The relational benefits of personalized communications in an online environment

Abstract

This research investigates how personalized communications enhance customer-company relationships, which ultimately produce favourable marketing outcomes. Two factors were manipulated in an online experiment: the perceived effort made by customers to obtain a personalized newsletter (high vs. low) and the level of relevance of the message (high vs. low). The results indicate that perceived effort positively affects calculative commitment (even more so for highly involved customers), while the level of relevance of the message increases affective commitment. In addition, the interaction between perceived effort and message relevance has significant effects on calculative and affective commitment. Finally, affective commitment partially mediates the relationships between relevance and both loyalty and word-of-mouth intentions. Managerial implications regarding the best usage of personalized communications are discussed.

Affective commitment and future purchase intentions in the performing arts: An empirical approach

“…The customer will therefore be concerned about what happens to the company and recommend its services to acquaintances. Consistent with previous research on affective commitment and loyalty (Dantas & Carrillat, ; Fullerton, , ), our findings demonstrate that increasing affective commitment has a direct effect on consumers' future plans.…”

Piloting personalization research through data-rich environments: a literature review and future research agenda

“…Real-time learning involves the collection of data during consumer journeys as they take place and its immediate usage for personalization, whereas retrospective learning implies reconnecting to data collected during previous consumer-firm interactions and interpreting after firm-consumer interactions (e.g. analyzing and interpreting one's collected purchase history or web surfing patterns over time) (Dantas and Carrillat, 2013; Thirumalai and Sinha, 2009). 49.6% ( n = 67) of the articles in our set refer to timing of learning (28.1% focuses on retrospective learning only, 6.7% focuses on real-time learning , and 14.8% considers the combination – see Table 2).…”

“…More particularly, we discern digital, physical, and human touchpoints. Digital tailoring involves adapting technology-driven touchpoints like emails (Sahni et al ., 2018; Song et al ., 2016), electronic/mobile news/newsletters (Chung et al ., 2016; Dantas and Carrillat, 2013), online interactions (Thirumalai and Sinha, 2009; Pappas et al ., 2016), websites (Benlian, 2015; Nath and Mckechnie, 2016), and mobile apps (Guo et al ., 2016; Kang and Namkung, 2019). When it relates to online or mobile channels, firms can achieve digital tailoring through personalized promotions, including personalized offers and coupons (Pappas, 2018; Wierich and Zielke, 2014), personalized recommendations (Whang and Im, 2018), programmatic advertising (i.e.…”