Recast Pricing: Complete 2026 Breakdown
Recast is a Bayesian marketing mix modeling (MMM) platform that provides media investment measurement, incrementality testing, and scenario planning. It uses a proprietary Bayesian approach with uncertainty quantification and achieves 94%+ weekly forecast validation. Recast does not publish pricing publicly and operates on a custom enterprise model.
Pricing Model
Recast uses a custom enterprise subscription model. Pricing is not publicly disclosed. Based on industry benchmarks for dedicated MMM platforms at Recast's positioning, typical annual contract values are in the range of $50,000–$300,000+/year, depending on:
- Annual media spend under measurement (larger spend = more complexity = higher cost)
- Number of channels and markets modeled
- Frequency of model refreshes (weekly vs. monthly)
- Use of GeoLift incrementality testing (launched September 2025)
- Number of user seats and client-side data science involvement
These ranges reflect industry-standard MMM platform pricing at Recast's tier, not confirmed Recast quotes. Verify directly with Recast sales.
Pricing Overview
| Tier | Estimated Annual Cost | Best For |
|---|---|---|
| Mid-Market | ~$50K–$100K/year (estimated) | DTC and e-commerce brands with $10M–$50M in annual media spend |
| Enterprise | ~$100K–$300K+/year (estimated) | Enterprise advertisers with complex multi-channel, multi-market media mix |
Cost estimates are industry benchmarks for MMM platforms, not confirmed Recast pricing. Actual costs depend on scope. Source: industry analyst context for Bayesian MMM platforms.
What's Included
Recast's platform includes:
- Proprietary Bayesian MMM: Full-funnel marketing mix modeling with uncertainty quantification, avoiding overconfidence common in frequentist approaches
- Multi-stage modeling: Separate measurement for awareness, consideration, and conversion stages
- GeoLift incrementality testing (launched September 2025): Geographic hold-out tests to calibrate MMM with causal incrementality data
- Scenario planning: Budget allocation optimization and what-if scenario modeling
- Ongoing model maintenance: Regular model refreshes as new data arrives; 94%+ weekly forecast validation
- Client portal: Self-serve access to model outputs, charts, and scenario planning tools
Typical Total Cost of Ownership
- Annual subscription: MMM platforms typically require annual or multi-year contracts; spot or project-based pricing is uncommon at this tier
- Data preparation: Clients must provide clean, consistent media and outcome data for model inputs — internal data ops time is a real TCO factor
- GeoLift testing costs: Incrementality tests require media investment specifically allocated to holdout groups; this is a separate budget consideration, not a software cost
- Analyst time: Acting on MMM outputs requires in-house or agency analyst resources to translate model outputs into planning decisions
- Integration: Connecting media reporting systems and sales/conversion data to Recast's input format may require engineering time
Who It's Best For / Not For
Best for: Performance-oriented brands and DTC advertisers with $10M+ in annual media spend who need rigorous, incrementality-calibrated measurement. Particularly strong for brands that have moved past last-click attribution and need to understand true channel contribution. Recast's Bayesian approach is especially valued by data-science-forward teams.
Not ideal for: Small advertisers with limited media spend, brands without consistent data pipelines, or teams looking for a lightweight attribution tool. Recast requires meaningful data infrastructure and analyst involvement to deliver value. Brands spending under $5M/year in media may not generate enough signal for reliable MMM outputs.
How to Negotiate
- Get competitive quotes from Measured and Northbeam — Both compete in the measurement space and provide pricing leverage
- Start with a scoped pilot — Request a single-market or single-channel model first to evaluate fit before committing to a full platform contract
- Clarify model refresh frequency — Weekly refreshes cost more than monthly; determine what cadence your planning cycle actually needs
- Ask about incrementality test credits — GeoLift tests may be included in the base contract or separately priced; clarify before signing
Alternatives
- Measured — Incrementality-first measurement platform; mid-market and enterprise (see Measured pricing)
- Keen — Marketing mix optimization with scenario planning; mid-market positioning
See the full Recast alternatives page for a broader comparison.
Frequently Asked Questions
Does Recast publish pricing?
No. Recast does not publish pricing on its website. All contracts are custom-quoted based on scope. The cost ranges cited above are industry benchmarks for MMM platforms at Recast's positioning, not confirmed Recast pricing.
What media spend level is needed to use Recast effectively?
Recast is best suited to brands with at least $10M in annual media spend. Below this threshold, MMM may not generate sufficient signal across channels to produce reliable outputs. Smaller advertisers are generally better served by lighter-weight measurement tools.
How is Recast different from Google Meridian or Meta Robyn?
Google Meridian and Meta Robyn are open-source Bayesian MMM frameworks requiring significant data science resources to deploy and maintain. Recast is a managed platform — they run and maintain the model on your behalf. Recast is a better fit for teams without dedicated data science resources; open-source alternatives suit teams with in-house MMM expertise.
What is GeoLift and how does it affect pricing?
GeoLift (launched September 2025) is Recast's geographic holdout testing capability that calibrates MMM models with causal incrementality data. It may be included in enterprise contracts or separately priced. Ask Recast sales specifically about GeoLift inclusion when requesting a quote.
Does Recast require annual contracts?
Standard MMM platform contracts are annual. MMM is a continuous measurement practice — the model improves over time with more data — so shorter commitments are atypical in this category.
How does Recast's Bayesian approach affect accuracy?
Recast's Bayesian approach quantifies uncertainty in model estimates, giving planners confidence intervals rather than point estimates. The platform reports 94%+ weekly forecast validation. This contrasts with frequentist MMM approaches that may overstate precision.
Sources & Methodology
- Recast product documentation (verified April 2026)
- G2 — Recast — Platform context (verified April 2026)
- Industry analyst benchmarks for Bayesian MMM platform pricing (directional estimates only)
Methodology: Recast does not publish pricing. Cost ranges cited are industry benchmarks for platforms at comparable positioning. Verify all pricing directly with Recast before making purchasing decisions.
Last reviewed April 2026. See the full Recast listing, compare Recast alternatives, or explore all media planning tools in the directory.