1. “Multiple ‘buy buttons’ in the brain: Forecasting chocolate sales at point-of-sale based on functional brain activation using fMRI”

Takeaways

• Small-scale neuromarketing tests for product messaging may accurately forecast sales.
• Qualitative research on consumer preference for messaging may be a poor predictor of sales.

Study details

qualitative research is a better predictor of purchasing behavior than fMRI scans A group of researchers including Simone Kuhn, Enrique Strelow, and Jurgen Gallinat studied 18 women between the ages of 23 and 56 who all reported that they bought chocolate weekly.

The women were shown a picture of a product and six related communications, including a control (a toothbrush). The product image was briefly shown for two seconds, then a marketing message was displayed for three seconds before the product reappeared for another two seconds. The researchers studied the brain activity of several areas using fMRI imaging during the test.

The participants were asked to order the communications from most to least liked. The researchers made three sales predictions: one based on what the customers said they wanted, one based on brain activity while viewing the commercials, and one based on fMRI changes of product viewing before and after the commercials.

The researchers recorded the actual sales for each test treatment over the course of one week in German supermarkets. The fMRI signals during communications had the strongest correlation with actual sales. The pre- and post-messaging fMRI data was second. The subjects’ stated preference finished last.

While the researchers drew only tentative conclusions about the ability of neuroimaging tests to predict sales and the poor correlation between stated preference and sales, they highlighted the potential power of small sample sizes in neuromarketing:

The present results demonstrate the feasibility to use neuroimaging methods in a relatively small sample of participants to forecast the influence of communications on the actual consumer behavior at the point-of-sale.

2. “When Brain Beats Behavior: Neuroforecasting Crowdfunding Outcomes”

Takeaway

• Troves of online market-level data make it possible to validate individual neuromarketing tests against collective, real-world consumer decisions.

Study details

Can neuromarketing studies of individuals predict mass behavior? The researchers used Kickstarter to see if brain activity could predict how successful a crowdfunding campaign would be.

The researchers showed 30 subjects 36 different crowdfunding requests. Subjects decided whether they would fund each project, with the money they would get from participating in the study given to projects they supported. Researchers recorded brain activity of subjects during the initial selection process.

After the subjects rated each project, they stated their opinion on the project (whether it was positive or negative), how strong their opinion was, and whether they thought the project would reach its crowdfunding goal.

The researchers compared the subjects’ ratings and brain activity to the success or failure of the crowdfunding projects a few weeks later. The results? Brain activity was the only successful predictor of crowdfunding outcomes:

• “Neither average ratings of project likability nor of perceived likelihood of success were associated with Internet funding outcomes.”
• “Only [Nucleus accumbens, or NAcc,] activity generalized to forecast market funding outcomes weeks later on the Internet.”

The researchers found that there were certain neural predictors that could forecast crowdfunding outcomes better than the actual choices made by individuals.

Researchers replicated their findings in a second study.

3. “Measuring narrative engagement: The heart tells the story”

Takeaway

• Audio content (e.g. podcasts) may have the potential to create stronger connections with consumers, even if their stated preference is for video content.

Study details

Does audio or video content generate more user engagement? There is a discrepancy between what people claim and what their biometric data shows, according to the authors.

The researchers compared audiobook and film scenes from adaptations to see if they were equivalent. The researchers selected scenes that were emotionally charged and had audio and video that were nearly identical.

The audio in the scene lasted longer than the video, so the authors looked at a chart that showed how long each scene lasted.

While participants rated the video segments as, on average, 15% “more engaging,” the physiological measures suggested otherwise:

“In terms of raw measures, their average heart rate was higher when they were listening to audiobooks by about two beats a minute; they had a greater range of heart rate by about 4 beats per minute; they were roughly 2 degrees warmer in their body temperature (1.66°C), and their skin conductance (EDA) was higher by 0.02 microsiemens.”

This audio content is engaging because it requires active participation to create a scene in the mind’s eye.

Why? The authors hypothesized that “listening to a story is a more active process of co-creation (i.e. via imagination) than watching a video.” Thus:

“The act of listening to the narrative recreated the same basic pattern of brain activity as telling the story, suggesting that listening to the story is qualitatively and quantitatively similar to experiencing the speaker’s memory of the events. Moreover, activation was not limited to regions of the brain classically related to language, but also involved emotional, sensory and motor systems consistent with the notion that at some level, the listener actually experiences the story.”

4. “Willingness to pay lip service? Applying a neuroscience-based method to WTP for green electricity”

Takeaways

• “Neuropricing has been significantly better in predicting population behavior than reaction times, which in turn are significantly better than questionnaires.”
• Neuropricing may better assess consumer valuation of non-core product benefits like ethical production, region-specific origins, use of organic materials, etc.

Study details

What is the difference between qualitative data on willingness to pay and neuroscience data? Carsten Herbes and three co-authors did a study on how much people would be willing to pay for electricity from green sources. The findings have implications for a lot of other areas.

The researchers conducted a study with 40 participants. They asked them how much they would be willing to pay to get partially or entirely green energy sources.

The researchers showed the participants a series of images that included an electricity package, a price, and the word “expensive” or “cheap.” The participants could respond “Yes” or “No” to the image. The researchers monitored the brain activity of the participants while they were looking at the images.

According to neuropricing research, consumers are more likely to pay more than what was originally estimated.

The researchers monitored the brain activity and reaction time of each participant as they chose between 50 different combinations of packages, prices, and binary descriptors.

The study found that people were willing to tolerate a 15% price increase when Neuropricing was used, while qualitative data showed that people were only willing to tolerate a price increase of 3-19%. The result, according to researchers, highlights the value of neuromarketing research over traditional methodologies:

“Neuropricing delivers higher WTPs by the same respondents and thus apparently avoids the effects of strategic behavior. This yields a fundamental insight. Namely, a range of potential biases in and limitations of self-reported WTPs can be eliminated by our methodology.”

Additionally, the researchers suggest two other potential benefits:

1. The potential to “magnify the granularity of WTP research,” by “examining, for example, detailed product features such as proven regional origin or the effects of specific claims in marketing communications.”
2. The ability to obtain valid results with a small number of test subjects.

5. “Intuition, risk, and the formation of online trust”

Takeaways

• “‘Simple changes’ (such as page layouts and choices of fonts, images, and colors) may be far more critical to associative trust-formation processes than we previously understood.”
• “What seem like merely aesthetic design choices may actually be the way your customers learn to trust you (or don’t).”

Study details

How does the level of risk affect consumer trust? Authors Mahdi Roghanizad and Derrick Neufeld identified two hypotheses:

1. “When evaluating whether to trust a website while making low-risk decisions, consumers tend to rely on deliberative and explicitly logical reasoning processes.”
2. “When faced with higher-risk decisions, online consumers are more likely to turn to associative (intuitive) reasoning processes.”

The hypotheses were tested by dividing 245 research students into six groups. Some groups were shown the real version of the website while others were shown versions lacking security seals or return-policy information.

Subjects were asked to make two decisions:

1. Low risk: Determine whether, hypothetically, they would purchase a book from the site.
2. High risk: Determine, in reality, whether they would provide their personal information (name, address, phone number) to the site in exchange for a $20 gift card.

The research found that when making decisions involving risk, such as an online purchase from a website, consumers are more likely to rely on their intuition than on deliberate actions.

This means that people were more likely to trust a website if it looked good, rather than if it had explicit trust guarantees.

A single research study is rarely the defining opinion. Instead of experts thinking that each study contradicts or supports past research, experts think of each study as adding to a baseline of knowledge.

For conversion optimization, heuristic analysis is the starting point. How good your initial analysis is will guide what tests you do and how you prioritize them. This all depends on how much expertise you have.