Attribution shows how Prescient's models distribute performance across your media mix — comparing modeled results with what each channel reports, so you can see the incremental impact behind every dollar.
Choose a Target, the models to include, your channels, and a date range. These filters shape every section below — and can be saved as a View.
Start with the headline cards for the period (shown above). Metrics adapt to your target — the green cards are Prescient's modeled results, each split into Base (direct) and Halo (cross-channel).
Follow each ribbon from a media channel on the left to the outcome it drives on the right. Thicker flows mean larger contribution; click any node for a detailed breakdown.
Switch between Channels, Tactics and Campaigns to change the level of detail. Each row lines up modeled metrics against channel-reported ones — expand a row to see its trend and saturation.
| Modeled (MMM) | Channel Reported | ||||
|---|---|---|---|---|---|
| Channel | Spend | MMM Revenue | MMM ROAS | Channel Rev. | Ch. ROAS |
| Total | $257,868 | $1,933,742 | 7.50 | $800,458 | 3.10 |
| MMeta Ads | $117,712 | $748,497 | 6.36 | $351,645 | 2.99 |
| aAmazon Ads | $59,700 | $588,664 | 9.86 | $280,724 | 4.70 |
| tTikTok GMV Max | $20,363 | $302,078 | 14.83 | $0 | 0.00 |
Use Compare to plot two metrics together (e.g. Spend vs MMM Revenue), or Breakdown to split one metric by channel or tactic and see what's driving it.
The Saturation Plot uses historical model data to estimate how a campaign's incremental revenue changes at different spend levels — making it easier to spot room to scale, or the point where returns begin to diminish.
Toggle Seasonal Forecast to fold expected seasonal patterns into the curve — so you can evaluate scenarios during periods of unusually high or low demand, not just the flat historical model.
The plot is based on historical modeled performance. Use it to weigh budget scenarios — not to predict exact results. Treat scenarios far outside your historical spend as directional only.
Compare scenarios close to your historical spend for the most reliable estimates.
Weigh both incremental ROAS and estimated incremental revenue when changing budget.
Use the confidence band to gauge how certain the model is at each spend level.
Enable Seasonal Forecast when judging spend during peak or off-peak periods.
Base is a channel's direct contribution to an outcome. Halo is its indirect lift — where one channel influences another channel, retailer, or model. MMM Revenue includes both.
Channel reporting asks "which conversions did this platform claim?" Prescient asks "what incremental impact did this investment have across the business?" Differences are expected — and useful.
Compare similar date ranges when reviewing performance changes.
Read modeled and reported metrics together — never one in isolation.
Weigh both Base and Halo — a channel's real value is often in the Halo.
Save filter combinations you use often as Views for one-click access.
Confirm model health before acting on any unexpected finding.
Testing a future budget change? Head to Media Forecaster next.