AI for Marketing Analytics and Attribution

Measure marketing accurately with AI-driven analytics and attribution

Analytics and attribution connect spend to outcomes across channels. AI enhances data quality, modeling, and anomaly detection, but must handle privacy, identity loss, and incrementality with care.

Provide trustworthy, incrementality-aware insights that drive smarter budget and creative decisions.

MMM, MTA (where signals allow), causal uplift, anomaly detection, fore

Dashboards with lift, ROAS/CPA, scenarios, budget simulators, and alerting for anomalies or drift.

Versioned models, governance board, documentation of assumptions, and regular backtesting.

live demo · related simulation● LIVE

Implementation Blueprint

Foundation: Define KPIs/attribution rules; ensure consent; set taxonomy for channels/campaigns; instrument experiments.

Pilot: Run MMM + at least one holdout; compare against platform numbers; validate stability and actionability.

Frequently asked questions

What are backtests, MAPE checks, and anomaly monitoring?

Backtests, MAPE checks, and anomaly monitoring

How can we guard against overfitting and unstable reallocations?

Guard against overfitting and unstable reallocations; keep human review.

Did MMM + uplift move budget to high-return channels, improving ROAS?

MMM + uplift moved budget to high-return channels, improving ROAS.

Did anomaly alerts catch tag breaks, preventing bad decisions?

Anomaly alerts caught tag breaks, preventing bad decisions.

▶ Try it live

Everything above runs in your browser — open Earthquake Wave Propagation Simulation and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.

▶ Open Earthquake Wave Propagation Simulation simulation