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Referral Incentives in Crowdfunding

Victor Naroditskiy (), Sebastian Stein (), Mirco Tonin, Tran-Thanh, Long (), Michael Vlassopoulos () and Nicholas R. Jennings
Additional contact information
Victor Naroditskiy: University of Southampton
Sebastian Stein: University of Southampton
Tran-Thanh, Long: University of Southampton
Nicholas R. Jennings: University of Southampton

No 7995, IZA Discussion Papers from Institute of Labor Economics (IZA)

Abstract: Word-of-mouth, referral, or viral marketing is a highly sought-after way of advertising. We undertake a field experiment that compares incentive mechanisms for encouraging social media shares to support a given cause. Our experiment takes place on a website set up to promote a fundraising drive by a large cancer research charity. Site visitors who choose to sign up to support the cause are then asked to spread the word about the cause on Facebook, Twitter or other channels. Visitors are randomly assigned to one of four treatments that differ in the way social sharing activities are incentivised. Under the control treatment, no extra incentive is provided. Under two of the other mechanisms, the sharers are offered a fixed number of points that help take the campaign further. We compare low and high levels of such incentives for direct referrals. In the final treatment, we adopt a multi-level incentive mechanism that rewards direct as well as indirect referrals (where referred contacts refer others). We find that providing high level of incentives results in a statistically significant increase in sharing behaviour and resulting signups. Our data does not indicate a statistically significant increase for the low and recursive incentive mechanisms.

Keywords: referral marketing; crowdfunding (search for similar items in EconPapers)
JEL-codes: C93 D64 L31 M31 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-exp, nep-mkt and nep-soc
Date: 2014-02
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Published in: Proceedings of the Second AAAI Conference on Human Computation and Crowdsourcing, 2014, 171-183

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