Winning post strategies that generate engagement: A QCA approach
Abstract
Purpose: Fashion companies are using an increasing amount of resources to generate social media content to provoke an impact and engage customers. A wrong message or image – but also an inaccurate combination of the different elements that characterise a post – can jeopardise brand reputation. The way brands communicate with potential customers is of utmost importance as it creates its online identity and presence, and this is ultimately linked to customer loyalty. Given that a post contains different elements (e.g., image, people, background) this study seeks to explore which combination(s) of elements should brands take into account to generate superior user engagement with their posts.
Design/methodology/approach: After conducting a comprehensive literature review on social media marketing a set of critical factors that relate to content engagement are envisioned. Next, drawing on complexity and configuration theories, we perform fuzzy-set qualitative comparative analysis (fsQCA) to identify different strategies (i.e., combinations of critical factors) companies might follow to engage with customers successfully. The empirical application focuses on the Instagram activity of a retail clothing company.
Findings: The findings reveal that posts conducive to superior engagement should: (i) be simple, product-related or experience-related, (ii) use few but meaningful hashtags that are representative of the brand, (iii) show people’s faces, and (iv) send an inclusive message.
Practical implications: This study sheds new light on how brands should communicate on social media networks to generate improved impact for their posts.
Originality/value: This study goes beyond traditional approaches that overlook the joint effect of the different strategic design choices (i.e., combination of critical factors) for posts on the outcomes of interest (in our case, number of likes, comments and views).
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PDFDOI: https://doi.org/10.3926/ic.2267
This work is licensed under a Creative Commons Attribution 4.0 International License
Intangible Capital, 2004-2024
Online ISSN: 1697-9818; Print ISSN: 2014-3214; DL: B-33375-2004
Publisher: OmniaScience