Having taken a backseat during the cost-of-living crisis, health and well-being is poised to rise in importance as consumer finances gradually improve. The home is central to a healthy lifestyle, yet three-quarters of UK adults struggle to maintain their health and wellness within their own spaces.
Motivation and financial constraints are the primary obstacles, with the extent of their impact varying by demographic. Consumers also remain sceptical about the credibility of products marketed as promoting health and wellness at home, with nearly three-quarters believing such products should have scientific evidence to support their claims.
Science-backed solutions that can be seamlessly integrated into daily routines are well-placed to encourage adoption. As health and wellness priorities and challenges vary across different demographics, brands acknowledging these diverse needs and embracing individuality have the potential to forge meaningful connections with their customers.
A renewed emphasis on health and wellbeing has led consumers to incorporate this focus into various aspects of their lives, with the home serving as a cornerstone.
Sam Nguyen, Retail Analyst
Mintel commissioned consumer research for this Report to assess consumer attitudes and behaviours towards health and wellness in the home. Research was carried out by Kantar Profiles among 1,952 internet users aged 18+ in September 2024. Detailed demographics are given in the Interactive Databook.
CHAID methodology
CHAID (Chi-squared Automatic Interaction Detection) is a target group identification method that is used to highlight key target groups. CHAID is a classification system that subdivides the sample into a series of subgroups that share similar characteristics towards a specific response variable and allows us to identify which combinations have the highest response rates for the target variable. The first predictor category (on which the sample will be split) is the predictor that is associated the most with the response variable. i.e. it gives the most differentiating groups of respondents. Each subgroup is then further split until the analysis does not find any significantly discriminating predictor any more. The output is a tree of which the branches are the predictor variables that split the sample in discriminating groups.
For further details see the research methodology.
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