What it does
Recast MMM combines Bayesian marketing-mix models with forecasting, channel-saturation analysis and budget planning. It models changing channel performance, delayed effects, promotions and multi-stage or cross-commerce outcomes.
Recast needs daily channel spend and business results, plus a promotional calendar when relevant. Its data guide recommends substantial historical coverage and a weekly resupply of the full dataset so corrections to earlier days reach the model. Keep missing values distinct from zero spend and coordinate schema or channel changes before updating the feed.
Reports that follow model refreshes
Open Reporter, choose Recurring Reports, select a report type and supply its parameters. In the report library, Show only auto-run isolates these recurring outputs. Relative date ranges move with the latest model data; a completed-month report waits until the whole month is available.
The Insights Overview report separates observed totals from estimated paid and baseline outcomes. Its channel view includes uncertainty, and the page provides downloads of the confidence intervals. This makes it possible to inspect how precise a channel estimate is alongside its return.
An account is required. Contact Recast to arrange the implementation and access. Critical data errors can stop a model refresh; warnings can leave the run active while the issue is investigated.
Strengths
- Models delayed effects, promotions and changing channel performance.
- Provides forecast-validation reports and explicit input-error handling.
Watch out for
- Requires a maintained historical daily spend and KPI feed.
- Schema or channel changes can delay model refreshes.
Best for
- Marketing teams able to maintain historical channel and outcome data for MMM
Sources
- Recast Data Guide (Oct 27, 2026)
- Recast MMM (Oct 27, 2026)
- Recast Reporter (Oct 27, 2026)
- The Recast API (Oct 27, 2026)
- Recast company and product overview (Oct 27, 2026)
- 🚀 Implementation with Recast | Recast MMM Knowledge Base (Oct 25, 2026)