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Casualprecision

AttributionPrecision uses Bayesian causal marketing mix modeling to combine media, seasonality, economic, and internal data into a single probabilistic model that isolates each driver’s incremental impact. The platform delivers unified attribution dashboards, direct and spot TV/audio attribution, and scenario forecasting to help marketers and finance teams optimize spend and meet ROI targets.

Newport Beach, United StatesFounded 2015261K+ followers
Updated 3 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Marketers struggle to determine the true incremental impact of each media channel and business driver because traditional attribution methods double‑count sales, rely on siloed platform metrics, and often conflict with finance’s ROI expectations.

Solution

AttributionPrecision applies Bayesian causal marketing mix modeling to integrate cross‑channel media data, seasonality, economic conditions, and internal factors such as pricing and promotions. The platform builds a nonlinear probabilistic model that isolates the incremental contribution of each driver, producing a unified attribution view for budgeting and ROI reporting. Marketers can identify inefficient spend, manage customer‑acquisition cost and payback periods, and align marketing plans with finance expectations. The solution also offers privacy‑first direct and spot attribution tools for TV, radio, CTV, and digital audio, enabling granular optimization of media buys. Results are delivered through dashboards that compare channel contributions and forecast the impact of budget changes.

Target Audience

Primary customers are senior marketers and finance teams at large enterprises who need rigorous, cross‑channel attribution for media budgeting and performance reporting.

Features

  • Bayesian MMM framework that combines media, seasonality, economic factors, and internal variables in a single probabilistic model
  • Nonlinear multistage modeling with ad‑stock and saturation curves to capture diminishing returns
  • Direct attribution for CTV, streaming, and digital audio using privacy‑first identity matching and A/B holdout counterfactuals
  • Spot attribution for linear TV and radio that quantifies digital surge and cross‑media lift
  • Unified attribution dashboard showing channel contribution percentages, CAC impact, and payback insights
  • Integration of external economic and competitor data to adjust for market conditions
  • Customizable scenario analysis to forecast spend shifts and incremental ROI
This profile is AI-generated and may contain inaccuracies.