Tracking ‘fake data’ on the chain, understanding the ‘fur-lovers’ and the fur-lover industry

Uncovering 'Fake Data' on the Chain A Deep Dive into the Fur-Lover Culture and Industry

As long as the cost is lower than the potential reward, airdrop farming will prevail.

Original article title: Follow the (fake) Data: Understand the “airdrop farming stack” and the industry around it

Original author: Kerman Kohli

Original source: substack

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Translation by: Kaori

One thing that has increasingly troubled me in the past few years is how much this industry relies on “data.” I put it in quotes because most of it is fake/not real. To show what’s happening and how it works, I thought I should write a longer article on the whole issue.

When I started researching this article, I realized how industrialized the whole thing is and how many investors are being fooled by it. The whole thing is a huge joke, showing how far the entire industry has to go.

Layer 1 Valuation

Our problem starts with these overpriced, overhyped tokens that investors are willing to pay billions of dollars for. All you need is a fancy whitepaper and you can twist the entire unit economics. My research starts with Dune, where I found this dashboard that calculates the Customer Acquisition Cost (CAC) for multiple airdrops.

It’s a good start, although I do want to point out that these CAC numbers (from the project’s perspective) are underestimated because they’re just: Dollar value ($) / Claimed addresses. This calculation doesn’t take into account the actual percentage of airdrops held. Given that usually only 10%-20% of addresses hold airdrops, it’s safe to assume that these CAC numbers are 5 to 10 times higher than what you see above.

The second thing is that we have an implicit airdrop value hierarchy:

Layer 1 / layer 2 / hyped protocol = thousands of dollars spent

Small to medium-sized applications = hundreds of dollars spent

Fortunately, the two are not mutually exclusive! If you’re on the right chain with the right application, you’ll get both airdrops.

So, ideally, you’d want to focus on airdropping on a chain first and then interact as much as possible. Well, what happens next?

Finding the right airdrops

Luckily, for you, the airdrop hunter, there’s already an entire industry built to help you find airdrops. Typically, these airdrop discovery websites require you to perform very specific “tasks” and provide evidence on-chain that you’ve completed these tasks. Whether it’s your grandma or your robot performing the tasks, as long as the transaction is visible on the chain, it counts.

All these “task” platforms are essentially disguised airdrop discovery websites. If these sites attract high-quality users, there usually aren’t any issues, but the users attracted through these sites tend to be highly mercenary, representing the short-term speculation that the industry as a whole suffers from.

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Let’s reach out to our trusted friends at dApp Radar to see what airdrop activities might be happening right now.

Based on this, my game plan is likely to be:

· Use zkSync as my base chain

· Bridge my funds with Layer Zero

· Use Metamask as my chain wallet

All of this could be just my natural workflow without any extra work. But the question is, what do you need to do to know your ranking in these potential airdrops? Surprisingly, a whole community has emerged consisting of “airdrop simulators.” These people exist to help you understand where you stand relative to other airdrop farmers. Simply search for “airdrop” and you’ll find dashboards that simulate how projects distribute airdrops using past airdrop criteria.

What’s fascinating is the level of detail depicted. Check out all the columns mapped out in this table. Arbitrary scores, last transaction time, transaction count, unique contracts, total transaction USD amount, unique active days/weeks/months, wallet age, and block time.

When your “community” has already done the airdrop calculations for you, why bother doing them yourself?

Playing the system

If you’re surprised by the planning involved in this whole affair, wait until you see the next part: If you know all the permutations and combinations for things used as standards, you can start automating and building efficient systems around it. I spent some time researching and discovered these two magical tools. Might be worth a try, just to report how corrupt the entire airdrop game is.

The first one is our friends at nftcopilot.com, who have built a flexible dashboard for you to automate and set up your farm.

What’s amazing is the depth and detail they go into. In their product, you can create “groups” where you can customize the following parameters:

1. Number of transactions through the bridge router

2. Bridging networks (Ethereum, Polygon, Binance Smart Chain, Arbitrum, Avalanche, Optimism, Metis, Aptos)

3. The random operations in the configuration include the probability of opportunities, sleep intervals, and the maximum random transactions per transaction.

Let’s be clear, for the entire ecosystem, this is far from value-added and value destruction.

Fake products are used to prove the reasonableness of false valuations.

If you narrow the scope, what really happens is that the cost of proving the reasonableness of these airdrops is lower than the potential return that this effort may bring. I found another website that helps make transactions clearer by detailing prices and potential investment returns.

Now, you can use your own simplified mathematics to calculate how much money you want to invest and how much money you expect to see. Voila, I solved a practical problem for everyone. In some ways, it may be more profitable for venture capital companies to grab airdrops than to invest in actual projects. It’s faster liquidity, and there’s less psychological burden.

As long as the cost of the airdrop is lower than the potential reward, grabbing airdrops will prevail.

Final Result

So, what do you think is the result of establishing a sub-industry of agriculture on top of these overhyped projects? It’s just a battle to see who can build a bigger zombie network industry on top of it. If the numbers on the chain are inflated, then those participants who don’t know how to analyze the data without caution will report what they see and ultimately deceive retail investors into believing that the projects they have invested in have real market appeal.

Take a look at the tweets below. If you’re on Twitter, you might be confused by this and think, “Wow, this thing is really starting to work, I should buy it.” The more people believe in this data, the more this cycle will continue. Below are some examples I found on Twitter of misuse of data.

Based on the content I have shown you in this article, do you think any of the numbers in these traction indicators are real? Of course not, they’re all fake. The data is fake.

Answer

Unlicensed identity.

We are deceiving ourselves until we truly review who is generating these metrics for this activity. Calculating the basic numbers as they are means that you set the standard for the identity very low (considering that the cost of creating an unlicensed identity is zero).

The common point in all these questions is the lack of consideration for past behavior or behavior in a broader context. So, if you have a stronger identity layer in the crypto space, how do you address the above issues?

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