The Consumer Neuroscience Company
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16. March 2019

Pricing the brain

A recent study shows how brain responses can predict how much we are likely to pay for a product.
Young surprised woman searching for clothing in a closet

How do we choose how much to pay for a product? Pricing is a large part of one’s marketing strategy, and expertise on pricing abound in the academic realms. In most traditional economics scenarios, the assumption is that we inspect a product, weigh the pros and cons available to us, and then make an informed choice about whether we want the product and how much we are willing to pay for it. Alternatively, whether a given price is acceptable to us.

Our recent neuroscience publication

In a recently published study in the prestigious journal Frontiers in Neuroscience, we report finding a particular brain response that is related to such computations. The asymmetric engagement of the frontal lobes has long been known to be related to value-based decision. That is, in right-handers, research over about three decades, and with many different methods, has robustly demonstrated the following pattern:

  • higher engagement of the left relative to the right frontal lobe is related to approach behaviors
  • the opposite pattern, higher activity in right relative to the left frontal lobe is related to avoidance behaviors

In this study, we were interested in the relationship between frontal asymmetry and how we decide what to pay for products, or how much we are willing to pay (WTP). In doing so, we used EEG (electroencephalography) to measure brain activation while participants were performing consumer decisions. More specifically, we asked participants to first inspect products of different types of products: bags, clothes, women’s shoes, and fast-moving consumer goods (FMCG). We then asked them to rate how much they were willing to pay for the products. To ensure that the choices were real, participants were instructed that their choices could be actuated, thus incentivizing them to maximize their choices.

In the study design, participants first saw a product for 3 seconds, and then made a choice about how much they wanted to pay for the product

On a technical note, we were also interested in studying and comparing different types of brain activity. In most traditional research on frontal asymmetry, researchers have been looking at activity in the alpha frequency band (8-13 Hz). However, as this particular type of activity is related to deactivation rather than activation, we also included other frequency bands to assess activity — the beta (13-25 Hz) and gamma (25-40 Hz) bands.

Brain responses predict price

The results showed that frontal asymmetry in the gamma frequency band was highly related to participants’ willingness to pay for products. Just by looking at this frequency alone, we could predict about 27% of the variation in pricing. In addition to this, when we took the types of products into account (since people are typically willing to pay more for purses than FMCG), that explanatory power went to 64%.

Three more findings should be noted:

  1. other frequencies, such as the beta and particular alpha frequency band, were not significantly related to WTP calculations. This suggests that the gamma frequency in is highly relevant for consumer-related decisions, and perhaps in particular for WTP calculations
  2. the predictive power of the gamma frequency response occurred already around 100 milliseconds of product viewing, which is typically too fast for conscious evaluation to take place. This suggests that the gamma response at this stage is mainly subconscious
  3. the relationship between the frontal gamma asymmetry and WTP became stronger as participants were closer to make their WTP choice. This suggests that gamma is not only a passive evaluation response, but actively involved in the WTP calculation and execution of the response

Left: The frontal asymmetry was calculated using the AF3 and AF4 electrodes (see left hand image). By plotting a normalized frequency band over time. Right: Asymmetry already from 100 milliseconds are indicative of early product evaluation, while alpha and to some extent beta frequencies comes online later. Gamma frequency is also more consistently related to WTP calculations up until the decision-making point.

Better tools, better prediction

Together, this study is the first of its kind to demonstrate that certain brain responses are related to how much we are willing to pay for products. It also is a clear demonstration of the feasibility of using more accessible neuroimaging equipment such as EEG (instead of the more expensive and artificial testing environments of functional Magnetic Resonance Imaging, or fMRI) in evaluating consumer choice.

What is next? We already have data that link this response to in-store choices (paper submitted, and conference proceeding available here: https://goo.gl/8r6CsG) as well as other types of studies on frontal asymmetry and choice (e.g., healthy food choice). In effect, we are using the gamma frontal asymmetry score as foundation of our Motivation score, which has consistently demonstrated a high predictive value of actual choice.

The larger context — neuroscience in business

In recent years there have been debates as to how reliable the commercial use of neuroscience measures are. Very often, we see that commercial companies offering measures of emotions and other responses are not willing to share the actual calculations behind their metrics (aka “black box” solution). This leads to several issues, as clients need to rely on a basic element of trust in their vendors that they are both truthful and that they have done their internal consistency and validity checks. But this is highly problematic, as neuroscience methods are in no way comparable to your everyday statistics, nor does it relate to easily translateable findings.

For example, in an effort to compare different vendors, the Advertising Research Foundation launched their Neurostandards Collaboration Project. The results showed a staggering inconsistency between companies to the exact same materials. However, as these results took every vendor as equally reliable, and their methods and calculations were not accessible to scrutiny, the job of finding the causes of this inconsistency was impossible. Sorting the wheat from the chaff was equally impossible.

Our findings position itself in stark contrast to this: all metrics from Neurons rely on openly published metrics, and our methods are available for scrutiny. Secrecy is not the way forward for this industry — the true power of Neurons comes through our full transparency and world-class excellence in our work 😉