Comparison

Measured vs Haus vs Statsig

Three specialist lift testing vendors compared. Geographic vs platform-side, methodology depth, integration with MMM, and which to pick.

By Ramanath, CTO & Co-Founder at Presenc AI · Last updated: May 18, 2026

Three Lift Testing Vendors

Measured, Haus, and Statsig are three specialist lift testing vendors offering different approaches to incrementality measurement. All three help brands run causal experiments on marketing channels; they differ in methodology, scope, and operating model.

Measured

Measured focuses on cross-channel incrementality testing with a managed-service model. The platform runs experiments on behalf of the brand across paid channels and integrates results into MMM-style decomposition. Strong for brands with diverse paid media portfolios and the need for systematic cross-channel lift measurement. Pricing is enterprise-tier ($150K-$500K+ annual).

Haus

Haus emphasizes geographic incrementality testing with sophisticated synthetic control methodology. The platform specializes in geo experiments for channels without platform-side randomization (TV, OOH, podcast, PR, AI search). Strong for brands testing upper-funnel and offline channels where geographic randomization is the only causal option. Pricing is mid-to-enterprise tier ($100K-$300K annual).

Statsig

Statsig is primarily a platform-side experimentation tool that has expanded into marketing-side lift testing. Strong technical foundation in product experimentation; marketing lift testing is a newer offering. Best fit for tech-forward brands with strong engineering teams that want experimentation infrastructure that spans product and marketing.

Feature Comparison

DimensionMeasuredHausStatsig
Primary methodologyCross-channel liftGeographic synthetic controlPlatform-side experimentation
AI search testingLimitedStrong (geo lift)Limited
TV/OOH/PR testingLimitedStrongLimited
Paid digital liftStrongCapableStrong
MMM integrationBuilt inPartner integrationsCustom
Operating modelManaged serviceHybridSelf-service tooling
Best brand size$50M+ revenue$25M+ revenue$10M+ revenue
Pricing tierEnterpriseMid to enterpriseMid

How to Choose

For brands with diverse paid media portfolios and need for cross-channel coordination: Measured. For brands testing upper-funnel and offline channels including AI search via geographic holdouts: Haus. For tech-forward brands integrating marketing and product experimentation: Statsig. Many sophisticated brands run more than one for different test types.

For AI Search Lift Testing

Haus is the clearest fit for AI search lift testing. The platform's geographic synthetic control methodology is the right design for channels without platform-side randomization, including AI search. Measured and Statsig can support AI search lift testing but it is less their core offering.

How Presenc AI Helps

Presenc AI provides the AI visibility data layer that any of these lift testing vendors needs to run AI search experiments. DMA-level visibility data feeds the synthetic control donor pool; weekly national visibility confirms the test's first-stage effect. The lift testing vendor handles the methodology; Presenc handles the data.

Frequently Asked Questions

Yes, for causal calibration. MMM produces correlational coefficients; lift testing produces causal estimates that anchor the MMM. Brands running MMM without periodic lift test calibration are running uncalibrated correlational models, which is not the same as causal evidence.
Once per quarter on a rotating channel basis. Mature programs cycle through all material channels every six to eight quarters. AI search should be in the rotation alongside paid digital, TV, and other major channels.
Yes, for platform-side conversion lift via Meta and Google built-in products. Geographic lift testing with synthetic control is technically feasible in-house but requires marketing science capability that most teams do not have. Vendors are mostly buying methodology depth and operating support; the underlying statistics are public.
Vendor-managed: $100K-$500K+ annual depending on test volume and methodology depth. Per-test cost in foregone revenue from the holdout is typically 5-15 percent of the tested channel's spend during the test window. Total cost (vendor plus opportunity) often runs 10-25 percent of the tested channel's annual spend, justified by the budget allocation improvements the tests enable.

Track Your AI Visibility

See how your brand appears across ChatGPT, Claude, Perplexity, and other AI platforms. Start monitoring today.