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

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

To address these challenges, the Denmark-based company, Neuron, which combines the power of neuroscience with machine learning (ML). The company provides a platform that predicts customer behavior, such as attention and focus, in seconds, helping businesses optimize every part of the customer journey, from advertising to experience. users and technology. Today, Neurons announced they have raised $6 million in a seed funding round.

Predictive foundation of neurons

Neurons provides a cloud-based customer prediction platform that has three key tools for predicting, understanding, and adapting to customer decision-making: Prediction, Discovery, and Research.

Prediction, as the company explains, is a cloud-based attention-prediction AI that automatically generates validated heat maps and perception scores to predict customer responses. Its insights help to test and decide which ads will perform best or which brand designs will work best based on brand recognition.


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“Our AI is built on one of the largest eye-tracking databases in the world, constantly updated and validated through our lab research functionality,” says Thomas Zoëga Ramsøy, founder of Neurons and CEO at Neurons, told VentureBeat. “With that database, we trained our AI to make accurate and fast content predictions for human responses such as attention, focus, cognitive response, and level of response. interaction with 95% accuracy. AI models are built and validated in-house with our ML engineers and neuroscience experts using state-of-the-art standards such as Tensorflow and Google Cloud Platform tools that allow users to scale based on need. ”

While Prediction is automated and data-driven, the Discover feature serves as a self-service online dashboard testing tool. It allows users to build custom tests to collect unconscious and conscious responses – such as emotions, memory and motivation – from a targeted audience sample for creative content. .

“We have developed a system where users can easily build and conduct online studies, send them to groups of participants based on their target audience, and collect their feedback. within a few days. They can then use these results to predict reactions in the market to gain insight, such as what to say about their brand/product, what channels they should use to communicate or even what kind of content to promote,” Ramsøy explains.

The Research aspect of the platform is a separate, full-scale offering for detailed research. As part of this, the company can test participants with hardware-assisted eye trackers and brain scanners (EEGs) to gain unique access to their responses to advertisements and how they play out over time. This provides a way to analyze and diagnose where the customer experience succeeds and where it goes wrong.

Growth trajectory

Neural started in 2013, but the enterprise SaaS division was only recently founded. Since then, the company claims to have grown from zero to more than 150 customers, including Google, Coca-Cola, Mercedes, Capital One, NBC, Vodafone and Ikea.

“The growth has been quite positive,” the founder noted, with a more than threefold increase in the first six months of 2022 compared to SaaS revenue in 2021.

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

“As part of this, we have moved beyond expectations and will soon be releasing Sentiment AI and other models,” Ramsøy said. “Over time, additional AI products will emerge, including emotion prediction. The second move is to go beyond mere prediction and provide recommendations, allowing designers, brand owners, and others to not only see if the content is performing, but also receive automatic suggestions on what to do with it. “

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

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