L’Oréal and EMOTIV developed Scent-sation, an interactive shopping experience that matches products based on your emotional responses.
Customers answer a series of questions about their preferences from textiles to environments, then don an EMOTIV Insight EEG headset. Customers test different scent accords, such as "floral" or "woody." At the same time, sophisticated algorithms translate their brainwaves into real-time performance metrics like focus, stimulation and stress levels. Scent-sation recommends three of Yves Saint Laurent (YSL) luxury fragrances based on each person's biometric reactions.
Scent-sation debuted at the 2021 Dubai Expo at the YSL Tech Innovation Lab. Attendees were able to try the interactive shopping experience for themselves in a stylish setting. After the successful display, they installed Scent-sation in select Yves Saint Laurent flagship stores worldwide. L’Oréal presented its innovative approach to neuromarketing at the Consumer Electronics Show in 2024, for which Scent-sation received a prestigious Innovation Award.
“Through this immersive system, we were able to get 95% of people the right fragrance personalized to their needs and desires, which is enormously higher than without this technology," Stephan Bezy, International General Manager at Yves Saint Laurent Beauté, said of the partnership with EMOTIV. "It’s a huge first step in this category. Once we know which scents make people feel happy, energized, or other emotions, we can customize fragrances even more – the potential is boundless.”
The Link Between Smell and Emotions
Humans have an intimate relationship between our sense of smell and the formation of memories and emotions. We have around 300 genes that help us detect many different smells using olfactory receptors [1]. Research shows that smell-related memories can go further back in a person's life than memories triggered by other senses [2].
According to L’Oréal's internal research, 77% of consumers want their fragrance to bring them emotional benefits. Through a blind test, L’Oréal also found that people connect various emotions, including happiness and relaxation, to their scent preference. More than half of consumers ages 12-34 say they choose a fragrance based on their mood [3].
Modern technology has promised us efficiency, but often the sheer number of available options can be overwhelming. Technology helps us make better choices by showing only the options that matter. L’Oréal and other leading brands have turned to neuromarketing to make this possible. Ethical neuromarketing doesn't tell customers what to want, but helps them discover what they actually want, increasing customer loyalty.
How does Scent-sation work?
At the heart of the Scent-sation experience is electroencephalography, or EEG. A wearable headset measures the electrical activity generated by your brain when your neurons fire. Researchers measure EEG on the scalp as an indicator of the underlying brain activity.
When you look at a person's face, sensors can measure a unique electrical signal in your brain. Similarly, when you smell something you love or hate, researchers can observe recognizable electrical patterns. Researchers can measure and study changes in electrical activity to understand brain functions and emotional reactions in real-time.
EMOTIV leveraged our years of research expertise and experience developing custom, sophisticated detection algorithms to devise and deliver a custom olfactory detection product. In partnership with L’Oréal, we collected data from hundreds of participants who were exposed to a range of YSL fragrances and accords. Participants also provided subjective ratings for each of these scents on various domains (likeability, familiarity, likelihood to buy, etc.).
Using the olfactory-related EEG, EMOTIV data scientists created a new detection algorithm that captures specific features related to each scent. The algorithm was trained to predict each individual’s self-reported “like/dislike” response to each exposure. Brain responses to a small set of accords are combined in a second model which predicts the likelihood a participant will find each of the 27 YSL fragrances appealing, then recommending the top three fragrances.
Unique store experiences, paired with a fragrance, can create lasting fond memories of the brand. After completing the experience, individuals make buying decisions with increased confidence.
What can you learn from EEG?
EEG is a common method of data collection in research studies. EEG has an advantage over MRI and fMRI because it can quickly detect brain activity processes. It is also considerably more affordable and less time-consuming than reserving an MRI machine.
Wireless EEG, pioneered by EMOTIV, allows for the collection of real-time brain data in a more natural environment - even remotely. This makes it a tool uniquely positioned for “online” uses [4]. In other words, producing insights in real-time rather than at a later time after all the data has been collected.
Raw EEG is similar to looking at a soundwave, in that it's highly unlikely a person can discern meaning with the naked eye. There are very few things that can be discerned from looking at “raw” EEG. Generally, scientists will look at EEG that is averaged across many people who are repeatedly exposed to a stimulus. Learn more about the Basics of Neural Oscillations.
EEG must be processed to clean up the “noise” and often transformed or otherwise mathematically altered in order to deduce any meaningful patterns. This is generally done long after the actual data collection has occurred.
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Producing real-time EEG insights
If EEG has to be cleaned and transformed to be meaningful, how can it be useful in real-time? By using previously-collected data, we can generate machine-learning algorithms that identify the general patterns of brain activity associated with specific circumstances. You can then tune these algorithms to be sensitive to other situations.
For example, we collected EEG from many people while they performed several frustrating tasks. We then developed a mathematical model of what this frustrated EEG looked like and quantified the level of frustration between 0 and 100%. This model can be integrated into software that indicates when a new person is doing something that frustrates them.
EMOTIV has spent over a decade developing these real-time EEG insights. We have collected EEG from thousands of people under controlled experimental conditions. Using our unique database and methods, we developed several distinct machine-learning algorithms that can identify cognitive states in real time.
These EMOTIV “detections,” aka Performance Metrics, include Frustration, Interest, Relaxation, Engagement, Excitement, Stress, and Attention. We fine-tune these detections and develop new ones through further testing.
Integrating real-time detections into a consumer experience
In cooperation with L’Oréal, EMOTIV integrated our olfactory detection algorithm into a seamless app-based beauty experience. Alongside a beauty advisor, customers first answered eight emotional profiling questions that determined which six accords were most likely to stimulate them.
With six accords determined, the beauty advisor then fitted the EMOTIV headset to the customer and guided them through the exposure. Customers sampled each of the accords while brain responses were wirelessly transmitted to a mobile device. During this process, the EMOTIV real-time detections continuously adjusted the individual probability that the customer would find each of the YSL fragrances appealing.
The experience then provided customers with a personal profile. This likeability curve gave customers the opportunity to compare their profile with the YSL beauty community.
The experience culminated with three YSL fragrance recommendations. Two of these were predicted to perfectly align with the customer’s individual emotional and brain responses. To widen a customer’s sensory choice profile, the third recommendation was either a unisex or gender-opposite fragrance that still aligned with the predictive brain olfactory algorithm.
The resulting experience was a resounding success from the perspective of the customers, beauty advisors, L’Oréal, and EMOTIV.
The future of consumer-facing neuroscience
This partnership demonstrates how EMOTIV industry-leading hardware can be combined with our neuroscience processing pipelines to produce effective and accurate predictive applications.
With hardware and software technological innovations, we have entered an era in which neuroscience can be harnessed for a wide range of real-world applications.
Whether a company is looking to gain actionable insights into how customers are engaging with their products or seeking to bolster employee well-being through objective assessment of workflows and environments, modern neurotech is now positioned to be the go-to tool of the future. It quickly supplants subjective measures, such as surveys and questionnaires, as the most effective method for companies seeking to better understand their employees, customers, products, and markets. Develop with EMOTIV
Updated August 21, 2024
Written by Dr. Nikolas S. Williams
H.B. Duran contributed to this story.
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References
- K. Sowndhararajan and S. Kim, “Influence of fragrances on human psychophysiological activity: with special reference to human electroencephalographic response,” Scientia Pharmaceutica, vol. 84, no. 4, pp. 724–751, Nov. 2016, doi: 10.3390/scipharm84040724. Available: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5198031/
- A. N. Miles and D. Berntsen, “Odour-induced mental time travel into the past and future: Do odour cues retain a unique link to our distant past?,” Memory, vol. 19, no. 8, pp. 930–940, Nov. 2011, doi: 10.1080/09658211.2011.613847. Available: https://www.tandfonline.com/doi/abs/10.1080/09658211.2011.613847
- L’Oréal, “L’ORÉAL USA ANNOUNCES 2024 INCLUSIVE BEAUTY FUND RECIPIENTS,” L’Oréal, Jun. 25, 2024. Available: https://www.loreal.com/en/press-release/group/press-release-scent--sation/
- N. S. Williams, W. King, G. Mackellar, R. Randeniya, A. McCormick, and N. A. Badcock, “Crowdsourced EEG experiments: A proof of concept for remote EEG acquisition using EmotivPRO Builder and EmotivLABS,” Heliyon, vol. 9, no. 8, p. e18433, Aug. 2023, doi: 10.1016/j.heliyon.2023.e18433. Available: https://www.cell.com/heliyon/fulltext/S2405-8440(23)05641-4?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS2405844023056414%3Fshowall%3Dtrue
