Linguistic Elements of Engaging Customer Service Discourse on Social Media

TL;DR

This paper analyzes linguistic features of social media customer service interactions, demonstrating that initial responses' language style and content can predict engagement levels, thereby improving understanding of effective communication strategies.

Contribution

It introduces a novel analysis of linguistic and stylistic elements influencing engagement in social media customer service interactions, with predictive models based on initial posts.

Findings

Linguistic features like empathy and personalization correlate with higher engagement.

Initial responses can predict overall interaction engagement.

Stylistic elements significantly impact customer response and satisfaction.

Abstract

Customers are rapidly turning to social media for customer support. While brand agents on these platforms are motivated and well-intentioned to help and engage with customers, their efforts are often ignored if their initial response to the customer does not match a specific tone, style, or topic the customer is aiming to receive. The length of a conversation can reflect the effort and quality of the initial response made by a brand toward collaborating and helping consumers, even when the overall sentiment of the conversation might not be very positive. Thus, through this study, we aim to bridge this critical gap in the existing literature by analyzing language's content and stylistic aspects such as expressed empathy, psycho-linguistic features, dialogue tags, and metrics for quantifying personalization of the utterances that can influence the engagement of an interaction. This paper demonstrates that we can predict engagement using initial customer and brand posts.