Spot shifts before they surface: Keyword data, import records, and behavioral signals triangulated to size markets and spot shifts early.
The data you need often doesn't exist directly. We find what correlates: search patterns as demand, marketplace rank as share, environmental signals as supply
Economic models that answer investment questions before you commit. Scenario analysis across spending shifts, commodity cycles, and market timing
Real-time signals feeding share analysis and pricing decisions. Know where you stand and when to move
Signals triangulated to size markets and spot shifts before they surface
A CPG company wanted visibility into supply-side dynamics that futures markets couldn't see. We built a model tracking West African pod health, weather patterns, and macroeconomic indicators as early warning signals. The output: a monitoring system that flagged supply disruptions before they surfaced in market data.
No reliable market share data existed for specialty auto aftermarket segment. We constructed it using SEMRUSH keyword volumes as demand proxy, Google Trends for trajectory, and Amazon sales rank as a share signal. The client walked away with a competitive positioning map built from public data.
A government services contractor needed to evaluate platform investment under uncertain budget environments. We built scenario models across defense spending trajectories, mapping probability-weighted outcomes to unit economics. The client used it to stage investment gates tied to political and budgetary triggers
An industrial services company needed demand forecasts by geography and customer vertical but had no reliable model. We built regressions against market indicators, economic data, weather patterns, and competitive intensity. The output: vertical-level demand forecasts that fed directly into territory sales targets