Conflict or interest? Using consumer purchase data to support food systems transformation

Population dietary behaviours have considerable impact on major global challenges including diet-related non-communicable diseases, climate change, and food insecurity. Aligning diets with national recommendations, such as the UK Eatwell Guide, have the potential to deliver substantial co-benefits for health and environmental sustainability. To accelerate progress, scalable and timely methods for monitoring dietary patterns are required. Routinely generated smart data, such as supermarket transaction records and loyalty card purchases, represent a novel resource for population-level dietary assessment. These datasets provide objective, high-resolution, and near real-time information on food purchasing behaviours. However, deriving meaningful nutrition insights from such data necessitates advanced computational infrastructure, data science and AI capability, and specialist nutrition interpretation. Importantly, these data enable evaluation of natural experiments in real-world food environments. The use of commercial sales data introduces unique governance and data-security challenges. Commercial sensitivity requires robust secure-data environments, transparent processes, and strong collaborative partnerships between industry and academia. Effective data sharing is contingent on champions within both sectors, as such collaboration is not yet routine. When appropriately governed, consumer purchase data can complement traditional dietary assessment methods and support transformation of the wider food system. This review paper presents academic and industry insights on the use of these novel data sources, highlighting methodological challenges associated with nutrition, health and sustainability metrics. It concludes with recommendations to guide future research employing consumer purchasing data to strengthen evidence generation across the food and population and planetary health landscape.