Haus
Marketing incrementality measurement platform using geo-lift experiments and causal inference for channel ROI.
Our Verdict
Strong pick for causal incrementality, but it is a measurement layer on top of an MMP rather than a replacement.
Pros
- Rigorous geo-lift and causal inference methodology
- Clean, opinionated UX for experiment design
- Good fit for mid-to-large brands testing incrementality
- Methodology transparent enough for data teams
Cons
- Requires meaningful budget to power tests
- Not a real-time attribution platform
- Limited direct mobile MMP functionality
- Experiment cadence slower than MTA
Best for: Mid-market and enterprise brands running geo and holdout experiments for channel ROI.
Not for: Small budgets or teams that need per-install deterministic attribution.
When to Use Haus
Good fit if you need
- Geo-lift incrementality experiments for measuring true channel ROI
- Causal inference-based marketing measurement for DTC and mobile growth teams
- Testing marketing budget changes with holdout regions for clean signal
- Incrementality testing for Meta, TikTok, and Google paid UA campaigns
Lock-in Assessment
High 2/5
Lock-in Score 2/5
Pricing
Price wrong?Haus Pricing
- Pricing Model
- custom
- Free Tier
- No
- Entry Price
- —
- Enterprise Available
- No
- Transparency Score
- —
Beta — estimates may differ from actual pricing
1,000
1001K10K100K1M
Estimated Monthly Cost
$25
Estimated Annual Cost
$300
Estimates are approximate and may not reflect current pricing. Always check the official pricing page.
Community Discussion
Comments powered by Giscus (GitHub Discussions). You need a GitHub account to comment.