Altruistic referrals are 86% more effective
Use an altruistic CTA for your referral program (“give $20 off to a friend”). It increases likelihood of referrals by 60% and total referrals by 86% compared to the most commonly used CTAs.
Today’s research is closely linked to a previous tip (Tianshu Sun is an author of both studies): Pre-fill referral messages to make them more effective.
The findings of this research build on a core human behavior we often forget about: we are much more altruistic - and less selfish - than we think. We love helping others.
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Previous tip: Increase social media engagement using these words (All tips here)
Use an altruistic message to make referral CTAs much more effective
Impacted metrics: Referrals | Website/app conversions
Channels: Word-of-mouth | Ecommerce sales
When asking customers to refer you, use the altruistic “Invite a friend to give them $20 off, you will get $20 too” rather than the selfish “Invite a friend to get $20 off, they will also get $20 off” or the commonly used “Invite a friend to both get $20 off”.
Try to ask for a referral right after the customer has purchased your product (or consumed it, depending on what you sell).
If you can segment your audience, target your referral campaign to loyal and/or highly satisfied customers (e.g. made repeat purchases) and a promotional campaign to repurchase to other customers.
The researchers tested the same offer (both the sender and recipient will always get 70% off) and compare different subject lines and CTAs when asking for a referral (see image below).
They find that an altruistic description of the referral (Subject: “Give your friend a 70% discount!” CTA: “your friend will get 70% off, you will also get 70% off”) is by far the most effective of all options.
The altruistic description increases by 60% the probability of a customer making at least one referral and the total number of referrals by 86% compared to the control option.
The effect is significantly higher on customers that have made at least 2 purchases, and an additional 73% higher for those that report high NPS scores.
In general, referral campaigns become less effective the more time passes after the last purchase.
Combining this with previous research, the best way to maximize growth is to target loyal and/or satisfied customers with the altruistic referral program, while targeting less loyal and satisfied customers with a promotion to repurchase or stop them from churning.
Why it works
Word-of-mouth (a referral) is by nature something we do altruistically because we think the other person would enjoy it. When we add a selfish financial incentive, the two incentives contrast each other and damage each other. As the authors say “it’s akin to mixing oil and water”.
Instead, describing a referral as something altruistic, reduces the senders’ guild from getting a financial reward.
It also encourages better targeting by senders, which then leads to higher overall conversion rates.
The researchers conducted the experiment mainly on a hobby collage website (Collage.com). That might make it riskier to generalize to other industries (e.g. Uber) or higher-priced products (e.g. Home, Pets, Education).
The study did not test different offers referral offers, such as only giving the benefit to the receiving friend. It only tested variations in describing the same offer.
Steps to implement
Update (or create) your referral CTA copy to emphasize the benefit it will give the receiver (“your friend will get X% off, you will also receive X% off”).
Test how well offering the discount/bonus only to the receiver works, which could help you reduce costs.
Online survey and market experiment (on 100,000 Collage.com users), United States
Jung, J., Bapna, R., Golden, J. M., & Sun, T. (May 2020). Words Matter! Toward a Prosocial Call-to-Action for Online Referral: Evidence from Two Field Experiments. Information Systems Research, 31(1), 16-36.
Fox School of Business and Management, Temple University; University of Minnesota; Collage.com; and Marshall School of Business, University of Southern California.
Remember: This research could be disproven in the future (although this is rare). It also may not be generalizable to your situation. If it’s a risky change, always test it on a small scale before rolling it out widely.
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