Marketing Measurement
Without the Enterprise Price

Causal measurement using geographic holdouts, side-by-side counterfactual models, and transparent uncertainty intervals.

Calibrate Bayesian MMM with lift tests, response curves, and budget optimization workflows.

Measure intervention-driven lift with ITS, comparative time series, and Bayesian counterfactual models.

Forecast revenue and scenario outcomes using marketing inputs, intervals, and planning assumptions.

Store, tag, and analyze lift tests from Meta, Google, TikTok, and other external measurement systems.

Run holdout-based experiments for CRM, direct mail, push, and other addressable channels.

Use journey analytics and algorithmic attribution as a directional complement to incrementality and MMM.

Measure creative variables, attention signals, and concept win rates with reusable experiment logs.

Predict downstream customer value to set smarter CAC, retention, and audience priorities.

Track ARPU by cohort, channel, and segment to monitor monetization quality and planning inputs.

Build exportable acquisition audiences with better targeting, suppressions, and testable universes.

Create higher-quality expansion audiences from value-based or segment-specific seeds.

Score existing customers for retention, churn, cross-sell, and next best action.

Blend clustering, RFM, value, and need-state logic to build actionable persona segments.

And more coming soon! We have many more features in the works that we are actively developing.