How successful has airdrop design been?

In our last article, we looked at the differences in airdrop design spanning retroactive, conditional and recurring airdrops. We’ve argued most airdrop designs to date, in particular, retroactive airdrops attract sybil farmers and mercenary capital. And if airdrops are supposedly the most effective user acquisition and retention mechanism designed to help bootstrap network effects then most protocols haven’t been too successful.

We’ll show a series of graphs from Dune dashboards - the graphics below are easier viewed in Dune (please note I’m still learning SQL so the dashboards shown are forked with minor modifications - creators’ original work is linked in the respective dashboards). We will be comparing:

1. Retroactive design in DEX aggregators

2. Retroactive vs. recurring design from Arbitrum and Optimism

3. Recurring design of Blur’s airdrop and NFT marketplace performance.

DEX Aggregators

For DEX aggregators we used monthly transactions, weekly volume, swap volume and active users as our main metrics. (Link to Dune)

Findings

• With the exception of 1inch, both Cowswap and Paraswap saw their highest monthly transactions count in the runup to their airdrops.

• 1inch unique wallet - 36% decline, 70% for Paraswap whilst Cowswap has a steady amount of new and returning traders

• We saw similar declines in weekly volumes across the board as well as average swap volume

• Despite initially dropping after the airdrop, the monthly trades count has slowly trended up

• 1inch has seen its weekly active users uponly since its airdrop, the same can’t be said for Paraswap or Cowswap with the former seeing the steepest drop in which it is only beginning to recover from.

Takeaways

• Whilst airdrops are important, they certainly can’t make up for a good product which for DEX aggregators, the most important feature traders want is superior price execution. See this thread here. As a result, 1inch’s outperformance is no surprise here.

• Meanwhile, the sudden drop off in metrics from Paraswap’s case highlights that whilst I understand their desire to reward their most loyal users, having a retroactive airdrop that does not have a wide distribution can disastrously affect sentiment.

Arbitrum vs. Optimism

Metrics focused on: transactions, active / new users and TVL. (Link to Dune)

Findings

• Arbitrum on average has seen a slow increase in average transactions, but a small decrease since the airdrop. Same with Optimism. It is notable that Optimism’s transactions rose into the end of their quests but fell off a cliff shortly afterwards but have since been steadily increasing upwards.

• It is a similar story when we compare their weekly active users with a steady drop off in the 6 months after Arbitrum’s airdrop, however, a steady increase in Optimism’s.

• Optimism’s DAU as a % of Arbitrum’s has steadily climbed from roughly 40 > 70%.

• When it comes to their TVL - Arbitrum had a roughly 30% drop whilst Optimism fell ~40% but the latter has proven to be more sticky at least in the following year post airdrop.

Takeaways

• Whilst Optimism appears to have stickier retention metrics, metrics like DAU have consistently gained market share vs. Arbitrum but still are significantly below.

• Part of Optimism’s GTM strategy is retroactive public goods in which OP tokens are distributed towards protocols aligned with the OP ecosystem. Continuous incentives and almost 2/3rds of their airdrop supply yet to be released have created stickier users.

• However, despite the better success of recurring airdrops, it is important not to neglect other aspects of your GTM strategy such as initial community building, attracting developers (such as GMX) that will help to bootstrap your initial launch and can sustain better underlying metrics despite ongoing incentives from competitors.

Blur & NFT marketplaces

Metrics here looked at include: the number of listings, average $ value per listing, number of platform users & transaction volume. (Link to Dune)

Findings

• Blur is one of the clearest examples of the effect of recurring airdrops, in particular, how protocol metrics change with the introductions of each season.

• For instance, their share of weekly trades peaked on 20/02 with Blur taking 56% vs Opensea’s 35%. However, since then this figure has essentially reversed.

• Big increase in activity with Blur season 2 but after stopping it has retained % of sales 30% with no substantial decrease

• % of unique users has overall grown but steadily declined since season 2 of Blur. But since March ‘22 bull market top OS’ dominance has fallen from 96 > 55%.

Takeaways

• What’s interesting is phase 2 in October - rewarded users who listed NFTs on platform (supply)

• Phase 3 focused on rewarding users for bidding on NFTs (demand)

• What’s notable is you can see after each round of incentives, there’s a clear increase in % of users by volume, sales and unique users and these metrics never fall below their pre-airdrop phase numbers.

Stay tuned for part 2 which will look at the lessons learnt and how we can go about designing future airdrops!