Problem
Raw market data is messy, unstructured, and difficult to integrate directly into database models or BI analysis platforms.
Solution
Clean, structured, and normalized pricing datasets delivered on a scheduled cadence via API or cloud storage, matching your exact catalog specifications.
Features
Alternative Data Feeds: Get non-traditional market signals to support algorithmic pricing.
Tick-Level Freshness: Low-latency data streams to fuel fast trading and pricing models.
Asset Mapping: Map competitor products across different platforms, catalog formats, and currencies.
Volatility & Sentiment Analysis: Capture promotional spikes and market sentiment changes.
Benefits and outcomes
Market Share Defense: Anticipate demand shifts and adjust pricing based on comprehensive dataset trends.
Quant-Ready Integration: Clean, normalized data prepared directly for database tables, models, and BI tools.
Automated Delivery: Leverage secure cloud buckets (S3, GCS) for scheduled data delivery.
How it works
Step 1
Define Scope & Catalog: Specify categories, brands, competitors, and update frequency.
Step 2
Ingestion & Cleaning: Our engine collects, matches, and normalizes raw marketplace signals.
Step 3
Structured Delivery: Retrieve data via direct API, Snowflake, AWS S3, or Google Cloud Storage.
FAQ
Which industries can use this dataset?
The dataset supports multiple sectors including retail, travel, and automotive use cases.
Can data be integrated with BI or ERP systems?
Yes. API and structured delivery options support integration with existing analytics and operations tools.