Hashwei Foundation

User Research Report: The Hidden Costs Dragging Crypto Analytics into a $92M Crisis by 2030 Over the past 12 months, the Hashwei Foundation conducted an in-depth behavioral study across thousands of traders, funds, and power users of leading crypto analytics platforms. The findings are stark and costly. It's systemic failure quietly eroding capital, confidence, and conviction in data-driven decision-making. These 4 Problems are killing users and the crypto analytics 1. Data Latency: Market movements happen faster than the data arrives, missing the edge A 15s (Second) Delay = A $10K Liquidation Crypto doesn’t wait. A single 15–30 second lag in On-Chain or Derivatives data can trigger: - Missed entries during pump/dump - Forced liquidations in volatility spikes - Chasing false breakouts EX: “I watched BTC break $108K on my chart, 45 seconds after it happened On-Chain.” (Anonymous Whale, $21M AUM) 2. Data Noise: 99% Junk, 1% Signal, and you’re drowning Users are bombarded with: - Wash trading loops - Spam transactions - MEV bot spam - Fake airdrop txs - Sybil wallet clusters => Result? Alert fatigue. FOMO trades. Rug-pull exposure. The real alpha? Buried under digital garbage. 3. Data Fragmentation: Insights are scattered across too many tools Average user's workflow: Check volume => Tool A Check whale flow => Tool B Check DEX liquidity => Tool C Check CEX orderbook => Tool D Check On-Chain holders => Tool E Check metric => Tool G Manually sync in Notion/Excel 🥲 Cost of fragmentation: => 2 - 3 hours lost per deep analysis session => 41% of insights are outdated by the time they’re compiled => Zero cross-validation = blind spots = rug pulls Fragmentation doesn’t just waste time. It creates dangerous blind spots. 4. High Cost, Negative ROI: Users pay premium (SaaS model) prices for data that delivers subpar value and negative ROI. Average yearly spend on analytics: $1,200 (retail) → Over $10,000 (funds) Average ROI from current tools: -12% to +3% (self-reported P&L attribution) Industry-wide waste (GetLatka, 2024): => $35M–$50M/year on inaccurate, delayed, noisy data => Projected 2030: $75M–$92M, a growing black hole Users are not investing in intelligence. Users are subsidizing inefficiency.

Liquidity bubbles represent position leverage. LONG positions are continuously liquidated in the Leverage Liquidation weekly chart $ETH price has moved into large bubbles indicating that LONG positions are being highly leveraged leading to liquidations The key question: Will the $4,296–$4,275 zone act as a short-term support area as the market clears these remaining overleveraged positions?