Original title: Follow the (fake) Data: Understand the airdrop farming stack and the industry around it
Original author: Kerman Kohli
Original compilation: Kaori, BlockBeats
One thing that has bothered me more and more over the past few years is the industry’s increasing reliance on “data.” I put that in quotes because most of it is fake/not true. To show whats going on and how it works, I thought Id write a longer article around the whole issue.
When I started researching this article, I realized how industrial this whole thing is and how many investors are fooled by it. The whole thing is a huge joke and shows how far the industry still has to go.
Layer 1 Valuation
Our problems start with these overpriced, over-hyped tokens that investors are willing to pay billions of dollars for. All you need is a nice white paper and you can twist the unit economics of it all. My research started with Dune and I found this dashboard that calculates the CAC of multiple airdrops.
Thats a good start, although I do want to point out that these CACs (from a project perspective) are both understated numbers, as they are simply: dollar value ($) / claimed address. This calculation does not take into account the percentage of airdrops that are actually retained. Given that typically only 10%-20% of addresses hold airdrops, its safe to assume that these CAC numbers are 5x to 10x higher than what you see above.
The second thing is that we have an implicit airdrop value level:
Layer 1 / layer 2 / hyped protocol = thousands of dollars spent
Small to medium size app = hundreds of dollars spent
Fortunately, the two are not mutually exclusive! If you use the right application on the right chain, you will get two airdrops.
So ideally you want to focus your airdrops on the chain first and then interact with them as much as possible. Okay, but the question is what happens next?
Find the right airdrop
Luckily for you airdrop hunter, there’s an entire industry of finding airdrops built just for you. Typically, these airdrop discovery sites require you to perform some very specific actions and require on-chain evidence that you have performed those actions. Whether it was your grandma or your bot that performed the action, just make sure the transaction is visible on the chain.
All of these mission platforms are actually airdrop discovery sites disguised as such. If these sites can attract high-quality users, this usually wont be a problem, but the users attracted by using these sites are often highly employed and represent the short-term speculation that the industry as a whole suffers from.
Let’s reach out to our trusted friends at dApp Radar to see what airdrop activity might be happening at this time.
Based on this, my game plan would most likely be:
· Using zkSync as my base chain
· Layer Zero bridges my funds
· Metamask as my chain wallet
This could all just be my natural workflow and not require any extra work. But the question is, what do you need to do to know where you rank among these potential airdrops? To my surprise, a whole community of airdrop simulators emerged. These people exist to help you understand your standing relative to other airdrop farmers. Simply search for “airdrop” and you can find a dashboard that models how projects distribute airdrops using past airdrop criteria.
Whats fascinating is the level of detail thats drawn. View all columns mapped using this table. Arbitrary score, last transaction time, transaction count, unique contracts, total transaction dollar amount, unique active days/weeks/months, wallet age and block time.
Why bother with airdrop calculations when your “community” has already done it for you?
Game the system
If youre surprised at how well the whole thing is planned, wait until you see the next part: If you know all the permutations and combinations of things that work for a standard, you can start automating it and building an efficient system around it. I spent some time researching and discovered these two amazing tools. Might give it a try just to report how corrupt the whole airdrop game is.
The first is from our friends at nftcopilot.com who built a flexible dashboard for you to automate and set up your farm.
What’s amazing is the depth and detail they go into with it. In the product, you can create groups and you can customize the following parameters:
1. Number of transactions routed through the bridge
2. Bridge network (Ethereum, Polygon, Binance Smart Chain, Arbitrum, Avalanche, Optimism, Metis, Aptos)
3. The configured random operation includes the configured chance probability, sleep interval and the maximum number of random transactions for each transaction.
Let’s be clear, this is far from value-adding and value-destroying for the entire ecosystem.
Counterfeit products to justify false valuations.
If you zoom out, whats really happening is that the cost of justifying these airdrops is less than the return that the effort might bring. Another website I found helped make the deal clearer by detailing the price and possible ROI.
Now you can use your own simplified math to figure out how much money you want to invest and how much money you expect to see. Phew, I solved a practical problem for everyone. To some extent, it may be more profitable for venture capital firms to launch airdrops than invest in actual projects. Liquidity is faster and there is less mental burden.
As long as the cost of airdrops is lower than the potential rewards, airdrops will prevail.
Final Results
So, what do you think are the consequences of the agricultural sub-sector being built on top of these over-hyped projects? Its just a battle to see who builds the bigger botnet industry on its foundation. If the on-chain numbers are inflated, then unsuspecting participants who dont know how to parse the data will report what they see and ultimately deceive end retail investors into believing that the projects they invest in have real market appeal. force.
Check out the tweet below. If youre on Twitter, you might be confused by this and think Wow, this thing is really starting to work, I should buy in. The more people believe the data, the further this cycle will continue. Here are some examples of inappropriate use of data I’ve found on Twitter.
Based on what Ive shown you in this article, do you think any of the numbers in these traction metrics are real? Of course not, its all fake. The data is fake.
Answer
No permission required.
Until we actually review metrics based on who is generating this activity, we are all fooling ourselves. Just counting the base numbers as-is means youre setting the bar very low for which identities are included (considering that the cost of creating a permissionless identity is zero).
What all of the above issues have in common is that there is no regard for past behavior or behavior in the wider context. So how do you solve the above problem if you have a stronger identity layer in the crypto space?
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