Refocusing loyalty programs in the era of big data: a societal lens paradigm

Stourm, Valeria; Neslin, Scott A.; Bradlow, Eric T.; Breugelmans, Els; Chun, So Yeon; Gardete, Pedro M.; Kannan, P.K.; Kopalle, Praveen K.; Park, Young-Hoon; Amariles, David Restrepo; Thomadsen, Raphael; Liu‐Thompkins, Yuping; Venkatesan, Rajkumar

doi:10.1007/s11002-020-09523-x

Cited by 19 publications

(10 citation statements)

References 28 publications

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“…As Moon (2000) argued, reciprocal dialogues emerge first and foremost in one-to-one customer-company exchanges. Extant research and meta-analyses exist on the “one-to-many” or cumulative rewards such as loyalty programs (for extensive overviews see Kumar and Shah, 2004; Otto et al , 2020; Palmatier et al , 2006; Stourm et al , 2020; Watson et al , 2015) and their effectiveness for customer metrics, such as share-of-wallet or profitability. This study adds to relationship marketing literature by showing that situational customer spending can be triggered by dynamic, reciprocal exchanges between the customer and the company (i.e.…”

Section: Discussionmentioning

confidence: 99%

“…Some companies cannot or do not want to launch loyalty programs though as these programs often fail to perform as expected (Bombaij and Dekimpe, 2020;Wang and Lalwani, 2019). Loyalty programs have also been criticized to potentially infringe on customer privacy (Stourm et al, 2020). Different to such institutionalized programs, this study explores alternatives for rewarding customers understanding that customer-company relationships involve social exchanges based on reciprocity (Henderson et al, 2011).…”

Section: Loyal Customers' Spendingmentioning

confidence: 99%

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Loyal customers’ tipping points of spending for services: a reciprocity perspective

Teichmann

2021

EJM

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Purpose Controversy exists about the shape of the relationship between loyalty and profitability. This paper aims to address the possibly nonlinear effects of behavioral loyalty (BLOY) on customer spending (as a proxy for profitability). Building on social exchange theory and the norm of reciprocity, it examines the asymmetries between BLOY and customer spending and the moderating influence of personal communication (PCOMM) as a social reward and dispositional positive reciprocity as process evidence. Design/methodology/approach Study 1a (n = 309) gathered customer data from four restaurants and Study 1b (n = 252) data from hotel guests after they checked out. Study 2 is an experimental study with two manipulated factors BLOY and PCOMM). In total, 295 participants from a large German online panel completed the study. Findings The results indicate an inverted-U shaped relationship between BLOY and customer spending: after reaching a turning point, customers gradually curb spending as their BLOY further increases. High PCOMM acts as a reciprocal response while triggering additional customer spending particularly at higher levels of behavioral loyalty; positive reciprocity adjusts the differences in customer spending when social rewards such as PCOMM are present. Research limitations/implications The asymmetric relationship between BLOY and customer spending is tested only for hedonic service settings. Practical implications Not all loyal customers spend more – companies need to meet their reciprocal obligations before they can benefit from increased customer spending. Originality/value The present research re-considers the nature of the relationship between BLOY and customer spending and reveals an inverted-U shaped relationship, with a turning point beyond which greater customer loyalty decreases customer spending. It finds converging process evidence for the mechanism of reciprocity underlying this relationship. This study also details the financial impact of BLOY on the firm by investigating actual customer spending.

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Section: Discussionmentioning

confidence: 99%

Section: Loyal Customers' Spendingmentioning

confidence: 99%

Loyal customers’ tipping points of spending for services: a reciprocity perspective

Teichmann

2021

EJM

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“…Digital marketing has opened many opportunities for B2B marketers; however, scholarly research in this area is still at the embryonic stage (Vieira et al, 2019). Online schemes capture detailed customer information through various interactions across all channels -also known as big data (Stourm et al, 2020), through the integration of intelligent analytics and communication technology (Saura et al, 2017). Apart from interactive tools to connect with consumers (Chaffey & Smith, 2017), big data helps generate precise insights reflecting customers' behaviour (Pandey & Gudipudi, 2019).…”

Section: Loyalty Programmes In Digital Marketingmentioning

confidence: 99%

Digital Loyalty Programmes

Marjan

Graham

Bruce

et al. 2021

Advances in Marketing, Customer Relationship Management, and E-Services

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Digital loyalty programmes are an increasingly common tool for business-to-business marketers hoping to increase repeat sales through deeper customer engagement. In consumer markets, such programmes do little to influence behavioural loyalty and disproportionately attract the firm's existing heavy buyers. Industrial buying, however, relies on direct sales channels and features negotiation and reciprocity. Loyalty effects may therefore differ in B2B, and although no clear picture yet exists, such knowledge is important as B2C digital loyalty programmes grow in popularity. Here, the authors describe programme membership's evolving characteristics over in a B2B scheme that was launched in the US metal-cutting tools manufacturer customer base. Findings are consistent with the idea that the scheme recruited the heaviest buyers earliest and had an insignificant effect on total revenue. The authors discuss managerial implications, particularly about (1) managing the rollout of similar schemes and (2) refocussing on the programme objectives to maintain sales from the lightest rather than the heaviest buyers.

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“…The urgency of this research is that loyalty programs in banking need to look at the dynamics of female consumers, especially when digital businesses dominate marketing transactions. Big data and technological change have made loyalty programs more common and complex (Stourm et al, 2020). Even though there is a potentially harmful effect on loyalty programs (Baker and Legendre, 2021), and this study is still fragmented, quite a lot has been studied (Kim et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Understanding Female Segments Based on Benefit of Loyalty Program

Sutarso,

Sekarsari,

Ilfitiah

et al. 2023

JAM

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Loyalty programs in banking need to look at the dynamics of female consumers, especially when digital businesses dominate marketing transactions. In the literature, segmentation studies are mostly carried out on retail services, airlines, and hotels, which are rare in banking, especially related to loyalty program services. Therefore, this study is expected to close the gap without a segmentation study in a banking context. This study aims to identify the female customer segment by assessing the bank's loyalty program and relating it to its perceived convenience, security, and reliability. The study employed the two most prominent banks in Indonesia, with 208 female customers as respondents. The purposive sampling method was used as a method of selecting samples. Data were reduced using factor analysis and categorized using cluster analysis. The main result identifies four factors underlying the benefits of loyalty programs: quality of communication, policy, rewards, and website quality. Three segments of loyalty program female consumers were identified: apathetic (25%), active (31%), and passive segments (44%). In further analysis, three segments of females were analyzed regarding the bank saving account's convenience, reliability, and security. Results confirm that all three segments were unique and distinguished one from another. This study's implication guides managing the types of female customers at the bank, especially loyalty programs.

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Refocusing loyalty programs in the era of big data: a societal lens paradigm

Cited by 19 publications

References 28 publications

Loyal customers’ tipping points of spending for services: a reciprocity perspective

Loyal customers’ tipping points of spending for services: a reciprocity perspective

Digital Loyalty Programmes

Understanding Female Segments Based on Benefit of Loyalty Program

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