Get more referrals by rewarding your customers the right way
The best refer-a-friend program motivates your customers to share your product or service with their friends. Your Customers’ friends then visit you site and are driven to become new customers. But, you need to balance the interests of three key players to get maximum results.
The three important elements are, (1) The interests of your company, (2) the interests of your existing customers and (3) the interests of your customers’ friends.
The most critical element is your customers’ Metacognition. I.e. How do they think they will be perceived by their friends when they go out and promote your business with your refer-a-friend program. While that is the core of Recommend.to’s automatic incentive optimization, let’s consider how you can manually optimize your refer-a-friend program.
While automatic optimization lies at the core of Recommend.to, let’s consider how you can manually optimize your referral program.
How much will it cost?
Setup: Setting up a refer-a-friend program is often perceived to be difficult. Time and personal need to use additional software and tamper with established processes. Luckily, Recommend.to strives to be the easiest to implement and the expected return on investment usually justifies short term costs.
Monetary Incentives: Determining the amount of money you can offer your customers for a successful referral depends on your customer acquisition cost (CAC) and customer lifetime value (CLV). You can calculate your CAC and CLV with this guide.
In essence, you should always pay less for acquiring a new customer via a referral than that customer is worth to your business. But don’t worry, Recommend.to automatically finds the optimal value for optimizing referral success and revenue. Just give us the key metrics, and our system will find the optimal values for maximum referral counts, conversion rate and revenue.
Non-Monetary incentives: Money isn’t always the most effective incentive. You can also offer discounts, internal credit or coupons to incentivize referrals. Deciding on the options depends on your understanding of your customer. Ask yourself (or your customers) what they like most about your product.
For a cloud accounting company like FastBill, it may be having prolonged access to writing beautiful invoices. For other businesses, it may be getting more nuts in their next Health Box.
Warning: Always consider the monetary repercussions before choosing non-monetary incentives, like lost revenue and higher overhead costs. You should also test which incentives your customers prefer by either asking them directly or running surveys. We prefer on testing all possible incentives and check how each of them stimulates referrals, clicks, and conversions.
What Return can I expect from a refer-a-friend program?
Here are some numbers regarding refer-a-friend programs collected from public information. Keep in mind that your results will differ based on the amount of optimization.
Optimal Incentive Structure for your refer-a-friend partner program:
Which incentive structure will drive the most shares and referral successes? The amount of incentive structures is virtually limitless, but they group into four varieties.
- Both: Referrer and Referrer’s Friend get a reward
- Only Referrer: Only Referrer gets reward
- Only Friend: Only Referrer’s Friend gets reward
- No Incentive: No one gets an immediate reward
Shared and “referrer only” rewards are the most common incentive structures. However, much depends on the idea that people have about how they are perceived when they go out and promote your business . Much of that consideration hinges on the perceived risk associated with your brand.
Imagine you tell all your friends about an unknown company you like. Chances are, you are a bit hesitant, given your limited experience with a company that is fresh in the marketplace and has a limited positive track record. Compared to an established brand with a long track record, a startup may need to put in a stronger incentive to get shared.
This “Brand-Strength Effect” and “referral incentive structure preference” is exactly what Ryu & Feick (2007) have found in their study . As you can see in the figure below, when your brand is weak (less known), rewarding the referrer or rewarding both increases referral likelihood. Strong brands on the other hand should expect a significantly higher referral rate when both, the referrer and the referrers’ friends are rewarded.
Penny for Your Thoughts: Referral Reward Programs and Referral Likelihood, Journal of Marke.ng, 2007
However, every Startup and every customer is different. Brand strength can change quickly or may be differently perceived by certain individuals. For example, your brand may get a big publicity boost because it just appeared on TechCrunch changing the current brand strength.
That’s why constant automatic testing and optimization on an average customer and individual customer level are key to finding the incentive structure that delivers the highest returns. But if you don’t want recommend.to to do the continuous optimization for you, just use this decision tree to find the best incentive structure and reward scheme.
Conclusion: Finding the ideal incentive combination for your Refer-a-Friend program
Imagine you are a startup, e.g. SendAndStore. If you have the manpower to test multiple incentive variants, you create different versions with each of the 4 incentive structures and different incentives (monetary, non-monetary etc.). For example, “BOX FOR BOX. Invite a friend to try SendAndStore and when your friend gets his first box, both of you receive a free Box credit”. This would be the “both receive an incentive”-structure with a non-monetary incentive. Given the amount of incentives you want to offer, there are many different versions possible.
Thus, if you are limited in your testing infrastructure, use the above decision tree. SendAndStore is not a strong brand yet, so both sides should receive a reward. Depending on the CLV / CAC situation, choose a monetary (CLV > CAC) or non-monetary (CLV< CAC) incentive and measure how your customers behave.
What’s next for recommend.to and you?
We are currently testing the latest recommendation optimization engine on www.FastBill.com. Once we have analyzed the data we’ll share what we’ve learned. Now, how about you? With which incentive structure did you find the best results?
Originally published at blog.recommend.to on June 1, 2015.