Following on from my last article about the multiple Optimism airdrops, I wanted to take a look at the Starkware airdrop since I managed to extract the data at the same time. The main difference between Starkware and the Optimism airdrop that I wanted to investigate was the impact of the claim mechanism on these criteria. This data has been out of date for about a month now, but won't be too far off from the actual numbers given that the airdrop was made several months ago.
The main difference between the two approaches was that Optimism said “we will personally deliver the drop to your wallet” whereas, as Starkware said “come to us to claim your drop”. The first argument is that it is easier for users and saves gas. My personal philosophy is that if you're doing this on a low cost channel (that's what your rating is based on, right?!), then cost shouldn't be an issue and the least anyone The only way to claim free money is to click a button. .
With that being said, let's take a look at Starkware's release. Unfortunately, data was extremely difficult to obtain because:
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Starkware hasn't released data explaining how people claimed the drop after the drop.
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Starkware doesn't have addresses in standard EVM format (they're much larger than 20 bytes), which means I had to hack to get data available on-chain.
Anyway, here is the official table explaining how the airdrop was awarded:
To get the data I needed I basically used:
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0x06793d9e6ed7182978454c79270e5b14d2655204ba6565ce9b0aa8a3c3121025
like my airdrop to get all claim events from -
0x00ebc61c7ccf056f04886aac8fd9c87eb4a03d7fdc8a162d7015bec3144c3733
as hash of my starting block -
0x04718f5a0fc34cc1af16a1cdee98ffb20c31f5cd61d6ab07201858f4287c938d
like the contract to get STRK balances from
Some funny snippets show that I have to get balances through lots of for loops and byte hacking to get the data I wanted.
Anyway, upon extraction I found 519,282
events on the claims contract. There was a total 1,304,079
requesters, meaning only 39.8% requested the drop. The remaining users were basically used as marketing support – which I think is a good result! Some might say it was bad, but if you can get the message out to as many people as possible without giving it all away, you've kind of struck the sweet spot. The broad criteria made most people feel included, which generates goodwill within the community.
So basically what I did was get all the addresses of the claim events I received and then ran a script to get all their balance at the time I ran the script. I was then able to see what the balance compartments were by segmenting them. I wish I could understand these users better, but the limited data made this exercise much more difficult.
Without further ado, here are the results! I used less than 100 STRK as a threshold because the smallest airdrop given was a 111.1 STRK. Here are the details of the amounts:
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StarkEx Users: 111.1 STRK each
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Open Source Developers: 111.1 STRK each
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Starknet users: Range from 500 to 10,000 STRK, with variable multipliers
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Starknet Community Members: Range 10,000 to 180,000 STRK
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Starknet Developers: 10,000 STRK each
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Ethereum Staking Pools: 360 STRK per validator
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Solo players: 1,800 STRK per validator, up to 3,200 STRK for those with higher risk profiles
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Ethereum Developers: 1,800 STRK each
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Protocol Guild Members: 10,000 STRK each
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PEI authors: 2,000 STRK each
To further defend my choice of bucket 101, the total amount held by this group is: Total recipient amount for '<100' bucket: 1,896,317.6861687868
/ less than 3%.
Overall, not a very good airdrop! A 13.5% retention rate is close to the industry standard (which is bad). However, given that a normal Github user like me received 1800 STRK, my deepest view is that the airdrop is worse than you expected! Only 1.1% of users who received something substantial were retained! I'm a little hesitant because the interpretation of this drop can go either way. However, let's look at other data points to determine whether or not this airdrop was a success.
A simple proxy is a token. Here is the 3-month chart of the STRK token. Down 50%, but there was also a strong market sell-off. Not great but at least it's not down 90%?
Let's look at another angle: TVL. At least our friends at DeFi Llama can help us with this exercise.
TVL grew to around $320 million and then dropped to around $210 million, which is pretty good retention. However, we don't know how much Starkware spent to get these numbers. Luckily I have the numbers. These figures are 67,078,250.942674
.
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If we assume an average token price of $1.50
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We can re-express this equation since Starkware spent $100,617,376 to acquire approximately $300 million in TVL.
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Or in other words, approximately $3 in STRK tokens to acquire $1 in TVL
My next question is what the number of users looks like so we can understand a CAC model for this equation. I redrew my graph above with percentages in number of users.
Okay, so I'm giving Starknet the benefit of the doubt here and only counting the under 100 buckets. We spent nearly $100 million to acquire 519,282
users. This translates to around $200 per user. Now if we re-express this in terms of retained users (above 101 tokens), we get $1,341 per retained wallet.
This is lower than what we saw in the Arbitrum airdrop and others where the retained CAC is in the thousands of dollars, or even tens of thousands of dollars. While Starkware's drop wasn't great from a retention standpoint, it was decent from an ACC standpoint compared to others I've seen. My thesis on this is similar to what we saw during the Optimism airdrops:
Starkware has been relatively thoughtful in how they have given many tokens to many different groups and the data clearly shows this. This is a common theme I see in airdrops that perform well versus those that don't.
So why don't more projects choose various user attributes to airdrop tokens to users? Well, it comes down to the fact that it is difficult to collect, analyze and draw conclusions from data, especially when you have large amounts of it. Starkware has managed to use relatively simple criteria that still ensure diversity, although there are ways to be even more targeted with the right tools.
I have many thoughts on this subject that I will write about in future articles, but for now I will leave you with this clue to the airdrop puzzle: data is the biggest limitation, although a way that very few people can see.