Paper Info
Title
Words Matter! Toward a Prosocial Call-to-Action for Online Referral: Evidence from Two Field Experiments
Abstract
AbstractThe underlying premise of referral marketing is to target existing ostensibly delighted customers to spread awareness and influence adoption of a focal product among their friends who are also likely to benefit from adopting the product. In other words, referral programs are designed to accelerate organic word-of-mouth (WOM) exposure using financial incentives. This poses a challenge, in that it mixes an intrinsically motivated process (stemming from the desire to share a customer’s delight with a product or a service) with an extrinsic trigger in the form of a financial incentive. In this paper, we demonstrate how firms can benefit from framing calls-to-action for referral programs in such a way as to move closer to the original intent of organic, intrinsically motivated WOM marketing, and yet at the same time reap the benefits of using a financial incentive to increase referral rates. In particular, via two large-scale randomized field experiment involving 100,000 customers each, we show the efficacy of a prosocial call-to-action over some of the more commonly used calls-to-action observed in practice. Additional mechanism-level analysis confirms the importance of an altruistic element in generating a higher quality of advocacy and reducing referral frictions.The underlying premise of referral marketing is to target existing, ostensibly delighted customers to spread awareness and influence adoption of a focal product among their friends who are also likely to benefit from adopting the product. In other words, referral programs are designed to accelerate organic word-of-mouth (WOM) exposure using financial incentives. This poses a challenge, in that it mixes an intrinsically motivated process (stemming from the desire to share a customer’s delight with a product or a service) with an extrinsic trigger in the form of a financial incentive. Prior research has shown that mixing intrinsic and extrinsic motivations can lead to suboptimal outcomes, which, in turn, presents a conceptual dilemma in the design of referral programs. In this paper, we demonstrate how firms can benefit from framing calls-to-action for referral programs in such a way as to move closer to the original intent of organic, intrinsically motivated WOM marketing and yet at the same time reap the benefits of using a financial incentive to increase referral rates. In particular, given a fixed incentive scheme, ceteris paribus, we show the efficacy of a prosocial call-to-action over some of the more commonly used calls-to-action observed in practice. We posit, and causally demonstrate via a large-scale randomized field experiment involving 100,000 customers, that an intrinsically prosocial element in framing the call-to-action to initiate the referral process is a necessary condition for success. When contrasted with egoistic and equitable framing of calls-to-action, the prosocial framing yields a significantly higher propensity to initiate a referral, as well as a significantly higher number of successful referrals. Additional mechanism-level analysis that interacts the treatments with customer characteristics such as repeat purchase, net promoter score, and time since last purchase, an additional field experiment with more attractive referral reward and an Amazon Mechanical Turk experiment confirm the importance of an altruistic element in generating a higher quality of advocacy and reducing referral frictions. Subjects in the prosocial group report lower levels of guilt associated with sending a referral and are more able to identify family and friends’ benefit as a motive for sharing referrals and therefore are more selective in sharing the referral message.
Year
DOI
Venue
2020
10.1287/isre.2019.0873
Periodicals
Keywords
DocType
Volume
online referrals, intrinsically prosocial framing, randomized field experiment, call-to-action
Journal
31
Issue
ISSN
Citations 
1
1526-5536
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
JaeHwuen Jung112.05
Ravi Bapna263160.76
Joseph M. Golden300.34
Tianshu Sun400.34