Neurons combine ML with science to predict conscious and unconscious consumer behavior

Neurons combine ML with science to predict conscious and unconscious consumer behavior

Neurons combine ML with science to predict conscious and unconscious consumer behavior

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Companies have long used cookies and surveys to gauge exactly what their consumers prefer or want. These methods help define marketing and product strategies, but they remain poor indicators of what consumers would actually choose. According to Geo Technologies, up to 82% of Americans still ignore online advertisements, finding them irrelevant or unappealing, while Merle & Cooper estimate that 35-48% of products fail in the marketplace.

To address these challenges, Danish company Neurons is combining the power of neuroscience with machine learning (ML). The company offers a platform that predicts customer behaviors, such as attention and focus, in seconds, helping businesses optimize every part of their customer journey, from advertising to user experience and technology. Today, Neurones announced that it has raised $6 million in a first round of funding.

Neural predictive platform

Neurones provides a cloud-based customer prediction platform that has three key tools to predict, understand and adapt to customer decision-making processes: Predict, Explore and Research.

Predict, as the company explains, is a cloud-based attention prediction AI that automatically produces heatmaps and validated cognitive scores to predict customer responses. Its insights help in testing and deciding which creatives would perform best or which brand design would be best based on brand recognition.


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“Our AI is based on one of the largest eye tracking databases in the world which is both continuously updated and validated through our lab search function,” said Thomas Zoëga Ramsøy, Founder of Neurons. and CEO of Neurons, to VentureBeat. “With this database, we trained our AI to make accurate and fast predictions about the content of human responses such as attention, concentration, cognitive responses and engagement with 95% accuracy. The models are built and validated in-house with our ML engineers and neuroscience experts using modern standards such as Tensorflow and Google Cloud Platform tools to allow users to scale as needed.

While Predict is automated and data-driven, the Explorer function serves as a self-service online panel testing tool. It allows users to create custom tests to collect unconscious and conscious responses – like emotion, memory, and motivation – from a sample target audience to a creative asset.

“We’ve developed a system that allows users to easily create and run surveys online, send them to panels of participants based on their target audience, and collect their responses within days. They can then use these results to predict responses in the market to better understand, for example, what to say with their brand/products, which channels they should use to communicate or even what types of content to promote. ”, explained Ramsøy.

The Research aspect of the platform is a complete and tailor-made offer for detailed study. As part of this, the company may test participants with hardware-enabled eye trackers and brain scanners (EEG) to gain unique access to their responses to creatives and ads and their timing. This gives a way to analyze and diagnose where the customer experience is succeeding and where it is not.

Growth trajectory

Neurones started in 2013, but the SaaS part of the business was only recently established. Since then, the company says it has grown from zero to more than 150 customers, including Google, Coca-Cola, Mercedes, Capital One, NBC, Vodafone and Ikea.

“Growth has been quite aggressive,” the founder noted, with SaaS revenue more than tripling in the first six months of 2022 compared to 2021.

Now, with this round of funding from Vækstfonden Ventures, Finance Zealand and Fairpoint Capital, the company will work to hire new talent and strengthen its product portfolio to predict consumer behavior.

“As part of this, we are already going well beyond attention prediction and will soon be releasing Sentiment AI and other models,” Ramsøy said. “Over time, other AI products will come, including emotion prediction. A second step is to go beyond simple prediction and provide suggestions, enabling designers, brand owners and others not only to see if an asset will work or not, but also to get automatic suggestions on what to do about it.

Other companies working in the same field are, Attention Insight, CoolTool, Hotjar, Sentient Decision Science and Nielsen Neuro.

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