Bayesian marketing mix modeling built for modern brand advertisers
Recast is a marketing mix modeling (MMM) platform that applies a proprietary Bayesian framework to help brand advertisers measure, forecast, and optimize their marketing spend. Unlike simpler analytics tools, Recast is designed for organizations with complex media mixes — building models with weekly forecast validation that achieve 94%+ accuracy, and calibrating them with real incrementality experiments through its GeoLift product.
Key Features
Proprietary Bayesian MMM
- Bayesian statistical framework providing uncertainty quantification alongside point estimates
- Weekly forecast validation with documented 94%+ accuracy
- Handles complex, multi-channel media mixes across digital and traditional channels
- Time-varying ROIs and promotional effects to capture seasonal and market dynamics
Multi-Stage Modeling
- Multi-stage MMM framework (launched late 2025) for modeling complex customer journeys
- Captures downstream effects of upper-funnel media on lower-funnel conversions
- More granular than single-stage MMMs for brands with long consideration cycles
GeoLift Incrementality Testing
- Geo-based lift experiments to calibrate and validate MMM findings (launched September 2025)
- Incrementality testing that feeds back into model calibration for higher accuracy
- Reduces reliance on assumption-based priors by grounding models in real experiments
- Enables direct comparison between model-predicted and experiment-measured lift
Scenario Planning and Uncertainty Reduction
- Budget scenario planning with uncertainty ranges (not just point estimates)
- Channel-level and total portfolio scenario modeling
- Clear communication of model uncertainty to support decision-making
- Ongoing model refit to reflect changing media conditions
Business Impact
Recast is built for brand advertisers and performance marketing teams that have moved beyond last-click attribution and need a rigorous, statistically grounded view of media effectiveness. Its documented 94%+ weekly forecast accuracy positions it among the more accurate MMM solutions in the market.
- Media Efficiency: Identifies over- and under-invested channels with statistical confidence
- Budget Optimization: Scenario planning reveals optimal budget allocations before execution
- Incrementality Validation: GeoLift experiments provide ground-truth calibration for model outputs
- Reduced Uncertainty: Bayesian framework quantifies uncertainty so teams can act with appropriate confidence
Why Bayesian MMM?
Traditional MMM produces single point estimates for media effectiveness. Recast’s Bayesian approach produces full probability distributions — giving teams not just “display ads drove X% of sales” but “display ads drove X% of sales, with 90% confidence the true value is between Y% and Z%.” This matters for budget decisions where overconfidence in point estimates leads to poor allocation.
Pricing
Recast does not publish pricing. It is an Enterprise SaaS platform with custom pricing designed for complex brand advertisers. Pricing reflects the bespoke modeling work involved and the sophistication of the platform. Contact Recast for a quote.
Frequently Asked Questions
How much does Recast cost? Recast does not publish pricing. It is an enterprise platform with custom quotes. Based on its positioning and typical MMM market rates, expect significant investment — MMM platforms for large advertisers commonly range from $50K–$300K+ annually. Contact Recast directly for pricing.
Is Recast free? No. Recast is a paid enterprise platform with no free tier. There is no self-serve access or public trial.
What is the difference between Recast’s MMM and open-source options like Robyn or LightweightMMM? Recast offers a fully managed Bayesian MMM with proprietary calibration, weekly forecast validation, and the GeoLift incrementality product. Open-source options like Meta’s Robyn or Google’s LightweightMMM require in-house data science resources to build, maintain, and interpret. Recast provides the model infrastructure and ongoing support; open-source tools provide the framework but require internal expertise. Recast has published a direct comparison on its website.
What is GeoLift and why does it matter for MMM? GeoLift is Recast’s geo-based incrementality testing product, launched in September 2025. It runs geographic lift experiments — comparing test and control markets — to validate and calibrate the MMM. Without incrementality calibration, MMMs can overestimate or underestimate channel contributions. GeoLift bridges the gap between model estimates and real experimental evidence.
How does Recast compare to Measured? Measured is an incrementality testing platform that evaluates media performance through controlled experiments. Recast is primarily an MMM platform with incrementality calibration (GeoLift). Measured focuses on experiment-first measurement; Recast uses experiments to improve a broader Bayesian MMM. Both are used by sophisticated performance marketing teams, often together.
How does Recast compare to Keen? Keen is a marketing investment intelligence platform designed for ongoing budget optimization, often accessible to non-data-science teams. Recast is a technically rigorous Bayesian MMM platform designed for brands with complex media mixes and in-house or agency data science support. Recast provides more statistical depth; Keen offers more accessible ongoing budget planning.
Does Recast work for both digital and traditional media? Yes. Recast’s MMM framework covers all media channels — digital (paid search, social, programmatic, streaming) and traditional (TV, OOH, print, radio). Multi-channel coverage is fundamental to MMM’s value as a measurement approach.
User Reviews & Social Proof
No public reviews for Recast are available on G2 or Capterra. Given the enterprise and technically specialist nature of MMM platforms, user feedback primarily surfaces through industry analyst reports, case studies, and marketing conferences rather than public review platforms.
Recast has been featured in industry top-10 MMM platform lists in 2026, including coverage by Measured in their roundup of top MMM solutions. Its presence on these lists reflects recognition within the media measurement community.
Recast vs Alternatives
Recast vs Measured
Measured takes an experiment-first approach to media measurement — running controlled holdout tests to determine true media incrementality. Recast builds a Bayesian MMM and uses geo experiments (GeoLift) to calibrate it. They are complementary measurement philosophies: Measured for direct incrementality measurement, Recast for portfolio-level MMM with experimental grounding. Many large advertisers use both.
Recast vs Keen
Keen is a marketing investment intelligence platform focused on making MMM-style budget optimization accessible to marketing teams without heavy data science resources. Recast is built for organizations with more complex needs and tolerance for statistical rigor. Keen is more accessible; Recast goes deeper.
Recast vs Nielsen (MMM)
Nielsen offers custom marketing mix modeling as a managed service for large advertisers. Recast is a SaaS platform with a proprietary Bayesian approach that clients can use more interactively. Recast’s Bayesian framework provides uncertainty quantification that traditional frequentist MMM methods (used by many legacy providers including Nielsen) do not.
Recast vs Northbeam
Northbeam is a multi-touch attribution platform designed for DTC and e-commerce brands, providing channel-level performance data and optimization recommendations. Recast is a Bayesian MMM platform — better for brands that need portfolio-level incrementality estimates across all media, including offline. Northbeam is better for granular digital attribution in real-time; Recast for strategic budget allocation modeling.
Recast vs Optimine
Optimine provides marketing mix modeling and continuous budget optimization with a focus on accessible scenario planning for brand teams. Recast provides a more rigorous Bayesian statistical framework with GeoLift calibration. Both address budget optimization, but at different levels of statistical complexity.
Recent Updates (2025–2026)
- Late 2025: Released multi-stage MMM framework, enabling more accurate modeling of complex customer journeys where upper-funnel media influences lower-funnel conversions over time.
- September 2025: Launched GeoLift — a geo-based incrementality testing product that calibrates and validates MMM outputs with real experimental data.
- 2026: Featured in multiple industry top-10 MMM platform lists, including Measured’s roundup of best MMM solutions for 2026.
- 2025 (ongoing): Active presence in the MMM discourse, including publication of comparisons against open-source alternatives (Robyn, LightweightMMM) to help brands evaluate options.
Explore More Media Planning Tools
- Measured — Incrementality testing platform for direct experimental measurement of media effectiveness
- Keen — Marketing investment intelligence for accessible budget optimization and scenario planning
- Northbeam — Multi-touch attribution and spend optimization for DTC and e-commerce brands
- Optimine — Marketing mix modeling and budget optimization for brand teams
- Akkio — AI analytics platform for media agencies with predictive modeling and reporting automation
- Nielsen Media Impact — Nielsen’s cross-media reach and frequency planning tool
- Halliard — Media planning and flowchart tool built for independent agencies