Measuring social media customer engagement with brands based on information entropy: an application case of luxury brand
Siwei Xiao & Xiaoyu Chen
Abstract
Customer engagement (CE) within social media has emerged as a focal point in marketing research due to its significant impact on brand and firm-related outcomes. However, effective measurement methodologies for CE behaviours remain underexplored in this context. Building upon the existing concept of CE behaviour proposed by Brodie et al. (J Serv Res 14(3):252–271, 2013), and the CE cycle theory, this paper introduces an operational definition that supports an entropy-based CE behaviour measurement framework, offering a nuanced reflection of social media dynamics. The proposed measurement approach, among the initial attempts to integrate the multi-criteria decision-making (MCDM) weighting method into brand marketing analytics, ensures a reliable and rigorous assessment of CE performance with brands. Additionally, a range of analytical methods, including regression modelling using dummy variables, sentiment analysis, and hierarchical clustering algorithm, were synthesized to assist the objective evaluation of brands’ impacts on CE behaviour outcomes. A peer group of six luxury brands were chosen to analyse their impacts on engagement performance independently. Key findings from this application demonstrate the approach’s ability to compare the engagement performance of different brands, offering a significant tool to differentiate engagement behaviour levels while providing actionable insights for brand marketing initiatives.
11 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.57 × 0.4 = 0.23 |
| M · momentum | 0.78 × 0.15 = 0.12 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.