Quick Verdict
Sellforte scores 27 out of 31 in our structured evaluation; Haus scores 15 out of 31.
Haus is a strong, focused geo experimentation platform with best-in-class experiment recommendations and AI-powered readouts.
Sellforte is the broader platform: it covers all three incrementality test types (geo, A/B, and conversion lift), unifies them into a single experiment library, integrates them into an MMM, and meets enterprise IT requirements that Haus does not yet address.
If geo testing is your entire incrementality program, Haus is a credible choice. If you need A/B test analysis, conversion lift ingestion, MMM calibration, or multi-region enterprise support, Sellforte is the stronger fit.
Introduction and Table of Contents
This article compares Haus and Sellforte head-to-head on incrementality testing capabilities, using the same 31-criterion framework we developed for our in-depth comparison of all major incrementality testing vendors. Here's what we're covering in this article
- Quick Verdict
- How We Evaluated
- About the Vendors
- Side-by-Side Scorecard
- Category-by-Category Breakdown
- Where Haus Wins
- Where Sellforte Wins
- Which Should You Choose?
- Frequently Asked Questions
How We Evaluated
Both platforms are scored against the same 31-criterion, 7-category framework developed for our in-depth comparison of incrementality testing tools in 2026. The criteria are presented in full detail in How to Choose an Incrementality Testing Tool: 31 Evaluation Criteria. They were derived from more than 700 discussions with marketers and marketing analytics professionals across retail, ecommerce, DTC, travel, and restaurants.
Each criterion is scored 1 (fully supported), 0.5 (partially supported or inconclusive evidence), or 0 (not supported or no public evidence found). Scores are based on public first-party vendor documentation, vendor-disclosed information on third-party platforms, and third-party review sites. Absence of evidence counted as 0.
Side-by-Side Scorecard
| Category | Haus | Sellforte |
|---|---|---|
| 1. Geo Test Analysis | 5 / 6 | 4 / 6 |
| 2. A/B Test Analysis | 0 / 4 | 4 / 4 |
| 3. Conversion Lift Test Analysis | 0 / 5 | 5 / 5 |
| 4. Experiment Recs & Insights | 5 / 5 | 3 / 5 |
| 5. Unified Experiment Library | 1.5 / 3 | 3 / 3 |
| 6. MMM Integration | 1.5 / 3 | 3 / 3 |
| 7. Enterprise-Grade Platform | 2 / 5 | 5 / 5 |
| Total score out of 31 | 15 | 27 |
About the Vendors
About Haus
Haus is a marketing science company founded in 2021 by Zach Epstein. Its platform centers on geo-based incrementality experimentation, with a focus on helping marketing teams design, run, and analyze geo lift tests to measure the true causal impact of advertising spend. Haus has more recently added Marketing Mix Modeling to its product offering.
About Sellforte
Sellforte is a SaaS platform that unifies Marketing Mix Modeling, Incrementality Testing, and Attribution into a single operating system for retail and ecommerce.
Unlike most other measurement vendors, Sellforte measures incremental ROAS at the campaign and ad set level, providing spend and bidding recommendations for tactical budget steering. Incrementality testing is one major component of the Sellforte platform, alongside Marketing Mix Modeling and incrementality-corrected attribution. Sellforte is used by enterprise retailers and ecommerce brands including bonprix, Lidl, C&A, Douglas, and Tchibo.
Category-by-Category Breakdown
1. Geo Test Analysis (Haus: 5/6, Sellforte: 4/6)
| Criterion | Haus | Sellforte |
|---|---|---|
| 1.1 Analyzes geo tests with synthetic control method, providing iROAS and confidence interval | 1 | 1 |
| 1.2 Self-serve UI for analyzing and reviewing geo test results | 1 | 1 |
| 1.3 Estimates media counterfactual for lost/incremental spend | 1 | 1 |
| 1.4 Configurable default post-test treatment / measurement window | 1 | 1 |
| 1.5 Executes geo experiments on ad platform | 1 | 0 |
| 1.6 Automatically detects geo tests from media and sales data | 0 | 0 |
| Category total | 5 / 6 | 4 / 6 |
This is Haus's strongest area, and the one where it outscores Sellforte. Both platforms analyze geo tests using the synthetic control method, produce iROAS and confidence intervals, estimate the media counterfactual for lost or incremental spend, and offer a self-serve UI for reviewing results. The difference comes down to two criteria.
Haus can execute geo experiments directly on ad platforms via API, meaning it can launch and manage tests inside Meta or Google without requiring teams to configure experiments separately. Sellforte does not offer this: tests must be configured on the ad platform side, with Sellforte handling the analysis. In practice, enterprise advertisers with dedicated ad platform support often handle execution separately regardless of which tool they use, but for smaller teams the Haus capability is a meaningful convenience.
Neither platform automatically detects geo tests from media and sales patterns. Both score 0 on criterion 1.6.
2. A/B Test Analysis for Owned Media (Haus: 0/4, Sellforte: 4/4)
| Criterion | Haus | Sellforte |
|---|---|---|
| 2.1 Analyzes own media A/B tests with synthetic control method, providing iROAS and confidence interval | 0 | 1 |
| 2.2 Self-serve UI for analyzing and reviewing own media A/B test results | 0 | 1 |
| 2.3 Estimates media counterfactual for A/B tests | 0 | 1 |
| 2.4 Configurable default post-test treatment / measurement window for A/B tests | 0 | 1 |
| Category total | 0 / 4 | 4 / 4 |
This is one of the sharpest gaps in the comparison. Sellforte covers all four criteria in this category: it analyzes audience-level A/B tests using the synthetic control method, outputs iROAS with confidence intervals, estimates the media counterfactual, and supports configurable measurement windows. Haus scores zero across all four criteria. Haus has not built A/B test analysis into its platform.
This matters for any advertiser running owned media experiments. Catalog tests, email holdout groups, and loyalty program tests are all A/B experiments at the audience level. If those tests are part of your measurement program, Haus cannot analyze them but Sellforte can.
3. Conversion Lift Test Analysis (Haus: 0/5, Sellforte: 5/5)
| Criterion | Haus | Sellforte |
|---|---|---|
| 3.1 Ingests Conversion Lift test results, providing iROAS and confidence interval | 0 | 1 |
| 3.2 Self-serve UI for analyzing Conversion Lift test results | 0 | 1 |
| 3.3 API connectors for automated conversion lift test ingestion | 0 | 1 |
| 3.4 Results comparable to ad platform data on campaign and ad set level | 0 | 1 |
| 3.5 Daily snapshot of conversion lift test progress, including iROAS and confidence interval | 0 | 1 |
| Category total | 0 / 5 | 5 / 5 |
Sellforte is the only platform in ourbroader incrementality testing tool comparison that fully supports conversion lift test analysis, and the gap with Haus is total: Haus scores 0 across all five criteria in this category.
Conversion lift tests are run inside ad platforms (Meta, Google, TikTok) and are part of most enterprise advertisers' measurement programs. Sellforte ingests them via API connectors, normalizes results to the campaign and ad set level, provides a self-serve UI for analysis, and offers daily in-flight snapshots so teams can monitor tests as they run rather than waiting for completion. Haus does not ingest, analyze, or display conversion lift test results.
For teams that run Meta or Google conversion lift tests alongside geo tests, this means Haus leaves a significant portion of their incrementality evidence outside the platform entirely.
4. Experiment Recommendations and Insights (Haus: 5/5, Sellforte: 3/5)
| Criterion | Haus | Sellforte |
|---|---|---|
| 4.1 Platform recommends which channels to test | 1 | 1 |
| 4.2 Platform recommends control and test groups | 1 | 0 |
| 4.3 Platform recommends test design (type, methodology) and predicts test success | 1 | 0 |
| 4.4 AI-generated plain-language readouts / executive summaries | 1 | 1 |
| 4.5 Conversational AI for discussing experiments | 1 | 1 |
| Category total | 5 / 5 | 3 / 5 |
This is Haus's other standout area, scoring higher than Sellforte. Haus achieves a perfect 5 out of 5: it recommends which channels to test, helps design control and test groups, recommends the test type and methodology and predicts test success, generates AI plain-language readouts and executive summaries, and offers a conversational AI interface for asking natural-language questions about experiments.
Sellforte scores 3 out of 5 here. It recommends which channels to test, provides AI-generated summaries, and offers conversational AI for discussing experiments. Where it falls short is in automated recommendations for control and test group design, and in predicting the probability of detecting a meaningful effect before a test runs. Sellforte has not prioritized these features partly because enterprise clients typically rely on open-source design packages or dedicated data science support for this step.
For teams that want the platform to guide them through test design end-to-end, particularly smaller teams without in-house statisticians, Haus's coverage in this category is a genuine advantage.
5. Unified Experiment Library (Haus: 1.5/3, Sellforte: 3/3)
| Criterion | Haus | Sellforte |
|---|---|---|
| 5.1 Central library covers all experiments regardless of type | 0.5 | 1 |
| 5.2 Filterable by country, channel, brand, campaign, team, date | 1 | 1 |
| 5.3 Role-based access and governance for the experiment library | 0 | 1 |
| Category total | 1.5 / 3 | 3 / 3 |
Sellforte offers a complete unified experiment library: all test types (geo, A/B, conversion lift) in a single searchable and filterable repository, with role-based access controls and governance. Haus scores 1.5 out of 3. Its library covers geo tests but does not include conversion lift tests, reflecting the broader gap in that category. It also does not offer role-based access controls for the experiment library, which is a requirement that frequently appears in enterprise procurement processes.
For large organizations running hundreds of tests per year across teams and regions, the difference between a partial library and a complete one compounds over time. Gaps in the library mean duplicate tests get run, learnings stay siloed, and governance becomes difficult to enforce.
6. MMM Integration (Haus: 1.5/3, Sellforte: 3/3)
| Criterion | Haus | Sellforte |
|---|---|---|
| 6.1 Bayesian MMM that can be calibrated by the user | 1 | 1 |
| 6.2 UI to connect experiment results to MMM | 0.5 | 1 |
| 6.3 Experiment-based priors comparable to attribution-based priors | 0 | 1 |
| Category total | 1.5 / 3 | 3 / 3 |
Both platforms include a Bayesian MMM that can be calibrated by the user. Beyond that, Sellforte pulls ahead. It offers a UI-based workflow for connecting experiment results to the MMM as calibration inputs, and supports side-by-side comparison of experiment-based priors against attribution-based priors. Haus scores 0.5 on the UI-based calibration criterion and 0 on prior comparison.
This reflects a deeper architectural difference. Sellforte is built as an integrated platform where experiments feed directly into the MMM through a product interface. Haus is primarily an experimentation platform that has added MMM. The integration between the two in Haus is lighter, and users looking for a seamless workflow from experiment result to model calibration will find Sellforte more mature here.
7. Enterprise-Grade Platform (Haus: 2/5, Sellforte: 5/5)
| Criterion | Haus | Sellforte |
|---|---|---|
| 7.1 At least 10 public reference customers from $1B+ revenue brands | 1 | 1 |
| 7.2 SOC 2, ISO 27001, or audited IT security by a third-party auditor | 1 | 1 |
| 7.3 Data residency: US and EU options | 0 | 1 |
| 7.4 Multi-cloud option between AWS, GCP, and Azure | 0 | 1 |
| 7.5 Single sign-on (SSO) for enterprises | 0 | 1 |
| Category total | 2 / 5 | 5 / 5 |
Sellforte scores a perfect 5 out of 5 across all enterprise criteria: it has at least 10 publicly named reference customers from brands with more than $1B in revenue, holds SOC 2 and ISO 27001 certification, offers data residency options in both the US and EU, supports multi-cloud deployment across AWS, GCP, and Azure, and supports single sign-on (SSO) for enterprise authentication.
Haus scores 2 out of 5. It has credible enterprise reference customers and holds security certification. However, it does not offer US/EU data residency options, multi-cloud deployment, or SSO support. These are not niche requirements: they appear regularly in enterprise RFPs, and their absence can create procurement blockers for multi-region or heavily regulated organizations.
Where Haus Wins
Haus is a genuinely strong product in its area of focus, geo testing. On geo test analysis, it has a high score (5/6), including the ability to launch and manage tests on ad platforms via API. On experiment recommendations and insights, it achieves a perfect 5/5. Its AI-generated readouts and conversational AI interface are well-regarded by users.
For a team that runs geo tests exclusively, wants the platform to guide test design end-to-end, and does not have complex enterprise IT requirements, Haus delivers a focused and polished experience.
Where Sellforte Wins
Sellforte's advantage is breadth and depth of integration. Sellforte has complete coverage of all three incrementality test types across geo tests, A/B tests and conversion lift tests. Its unified experiment library consolidates all tests into a single repository for easy access and analysis. It's MMM is deeply integrated with incrementality tests, with UI-based calibration and prior comparison. Sellforte is enterprise-grade covering all evaluated enterprise requirements.
For organizations that need all of these capabilities in a single platform, Sellforte is clearly the stronger choice.
Which Should You Choose?
Choose Haus if: your incrementality program is built entirely around geo tests, you want the platform to guide test design and automate recommendations end-to-end, and you do not run owned media A/B tests or conversion lift tests.
Choose Sellforte if: you run more than one type of incrementality test and want all results in a single platform, you need conversion lift test ingestion from Meta or Google, you want experiments to feed directly into an integrated MMM, or your organization requires EU data residency, multi-cloud deployment, or SSO. Sellforte is also the stronger fit for retail and ecommerce organizations with large enterprise IT requirements.
Frequently Asked Questions
What is Haus used for?
Haus is an incrementality testing platform focused on geo-based experiments. It helps marketing teams design, run, and analyze geo lift tests to measure the true causal impact of advertising spend. It also includes experiment design recommendations and AI-powered readouts. Haus has more recently added Marketing Mix Modeling to its offering.
Does Haus support A/B test analysis?
No. Based on our evaluation of publicly available documentation, Haus does not offer A/B test analysis for owned media. Platforms that do offer this capability include Sellforte and Measured.
Does Haus integrate with Meta or Google conversion lift tests?
No. Haus does not ingest, analyze, or display conversion lift test results from ad platforms such as Meta, Google, or TikTok. Sellforte is the only platform in our comparison that fully supports conversion lift test analysis.
What are the best Haus alternatives?
The closest alternatives to Haus for geo incrementality testing are Sellforte and Measured. Sellforte covers a broader set of test types and enterprise requirements; Measured also covers geo tests and A/B tests but not conversion lift. For teams committed to open-source approaches, Google's Meridian GeoX is a no-cost option but requires significant in-house engineering to operationalize.
Is Haus good for enterprise?
Haus has credible enterprise reference customers and holds security certification. However, it does not currently offer US/EU data residency options, multi-cloud deployment across AWS, GCP, and Azure, or SSO. These requirements are common in enterprise procurement. Organizations with strict IT or data governance requirements should verify whether these gaps are a blocker before committing to Haus.
How does Sellforte compare to Haus on geo testing specifically?
Haus scores 5 out of 6 on geo test analysis; Sellforte scores 4 out of 6. Both platforms use the synthetic control method, produce iROAS with confidence intervals, and offer self-serve analysis. Haus's advantage is its ability to execute geo tests directly on ad platforms via API. Sellforte does not offer this: geo tests must be configured on the ad platform side, with Sellforte handling the analysis.
Further Reading
How to Choose an Incrementality Testing Tool: 31 Evaluation Criteria
Best Incrementality Testing Tools: In-depth Vendor Comparison
Commentary
Snapshot in time. Vendor capabilities evolve quickly. This comparison reflects publicly available information at the time of publication.
Corrections welcome. We will revise this comparison as new information becomes available. If a vendor believes a score is inaccurate, we welcome corrections with supporting documentation. Please email sales@sellforte.com.
Recommendation for buyers. Use this comparison as a structured starting point for your own evaluation, not as a final answer. We recommend conducting evaluation calls or demos with the vendors to verify fit against your organization's specific requirements.
Authors
Lauri Potka is the Chief Operating Officer at Sellforte, with over 15 years of experience in Marketing Mix Modeling, marketing measurement, and media spend optimization. Before joining Sellforte, he worked as a management consultant at the Boston Consulting Group, advising some of the world’s largest advertisers on data-driven marketing optimization. Follow Lauri in LinkedIn, where he is one of the leading voices in MMM and marketing measurement.
Kacper Solarski is a Lead Data Scientist at Sellforte, focused on developing Sellforte's Experiments product. Kacper is one of the most senior data scientists and developers at Sellforte, where he has implemented Marketing Mix Models and incrementality testing solutions to Sellforte customers, while at the same time developing Sellforte's platform. Follow Kacper in LinkedIn.
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Juha Nuutinen is the Chief Executive Officer and co-founder at Sellforte, with over 15 years of experience in optimizing marketing spend and promotional activity for the largest advertisers in the world. Before co-founding Sellforte, he worked as a management consultant at the Boston Consulting Group, specializing in promotion optimization. Follow Juha in LinkedIn, where he is actively sharing his views on marketing measurement.
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