The application of secondary data in food labelling research has gained substantial traction. This trend is due to due to the increasing availability of large-scale datasets from retailers, consumer analytics companies, and public health organizations. As opportunities from the data-rich food retail industry increase, the ability to examine real-world impact of health-focused food labelling systems through existing data remains a scalable and cost-effective alternative to primary research (Smith & Thompson, 2023).

Sources of secondary data include consumers’ online purchasing habits (intent data), point-of-sale data, customer satisfaction surveys, consumer loyalty card transactions, and market research reports. Jackson and Barnes (2022) noted that these datasets offer longitudinal insights into the impact of health-focused labels on consumer purchasing behaviour across different demographic segments and within a period. A remarkable example is the study by Braesco, V. and Drewnowski (2023). The scholars examined data extracted from Tesco sales across multiple branches for a period of twelve months. In their findings from the study, they asserted that health-labelled products, particularly those with “light traffic labelling (TLL) system,” attract higher purchase rates in stores that actively run educational in-store campaigns such as mounting “Healthy Choices” signage and designing nutrition advice booths. Thus, supporting food labels with other store-level interventions can nudge consumers towards healthier options.

Similarly, another empirical study by Priya and Alur, (2023) found that integrating loyalty card data (such as Tesco’s Clubcard programme) with label exposure has a significant impact on consumer behaviour. The scholars further emphasized individuals who consistently purchased products with green or amber nutritional labels have higher chances of engaging with targeted health promotions and promotional digital content (e.g., emails recommending lower-sugar alternatives). The study used segmentation of customer types based on responsiveness to labelling, a method which they concluded with evidence-based data can support health-driven interventions.

Bryant and Halford (2022) added that use of secondary data in food labelling studies not only reveals what consumers buy from retailers but also offers deep insight into buyers’ locations and reason for their shopping behaviours. The datasets are crucial for refining product placement and timing promotional activities. For example, an analysis of basket composition pre- and post-label implementation also provides compelling evidence of behavioural shifts among consumers influenced by label visibility and accessibility.

Tesco also explores its own internal analytics to assess the potential of data-driven evaluation. The retail brand uses intent data from advanced analytical tools to track uptake of labelled products in various regions across the United Kingdom, including Middlesbrough. Such insights reveal that the effectiveness of food labels varies with educational attainment, cultural food norms, and local income levels. Therefore, studies relating to health-focused food labels and consumer behaviour underscore the importance of contextualizing secondary data and applying geospatial and demographic filters in analysis.

Researchers also noted that secondary data has certain limitations. O’Reilly and Patel (2022) pointed out that retailers and researchers often gather datasets for commercial purposes such as strengthening competitive advantage and creating sustainable profits, rather than knowledge-based benefits. This conflict of interest potentially limits variable control and data transparency. The scholars also argued that causality is difficult to establish when there are no complementary qualitative insights such as interviews or observational studies. However, secondary data provides a robust perspective for understanding past and future trends, as well as real-time consumer behaviour towards food labels when supported with other research methods. The research approach with the new shift toward evidence-based public health policy research. Integrating large datasets from business environments like supermarkets can inform strategic decisions on nutrition labelling, product placement, and marketing activities.

In sum, secondary data analysis is an effective tool for evaluating the effectiveness of health-focused food labels, particularly in settings like Tesco supermarkets, where customer interaction data are easily accessible. Integration of secondary data, thus, empowers researchers to analyse a vast, dynamic population, and supports a deeper understanding of how consumers in diverse, real-world retail environments react to health-focused food labels.