Understanding customer conversations in social media support interactions: divergent sentiments in material and experiential brands

Abstract

Purpose: This study aims to investigate how customer sentiments differ in social media interactions with customer support accounts of material and experiential brands. It seeks to understand the impact of these interactions on customer sentiment dynamics and their implications for customer support strategies.

Design/methodology/approach: Drawing on experiential recommendation literature, this study employs a sentiment analysis approach to analyze 60,000 tweets directed at customer support accounts of three experiential and three material brands on X (formerly known as Twitter). Regression analysis is also applied to investigate the influence of post characteristics and content types (e.g. emojis) on sentiment.

Findings: Results reveal significant differences between material and experiential brands in both overall sentiment and sentiment evolution during customer support interactions. Conversations with experiential brands exhibit more positive overall sentiments; whereas interactions with material brands demonstrate a greater positive sentiment shift despite initially exhibiting more negative sentiments. The findings also show that tweet length is a strong predictor of customer sentiment.

Originality/value: This research underscores the unique roles of material and experiential brands in shaping customer sentiment during social media interactions. The study provides novel insights into online customer support dynamics and offers actionable recommendations for improving after-sales management strategies in social media contexts.