Sensory Marketing 2.0: Unlocking the Power of the Brain's Predictive Coding Framework

12-minute read

Introduction

Marketers are always on searching for innovative ways to connect with consumers and create a lasting impression of their brand. In recent years, the concept of sensory marketing has gained popularity as an effective tool for achieving these goals (Krishna, 2012). 

In this blog post, we aim to delve deeper into the field of sensory marketing by incorporating recent advances in neuroscience. By doing so, we hope to provide a fresh perspective on the topic and a clearer understanding of the most effective marketing practices.

First, we will provide a brief overview of the basics of Sensory Marketing. We will then delve into the neuroscience of perception, with a particular focus on the “predictive coding” framework. This will help us to better understand how sensory information is processed by the brain and how we can use this knowledge in our marketing strategies.

Conceptual Framework of Sensory Marketing

Sensory marketing refers to the strategic use of sensory stimuli, such as scent, sound, touch, taste, and sight, to shape consumer perceptions, emotions, and behaviors. This approach was first introduced by Aradhna Krishna, who highlighted the immense impact that sensory inputs can have on consumer perception, decision-making, and behavior (Krishna 2012).

Sensory marketing model is typically explained by a series of boxes arranged in a linear fashion, like the one above. Sensory inputs are the various stimuli that customers are exposed to through their senses, such as visual, auditory, olfactory, gustatory, and tactile inputs. Perceptual processing refers to the interpretation of these stimuli by the brain, which interacts with cognition and emotion. This leads to behavioral and attitudinal responses, such as buying, using, or avoiding a product.

Thus, the original framework of sensory marketing is rooted in the bottom-up process of sensation and perception, where sensory stimuli are processed by the sensory organs and interpreted by the brain to influence behavior. However, a more comprehensive understanding of human perceptual processes can provide a more nuanced view of how consumers perceive and respond to sensory stimuli. This is where the top-down process of perception comes into play.

Bottom-up vs. top-down processes of perception

The human perceptual mechanism can be divided into two distinct and complementary processes: bottom-up and top-down. 

Bottom-up processing begins with incoming sensory information and progresses to higher levels of cognition. It is driven by the physical properties of stimuli, such as the intensity and frequency of light or sound and is considered data-driven or stimulus-driven. This means that perception is progressively constructed from the raw sensory information received.

Top-down processing, on the other hand, is a knowledge-driven or concept-driven process that starts with higher levels of cognition, such as prior knowledge, expectations, and attention, and influences the interpretation of sensory information. This process is influenced by mental processes such as attention, expectation, and context, and is influenced by an individual's prior experience and mental state, as well as the context in which the sensory information is received.

As we reviewed above, the typical sensory marketing model focuses primarily on bottom-up processing, attempting to elicit emotions and memories through the senses. For example, a clothing store might use soothing music to create a calming atmosphere, thereby influencing customers' emotions and behaviors and potentially leading to purchase decisions.

Recent advances in neuroscience, however, challenge this classical view of information flow from sensation to action. Instead, they point to the existence and importance of a more comprehensive framework that overturns the traditional bottom-up process of perception (Rao and Ballard, 1999). 

The Predictive Coding Framework in Perception

One of such frameworks is Predictive Coding. The fundamental idea behind it is that the brain generates predictions about the incoming sensory information, based on prior knowledge and expectations, and adjusts its processing of the sensory input based on the accuracy of those predictions (Clark, 2013).

Think of it this way: if you expect to see a cup on a table in front of you, your brain makes a prediction about what the cup should look like, which then guides its processing of the incoming visual information. If the sensory information matches the prediction, the brain refines its prediction. If the sensory information does not match the prediction, the brain updates its prediction to reflect the discrepancy. In this way, the brain attempts to reduce the discrepancy between its sensory inputs and its understanding of the causes of those inputs (Friston, 2010).

The predictive coding framework proposes that the brain operates in a feedback loop in which higher levels of cortex generate predictions and the lower levels of the cortex send prediction error signals back up to the higher levels, which are used to adjust the predictions. This cycle of prediction and adjustment helps the brain to efficiently process the large amount of sensory information it receives and quickly adapt to changing sensory information.

Studies in cognitive neuroscience and neuroimaging have supported the predictive coding framework by demonstrating that the brain's processing of sensory information is shaped by prior knowledge and expectations and that the brain is able to use prediction error signals to adjust its processing. 

Implications of Predictive Coding for Marketing and Branding

Thus, the predictive coding framework portrays the brain as an active “prediction machine” rather than passively waiting to be activated by sensations. This framework has implications for the fields of marketing and branding.

In general, a clear and/or familiar context helps consumers process incoming information more efficiently, while an unexpected event can also provide a positive surprise.

More specifically, using consumer expectations in communication and product development can lead to successful marketing strategies. A famous example of this is the sound effect of car door closing, where it was assumed that consumers have an internal model of a typical sound and therefore associate positive deviations from the prediction with perceptions of, say, luxury, safety, and reliability (Hamilton, 1999).

Similarly, making consumers expect to use or consume a product, such as Coke Europe’s "Try not to hear this" campaign, can also be effective. This print campaign created a series of ads that featured macro images of classic Coca-Cola moments and asked consumers to "try not to hear this", which primed mental representations of the brand.

The predictive coding framework highlights the brain's ability to continuously adapt to changing circumstances, allowing brands to stay relevant and appealing to consumers. For example, food brands such as Subway can monitor changes in consumer preferences for healthier options and adapt their menu accordingly to maintain a relevant and engaging brand image.

The framework also provides theoretical support for the importance of brand image. A luxury car brand like Mercedes-Benz can build a strong brand image by consistently delivering high-quality products and exceptional customer service, thereby creating an expectation that its future products will also be of high quality and increasing the likelihood that consumers will perceive them favorably. 

In summary, the predictive coding framework in the neuroscience of perception offers insights that can inform and enhance marketing and branding strategies. By considering consumers’ prior beliefs, ability to adapt to change, and motivations, marketers and brand managers can create effective and engaging campaigns that capture consumer attention and build brand loyalty.

 

References

Clark A (2013) Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behavioral and Brain Sciences, 36: 181 – 253.

Friston K (2010) The free-energy principle: A unified brain theory? Nature Reviews Neuroscience, 11: 127 – 138.

Hamilton D (1999) Sound quality of impulsive noises: An applied study of automotive door closing sounds. SAE Transactions, 108: 2591 – 2601.

Krishna A (2012) An Integrative Review of Sensory Marketing: Engaging the Senses to Affect Perception, Judgment and Behavior, Journal of Consumer Psychology, 22: 332 – 351.

Rao RPN, Ballard DH (1999) Predictive coding in the visual cortex: A functional interpretation of some extra-classical receptive-field effects. Nature Neuroscience, 2: 79 – 87.

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