Branding in the nth Dimension (Systems Theory in Branded Markets)

It is important to make a distinction between what we are measuring (the concept) and the tool we are using to measure it. Our measurement tools or metrics are generally proxies for a more complex idea that we are trying to measure or visualise e.g. we might use the measure of ‘loyalty’ to understand the concept of ‘brand equity’

Feldwick: “ I break brand equity down into three components: Brand valuation - “The total value of a brand as a separable asset – when it is sold, or included, on a balance sheet” ; Brand strength - “A measure of the strength of consumers’ attachment to a brand” Brand image - “A description of the associations and beliefs the consumer has about the brand””

Raw materials and the physical product go a long way towards encapsulating what a brand means to people. However, there is an intangible bundle of associations and perceptions surrounding a brand that only lives inside customers’ heads. We need to add this bundle, which represents a brand’s equity, into the equation to get the full picture of a brand.

As we reduce the dimensions of our data, we lose information. Conversely, by adding dimensions, we often gain information… (although, if you have reduced your data correctly, the first dimension will hold the most information)

Edwin Abbot wrote Flatland in the 19 th century as a social critique on the position of women in society, who he thought of as living in a 2-dimensional ‘flatland’, bereft of the 3-dimensional richness that men enjoyed. It’s most lasting impact though has been the intuitive analogy he used to make a distinction between 2-dimensional and 3-dimensional space – women had a reduced experience in 2-dimensions in comparison to men who enjoyed the richness of 3-dimensional space. In other words, men had more information to colour their experience thanks to the added dimension. In this way, he helped his readers think about higher dimensional space. His lesson is still valuable more than a century later!

Market researchers have their own version of Flatland. We use certain metrics to shine a light on the concept in 2-dimensions. This gets us some of the way to understanding this complex concept, but inevitably falls short.

Similar to Flatlanders trying to perceive a cube as it passes their world, the above measures are just some of the 1-dimensional tools that market researchers use to understand the multi-dimensional concept of ‘brand equity’ as it passes through their world.

Relationship strength… … affects customers’ willingness to pay a price premium i.e. price elasticity … impacts on how much customers will put up with and whether they will go out of their way to buy your brand e.g. inertia (to stay with your brand) … can be understood as the differential value unique to the brand that customers place in it relative to other similar brands i.e. differentiation … makes advocates out of your customers that will defend your brand in the face of criticism … can act as an early warning sign of impending decline for the brand … is comparable across brands and categories … is non-linear , just like the real world. Relationships change suddenly and dramatically when they reach tipping points. This is directly at odds with traditional linear, Newtonian, direct measures of brand equity such as loyalty which cannot account for sudden shifts What we are talking about is “relationship” as a measure of the “gravity” that a brand exerts. Brand equity is a measure of a brand’s gravity.

Systems theory helps us to understand systems in multiple dimensions. Systems tend to come to rest at a state of lowest energy, called an attractor. Attractors can be thought of as basins into which balls roll and come to rest at the lowest point. "Left to their own devices, systems (even a 'system' as simple as a marble in a mixing bowl) tend to sink to a state of minimum energy and maximum entropy - provided there is no input of energy from outside." [Gribbin, 2004] A low energy state equates to a stable state, of the kind described by Ehrenberg for brands.

If we take a step back, we can see that a system can have multiple basins of attraction. In such a scenario, any single basin can be referred to as a “strange attractor” or “local maxima/minima”. "The state that systems settle into is called an attractor. In the example shown, the attractor is a single point at the bottom of the bowl. But an attractor can also be a spread-out region, as in this illustration. The marble on the hill is bound to roll off into the valley, but everywhere in the valley bottom is equally attractive." [Gribbin, 2004] Different brands come to rest in different basins, or stable states. These basins collectively represent the landscape of the market, where the depth of each brand’s basin represents the size of its market share.

We can start zooming out even further to see our basins in their positions on a 3-dimensional surface. This allows us to start perceiving brands and markets as landscapes with peaks and troughs, valleys and mountains. Albert Einstein realised this when he came up with his theories of relativity. Einstein specifically noted how all objects exert a force (gravity) on the space around them, bending the dimensions of space-time. Brands can be thought of as operating in a multi-dimensional space (i.e. a ‘market’). Thus, in order to derive the most accurate measure of brand equity, we need to measure as many of these dimensions as possible (or at least until seriously diminishing returns start kicking in) [Image source: Wikipedia]

A Lyapunov map gives us a 2-d idea of the various areas of relative stability (i.e. maxima and minima) in a system . Each map can be thought of as a bird’s-eye-view representation of a 3-d landscape, similar to a geographic map of a piece of land. Black and yellow areas represent the deepest chasms, while deep blue areas represent flat plateaus. The ‘deep chasms’ are low energy regions of relative stability (and thus predictability), while the valleys represent areas of unpredictable complexity and chaos.

Certain classes of complex numbers and iterative algorithms can be thought of as the DNA of a system. They generate complex patterns over time through iteration i.e. the results of the equation are continually fed back into the same equation as the next starting point. Over time, and after many iterations, interesting patterns begin to form. The Mandelbrot Set is probably one of the most interesting of these DNA-like algorithms. It is an example of a fractal. Fractals describe most of the patterns we see in nature e.g. leaves, coastlines, snowflakes, etc. Thus, by knowing the algorithm that produces these patterns, we can simplify what we know enough to capture a formula that represents a surprisingly complex real-world phenomenon.

The difference between fractals like the Mandelbrot set on the previous slide and a measure like market share is that the fractal functions are iterative i.e. they repeat over and over to build up the patterns they define. Most measures of market share are static measurements, taken at a point in time. Thus, they can be used to describe what the market looked like at the specific point in time when the measurement was made. Unlike an iterative function like the Mandelbrot set, it cannot always be used to predict how the market will continue to evolve in the future (although even the Mandelbrot set leads to surprising, emergent outcomes more often than not).

Something to remember about markets, and indeed, all systems, is that they are dynamical in nature. That is, they are always changing. While we may observe a system that exists in a point of relative stability, nothing lasts forever. Eventually the system will be pushed over into a state of flux before settling down into a new stable state. We sometimes refer to this state of flux as “disruptive innovation”, a ‘market bubble’ or ‘a recession’. Any patterns we observe in markets are only temporal in nature. Given time, they will always change.

Thinking of brands as attractors or basins into which customers roll and come to rest is essentially the same as thinking of gravity. Therefore, we can say that brands have a kind of gravity about them. The larger your brand, the more customers it pulls into its orbit. In marketing parlance, this gravitational effect is known as “Double Jeopardy”.

Let us now evaluate some of the new dimensions that digital technology give us…

“ Connections” Such as followers and fans on Facebook, Twitter, Flickr, YouTube, etc.

Coca-Cola has over 5 million fans on Facebook – what does this say about the brand’s gravity? Pepsi has a Klout factor of 57/100 on Twitter – what does this say about the brand?

“ Engagement” Are people interacting with your brand in an engaged manner e.g. contributing to discussions around the brand, retweeting brand messages, sharing links about the brand, visiting the brand website, etc.

The Brothers Streep made this entertaining music video about Steri Stumpi, their favourite brand of flavoured milk

“ Sentiment Analysis” What is the overall sentiment surrounding your brand online? Are people mostly saying negative, positive or neutral things about your brand?

MatterMeter asks a simple question, “If X no longer existed, would it matter?”. 86% of people asked said “yes, it would matter” if BMW disappeared. TweetFeel sifts through brand mentions on Twitter and categorises them in terms of sentiment. 81% of Coca-Cola mentions are positive.

“ Search Ranking” What does it mean if advanced algorithms employed by search providers like Google, Yahoo and Microsoft rate your brand content as particularly relevant?

Google ranks the Nike website in fifth position amongst the natural results when searching for the term “running shoes”.

“ Listening Tools” These suites of tools pull together several dimensions of online brand measurement.

Listening tools, or suites/platforms, incluede trackur, conversition and radian6. Apparently such tool abhor capital letters 

In order to understand a complex concept like brand equity, we need to view it from multiple dimensions, with each dimension adding a piece of the puzzle. In this way we build up multiple-dimensional holograms of our brands, much like Princess Leia in Star Wars 

Plato’s allegory of the cave talks about how we only ever perceive shades of reality. He uses the flickering shadows cast by the fire of reality onto a cave wall as an analogy for the proxies we, as individuals chained facing the cave wall, interpret as reality (Plato went on to say that only philosophers truly see reality, but that is not pertinent to this discussion).

Echo-location serves as an analogy for the way in which we build up a picture of reality (in this case, a market) by measuring 1-dimensional slices of it (e.g. point-in-time measures of market share, loyalty, awareness, etc.).

“ When we look for an operational definition of brand equity, we are asking the wrong question . Brand equity is necessarily a vague concept , like ‘personal health and fitness’, or ‘a sound economy’. These concepts imply general questions: how well are we doing now? How well can we expect to do in the future? Such questions are not answered fully by any one measure . At certain points in time, one or more measures may be of crucial importance – such as cholesterol level or inflation. But there is also a danger that continuing to concentrate on one measure to the exclusion of others creates its own problems (low inflation leads to unemployment; low cholesterol diets cause depression). Brand equity needs to be approached in the same spirit. ~ Paul Feldwick (1996)

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Branding in the nth Dimension (Systems Theory in Branded Markets)

by Social Physicist on Jul 06, 2010

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Branding in the nth Dimension (Systems Theory in Branded Markets) — Presentation Transcript