When and where to strike: the early warning system

Neurothinking principal, Dr. Peter Steidl
By Neurothinking principal, Dr. Peter Steidl | 15 August 2016
Neurothinking's Peter Steidl

Sometimes the drivers of disruptive change in the operating environment are transparent. For example, we have seen the government’s short-sighted abolition of renewable energy subsidies change the market overnight. Here agility is of immediate use if the change opens up unexpected opportunities or threats.

However, sometimes change is hidden. We may not know that we are bound to lose market share a few years down the track because of changes in buyer behaviour that are obscured in our brand tracking data. This is when we need an early warning system.

For many marketers, brand tracking serves as their Early Warning System. However, traditional brand tracking suffers from three key deficiencies:

  • It uses irrelevant measures.
  • It uses unreliable methodologies to measure them.
  • It obscures small but highly relevant changes by not differentiating between the key segments that make up the market structure.

Let’s start with what is being measured. The attributes that lie at the heart of much brand tracking follow the outdated AIDA formula (attention, interest, desire, action). Following this formula it makes sense to track a brand’s trajectory using measures such as:

  • unaided and aided brand and advertising awareness
  • perceived effectiveness of ads
  • degree of interest in the brand
  • perceived qualities associated with the brand
  • emotional connection with the brand (e.g., ‘brand love’)
  • purchase intent
  • willingness to recommend the brand

Today, we now know that AIDA is a purely theoretical concept that does not reflect the real world. Recently a client of mine, a multinational corporation, undertook an econometric study and found that there was no relationship between the sorts of variables listed above and sales.

When we look at what marketers actually do it is quite clear that the focus of most campaigns and initiatives is to associate a brand with particular attributes which the marketer believes are drivers of brand choice. In other words, we try to convince the consumer that our brand is less expensive, performs better, is used by more people or celebrities, looks great, and so on.

If a campaign is successful we should find that the brand is now more strongly associated with the qualities we promoted. It follows that we need to measure the strength of these associations to understand how our brand is faring and how effective our marketing initiatives are.

The second point is that the methodology used to measure is unreliable because it is based on asking consumers to make judgments they are unable to make (I won’t go into the scientific foundation for this claim – if you have doubts read up on neuromarketing). This problem can be addressed by resorting to an easy to administer, reliable and inexpensive response time test (e.g., Neurohm’s Biocode test, which can be administered via a smartphone, tablet or computer).

However, brand tracking needs to tell us not just if our brand has been strengthened by our marketing campaigns. We also want answers to two questions:

  • Have we strengthened the association between our brand and the specific attributes we believe drive purchase?
  • Were we actually right in assuming that these attributes are driving purchases?

Answers to these questions, provided by a reaction time test, allow us to differentiate between strategic failure and execution failure:

Strategic failure is a situation where our campaign or other marketing initiatives have succeeded in associating our brand more strongly with the desired attribute(s) but, unfortunately, these attributes are not what drives purchases. Our brand strategy is not working, even though the communications and other marketing initiatives based on that strategy are.

Execution failure is where we have not succeeded in associating the desired attributes more strongly with our brand. In other words, our communications and other marketing initiatives have not worked, because they have failed to create a strong link between the brand memory and the desired attributes.

It should be quite obvious that the actions we need to take are very different given a strategic failure versus an execution failure.

Having addressed the measurement issue and how to gain relevant and actionable insights, we need to take one more step to develop an Early Warning System. We need to differentiate between different types of consumer behaviour to understand the underlying market dynamics.

The structure of most markets is surprisingly simple. Four behavioural segments typically capture the essence of the market:

  • new category entrants, i.e., consumers who have not previously bought in your category
  • shoppers making considered purchases, i.e., considering options before they settle on the brand/product to buy (these consumers typically adopt shortcuts that eliminate the need to spend a lot of time thinking)
  • habitual shoppers who automatically buy the same brand/product
  • shoppers who have left the category.

The following illustration shows these respective segments and the flow between them:

Why do brands decline? There are a number of possibilities:

  • New market entrants may favour competitive brands to a greater extent than established shoppers. As new market entrants typically account for only a small percentage of all purchases we can expect our brand to decline very slowly.
  • Considered purchasers who habitualize their purchases may favour competitors’ brands to a greater extent than other segments. In a category where most purchases are habitual we can expect to see our market share decline slowly, but faster than in the case outlined above.
  • Habitual purchases are disrupted which leads to an increased number of habitual buyers becoming considered buyers. Our brand will decline when a disproportionately large number of these buyers choose our competitors’ brands. When habitual buying accounts for the largest share of purchases we can expect to lose market share quite rapidly.
  • Finally we could look at consumers leaving the category, but here we are likely to find that the attrition rate spreads across brands relative to their size (unless some brands attract older people) and thus is unlikely to have a significant impact on market shares.

It should be clear that tracking movements between these market structure segments will deliver an Early Warning of expected future market share movements, and should also allow us to get an indication of how soon and to what extent these changes are likely to be reflected in our brand’s market share.

What is not always quite as obvious is why tracking these flows will provide us with an Early Warning System while tracking overall sales or market share data won’t. There are two main reasons for this:

First, the change in flows – while quite large in their own right - may be too small to be reflected in aggregate data.

Secondly, it is quite possible - if not likely - that different segments (i.e., new entrants, considered buyers and habitual buyers) are affected differently by a strategy and its execution. You may have wins somewhere and losses somewhere else, balancing each other out and thus not showing any change in your aggregate data.

It follows that only a detailed assessment of the flow between these structural market segments will allow us to pick up early warning signals.

Clearly, marketers will need to adapt the framework I have outlined to suit their specific market’s structure, and will have to use their very own set of meaningful attributes in a response time test.

But that’s exactly the point: marketers need to go hunting and explore the tailor-made solution that works for their brands rather than buy into some generic, often irrelevant approach simply because it is widely used. Marketers need to be agile hunters and not staid settlers who follow (often outdated) category wisdom. The reward will not only be a greater return on marketing investment, but also the thrill of the chase.

By Neurothinking principal, Dr. Peter Steidl

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