research notes 1 1 attitudinal equity and market share

Research note 1.1

The Relationship between Attitudinal Equity and Market Share – initial findings Jan Hofmeyr, Martin Bongers, Victoria Goodall

Background

Synovate’s Brand Value Creator (BVC) is built around two core metrics, namely, attitudinal equity and barrier effects. ‘Attitudinal equity’ (AE) is about how much someone wants to use or buy a brand. ‘Barrier effects’ are about the extent to which market circumstances interfere with what people want to use or buy. Put the two together and you should get an accurate estimate of the likelihood that someone will use or buy each brand that is relevant to them in a product category.

The rationale behind the BVC is that marketers need valid and reliable survey measures of brand strength for at least the following reasons:

a. To know how well their brands are doing relative to competitors;

b. To use as dependent variables when modeling and developing brand strategy;

c. To calculate the potential $ pay-back from marketing efforts.

This means that validity is central to the BVC. This note is about the validity of the AE.

The Relationship between Attitudinal Equity and Market Share

Figure 1 is a scatter plot of the relationship between AE and market share for 99 brands in multiple countries and product categories. AE was measured in surveys. Market share came from industry sources and panel data.

Figure 1: Attitudinal equity and market share

BrandMarket Shares

The USA, the UK, China, Thailand, India, South Africa

Product Categories: Health care plans, cooking oil, financial services, soaps and gels, motor cars, motor oils, sparkling drinks, medicinesBrand

Market Shares

Brand Attitudinal Equities10 20 30 40

The USA, the UK, China, Thailand, India, South Africa

Product Categories: Health care plans, cooking oil, financial services, soaps and gels, motor cars, motor oils, sparkling drinks, medicines

y = 0.001x3 - 0.03x2 + 0.99x

RAdj. R 2

Countries:

R = 0.970Adj. R 2 = 0.929

Countries:

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There is a very strong relationship between survey-based AE and real-world market share (Adjusted R2 = 0.929). The equation is in the upper left corner. Put briefly: if you plug the AE of your brand (i.e. ‘x’), into the equation, the market share of your brand will pop out (i.e. ‘y’).

Implication for marketers: If you work out how to increase a brand’s AE (using, for example, a driver analysis with the AE as the dependent variable), then you can be confident that real market share gains will follow - as long as your strategy is successfully implemented, of course.

We show examples of how to use the equation in appendix one.

The difference between product categories with ‘big’ versus ‘small’ market leaders

Because of the way regression works, big brands play a dominant role in the ‘shape’ of the relationship in figure 1. Put into ordinary language: the steepness of the ‘upward curve’ (represented by the cubic term), is determined by the biggest brands. One way to moderate this effect is to divide the product categories into subsets as a function of the size of their market leading brands. This is what we’ve done for figures 2a-c. Our three subsets are: market leader has market share < 25% (three categories, 40 observations); 25% <= market leader’s market share < 50% (three categories, 34 observations); and market leader’s market share => 50% (3 categories, 59 observations). It leads to three separate models.

Figures 2a-c: AE and market share – variation as a function of the market leader’s share

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R = 0.97Adj. R 2 = 0.91

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Brand Attitudinal Equities

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Motor oils, health care plans, motor cars

BrandMarket Shares

y = 0.004x3 - 0.11x2 + 1.63x

R = 0.94Adj. R 2 = 0.86

The USA, the UK, China

Motor cars, financial institutions,soaps and gels

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y = 0.001x3 - 0.0002x2 + 0.43x

R = 0.99Adj. R 2 = 0.93

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Pharmaceuticals, sparkling drinks, cooking oils

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y = 0.0005x3 - 0.004x2 + 0.88x

R = 0.97Adj. R 2 = 0.91

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2a: 2b: 2c:

As in figure 1, cubic relationships fit best. They follow an interesting pattern.

Figure 2a shows the relationship for product categories in which the market leaders have a market share of less than 25%. It has a ‘back-to-front’ and ‘on its side’ S-shape. The kink is caused by the combination of the positive cubic (i.e. ‘0.004x3’) and negative quadratic (i.e. ‘0.11x2’) terms. It shows that market share gains are big for brands with low AE, but that at a market share of about 4%, increases in AE are associated with decreasing market share gains (the curve flattens out). This continues until somewhere around 15% where the curve slants upwards again.

In marketing terms this means that small initial gains in AE are associated with relatively big gains in market share. But brands then go through a frustrating period during which improvements in attitudinal equity are not matched by similar market share gains. At an AE of about 15%, however, a point is reached where improvements in AE lead to accelerating gains in market share.

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Research note 1.1

Figures 2b and c show the relationship for product categories in which the market leaders are bigger. The scale of the market leading brands is so dominant in these product categories that the ‘kink’ all but disappears.

Implications for marketers: The relationship between AE and market share varies systematically as a function of how dominant the market leader is. The bigger the market leading brand, the flatter the slope to begin with, but the steeper the slope, later.

What this means is that the bigger the market leading brand in your category, the harder it will be for you to gain market share to begin with - even if you succeed in creating demand for your brand through improvements in its AE.

Channel capacity constraints, big brands, and ‘tipping’ points

We know from the work of Ehrenburg (See Ehrenburg and Uncles, 1995) that big brands get more than their fair share of everything – more behaviourally loyal customers, more attitudinally positive ratings, more market share. Fader and Shmittlein (1993) show that market leading brands get even more of their fair share than Ehrenburg says they should. One reason for this is that market leading brands are a natural first choice whenever there are ‘channel’ capacity constraints. By ‘channel’ constraints we mean: anything that limits marketers’ ability to get brands to people. In other words, what are known in the BVC as ‘barriers’.

Now: all markets are characterized by channel constraints. To take just one example: banks and retailers (or any marketer needing buildings to create brand access) face a constraint on good locations. Packaged goods manufacturers face transport constraints - trucks are only so big; and only so many can get onto the roads - and then they face the constraint of limited shelf-space. This means that the cost of getting all people exactly the brands they want, is prohibitive. Brand suppliers therefore tend to steer their resources towards the brands for which there is the greatest demand; and away from the least wanted brands. In BVC terms: if we think of the BVC’s measure of AE as the natural demand level for a brand, brands with high equity tend to get more than their fair share of channel capacity.

An important question is: How high does the demand for a brand need to be, before its marketers can expect to derive benefits from the above kinds of market dominance effect? Put in another way: at what level of AE do market share gains start to exceed AE gains?

The answer to this question is to be found in the equations in figures 2a-c. By identifying the points where the ‘S-curve’ changes direction, we can identify the points at which the nature of the relationship between AE and market share changes. We refer to these levels of AE as ‘tipping points’ and show them in table 1.

Table 1: The relationship between size of leading brand and AE ‘tipping points’

First tipping point Second tipping point

2a: Less than 25% 4.2 14.2

2b: 25% - 49% n/a 14.2

2c: 50% + n/a 17.1

Interpretation: in product categories where the market leading brand is no bigger than 24%, a brand has to reach an AE of 14.2% before it will start to benefit from market dominance effects. When the market leader has between 25% and 49% share, the tipping point is still 14.2%. In product categories where the market leader has more than 50% market share, the tipping point is 17.1%. And so on…

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The ‘kink’ in figure 2a also creates a tipping point at low AEs. Initially, low equity brands gain market share fast. This stops when attitudinal equity reaches 4.2%.

Implications for marketers: by calculating the ‘tipping point’, we can answer the question about how big a brand has to be in order to benefit from market dominance effects. Where this point will be, is dependent on how dominant the market leader is in a product category.

It’s important to note that these results are based on limited observations to date; and that they may therefore change as we accumulate more information. However, they suggest an answer to the question: what is a small brand? If we define ‘small’ as: ‘not having reached the critical threshold beyond which dominance affects kick in, then ‘small’ is anything less than the ‘tipping point’ AE.

What the relationship looks like among the small brands

Because of the way that regression favours the big brands, it’s useful to look at a separate set of models for the small brands. We do this in figure 3 for brands from figures 2b/c with market shares < 4%.

Figure 3: The relationship between AE and market share among small brands

Actual Market Shares

The subset of 29 observations, y = -0.041x2 + 0.76x


R = 0.943 Adj. R2 = 0.847

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The relationship is best fit by an inverted quadratic equation. In other words, when we put the small brands from the ‘big brand’ product categories under a micros-scope, we see the beginnings of the full cubic relationship. Notice, however, that although the shape of the relationship is an inverted parabola, the small brands’ gains in market share do not exceed their gains in AE.

It is easy to explain why market share gains exceed AE gains for big brands - it has to do with the sensible use of limited channel capacity. The pattern we see here poses an interesting question however which is: why do the brands with the very smallest AEs appear to gain market share faster than slightly more popular brands?

We don’t have a definitive answer to this question; and we should probably wait for more data before drawing firm conclusions about the persistence of this pattern. But it is interesting to speculate. One possible answer is that there may be a ‘size’ below which it doesn’t make sense to continue dividing the channel. This would result in the least popular brands getting more than their proportional share of channel space. There may then be two aspects to the relationship between brand popularity (as reflected in the BVC’s AE) and channel management. When brands are very popular they get more than their fair share of channel space because it is a cost effective way to manage channel limitations. But the least popular brands also get more

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than their fair share of channel space because it becomes cost inefficient to try to match channel allocation with brand popularity for very small brands. Medium size brands suffer.

What the relationship looks like when there are market distorting barriers

In an ideal world, people would be able to buy or use exactly the brands they wanted. This would show up as a graph in which the relationship between AE and market share was one to one. Such a world would need massive channel capacity to ensure that all brands were available where they were wanted; and it would need massive information to eliminate search times and make desired brands easy to find. It would also need people with unlimited resources to buy whatever they wanted.

As everyone knows, the real world isn’t ideal. People don’t have unlimited resources and brand owners face constant competition for channel space. This leads to the kinds of effects we’ve been discussing.

Sometimes, however, the relationship can be distorted in a less natural way i.e. in a way which limits sales for popular brands. An obvious example comes from the situation of premium brands in poor countries. People may aspire to own or use such brands, but be unable to afford them. They will then use brands to which they are not as strongly attracted i.e. with relatively lower AE; and such brands will get more than their fair market share.

Figure 3 shows an example of two such markets.

Figure 3: The relationship between AE and market share when barriers distort relationships

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y = 0.003x 3 – 0.12x 2 + 1.85x

R = 0.959Adj. R2 = 0.919

Brand Market Shares

y = 0.003x 3 – 0.12x 2 + 1.85x

R = 0.959Adj. R2 = 0.919


This is the plot for a product category in two emerging markets. The brands highlighted by the red arrows are associated with lower market shares than we would expect, given the equations from figures 2a-c. By contrast, those highlighted by the black arrows are associated with higher market share than we would expect. It probably comes as no surprise to learn that the ‘red’ brands are premium brands which attract high AE, but are unaffordable. The ‘black’ brands are affordable local brands.

It’s the inclusion of these data in figure 2a that helps drive the shape of the relationship in 2a i.e. a sideways on and back-to-front ‘S’. The results suggest that one of the ways in which the presence of market distorting barriers – in this case, affordability – will tend to show up, is by the appearance of the quadratic term in the equation of the relationship. Here’s why: what characterizes market distorting barriers is that people can’t get the brands they want. This shows up in the plot as brands positioned relatively low, on the right i.e. a lot stronger on the horizontal (AE) axis than the vertical (market share). They’re wanted but not bought. They drag the line of best fit out to the right. Counter-balancing them are the low equity brands that that get

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Research note 1.1

bought instead. The latter drag the line of best fit up. The severity of this distortion may well be a good way to quantify the extent to which markets are faced by non-natural, in other words, market distorting barriers.

What can we conclude?

We need more data before we can start to make strong statements about the relationship between our equations and the real world. It’s therefore important not to use the equations in this paper too literally. However, the results are remarkably robust across product categories and countries.

In marketing terms, it means:

There is a strong, generally positive and probably cubic relationship between the BVC’s attitudinal equity and market share. As attitudinal equity increases, so market share increases.

This means that initial gains in attitudinal equity do not lead to equivalent gains in market share. However, there is a tipping point beyond which market share gains exceed attitudinal equity gains.

The relationship appears to vary as a function of two key parameters i.e. the market share of the market leading brand; and the presence of market factors which inhibit choice.

The overall strength of the relationship suggests that we can use the equations (with care) to predict how much market share a brand will gain, if it manages to improve its attitudinal equity.

Put simply, the results suggest that as long as we know the total annual spend in a category, we can calculate the likely top-line revenue gain that a brand should get as a function of improvements in its attitudinal equity (as measured using the BVC). This is a very powerful result. Used in conjunction with Synovate’s attitudinal equity simulators, it allows us to quantify the value to a brand of changes in brand image. Technical Note

We’re aware that there are numerous methods other than ordinary least squares regression to fit non-linear curves to a data set. Examples of these include the use of splines, kernal regression methods and other forms of local regression, such as the LOESS method. With parsimony and simplicity in mind, the ordinary least squares approach was used to illustrate the concepts discussed above.

References

Ehrenburg, A.S.C. and M.D. Uncles (1995), “Dirichlet Markets: A Review,” Working Paper, South Bank Business School and Bradford Management Centre

Fader, Peter S. and David C. Schmittlein (1993), “Excess Behavioural Loyalty for High-Share Brands: Deviations from the Dirichlet Model for Repeat Buying,” Journal of Marketing Research, 30 (November), 478 – 493

Hofmeyr, Jan and Butch Rice (2000), Commitment-Led Marketing, Wiley and Sons, Chichester, United Kingdom

Note: The Brand Lab team would like to thank Paul Holtzman (Global Head of Synovate’s Decision Systems

Division) for his many helpful and thought-provoking comments.

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Research note 1.1

Appendix One: Examples of how to calculate the pay-back from increasing attitudinal equity

Scenarios

One: Your attitudinal equity (AE) is 3%. Through modeling you discover that a 3% point increase in perceptions of quality takes your AE to 5%. The total spending in your product category is: $1.8 billion.

Market share associated with AE of 3: 0.001 * 33 - 0.03 * 32 + 0.99 * 3 = 2.7%


Therefore: increasing perceptions of ‘quality’ by 3% points leads to an increase of 1% point in AE; and 1.6% point in market share.

Value to the top-line (i.e. increased brand revenue): $1.8 billion * 0.016 = $28.8 million

Two: Your attitudinal equity (AE) is 10.5%. Through modeling you discover that a 3% point increase in perceptions of quality takes your AE to 12.5%. The total spending in your product category is: $1.8 billion.

Market share associated with AE of 10.5: 0.001 * 10.53 - 0.03 * 10.52 + 0.99 * 10.5 = 8.2%

Market share associated with AE of 12.5: 0.001 * 12.53 - 0.03 * 12.52 + 0.99 * 12.5 = 9.6%

Therefore: increasing perceptions of ‘quality’ by 3% points leads to an increase of 1% point in AE; and a 1.4% point in market share.


Three: Your attitudinal equity (AE) is 19%. Through modeling you discover that a 3% point increase in perceptions of quality takes your AE to 21%. The total spending in your product category is: $1.8 billion.



Therefore: increasing perceptions of ‘quality’ by 3% points leads to an increase of 1% point in AE; and a 2.0% point in market share.


Note the interesting result due to the back-to-front and sideways ‘s’ shape of the relationship: AE gains for the smaller brand (3%) pay-back more than AE gains for the mid-size brand (10.5%). But the biggest brand (19%) is also the biggest winner.

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research notes 1 1 attitudinal equity and market share

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