Why a "skip ahead N positions after referral" ranking algorithm is bad for your users

In Prefinery, you can specify how you'd like your users to be ranked in the leaderboard or waitlist. This is especially useful if you're looking to give priority to top-ranking users for beta invitations or if you're simply running a contest.

One of our available ranking algorithms is "Skip ahead N positions after referral" where, as it's aptly named, a user can move up the ladder, skipping over other users in multiple positions with each referral.

While this is a common idea among marketers when it comes to structuring their pre-launch campaign, it creates a terrible experience for your users.

For the benefit of your users, we recommend that you do NOT use this algorithm, and instead reward people for their efforts in referring friends by choosing either the "Order by total referrals" or "Order by most points" algorithm.

For users who joined late in big campaigns

In huge campaigns (for example 100k+ users), moving up the queue by a fixed number of positions can lead to someone who signed up late, but referred many friends, to still be placed behind someone who simply got in line weeks or months earlier as it is difficult to overcome a head start when dealing with long waitlist queues.

For example, in the first 30 days the campaign attracts 100,000 users to the waitlist. Along comes John who is initially ranked at #100,000. He is super excited and does a lot of referring, but each referral only allows him to skip ahead 5 spots. He is a very active referrer and referred 100 friends, more referrals than that of the currently top 5 users combined. Now, he’s at position #99,500 and is super frustrated.

For users who joined early in small campaigns

On the other side of the spectrum where a campaign has a few hundred users, the experience can also be terrible for users who signed up early to the campaign, immediately racked in a lot of referrals, then stopped doing so for awhile. This makes it easier for newer users to climb up the ladder.

For example, John and a dozen other users join the campaign in its first few days. Within the first week, John has earned 100 referrals, getting him to the top spot. In the second week though, John has to stop seeking referrals due to other things in life he had to attend to.

A month later, a new user Ben signs up, and in a day only needed 20 referrals to jump from position #100 to #1. A couple of other newer users are able to do the same, so now John has been significantly pushed down the ladder, even though he's referred 5x more people than the current #1.

Sure, he can still catch up by earning new referrals, but this only means his previous referrals were for nothing. Worst, he has already exhausted all possible referrals from his network.

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