Getting a “sweet” deal: does healthfulness of a sub-brand influence consumer loyalty?

Abstract

Purpose Increasing and maintaining the population’s consumption of healthful food may hinder the global obesity pandemic. The purpose of this paper is to empirically test whether it is possible for healthful sub-brands to achieve higher consumer behavioural loyalty than their less healthful counterparts. Design/methodology/approach The study analysed three years of consumer panel data detailing all purchases from five consumer goods categories for 15,000 UK households. The analysis uses best-practice techniques for measuring behavioural loyalty: double jeopardy, polarisation index, duplication of purchase and user profile comparisons. Each sub-brand’s healthfulness was objectively coded. Findings Despite the level of healthfulness, all sub-brands have predictable repeat purchase patterns, share customers as expected and have similar user profiles as each other. The size of the customer base, not nutrition content, is, by far, the biggest determinant of loyalty levels. Research limitations/implications Consumers do not show higher levels of loyalty to healthful sub-brands, or groups of healthful sub-brands. Nor do they buy less healthful sub-brands less often (as a “treat”). There are also no sub-groups of (health conscious) consumers who would only purchase healthful options. Practical implications Sub-brands do not have extraordinarily loyal or disloyal customers because of their healthfulness. Marketers need to focus on growing sub-brands by increasing their customer base, which will then naturally grow consumer loyalty towards them. Originality/value This research brings novel evidence-based knowledge to an emerging cross-disciplinary area of health marketing. This is the first study comparing behavioural loyalty and user profiles towards objectively defined healthful/less healthful sub-brands.

Analyzing proprietary, private label, and non-brands in fresh produce purchases

“…One questionable aspect of previous Dirichlet model deviations is the seemingly arbitrary 10% deviation benchmark (Anesbury, Nguyen, & Bogomolova, 2018;Kahn et al, 1988;Scriven et al, 2017). Our research, while using this approach, provides additional support for the work of Driesener et al (2017) who proposed using eight goodness-of-fit measures to provide a more robust determination of Dirichlet modeling.…”

“…When the difference between the observed behavior and theoretical behavior is greater than 10%, there is a deviation (e.g., if fewer consumers are buying a brand more often than theoretically expected, a niche classification). To be considered niche, the observed penetration is less than 10%, and the average purchase frequency is greater than 10% of that expected (Anesbury, Nguyen, & Bogomolova, 2018;Kahn et al, 1988;Scriven et al, 2017). Niche brands have a low market share because of their positioning to a small loyal customer base.…”

“…Alternatively, if consumers are buying a brand less frequently than expected, the brand is classified as a CoP. Therefore, the observed penetration is greater than 10%, and the average purchase frequency is less than 10% of that expected (Anesbury, Nguyen, & Bogomolova, 2018;Kahn et al, 1988;Scriven et al, 2017). There are three common causes of CoP deviations-seasonality, buying for others (Scriven et al, 2017), and variety seeking (Kahn et al, 1988).…”

“…Are proprietary, private label, and non-branded fresh produce bought as expected, given the DJ pattern? However, the 10% deviation proposed by Kahn et al (1988) and widely adopted (Anesbury, Nguyen, & Bogomolova, 2018;Scriven et al, 2017) is arbitrary (why not 5%, or 20%, or 50%? ), so we use a secondary approach.…”

“…DoP originated from research analyzing television channel viewer's loyalty, finding other factors (i.e., program content) had little influence Goodhardt, 1966). DoP also applies to radio listening (Lees & Wright, 2013) and FMCGs, including cereals (Anesbury, Nguyen, & Bogomolova, 2018), organic foods (Bryła, 2018), and fair trade coffee and tea (Winchester et al, 2015).…”