US Brands lost half their customers last year – more misleading metrics

Yesterday, Ad Age reported a study showing that US packaged goods brands typically lost more than half of their loyal users last year.  Oh no!  The sky is falling…next year we’ll have no loyal customers left at all!

“I think what’s surprising is the magnitude of some of the effects,” said Eric Anderson, associate professor of marketing at the Kellogg School of Management at Northwestern, who reviewed the study.

Hmm yes surprising.  Let’s put our brains into gear here, are we to accept that all these brands, which are essentially stable in market-share, lost half of their most loyal customers? There may be a recession on but this is still nonsense.

The truth is that the analysts misunderstood their own results, because of ignorance of the law-like patterns in brand buying.

The brands haven’t lost most of their loyal customers, the results are simply due to normal random fluctuations in buying, i.e. sampling (in time) variation – something any analyst should be aware of.  Nothing real or unusual is going on here.

Read on if you’d like to know why…


The marketing consultants who did the study used their loyalty program ‘panel’ data.  They classified a consumer as a ‘brand loyalist’ if the brand represented 70% or more of their 2007 repertoire.  If that consumer did not also devote 70%+ of their category buying to that brand in 2008 they  classed them as lost (typically about one third were ‘lost’ completely, while the other 20% still bought the brand but it wasn’t 70% of their repertoire in 2008).

But from one time period to another the brand’s weight in a consumer’s repertoire fluctuates.  And this normal fluctuation is what this study mistook for customer defection.  These loyals aren’t gone, they’ll be back again next year or the next.

Effectively their analysis excluded most heavy category buyers because these households will have larger repertoires, and so it’s much more difficult for one brand to represent 70% of their buying.  Most buyers are light category buyers and these light buyers are more likely to appear 70%+ loyal.  In other words their analysis largely is a report on lots of buyers who bought the brand once out of 1 category purchase, or twice out of 2, or three out of 4 – purchases in the loyalty program stores.

Now, all buyers are subject to random fluctuations in their on-going, steady, purchase patterns.  Sometimes you buy 3 times a year, sometimes 4.  Even if you buy two brands equally it’s seldom ABAB, it’s patterns like ABBABBBAABABAAB.  This stochastic variation is normal and follows predictable patterns.  This variation means that lots of people who were classed as “loyals” in 2007 fall out of this classification in 2008 – when nothing real has changed in their buying behaviour, and nothing has happened to the brand’s market share.


PS The study was by Catalina Marketing and the CMO Council.  The CMO Council should have known better.  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 loyalty level.

PPS I’ll leave the last word on the Ad Age article to Professor Gerald Goodhardt (co-discoverer of the Dirichlet model):

“After ‘Some brands lost more than a third…… while others held on to more than 60%……’ I stopped reading!”


Net Promoter Score (NPS) Does Not Predict Growth – it’s fake science

“Managers have adopted the Net Promoter Score on the basis that solid science underpins the technique and that it is superior to other metrics.

We find no support that for the claim that Net Promoter is the “single most reliable indicator of a company’s ability to grow.”

The above quote is from a Journal of Marketing article and winner of the Marketing Science Institute /H.Paul Root Award “A Longitudinal Examination of Net Promoter and Firm Revenue Growth”, Journal of Marketing (2007), Vol.71, by Tim Keiningham et al.

The Net Promoter Score was developed by Frederick Reichheld a consultant now well known for making headline grabbing conclusions based on sloppy research and thinking.

I previously pointed out what was wrong with his claim that small reductions in customer defection cause massive profit increases.

Then in 2004 he is said to have had an epiphany describing his prevous work on loyalty as “powerful but useless”. Keeping customers didn’t matter so much, having customers who would recommend you was everything.

So the latest myth he peddles is that asking customers their likelihood of recommending the company predicts company growth. He claims it does so much better than traditional metrics such as customer satisfaction.

Actually, if you read Reichheld’s Harvard Business Review article carefully you can see he employs the same sort of sleight of hand he did in his customer defection work. Pay careful attention to the dates, Reichheld in 2003 writes that starting in the first quarter of 2001 consultancy firm Satmetrix began collecting customer likelihood-to-recommend responses via email survey. Each quarter collected 10-15,000 responses gradually building a small dataset covering 400 companies in a dozen industries. Reichheld then calculated a Net Promoter score for each company and compared this to the company’s growth rate over 3 years (1999 to 2002). Yes, that’s the previous 3 years.

Yes, so the correlation he reports says that firms that score higher now have previously been growing.

Reicheld admits on his website that the statistical analysis in his book was sloppy but says that since then the consultany company he worked for (Bain & co) has done more extensive analysis showing no correlations between satisfaction scores and company growth, but excellent correlation for the NPS. However, Keiningham et al’s Journal of Marketing article perfectly repeated Reicheld’s analysis and they found the same or better correlation between old-fashion satisfaction and growth (hence the quote above).

Such correlations say little about causality (especially when they are backwards in time), as Reichheld tries to use in his defence, but then why on earth did he select these cases to ‘prove’ his case ? He even admitted he’d selected amongst the very best examples!

In sum, this is snake oil, fake science. It’s scary how many CEOs fell for this.  But then lots of people fell for the (completely wrong) zero defection idea too.

Loyalty Program Misleading Effects

The Journal of Marketing last year (2007) published an article titled “The Long-Term Impact of Loyalty Programs on Consumer Purchase Behavior and Loyalty” by Yuping Liu. It purports to show the impact of a loyalty program on the buying rates and loyalty of those who join the program. The key finding is that very large changes are observed for the lighter and moderate buyers in the loyalty program while the heaviest buyers exhibited no change.

However, this finding, and the consequently very large sales effects that the program seemed to generate, are actually artifacts of the analysis method. Continue reading

The loyalty patterns of repertoire and subscription markets

In 2002 I published with Malcolm Wright and Gerald Goodhardt on an empirical discovery. Repeat-purchase markets are polarized into those that show repertoire patterns and those that show subscription patterns of loyalty. With no markets showing ‘in between’ patterns.

We also found that the Dirichlet model of repeat-purchase fitted both sorts of markets, predicting brands’ loyalty metrics rather well. This was a surprise. It highlights what an achievement this scientific theory is.

Here is the paper for download.

Sharp, Byron, Malcolm Wright, and Gerald Goodhardt (2002), “Purchase loyalty is polarised into either repertoire or subscription patterns” Australasian Marketing Journal, 10 (3), 7-20.

There is also a related test of the boundaries of repertoire markets:

Sharp, Byron (2007) “Loyalty Limits for Repertoire Markets”, Journal of Empirical Generalisations in Marketing Science, Vol. 11.

Snake (oil) and loyalty ladders

Many market research houses now market a “loyalty ladder” or “loyalty pyramid” product. These dissect a brand’s customer base into 4-6 groups, starting with something like “no awareness” at the bottom and ending with something like “passionate loyals” at the top. This classification is usually based on behaviour (or claimed behaviour) such as share of category purchases devoted to the brand in question. Some add attitudinal statements into the customer classification. Others, like The Conversion Model, claim to be entirely attitidudinal.

All these do is reflect Continue reading

Do Loyalty Programs Increase Brand Loyalty ?

Do loyalty programs really affect consumer loyalty ? What effect do loyalty programs have ?

Back in 1997 Anne Sharp and I published the first empirical evaluation of a large scale loyalty program:

Sharp, Byron; Sharp, Anne (1997) “Loyalty Programs and their Impact on Repeat-purchase Loyalty Patterns”, International Journal of Research in Marketing, Vol 14, No. 5, p.473-486.

By using Dirichlet benchmarks we were able to assess the loyalty program’s affect on repeat-buying while avoiding the problem of self-selection (i.e. more loyal buyers of the brand are more likely to join the program). We documented weak effects.

Since this study we, and others have done more work. All using real world panel (i.e. individuals repeat buying) data. This evidence will be brought together in a forthcoming report, and possibly a chapter in my forthcoming book “Laws of Growth”.

More misguided loyalty programs

In a previous post I commented on Coles Myer’s misguided new loyalty program.

Now I read that they have hired Tom Lemke a former Kmart US executive in charge of loyalty programs. One hopes he will bring new knowledge to the company, but I doubt it. More likely he will consolidate blind faith in loyalty initiatives.

And today I read that they are testing a new program that asks shoppers to register and fill in a questionnaire on what brands they buy. They are then sent a shopping list which switches them to other brands – if they stick to this list they get large discounts in the form of loyalty points (that can later be converted to cash).

Good to see experimentation, but they would be better off first putting money into fundamental research into marketing. This program is doomed to be insignificant at best, and most probably a waste of money.

A 5% drop in defection does not lead to 80%+ more profits

Some of the most popular modern marketing myths come from the writing of Frederick Reichheld. In particular a famous article with Earl Sasser where, on the very first page they write:

Companies can boost profits by almost 100% by retaining just 5% more of their customers.

This has been quoted extensively. Even academics, who should know better, quote it in textbooks and in articles in leading scholarly journals.

And yet it is a grossly (and rather obviously) misleading line.

To read the full article go to the University site – click here.

Misguided Myer Marketing

Two major Australian newspapers ‘The Australian” and ‘The Age’ have reported that the department store chain Myer is to launch another loyalty card, they already have Fly Buys and a credit card.

Called ‘Myer One’ this loyalty program is to be aimed at Myer’s high value customers. According to chief executive Dawn Robertson “Myer One is for our most loyal customers”.

This is so fashionable, and so misguided.

Given the things Ms Robertson has said, this marketing initiative appears to have been planned in ignorance of the serious R&D into the effects of retail loyalty programs, not to mention fundamental patterns of buyer behaviour and brand performance.

And the logic is faulty.

Think about which customers a loyalty program might attract, and who are desirable to attract (from the perspective of making money):

1) Occasional buyers of the category – these customers are unlikely to be attracted to a loyalty program (they realise they won’t earn many points), indeed they aren’t even likely to hear about it let alone give it much thought.

2) Frequent buyers of the category but occasional Myer shoppers – these would be very attractive to gain, and they might be attracted to the program, after all they could earn a lot of points if they shift their buying towards Myer. Unfortunately all of our research shows that loyalty programs do very little to attract non and light customers of the loyalty program brand.

3) Frequent Myer buyers – these are the customers that Myer One is targeting. But these are the least desirable group. These customers represent the greatest subsidy cost of a loyalty program, ie giving people rewards for doing what they were doing anyway. They are of course the most likely group to join – they will see the program’s promotional activity (remember they shop at Myer regularly) AND they will realise what a good deal it is…something for nothing !

In short the Myer One will probably be a good deal for a few customers, and a poor marketing investment.

And it won’t lead to growth, real growth comes from winning more customers…and that’s mainly occasional customers. No brand ever got big by simply trying to get more out of its most loyal customers.