Cross-Platform Product Intelligence

A dropship seller monitors 50 products across Amazon and Walmart weekly via Scavio (100 queries = $0.50/week). They identify 3 products with >15% price gaps between platforms. One product: $29.99 on Amazon, $39.99 on Walmart. The seller lists on Walmart at $36.99, capturing the margin. Monthly monitoring cost: $2.00. Monthly profit from price gap arbitrage: $800+.

Cross-Platform Product Intelligence is relevant to Amazon, Walmart, Google, TikTok. Scavio provides a unified API to access data from all of these platforms.

Product intelligence in 2026 requires data from multiple marketplaces. A product's Amazon price, Walmart availability, Google Shopping ranking, and TikTok viral potential all influence sales strategy. Collecting this data separately from each platform requires 4+ integrations, each with its own authentication and response format. Cross-platform data points: (1) Amazon: pricing, ratings, review count, Best Seller Rank, fulfillment type (FBA/FBM). (2) Walmart: pricing, ratings, pickup/delivery options, Walmart+ eligibility. (3) Google Shopping: comparison pricing, merchant ratings, shipping costs. (4) TikTok: trending products, creator mentions, viral video engagement. Unified query via Scavio: search the same product across platforms with one API key. Query 'wireless earbuds' on Amazon, Walmart, and Google Shopping = 3 queries at $0.005 = $0.015 for cross-platform pricing. Add TikTok search for trend data = $0.02 total per product. Scale: monitoring 100 products across 4 platforms weekly = 400 queries/week = $2/week = $8/month. Compare to manual research (hours per product) or separate API integrations ($50-200/month per platform). Use cases: dropship product research (find products with Amazon/Walmart price gaps), brand monitoring (track unauthorized sellers across platforms), competitive pricing (adjust prices based on cross-platform data), trend detection (TikTok viral products before Amazon sellers saturate).