Automated Price Monitoring for Sneaker Reselling: Leveraging AcBuy Spreadsheet to Identify Abnormal Market Fluctuations
2025-06-22
In the fast-paced world of sneaker reselling, real-time price monitoring has become a game-changer. This article demonstrates how scraping AcBuy AJ's live pricing dataAcBuy Spreadsheet
Step 1: Data Collection Pipeline
Connect to AcBuy's API
- Current Price
- Seller Inventory Levels
- Transaction Frequency
=IMPORTJSON("https://api.acbuy.club/v1/aj1-greybear","/price,/sizes/9.5,/last_sale")
Step 2: Anomaly Detection Algorithm
The system flags anomalies when:
Condition | Action |
---|---|
30%+ price surge in 4h | Batch-buy recommendation |
3+ sellers out of stock | Demand surge alert |
Size 9.5 trade volume ↑200% | Inventory pre-allocation |
Example: When AJ1 patent bred prices spiked 47% on March 12, early adopters mitigated risks by splitting orders across 3 suppliers between $320-$380 ranges.
Step 3: Size Preference Analysis
Machine learning identifies regional/customer-specific trends:
[ Hypothetical Chart: AJ1 Top 5 Sizes - APAC vs. NA Markets ]
• Asia prefers sizes 38-40 (EU)
• North America favors US 9-11
Result: Reduced return rates by 22% through size-predicted inventory allocation. Want to implement this? Access live data at AcBuy.club.