveness due to clutter and ad avoidance. This is spite of research that shows advertising continues to perform as well as ever (1) (2) (3).

So says Seth, companies need to adopt his radical new marketing strategy which is…wait for it…. to produce remarkable products and market them in remarkable ways. Wow. I don’t remember my old Uni textbooks saying anything like this, they only used words like “great” not “remarkable”. What a step forward in thinking.

Seth’s a great story teller, his books are entertaining. But it is a sad reflection on our discipline that these best sellers are so shallow.

Professor Byron Sharp. July 2011

(1) Jamhouri, O., & Winiarz, M. (2009) “The enduring influence of TV advertising and communications clout patterns in the global marketplace”, Journal of Advertising Research, 49(2), 227-235.

(2) Rubinson, J. (2009) “Empirical evidence of TV advertising effectiveness”, Journal of Advertising Research, 49(2), 220-226.

(3) Hammer, P., Riebe, E., & Kennedy, R. (2009) “How clutter affects advertising effectiveness”, Journal of Advertising Research, 49(2), 159-163.

Footnote – Above I argue that Godin’s contribution to marketing theory is to merely replace words like “good” or “great” for “remarkable” so I had to laugh when I read this note in my dictionary about the word “remarkable”:

Properly, remarkable should not be used as a synonym for good. It is value-neutral and means only “worth being remarked upon.” Actually, what’s really remarkable is how many words, like this one, have lost their specific meanings as they’ve been corralled into the sterile confinement pen of synonyms for good, notably fabulous (literally, like something in a fable), fantastic (like something in a fantasy), wonderful (fills you with wonder), incredible (not to be believed). You help restore the richness of the language when you use these words in ways closer to their original meanings.
— DA