The world’s first large-scale voluntary panel that contributes digital receipt data from loyalty cards anonymously to assess the data’s potential to predict dietary behaviour automatically
The Receipt2Nutrition research project aims to develop a novel and scalable approach for delivering individual-level dietary monitoring by applying data science on automatically captured digital receipts.
- Digital Receipts: Shopping data used only includes product names, prices, and date of purchase. Hence, sales data first needs to have nutritional facts. For this, Auto-ID Lab has developed and maintained a product ingredient database, which now contains more than 30’000 most frequent Swiss products.
- FFQ: Sales data enriched with nutritional information is compared to the actual dietary intake. The latter is obtained through a Food Frequency Questionnaire (FFQ), which investigates into participants’ diet in the previous month for elaborating the usual dietary intake.
- Personas: anonymous users’ descriptions (socio-demographics, shopping and dietary behavior) help understanding more patterns for developing a reliable model.