The project partner, Machiel Reinders (Wageningen University & Research), presented FoodDataQuest results at EuroSense 2026 in Oslo on 10 September 2026. The talk titled “Sharing Data, Shaping Diets: Consumers’ Willingness to Share Data for Personalised Food Recommendations” is based on work with Liam Dwyer, Houkje Adema and Jos van den Puttelaar.
Consumer data can help companies and governments develop food messages that better fit individual behaviour and preferences, and digital technologies and AI can guide people more personally, if consumers share their personal data.
The research connected three parts: a cross-European survey of 1,330 consumers in the Netherlands, Finland, Belgium, Greece and Hungary on what private and personal data people will share, and with whom; a pilot experiment with 291 consumers in the Netherlands on whether personalising the style of texts and images with AI can support behaviour change; and a conversational survey with 291 consumers in the Netherlands on what transparency people expect when AI is used in food communication.
People were generally willing to share when benefits were clear and privacy risks remained moderate, highest in Finland and lowest in Belgium. They favoured sharing food and recipe preferences over physiological and location data, and trusted medical professionals such as doctors and dietitians most. Supermarkets and manufacturers attracted more willingness where purchase history and diet preferences had a clear shopping benefit. The government institutions ranked lowest, particularly for location and physiological data. Overall, three segments were defined: Optimists, Ambivalents and Sceptics, pointing to different data strategies.
People have preferences for how food messages look and sound, but matching recommendations to those stylistic preferences showed no significant difference from a control group. Changing the style of text and images alone may not be enough to influence more sustainable food choices.
Most participants wanted to know why a product was recommended, from previous purchases and motives such as price, taste, health or sustainability, plus basic or detailed information on how AI is used and which data it draws on, not full technical detail. On a hypothetical supermarket AI system, nearly half struggled to specify requirements or preferred no information.
This consumer data highlights the value of personalised food recommendations. When these recommendations offer clear benefits, protect people’s privacy, and explain how data and AI are used in an understandable way, they can better respond to different consumer needs. This can help support the shift towards healthier and more sustainable food choices.
