Below is an extract from How Brands Grow. It explains how loyalty metrics do NOT reflect the marketing strategy or image of the brand. Instead loyalty is perfectly able to be predicted from the market share of a brand in a category. So rival brands with similar market shares have similar loyalty metrics, irrespective of their history, brand images etc.

It’s unfortunately common for people, even senior academics, to say that there are no absolutes in marketing - but here is one – or do you know an example that breaks this law ? Then please tell me.

Extract from “How Brands Grow”:

Again and again it appears in numerous product categories, markets, and countries that there is a fundamental law of brand size. Big brands have markedly larger customer bases.
At first glance this seems obvious; more sales = more customers..... yet it need not have been this way. A brand’s sales volume depends on two things: (1) how many buyers it has, and (2) how often they buy the brand. One multiplied by the other equals sales. So a brand could be large because it is bought very often by its buyers, without having many buyers. Theoretically there could be two brands of equal size, one with many buyers who buy the brand occasionally, while the other brand has half the number of buyers but they buy it twice as often
. See the table below for illustration.

Hypothetical brands
of equal size
Annual market
penetration (%)
Theoretical purchases
per buyer pa
Resulting market
share (%)

Different metrics that can result in equal sales volumes and shares

But this happens only “in theory”, never in practice. In the real world, two rival brands of about equal market share have about equal penetration, and so they must also get bought by their buyers at a similar average rate.

I can think of ways of artificially creating this situation, e.g. comparing a brand that only sold in the USA with one sold in the USA, Canada and Mexico. Let’s put such data manipulation aside. Are there any marketers out there who see a pattern like the table below in your category’s brand performance metrics ? Take the challenge, look at your own data.