Causal Marketing Mix Modeling

Invest Your Next Marketing Dollar with Confidence

Know what’s really driving marginal incremental returns across the funnel. Transform those insights into precise forecasts, smarter budget plans, and actions that maximize profit.

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Invest Your Next Marketing Dollar with Confidence
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Why Legacy Measurement Models Miss the Mark

Learn how Causal MMM gives you the truth you need to plan your marketing investments better.

Touch-based Attribution Models

  • Doesn’t account for incrementality

  • Ignores non-digital media and impact of promotions

  • Signal loss due to privacy restrictions

  • Tied to click-based bias & correlation

Lifesight’s Causal Marketing Mix Modeling

  • Measures incrementality using statistical modeling

  • Accounts for all media types & business levers

  • Using aggregate data, privacy-safe by design

  • Estimate incremental marginal ROI

Forecast, Plan & Optimize Your Media Spend to Maximize Profit

Causal MMM blends advanced marketing mix modeling with geo-test calibration to reveal incremental ROI, saturation points, and profit-maximizing mixes you can act on instantly.

Marketing Mix Modeling, Powered by Causality

We create a digital twin of your business model and map how media, price, promotions, and seasonality influences revenue so you get a more accurate estimate of the ground truth.

Marketing Mix Modeling, Powered by Causality
Industry leading Ensemble Forecasting - Lifesight

Industry-leading Ensemble Forecasting

Lifesight runs multiple forecasting models in parallel, and the best mix is chosen automatically, delivering recommendations that will deliver maximum profit with highest accuracy among all scenarios.

Automated & Continuous Refresh & Calibration

Fresh geo-lift results feed into models every week, tightening coefficients and correcting drift. Your curves stay current with market changes, creative fatigue, and external factors.

Automated Continuous Refresh Calibration - Lifesight
Optimize For Profit Growth on Autopilot - Lifesight

Optimize For Profit & Growth, on Autopilot

See exactly where ROI flattens and profit peaks. Our optimizer allows one-click budget adjustments across all major channels that maximizes media spend efficiency.

Why Choose Causal Modeling for

Full-Funnel Measurement?

Measure the real contribution of each channel

Causal MMM quantifies how every marketing lever – brand, performance, pricing, seasonality drive revenue.

Confident budget optimization backed by incrementality

Find the optimal budget mix across channels and avoid over-spending based on incremental & marginal insights.

Forecast outcomes from a media mix before spending

Simulate outcomes with high confidence by forecasting the impact of spend reallocation across channels and tactics.

Causal MMM

Causal Marketing Mix Modeling in Lifesight’s UMM Framework

Causal MMM serves as the strategic backbone of the UMM Framework by generating high-confidence hypotheses for experiments and calibrating attribution models using iROAS and mROAS multipliers grounded in incrementality.

  • Insights ready in under 20 mins

  • Self-serve modeling experience

  • Profit, adstock & LTV calculation

  • 1-click MMM recalibration & refresh

Building a custom marketing Mix Model

Aggregate & Transform Your Data

Connect your marketing channels and sales data to instantly sync and aggregate it.

Train & Validate the Model

Map your causal graph and automatically build & validate your model.

Plan & optimize your marketing

Generate incrementality-based optimal scenario & plans with accurate ensemble forecasting.

Frequently asked questions

Cross-channel budget setting and next-dollar allocation. It produces response curves and profit-max recommendations you can hand to Finance, then pushes targets to Optimization.

It’s calibrated with real experiments (geo-RCTs / platform lift where appropriate), updates on a frequent cadence (monthly or better), and exposes confidence bands, so plans include ranges—not just point estimates.

Sales/conversions (by market or brand), media delivery/spend by channel/vendor, price/promo, seasonality, and key external drivers. Regional granularity improves curve quality and lets you validate with geo tests.

Yes-curves capture diminishing returns and lag (adstock), so the plan avoids underspend/overspend zones and respects channel momentum.

Significant lift results re-weight priors and tighten the curve’s bands for that channel/market. The change is versioned and visible in the Model Card.

Most teams run monthly refresh (some bi-weekly); drift alerts trigger re-fit when inputs shift (promo depth, pricing, mix).

Yes-MMM works on aggregate signals. We lean on regional variation and experiment reads to stabilize curves in low-granularity channels.