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After finishing this article, I spent some time going through the crypto payment card data on PaymentScan: Entry: https://paymentscan

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BITWU.ETH
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2 months ago
AI summarizes in 5 seconds.

After finishing this article, I spent some time reviewing the crypto payment card data on PaymentScan:

Entry: https://paymentscan.xyz/

For those interested in some Payment projects, you can take a look at the on-chain data comparison here, which is quite interesting;

After reviewing, I found that Tria @useTria's growth logic is clearer than I expected.

1️⃣ First, let's look at the results:

Tria currently has accumulated over $37M in actual spending, over 170,000 transactions, and over 9,000 users. The key is not the scale, but the structure: the average number of transactions per user and average spending are both noticeably healthy;

2️⃣ Now, let's look at the parameters:

A 1.5% base cashback is not aggressive, but a 6% max + $100K/year cap provides space for long-term, heavy spending users;

Apple Pay / Google Pay have "de-Web3-ified" the card-swiping behavior, turning it into a daily action; the 1% FX fee is basically swallowed by the cashback, making the psychological cost of cross-border spending very low.

So after Tria's monthly volume surges, it can still hold its ground;

That said, payment adoption is the slowest and hardest to fake.

The product parameters themselves and users are also in a situation of mutual selection.

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