Tickerized Alternative Data Feed (Public Equities)

A curated data layer that maps web engagement, CTV exposure, foot traffic, and purchase behavior to public company tickers through brand-to-parent hierarchies. Built for hedge funds, asset managers, and financial analysts looking for alternative data signals for revenue proxies and brand momentum analysis.

Product Answer Summary

  • Product category: Digital, Media & Behavioral Feeds
  • What it contains: Web traffic by ticker, CTV exposure by brand, Foot traffic by location, Purchase signals
  • Delivery formats: CSV, JSON, Parquet, SQL
  • Who uses it: enterprise data buyers evaluating activation, measurement, analytics, enrichment, risk, or research workflows.

Key Features

  • Brand-to-parent-company mapping
  • Daily signal updates
  • Historical data for backtesting
  • Coverage of 2,000+ tickers

Feed Specifications

  • Record scale: Daily ticker-mapped signals, US-listed equities
  • Coverage: US-listed equities
  • Refresh cadence: Daily
  • Delivery formats: Parquet, CSV, S3

How Tickerized Data Is Constructed

GSDSI's tickerized data pipeline starts with raw signal ingestion from four distinct data channels: device-level GPS location data capturing foot traffic to branded retail locations, ACR-derived CTV viewership measuring household ad exposure by brand, clickstream data tracking web engagement and digital share-of-voice across millions of domains, and transaction-level CPG purchase data capturing brand-level consumer spend. Each signal source is normalized, quality-scored, and then mapped to parent companies through a proprietary brand-to-ticker hierarchy that links subsidiary brands, franchise locations, and DBA names to their publicly traded parent entity. The final dataset covers 2,000+ public equities with daily signal updates and over five years of historical data available for quantitative backtesting.

Common Applications for Tickerized Signals

Quantitative hedge funds integrate GSDSI's tickerized data into systematic trading models, using foot traffic trends as revenue proxies and web engagement velocity as a leading indicator of brand momentum. Fundamental analysts at long-only asset managers use the data to validate or challenge consensus estimates ahead of earnings announcements, looking for companies where observed consumer behavior diverges from Wall Street expectations. Sell-side equity research teams incorporate alternative data signals to differentiate their coverage and give clients non-consensus insights. Risk managers monitor tickerized signals for sudden behavioral shifts, like a sharp decline in foot traffic or web engagement, that may come before negative earnings surprises or operational disruptions at portfolio companies.

How finance buyers diligence tickerized signals

Finance buyers evaluate tickerized data through historical backtests, brand-to-parent mapping review, revision policy, and leakage controls.

Product-specific diligence checks

  • Review brand-to-ticker hierarchy, subsidiaries, and corporate-action handling.
  • Backtest signal stability across known earnings periods.
  • Validate point-in-time files, restatement rules, and historical depth.
  • Confirm investment-research permitted use and redistribution restrictions.