Rewards or Upgrades? Incentive Designs in Referral Programs

40 Pages Posted: 4 Apr 2022

See all articles by Chenguang (Allen) Wu

Chenguang (Allen) Wu

Hong Kong University of Science & Technology (HKUST)

Chen Jin

National University of Singapore (NUS) - Department of Information Systems and Analytics

Ying-Ju Chen

Hong Kong University of Science & Technology (HKUST) - Department of Information Systems, Business Statistics and Operations Management

Date Written: July 30, 2024

Abstract

Referral programs are a popular strategy to enhance public awareness and drive sales of new products. These programs offer incentives to invite purchasing customers to refer their friends. These incentives are made in the form of monetary rewards in traditional referral programs. In this paper, we introduce a referralupgrade strategy, allowing incentives to be made in the quality dimension. Specifically, the firm sells a basic product and offers a free upgrade to a high-quality version if the referral generates new purchases. We first demonstrate the limitations of offering upgrades exclusively through referrals and then explore scenarios in which customers can return to purchasing the upgrade if their referrals are unsuccessful. Allowing customers to make multiple referrals, we introduce a referral reachability metric to measure potential overlaps in customer networks. We show that our proposed referral-upgrade program can be more profitable than the traditional referral-reward programs under a high referral reachability, a low referral cost, and a low referral cap. Moreover, the relative difference between these two referral programs is non-monotone in the referral cap, suggesting firms can achieve the most gains from offering quality incentives under intermediate values of the referral cap.

Keywords: referral-upgrade, referral-reward, product design, pricing

Suggested Citation

Wu, Chenguang (Allen) and Jin, Chen and Chen, Ying-Ju, Rewards or Upgrades? Incentive Designs in Referral Programs (July 30, 2024). Available at SSRN: https://ssrn.com/abstract=4052385 or http://dx.doi.org/10.2139/ssrn.4052385

Chenguang (Allen) Wu (Contact Author)

Hong Kong University of Science & Technology (HKUST) ( email )

Room 5559A, Academic Building
Hong Kong

Chen Jin

National University of Singapore (NUS) - Department of Information Systems and Analytics ( email )

Singapore

Ying-Ju Chen

Hong Kong University of Science & Technology (HKUST) - Department of Information Systems, Business Statistics and Operations Management ( email )

Clear Water Bay
Kowloon
Hong Kong

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