Since 2018
Privacy-safe enterprise data
VOSB & SDVOSB
U.S. Veteran-Owned, Service-Disabled
SCC Transfers
EU/UK/CH per privacy policy
GDPR · CCPA · CPRA
Consent-first data sourcing
Canonical solution route
Use the Alternative Data for Finance solution page as the canonical “what we deliver” route, then use the resources below for evaluation, governance, and implementation.
What buyers evaluate
- Ticker mapping: methodology, coverage, survivorship bias, and update cadence.
- Ground truth: how signal aligns to reported financials (lags, seasonality, calibration).
- Governance: permitted uses and privacy posture for consumer-derived signals.
Signal types
Compliance diligence
What makes a signal “tradeable” (and what doesn’t)
Financial buyers don’t need more datasets. They need signal that survives backtests. The same raw source can be useful or useless depending on mapping, bias controls, and whether the history is stable enough for research.
Validation checklist
- Ticker mapping: brand→parent hierarchies + survivorship handling.
- History: enough depth for backtesting and seasonality controls.
- Revisions: whether history is backfilled or restated.
Bias controls
- Panel composition and how drift is corrected.
- Geo and demographic skews; weighting availability.
- Coverage by ticker/sector, not just “events/day”.
Implementation notes
- Start with a matched sample for your universe/tickers.
- Define the KPI mapping (traffic→sales, exposure→lift) up front.
- Prefer formats that fit your stack (Parquet + S3/Snowflake).
Related buying guides
Most finance evaluations depend on the same underlying identity, location, and governance primitives.
Vendor comparisons
If your team is benchmarking providers, use the comparison pages as a bake-off template: coverage in your universe, mapping method, bias controls, and revision policy.
Frequently asked questions about alternative data procurement
Who should use the alternative data buying guide?
Equity research, quant, private equity, and corporate strategy teams evaluating tickerized panels, clickstream, CPG, and mobility for forecasting, channel checks, or event studies. The guide links finance-specific products and resources.
How do I validate ticker and brand mapping?
Backtest mapping tables against known revenue benchmarks, document parent/brand rollups, and confirm how corporate actions and survivorship are handled. Request revision policy and historical depth (GSDSI panels often reach back to 2019 on core signals).
What leakage controls matter for trading use cases?
Confirm aggregation thresholds, embargo rules, latency versus exchange close, and whether signals are derived from forward-looking panels. Pilots should include out-of-sample tests and documented refresh timing.
Which GSDSI feeds are most common for finance buyers?
Tickerized data, clickstream web intent, CPG purchase signals, and global mobility location data are frequent starting points. The alternative data for finance solution page describes typical joins and delivery into research notebooks or warehouses.
What delivery latency should I expect?
Latency is product- and license-specific. Daily panels differ from near-real-time clickstream cuts. Specify required timestamps, timezone normalization, and warehouse landing expectations in the SOW.
What resources support quant diligence?
Read alternative data in equity research, the tickerized data playbook, and linked evaluation checklists under /resources. Request a scoped sample through /contact with your ticker universe and backtest window.