TWIN T
Letting your digital
he golden rule of creating winning products has always been a simple one – talk to your consumers. Product development, traditionally required surveys,
interviews, and
focus groups. All this information is then used to create prototypes, and this is further validated by way of consumer panels or consumer testing. Today, however, digital twins are being touted as being game-changing technology for product innovation in the consumer-packaged goods sector in addition to helping streamline production processes.
Digital twins of consumers are virtual representations of target consumers, interactions of real-world consumers. These other datasets to provide organisations with actionable insights far beyond the capabilities of traditional focus groups. concepts against virtual twins of your own feedback on liking scores, purchase intent, and sensory drivers. Created and used correctly digital twins can offer the ability for organisations to save time and costs during product development. A report from McKinsey estimated that products developed using digital twins experience 25% fewer quality issues upon launch. Jonathan Raemdonck, Sales & Marketing
28 Kennedy’s Confection March 2025
DIGITAL TWIN TECHNOLOGY
help with consumer research
Suzanne Callander reports on how digital twin technology can be used to replicate the references of real-life consumers, as part of the new product development process.
Director at Foodpairing, points out that one of ability to sift through vast data sets – ranging from social media to taste reviews – to identify possible using traditional methods. “Digital twin technology is able to leverage this data consumer responses, offering confectionery manufacturers a faster and more accurate route to market,” he says. “These virtual representations of target consumers can provide instant feedback on whether consumers would be interested in buying a product and if they would like the product once they tasted it.” So, digital twins of consumers can allow perfect their new product developments without the need to organise consumer panels or build prototypes. “But to fully harness the power of digital twins, they do need to be built in the right way,” warns Jonathan. Creating effective digital twins isn’t as simple as feeding
approach that balances science, creativity, and real-world insights. Jonathan highlighted the following, as being important considerations: • Start with high-quality data: Access to chemistry is complex, and without reliable data preferences, digital twins will not be able to quality data sets is the foundation of building accurate virtual models. • Address algorithmic bias: One major
generates insights that are not grounded in real data – which affect prediction accuracy. Ensuring that digital twins are trained on diverse and representative data helps minimise these risks, leading to more reliable outcomes. • Account for subjective preferences: Flavour perception and buying intent varies widely based on culture, biology, and individual overcome this, digital twins need to incorporate consumer data from various demographics, ensuring product concepts resonate with different target audiences. • Combine AI with human expertise:
will not bring any value, instead it needs to complement human expertise. The real power
KennedysConfection.com
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