DIGITAL PROMOTION CHANNELS AND FITNESS MEMBERSHIP PURCHASE INTENTION

Abstract

The digitalisation of fitness-industry communications has transformed the membership purchase
decision from a predominantly offline choice into a multi-step process mediated by social networks, user reviews,
influencer marketing and location-based search platforms. This study empirically assesses which digital channels and
content types are most strongly associated with Kazakhstani consumers’ intention to purchase a fitness club membership,
and how perceived source trust mediates this process. Drawing on a survey of 77 respondents from a digital audience
predominantly connected to Almaty, the study performs correlation and multiple-regression analyses linking channel
exposure frequency, channel trust, content influence and influencer-marketing attitudes to purchase intention,
complemented by thematic analysis of open-ended responses. The intention scale showed high internal consistency (α =
0.959). The results indicate that the strongest associations with intention are produced not by the most visible channels
(Instagram, TikTok, paid targeting) but by independent verification channels — official websites (r = 0.634), 2GIS/Google
Maps listings (r = 0.562) and user reviews (r = 0.519). The multiple regression model explains 52% of the variance in
intention, with the consumer’s perceived ability to distinguish a genuine blogger recommendation from a paid integration
emerging as the most stable predictor (β = 0.295; p = 0.024). On this basis, the study proposes a conceptual model of
perceived digital trustworthiness, in which channel effectiveness is determined not by reach but by the channel’s capacity
to deliver transparency, verifiability and authenticity. The scientific contribution lies in the comparative empirical
assessment of seven channels within a single sample and in the formalisation of a latent mediator. The practical
contribution is a recommendation for Kazakhstani fitness clubs to shift from advertising volume toward the quality of
reputational infrastructure — open pricing, populated reviews, realistic visuals and clear communication.