PRISM turns marketing data into causal truth, governed intelligence, and business action. It unifies attribution, MMM reconciliation, causal intelligence, decision simulation, and governance in one auditable platform.
PRISM eliminates the fragmentation between attribution, MMM, and budget decisions. Three integrated products. One governed intelligence environment.
The Attribution Intelligence Platform defines the full operating pipeline: data ingestion, identity resolution, journey construction, modelling, validation, decisioning, and governance. Seven layers, one auditable environment.
The person-level intelligence layer. Reconstructs customer journeys, resolves identity, measures channel contribution, and estimates true incremental impact using hybrid attribution — Markov chains, Shapley values, and MMM reconciliation.
The evolved decision layer. Model tournaments, Bayesian reasoning, budget simulators, allocation optimisers, governed recommendations, and evidence-grade export packs — all within a single operating environment.
Markov attribution models each channel as a state in the conversion journey. It estimates each channel's contribution by measuring the probability of conversion with and without that channel — the removal effect.
Shapley values treat channels as players in a cooperative game. Each channel receives its average marginal contribution across all possible orderings — a provably fair, game-theoretically grounded attribution rule.
PRISM blends Markov and Shapley outputs using MMM-calibrated weights — so person-level MTA is constrained to be consistent with aggregate media mix findings. This reconciliation eliminates the classic conflict between attribution models and MMM.
Attribution without uncertainty quantification is false precision. PRISM's Confidence Index (CI) scores each attribution output on three dimensions — making it safe to act on the results.
PRISM vNext is where attribution intelligence becomes actionable. Model tournaments, Bayesian simulation, and allocation optimisation in one governed environment.
Multiple attribution models compete on held-out data. The winner's weights feed the Bayesian scenario engine — no single model lock-in.
Simulate any spend allocation and see projected outcomes — conversion, revenue, ROAS — with saturation-aware diminishing returns modelling.
Find the optimal budget split subject to channel minimums, maximums, and total budget constraints. The efficient frontier surfaces all Pareto-optimal solutions.
Recommendations are issued with confidence thresholds, evidence references, and audit trails. Every output is auditable from data to decision.
Ask "what if?" questions under uncertainty. The Bayesian engine propagates uncertainty through the causal graph, returning probability distributions over outcomes.
Board-ready PDF exports containing attribution analysis, model comparison, scenario results, and recommended allocation — fully audit-traceable.
Last-click winners are not the same as long-term growth drivers. PRISM is built on the conviction that marketing intelligence requires causal reasoning — not correlational shortcuts — and that every attribution output must be auditable, validated, and uncertainty-aware.
Attribution tells you who got credit. Incrementality tells you who created the outcome. PRISM ties both together through geo holdout experiments and MMM reconciliation.
The Confidence Index makes model reliability visible. You know not just what the attribution says, but how much to trust it — before you act.
PRISM unifies MTA, MMM, and experiment signals in one governed environment. Marketing, finance, and leadership work from the same validated intelligence.
Every PRISM output connects to an action: rebalance budget, cap a channel, shift to brand building. Attribution that does not drive decisions is not intelligence.
Start a conversation — we'll walk you through PRISM's capabilities and show you where it fits your environment.