Applying qualitative approach to identify the characteristics of effective messages in eWOM communications. Issue 1 (22nd February 2022)

• Record Type: Journal Article
• Authors: Makvandi, Rosha; Farzin, Milad
• Is Part Of: Management matters. Volume 19:Issue 1(2022)
• Page Start: 1
• Page End: 12
• Publication Date: 2022-02-22
• Subjects: Electronic word of mouth -- Social networks sites -- Message effectiveness -- Thematic analysis; 658.005
• DOI: 10.1108/MANM-01-2022-0009
• Languages: English
• ISSNs: 2752-8359

Abstract

Abstract : Purpose: The present study aimed to identify the characteristics of effective messages in electronic word of mouth (eWOM) communication on social networks to be considered in the planning of eWOM strategies. For this purpose, the present study tries to identify these factors through a qualitative approach. Design/methodology/approach: A qualitative approach based on the thematic analysis was used with semi-structured interviews and opinions of 25 experts in the field of e-marketing and e-retailing. The collected data were analyzed and coded in the MaxQDA software. Findings: The results of the study showed the extracted seven main themes of message sender specifications, aesthetic appearance, choosing the right content, sending strategy, message usefulness, correct targeting, type of information and also 47 subthemes. These seven criteria provide a way to design the right strategies. Research limitations/implications: Limited studies in this area were a challenge and also integrating the opinions of the interviewees due to contradictory and different views, as well as unfamiliarity with some new approaches to digital marketing, were among the limitations of the present study that managed and controlled their effects. Practical and theoretical implications for developing and planning effective eWOMs in social networks presented. Originality/value: Understanding the way of creating appropriate features of effective and suitable messages in the planning of eWOM strategies is crucial to digital marketers. This study recommends considering the extracted features in designing effective messages.