Towards digital loyalty programs: insights from customer medium preference segmentation

Abstract

Purpose The purpose of this paper is to identify patterns of medium preference for loyalty programs (LPs) among members to support the case for segmenting customers based on their medium preference. Design/methodology/approach A survey of nearly 2,000 customers who are enrolled in at least one supermarket LP was employed. LP members are segmented based on a latent class clustering model and then profiled in terms of socio-demographic variables by means of a multinomial logit regression model. Findings Medium preference is heterogeneous and differs at the customer segment and at the LP touchpoint level. Five segments emerge which display different medium preference patterns. LP medium preference is associated with age, gender, affluency and number of different LPs the customer is enrolled in. Practical implications Retailers, e-tailers and brands can benefit from this customer segmentation when faced with the challenges of adding online features or migrating their LPs online. Marketers should differentiate their investment in online and offline LP touchpoints according to the medium preference for each LP touchpoint of the customer segments of interest. Originality/value Retailers, e-tailers and brands are today introducing online marketing strategies and tactics, such as LPs, that have been traditionally used offline. So far, however, they have failed to answer the question whether online and offline LPs and related touchpoints have the same preference among consumers. Literature on LPs has not explored customer preference for the LP medium or the consumer characteristics related to medium preference. This work is unique in providing an overview of medium preference for LPs and their touchpoints.

Determinants of e-commerce satisfaction: a comparative study between Romania and Moldova

“…On the other hand, referring only to Romania, the consumers in this country are sensitive to factors such as the existence of periodic notification system, the reviews from previous customers, the possibility to use different payment methods, the ease of use of the web platform and the product customization feature. These results refute some previous partial research (Nisarz and Prabhakar, 2017;Phuong and Trang, 2018;Kumar and Johari, 2015;Lightner, 2004;Banerjee and Karforma, 2008;Zuo et al, 2013;Siraj et al, 2020;Relas, 2019;Elmorshidy, 2013;Bressolles and Durrieu, 2011;Choi et al, 2019;Consoli, 2017;eMAG, 2021;ITGalaxy, 2021;Tahal, 2014;Ieva and Ziliani, 2017;He et al, 2019). Thus, e-commerce companies that want to focus on the Romanian market do not have to allocate resources for aspects such as in-app after sales services, the live consultant support, price comparison tools or loyalty programs.…”

“…),Sulastri et al (2019),Kumar and Johari (2015) H3The possibility to cancel the order in a e-commerce application has a significant impact on e-commerce satisfaction levelLightner (2004),Banerjee and Karforma (2008),Zuo et al (2013) H4The existence of live consultant support has a significant impact on e-commerce satisfaction levelSiraj et al (2020), Relas (2019), Elmorshidy (2013) H5 The existence of price comparators has a significant impact on e-commerce satisfaction level Bressolles and Durrieu (2011), Choi et al (2019), Consoli (2017) H6 The existence of the reviews from previous customers has a significant impact on e-commerce satisfaction level Park and Lee (2009), Anastasiei and Dospinescu (2018), Lopes et al (2020); D'Acunto et al (2020), Ventre and Kolbe (2020) H7 The diversity of payment methods has a significant impact on e-commerce satisfaction level Khalid et al (2018), Rasli et al (2018), Ladkoom and Thanasopon (2020)H8The ease of use of the web platform has a significant impact on e-commerce satisfaction levelNisarz and Prabhakar (2017),Phuong and Trang (2018),Vijai and Nivetha (2020),Lula et al (2021), Ahmad and Khan (2017) H9The existence of package opening on delivery option has a significant impact on e-commerce satisfaction levelRasli et al (2018), eMAG (2021, ITGalaxy(2021)H10The product customization feature has a significant impact on e-commerce satisfaction levelPallant et al (2020), Guercini et al (2018), Bourlakis et al (2018)H11The existence of loyalty programs has a significant impact on e-commerce satisfaction levelTahal (2014),Ieva and Ziliani (2017), He et al…”

Clustering consumers' shopping journeys: eye tracking fashion m-retail

“…Customer segmentation is often based on demographics and reported usage activities. Digital consumer segmentation has been based on Internet usage, perceived risks, website attributes, intent to do online purchase in future, preference for website attributes (Mathew, 2016), recalled reach and frequency of exposure to the touch points (Ieva and Ziliani, 2018) and patterns of medium preference for loyalty programmes accompanied by socio-demographics (Ieva and Ziliani, 2017). Within the mobile consumer group, researchers are looking for new segmentation approaches which would more directly reflect actual customer activities on smartphones.…”

Digital or human touchpoints? Insights from consumer-facing in-store services

“…other customers, review sites, peer influences, environments) that may influence the shopping experience. Therefore, understanding, implementing and balancing different touchpoints (both human and digital) in each stage of the shopping journey is emerging as a key challenge for retailers, who need to maximize customer satisfaction and loyalty during the shopping journey (Baxendale et al, 2015;Straker et al 2015;Wind and Hays, 2016;Ieva and Ziliani, 2017).…”

“…Examples of the different typologies of touchpoints are smartphones and mobile apps, catalogs loyalty programs, e-mail, display ads, humanoid shopping assistants, and so on. (Baxendale et al, 2015;Bertacchini et al, 2017;Broussard, 2016;Li and Kannan, 2014;Straker et al 2015;Wind and Hays, 2016;Ieva and Ziliani, 2017). In particular, retailers introduce digital touchpoints to provide consumers with access to additional information on products to support them in finding, comparing, locating and buying goods, while enhancing their shopping experiences with entertaining and relaxing services (Van Kerrebroeck et al, 2017).…”