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Airdrop Design | Past, Present, & Future

0xF719
January 24th, 2023
500 Collected


When considering the future of airdrops, it's easy to feel optimistic about
their potential for aligning users of crypto networks. It’s just as valid to
express skepticism based on the current state of the instrument. While it's
clear that more experimentation is necessary in order to properly harness their
power, the required overhead and lack of tooling to execute airdrops are
prohibitive. But what are they, anyway?


WHAT IS AN AIRDROP?

Simply put, airdrops distribute tokens to past, present, or future network
participants. Airdrops are part of a broader subset of 'token incentives.' Token
incentives reward network participants for contributing resources like
attention, labor, or capital.

Incentives, themselves, are not a new concept, nor are they limited to crypto.
Traditional companies have long been utilizing them in some form to drive
growth, engagement, and organizational alignment.



Likewise, incentives drive various participation patterns in crypto like user
acquisition, retention, and engagement. They are also used to align long-term
protocol contributors and governance participants. Crypto-native incentives,
like airdrops, offer unique ways to reward users with ownership or governance
rights in a given network.

While airdrops can be a powerful tool for driving network health results, to
date most airdrop designs have been noted for their lack of effectiveness.

For airdrops to realize their potential, project teams must come to an
understanding of what kind of participation their protocol values, and to what
extent. The inability to answer these questions leads to inefficient airdrop
distributions, including the following problems:



Before examining how airdrops can be better configured to drive network health
results, let's take a deeper look at past and present design patterns.


HISTORY OF AIRDROPS: PAST

Most are familiar with airdrops on Ethereum and EVM-compatible chains. But, the
first airdrops occurred well before Ethereum had gone live.


‘PRIMITIVE’ AIRDROPS: 2014-2020 | BITTREX & BTC FORKS

The first known airdrop was Auroracoin, a cryptocurrency meant to challenge the
Icelandic krona. Each Icelandic citizen was eligible for a pre-mined airdrop
worth ~$385 at the time of distribution.

Following Auroracoin, some of the earliest airdrops were proof-of-work forks and
child chain airdrops delivered to holders on centralized exchanges like Bittrex.
For example, Bitcoin Private (a fork of Bitcoin) was distributed to holders of
Zclassic, a fork of Zcash. The intention of token creators was to distribute
tokens to holders who had a similar belief about crypto.

During the initial coin offering (ICO) craze, high-profile projects like OmiseGo
would airdrop a portion of their supply to prospective network participants.
They even began to experiment with criteria filters such as distributing to
Ethereum addresses holding 0.1 ETH or more.

One could say that the early days of airdrops were relatively crude, but on to
something. The shift to on-chain distribution and eligibility requirements
enabled more creative airdrop design principles. Once on-chain, airdrop
designers could segment based on user behavior for more impact.


‘RETROACTIVE’ AIRDROPS: 2020-2021 | UNISWAP, ENS

The next wave featured large distributions from crypto giants like Uniswap. This
kicked off the era of ‘Retroactive Airdrops'. Retroactive distributions
introduced more design sophistication, as past usage could determine eligibility
and reward tiers.

While these initial on-chain airdrops were innovative, they suffered from
several flaws. First, they were very often one-time distributions. These
distributions also tended to be untenably large in USD-value terms and in the
amount of a given token’s supply distributed. This design limited the ability to
iterate and optimize before making large outlays.

Participants would often become eligible for having only completed a basic
action pre-drop. Over time, an expectation of future airdrop eligibility for
using pre-token networks developed. This led to airdrop farming, a practice
where individuals would create many accounts to use a project in anticipation of
them all receiving a future airdrop. Farming practices tanked the efficiency of
early on-chain airdrops and likely make up most on-chain transaction activity
today.

These and other flaws caused airdrop-attributable growth to be underwhelming
relative to the value distributed. Here, one can see the large figures behind
UNI and other distributions from the ‘Retroactive’ airdrop era:



For further analysis, Uniswap’s UNI airdrop has become the subject of case
studies from Dune Analytics and Tomas Tunguz.


CONDITIONAL CLAIM AIRDROPS: 2020-2021 | DYDX, OSMOSIS

The next design iteration following the Retroactive airdrop era was
‘Conditional’ airdrops. The core innovation was the rule that a recipient
completes some defined action to claim their reward. On top of these conditions,
projects maintained the ability to segment and tier based on past behavior.

The highest-profile airdrops from this era came from projects like dYdX and
Osmosis. For dYdX, trading history determined one's airdrop eligibility, but new
trading volume was an additional requirement for claiming.



Ultimately, conditional airdrops improved upon the retroactive design philosophy
by promoting retentive activity. However, they suffered from similar
cost-efficiency problems due to their large, singular outlays. As with prior
designs, large initial distributions removed the capacity to apply minimum
viable rewards – an approach that would allow teams to get fast feedback loops
on their distributions to determine success.

Conditional airdrops compressed profits for Sybil farmers due to increased
overhead. Yet, some level of Sybil farm activity remained unchecked. This, too,
damaged the efficiency of these designs. Below, one can see more data on the
dYdX airdrop:




HISTORY OF AIRDROPS: PRESENT

The next era of airdrop innovation introduced new philosophies around their
frequency. In 2022, projects began taking a phased approach while also
integrating prior airdrop design elements.


‘RECURRING’ AIRDROPS: 2022-2023 | OPTIMISM, BLUR

Recurrence or phasing allows for incorporating more feedback into each
incremental design. Projects can efficiently drive network health by iterating
on the parameters, optimizing, and testing new hypotheses. Additionally, they
are able to somewhat avoid the wasteful practice of large initial outlays.

Recurring airdrop designs also improve upon the ability to mitigate Sybil
farming. Projects can update eligibility requirements to filter out Sybil
farming in successive iterations and lower initial airdrop amounts to demotivate
potential farmers.

With that said, there is room for improving the design choices in the recurring
airdrop era. Recurring airdrops have used smaller initial outlays than in
previous eras. Yet, the early phases of recurring airdrops have still produced
suboptimal results with sums that are too large.

There’s nothing inherently wrong with the baseline of a series of experiments
producing suboptimal results (in fact, it is to be expected!). But, projects
should be using a minimum viable rewards approach to early iterations to
mitigate waste.

The Optimism $OP phased airdrop is a great example of these principles. They
utilized a phased approach while maintaining retroactive eligibility
requirements (bonus points for the multiplier scheme!).



However, as seen below, the value distributed in the initial phase was
prohibitively large. Let’s take a look at some of the figures from the initial
distribution of the OP airdrop from the current ‘Recurring’ era:




HISTORY OF AIRDROPS: FUTURE

So what comes next in airdrop design philosophies? This is the billion-dollar
question.


QUESTS: 2023+ | RABBITHOLE-ENABLED

The key is velocity.

Recurring distributions, conditional claiming, and retrospective eligibility
requirements encompassed the past and present of airdrop design. RabbitHole
believes the next era of airdrop programs will come in the form of high-velocity
experiments called 'quests'.

This design philosophy would allow for a phased approach with minimum viable
rewards for initial distributions, driving faster feedback cycles between
projects and their token holders. Projects could continue to iterate until they
can achieve attractive results. At that point, deploying larger amounts to fuel
growth becomes more efficient.

These programs will expand the scope for segmenting eligible recipients from
on-chain behavior. Building on a mechanic made popular in NFT communities,
allowlists will become a powerful tool for establishing eligibility criteria and
staying ahead of airdrop farmers.

Quests will also expand the use of on-chain conditions for claiming. Projects
will require users to take specific on-chain actions in order to claim their
airdrop.


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Transitioning into this era will require an improvement in the available tools.
With RabbitHole, non-technical operators can spin up a quest in minutes to
create a reward for any on-chain action. This frees up engineering resources to
focus on improving core products.

While running a high-velocity, low-cost experimentation framework, project teams
using RabbitHole will have the ability to analyze and report results in
real-time, iterating based on the gathered data. Projects can also leverage a
built-in audience of on-chain RabbitHole users.

Once teams are running a process where they can hypothesize, deploy, observe,
measure, and iterate based on the results of experiments, they can then begin to
optimize for relevant network health metrics like retention, CAC, payback
period, and user:token holder ratio.

RabbitHole V2 is right around the corner. Subscribe to hear more about what’s
new in RabbitHole V2 and more Airdrop case studies.

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