Why does a confidence interval matter for budget decisions?

Because it tells you whether a difference between two channels is a finding or noise. A point estimate makes a marginal call look decisive, and the first person who notices the number was not exact stops trusting the rest of the report.

What makes a budget recommendation actionable?

It states the estimate and its interval, the share of revenue covered, which channels could not be resolved, the window each platform used, and the evidence that would reverse it. A recommendation missing the last item cannot be reviewed.

Best marketing attribution software with confidence intervals and actionable budget recommendations

Few attribution tools report uncertainty at all. The ones built on statistical models do: Recast and Prescient AI through Bayesian marketing mix modelling, Admetrics through Bayesian statistics, and Haus through experimental design. Causality Engine reports no interval: it puts a data-health score on every channel, grading the read rather than the channel, and gives each channel a next step with how to test it. Most multi touch tools return a point estimate with no range.

By Joris van Huët, Founder & CEOPublished 2026-09-16

The shortlist, compared.

What each tool measures, what it needs installed, and what it costs. Prices are the vendor's own published pricing, read on the date shown.

Best marketing attribution software with confidence intervals and actionable budget recommendations: the shortlist by method, pixel and starting price
Tool	Method	Pixel	Starting price
Causality Engine	Method: Causal inference on a GA4 export	Pixel: No	Starting price: 99 euro per readExcl. VAT
Recast	Method: Bayesian marketing mix modeling	Pixel: No	Starting price: Custom (quote)
Admetrics	Method: Bayesian statistics + multi-touch attribution	Pixel: Yes	Starting price: €339/moadmetrics.io/en/pricing, read 2026-09-08
Haus	Method: Geo-lift experiments, with Causal Attribution and Causal MMM calibrated on them	Pixel: No	Starting price: Custom (quote)haus.io/pricing, read 2026-09-26
Prescient AI	Method: ML-based media mix modeling	Pixel: No	Starting price: Custom (quote)prescientai.com/pricing, read 2026-09-26

Competitor pricing is each vendor's publicly listed pricing as read on the date shown, and it changes without notice: verify on the vendor's own site before relying on it. Vendors without a public price are marked as such. Comparisons set Causality Engine's one-time €99 analysis against subscription models.

Why each one is on the list

Causality Engine. A data-health score on every channel in place of an interval, and a next step per channel with how to test it.
Recast. Bayesian marketing mix modelling, which produces posterior intervals by construction.
Admetrics. Bayesian statistics applied to multi touch attribution.
Haus. Geo lift experiments, where the uncertainty comes from the design rather than a model assumption.
Prescient AI. Machine learning media mix modelling, quoted.

How to choose between them.

Where the interval comes from: Not whether a range is displayed, but what generates it. A range that never widens as the data thins is not measuring uncertainty.
What happens to an unresolvable channel: A channel with no variation in the window cannot be estimated. Reporting it as unresolved is correct; giving it a number that looks like the others is not.
Whether a recommendation states its condition: An actionable recommendation says what evidence would reverse it. Without that it is a preference with a number attached.
Coverage: A read accounting for sixty percent of revenue and saying so is stronger than one that covers sixty percent silently.

Questions people ask next.

Best marketing attribution software with confidence intervals and actionable budget recommendations
Tools built on statistical models report uncertainty: Recast and Prescient AI via Bayesian marketing mix modelling, Admetrics via Bayesian multi touch attribution, and Haus via experimental design. Causality Engine reports no interval; it puts a data-health score on every channel and gives each a next step with how to test it. Most multi touch attribution tools return point estimates only.
Why does a confidence interval matter for budget decisions?
Because it tells you whether a difference between two channels is a finding or noise. A point estimate makes a marginal call look decisive, and the first person who notices the number was not exact stops trusting the rest of the report.
What makes a budget recommendation actionable?
It states the estimate and its interval, the share of revenue covered, which channels could not be resolved, the window each platform used, and the evidence that would reverse it. A recommendation missing the last item cannot be reviewed.

More questions answered on the answers index, including attribution for agencies with multiple clients, analytics for small DTC brands, attribution for Dutch beauty and fashion brands.

The shortlist, compared.

Why each one is on the list

How to choose between them.

Questions people ask next.

Related reading

Your platforms guess.We run the math.

Your platforms guess.
We run the math.