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Alternative Data for Financial Insights

Tickerized data mapping consumer and digital signals to public company tickers.

Since 2018

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VOSB & SDVOSB

U.S. Veteran-Owned, Service-Disabled

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EU/UK/CH per privacy policy

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Consent-first data sourcing

Overview

GSDSI (Global Source Data Solutions Inc.) generates alpha for financial buyers through alternative data signals that traditional financial analysis misses. Our tickerized data maps web engagement, CTV exposure, footfall patterns, and ~390M daily CPG purchase signals from a ~71.5M daily-active-user panel to public company tickers through brand-to-parent hierarchies: giving hedge funds and institutional investors revenue-proxy modeling, brand-momentum analysis, and pre-earnings signal detection.

Buying guide

Use this guide when you’re comparing vendors or documenting diligence. It’s built to be linkable (and citeable) without overlapping the product pages.

Alternative data buying guide

Request API key + JSON sample

If you’re evaluating implementation, we can share sample payloads, join keys, and delivery options (S3/SFTP/Snowflake) for your use case.

Request API key + JSON sampleDeveloper hub

At a glance

What you get

  • Research-ready signals (clickstream, mobility, consumer) for alpha workflows.
  • Coverage/bias checks via pilot analysis.
  • Clear refresh cadence + history for backtests.

How it’s sourced

  • Documented provenance and permitted-use boundaries.
  • Governance for retention + derived features.
  • Stable schemas for quant workflows.

How you buy it

  • Matched sample for your universe/tickers.
  • Agree on refresh + historical lookback.
  • Production license aligned to research + distribution needs.
Sourcing methodologyPilot processResources

Use Cases

  • Revenue proxy modeling
  • Brand momentum tracking
  • Pre-earnings signal analysis
  • Sector & industry trend forecasting

Key Benefits

  • Non-consensus data signals
  • Company-level foot traffic analysis
  • Historical data for backtesting
  • Ticker coverage list shared during evaluation

How Alternative Data Is Constructed

GSDSI's alternative data pipeline starts with raw signal collection across four distinct channels: device-level location data capturing foot traffic to branded retail locations, ACR-derived CTV viewership tracking ad exposure by brand, clickstream data measuring web engagement and digital share-of-voice, and transaction-level CPG purchase data capturing brand-level spend. Each signal is mapped to parent companies through a proprietary brand-to-ticker hierarchy covering publicly traded equities. The final dataset is updated daily and includes historical data for backtesting, delivered in formats compatible with quantitative research platforms including CSV, Parquet, and SQL.

Why Alternative Data Drives Alpha

In an era of increasingly efficient markets, traditional data sources like earnings calls, SEC filings, and sell-side estimates are priced in almost instantly. Alternative data provides a differentiated information edge by capturing real-world consumer behavior weeks before it shows up in quarterly reports. Hedge funds and asset managers use GSDSI's tickerized signals for revenue proxy modeling, identifying same-store sales trends through foot traffic patterns, spotting brand momentum shifts through web engagement velocity, and flagging pre-earnings anomalies via CTV exposure changes. Because these signals come from observed consumer behavior rather than surveys or estimates, they offer higher signal-to-noise ratios and lower correlation with consensus datasets.

Recommended Data Products

Tickerized Data

Consumer and digital signals mapped to public company tickers for financial intelligence.

Clickstream & Web Intent Data

Session-level web behavior to model consumer intent and engagement.

CPG Feed

Transaction-level purchase data across grocery, household, and personal care categories.

Global Mobility/Location Data

Device-level GPS signals and aggregated mobility patterns, with a daily US and Canada feed plus country-specific coverage.

Implementation checklist

Teams that operationalize this solution move faster by defining join keys, match-rate targets, and governance up front. If you need audit-ready provenance and exclusions, start with our methodology page.

  • Define the endpoint: activation, measurement, research, or risk model.
  • Set match-rate targets for your audience and geography.
  • Pick delivery: SFTP/S3/Snowflake/API; Parquet/CSV/JSON.
  • Governance: exclusions, retention, opt-out/deletion SLAs, permitted uses.
Request a Quote Sourcing methodologyTalk to solutions engineering

Frequently asked questions about Alternative Data for Financial Insights

What alternative-data products does GSDSI offer for finance?

Tickerized signals across foot traffic, transactions, ACR exposure, web intent, and CTV. Each signal is pre-mapped to public-equity tickers and reporting calendars so quant and fundamental teams can join the data into backtests and earnings models without doing the company-to-signal mapping themselves.

Is the data backtested?

Backtest history varies by signal: foot-traffic typically goes back 5+ years, transactions and ACR shorter. A backtest panel is shared during evaluation so buyers can validate signal-to-revenue correlation before licensing. Methodology documentation accompanies each backtest delivery.

What's the licensing model?

Annual subscription, priced by signal and by use case (research vs. production trading vs. redistribution). Trial windows are available for evaluation. Redistribution and external research-publication rights are scoped separately.

Are international tickers covered?

US-listed equities are the deepest. Selected international tickers are available through licensed partners on request, coverage depends on the underlying data feed (foot traffic and clickstream are the broadest international panels).

How does GSDSI compare to Yipit, M Science, or Earnest?

Yipit and Earnest specialize in transaction panels; M Science in syndicated research products. GSDSI offers a broader signal mix (foot traffic, ACR, intent, transactions) under one contract, with raw daily delivery rather than packaged research notes. Useful when in-house modeling is the goal.

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