# Triple Whale vs Haus: Best marketing measurement software in 2026

> Triple Whale ranks #1 within the Marketing Measurement category, according to Ramp


**Author:** Kaleena Stroud  
**Published:** 2026-10-16  
**Category:** Attribution  
**Source:** https://www.triplewhale.com/blog/triple-whale-vs-haus

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*What is working today? Did that spend cause additional sales? Where should the next dollar go? *

Triple Whale and Haus both address these questions through marketing measurement, but they start from different centers of gravity.

Haus is "the AI-powered incrementality platform leading enterprises use to optimize tens of billions in annual marketing spend."

[Triple Whale](https://www.triplewhale.com/) is "the AI operating system built for modern commerce. It sees your whole business in real time, tells you what's actually driving growth, and executes when you say go."

Two taglines. Two very different ideas of what a platform should do for you.

Triple Whale connects marketing measurement to daily commerce decisions and supported execution. Haus specializes in incrementality testing and experiment-led media decisions.

Choosing between the two platforms depends on how your team wants measurement to support optimization, budget planning, and investment decisions. 

Below, we break down the key differences between Triple Whale and Haus so you can find what’s right for you.

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### Triple Whale vs Haus at a glance

|  | Triple Whale | Haus |
| --- | --- | --- |
| Founded | 2021 | 2021 |
| Price | Triple Whale starts at $219/mo (Foundation); pricing varies by annual GMV. Incrementality testing is included in Triple Whale’s Enterprise plan. | Not listed publicly |
| G2 rating | 4.5/5 with ~500 reviews | N/A |
| Built for | Commerce-wide data, measurement, decisions and supported work in one operating platform. | Incrementality-led marketing measurement and evidence-backed media decisions. |
| Measurement | Click-based and deterministic view-through attribution views, plus MMM and incrementality through Compass. | Causal measurement and experimentation, with first-click, last-click and linear comparisons in the supplied product assessment. |
| Data freshness | Fresh click-based activity for intraday checks; view-based signals follow a separate, daily cadence. | The supplied assessment describes daily Causal Attribution refreshes. Experiment readouts answer a different question from live click checks. |
| Ad changes | Moby can prepare or perform supported changes under saved rules, account settings and required approvals. | Architect can recommend and execute approved media changes. |
| Beyond measurement | Cost and profit views, first-purchase cohorts, scheduled reporting, creative, audience syncing and Shopify page workflows, subject to access. | The supplied assessment centers on measurement and media decisions; it does not establish a complete inventory of Haus's other capabilities. |

## Triple Whale vs. Haus: Attribution models for daily and weekly performance decisions

Attribution is most useful when it helps teams understand what’s happening while there is still time to act on it.

Triple Whale gives teams several [attribution models](https://www.triplewhale.com/blog/attribution-modeling) to show where channels, campaigns, ads, and creative have the most impact across the funnel, with the flexibility to adjust models and windows for sales periods.

Haus takes a different approach. Its experiment-calibrated Causal Attribution model is the primary daily performance view.

This matters because attribution has a different job from MMM or incrementality. Attribution can help teams make intra-day and intra-week performance decisions. MMM helps determine where to allocate budget over a longer-term planning cycle.

Incrementality helps validate whether marketing caused incremental outcomes, so budgets can be directed toward the channels and tactics most likely to have the greatest impact.

|  | Triple Whale | Haus |
| --- | --- | --- |
| Click-based rules | First Click, Last Click, Linear All, Linear Paid | One calibrated model, with first-click, last-click, and linear comparisons |
| Platform-level view | Triple Attribution gives last-click credit within each platform | Centers on the calibrated cross-channel model |
| Deterministic view-through attribution | Clicks & Deterministic Views: data-driven, with time decay and intent | Adjusts platform reporting based on experiment results |
| Post-purchase survey input | Post-purchase responses adjust Total Impact weights | Calibration centers on experiments |
| Refresh | Real-time clicks, daily views | Daily |
| Interpretation | Moby uses dynamic prompts to explain what each model shows, using Compass context | One debiased answer to work from |
| Best for | Teams that want full-funnel insight and the flexibility to adjust models and windows for sales periods | Teams that want a single calibrated number |

### Triple Whale

Triple Whale gives teams several attribution views rather than asking one methodology to carry the weight of every question.

Whether evaluating customer acquisition, cross-channel performance, or budget allocation, each model shows a different part of the funnel, grounded in the same unified data for a defensible view of performance.

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Triple Whale’s Moby AI lives directly on Attribution, helping teams move from seeing a performance shift to understanding whether an adjustment is likely to support stronger performance, without leaving the workflow.

- **Inputs:** Triple Whale uses Triple Pixel to connect eligible first-party interactions on your site with orders. Triple Whale uses post-purchase survey responses from its own survey tool, Fairing, or Kno to adjust channel weights in Total Impact. Total Impact needs at least seven days of survey responses, and without them it behaves much like Linear All.

- **Credit rules:** First Click shows what started the journey, and Last Click shows what closed it. Linear All splits credit in equal shares across every touch, while Linear Paid limits that credit to paid interactions, which helps when you're evaluating ad spend.

- **Platform and impression views**: Triple Attribution gives last-click credit within each platform, so platform totals can add up to more than your actual sales. Avoid summing them into a single figure. TA + Platform Views layers in platform-reported views, and Clicks & Deterministic Views is Triple Whale's data-driven model. It combines clicks and verified ad views, with time decay and intent built in, to distribute credit across the customer journey.

- **Freshness: **Click-based data updates in real time, so you can check today's activity before making a same-day change, or zoom out to the week for context before acting. View-based data updates daily.

- **Interpretation: **When models show different results, Moby connects the attribution read to your business question using Compass context from MMM and incrementality. It explains what each view shows about the customer journey so you can decide what to do next.

- **Use it for: **Checking recent click performance and week-to-date trends, comparing campaigns side by side, and digging into eligible journey and order details.

### Haus

- **Approach:** Haus builds its attribution around a single model. Causal Attribution uses experiment data to debias attribution, so the daily read reflects what Haus's tests show.

- **How it works:** Causal Attribution adjusts your platform reporting based on experiment results. It's also included with Haus experiments by default, so attribution and testing come as a package.

- **Comparison models:** First-click, last-click, and linear views are available as reference points. Haus positions them as secondary to the calibrated model.

- **Freshness:** Data is refreshed daily, which works for day-to-day budget reads. Haus documents a daily Causal Attribution refresh.

- **Trade-offs:** You get fewer credit rules to choose from, and calibration centers on experiments.

- **Use it for:** A single daily number grounded in your experiment results.

## Triple Whale vs Haus: Marketing mix modeling and incrementality

Triple Whale brings [marketing mix modeling](https://www.triplewhale.com/marketing-mix-modeling) and incrementality testing into the same decision workflow as your attribution and commerce data. You get a new model every week, tests you can run in the platform, and Moby to explain where the signals agree or conflict, so your team can act without reconciling separate tools.

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Haus specializes in experimentation, and its marketing mix model is built on test results. That focus suits teams whose measurement program revolves around running experiments. For teams that want measurement connected to everyday decisions about spend, profit, and growth, Triple Whale covers more of the work in one place.

|  | Marketing mix modeling (MMM) | Incrementality testing | Triple Whale | Haus |
| --- | --- | --- | --- | --- |
| Question it answers | How much is each channel contributing? | Did this spend cause additional sales? | Both, alongside attribution | Both, led by experiments |
| How it works | Models spend and revenue over time | Compares test and control groups | Weekly MMM plus in-platform tests | Geo experiments feeding a Causal MMM |
| How the methods connect | Estimates can be checked against tests | Results can confirm or challenge MMM | Flags where MMM and tests agree or conflict | Tests serve as the model's ground truth |
| Cadence | Usually refreshed weekly | Weeks per test | New MMM every Sunday | Updates as new tests come in |
| Data needs | A history of spend and sales | Enough volume to detect lift | MMM needs a minimum history | ColdStart covers launches without history |
| Best for | Cross-channel budget planning | Validating a channel before scaling | Planning connected to attribution and commerce data | Experiment-led teams and budget sign-off |

### Triple Whale

- **Approach:** Triple Whale runs marketing mix modeling and [incrementality testing](https://www.triplewhale.com/blog/incrementality-testing) through Compass, alongside the attribution you already use. The idea is to use the right evidence for the decision in front of you and see how each signal informs the others, without forcing one method to answer every question.

- **Marketing mix modeling:** In Compass, MMM updates every Sunday using the latest marketing and business data available in Triple Whale. Add additional context into the model, including offline media, from paid social and CTV to podcasts, out-of-home, influencers, and email.

- **Incrementality tests:** You can run geo holdout tests in the platform using two [methods](https://www.triplewhale.com/blog/incrementality-testing-methods). GeoLift compares locations that receive an advertising change against similar locations that don't. Meta Conversion Lift gives you a platform-level read for Meta campaigns.

- **Evidence check:** When a completed test overlaps with a channel in your MMM, Compass shows the two numbers side by side: the model's estimated efficiency and the test's measured incremental ROAS. A Verified badge means they agree, and a Contradicted badge means they point in different directions. Use test results as priors, meaning evidence that informs MMM estimates.

- **Interpretation:** Moby tells you what's driving a change in performance, which channels have room to scale, or where stronger proof could change a decision. It reasons across attribution, MMM, incrementality, and your commerce data, so you skip the manual reconciliation.

- **Keep in mind:** Because the MMM is trained on your own business data, it needs a minimum amount of history before it's reliable. Test options center on GeoLift and Meta Conversion Lift.

- **Use it for:** Weekly budget planning, checking model estimates against real test results, and keeping measurement in the same place as your attribution and daily performance data.

### Haus

- **Approach:** Incrementality is where Haus started, and it's still the center of the platform. Haus has built its reputation on randomized geo holdout experiments and scientific rigor. Its founder and CEO spent seven years at Google as a data scientist and product manager, and the rest of its measurement stack builds on those experiment results.

- **Test types:** Beyond standard geo tests, Haus offers Fixed Geo Tests for offline campaigns like billboards, linear TV, store openings, and out-of-home activations. If your spend leans heavily offline, that range matters.

- **Causal MMM:** Haus's marketing mix model uses experiments as ground truth, and each new test feeds back into the model. For channels you haven't tested yet, it falls back on observational data and priors, which can include third-party experiment results.

- **New products and markets:** ColdStart uses comparable KPIs to test the incrementality of new products, markets, and channels that don't have historical data yet. That helps newer brands or launches that would otherwise wait months to build enough history.

- **Architect:** As of September 2026, Haus's agentic decision system is live and integrated into Causal MMM. It recommends budget moves, shows the evidence behind each one, and sizes recommendations by confidence. Approved changes can then be pushed to ad platforms.

- **Keep in mind:** Architect requires human approval before executing a media change, so routine adjustments can't run unattended in that workflow. And because Causal MMM leans on experiments, its strongest estimates come from the channels you've tested.

- **Use it for:** Proving whether a channel drives incremental sales, measuring offline media, and grounding budget planning in experiment results, especially if your leadership team wants causal evidence before signing off on spend.

## Triple Whale vs Haus: Moby AI and Architect

An AI agent for marketing goes beyond answering questions about your data. It can investigate what changed, recommend what to do next, and carry out approved work in connected tools.

Triple Whale's Moby AI connects analysis to supported work across commerce workflows. Haus's Architect focuses on media investment decisions grounded in its causal measurement stack.

### Moby vs. Architect at a glance

|  | What to look for | Triple Whale (Moby) | Haus (Architect) |
| --- | --- | --- | --- |
| Scope | The range of work the AI covers | Analysis, recurring operations, and action across the business | Media investment decisions |
| Evidence | What the AI reasons over | Commerce data, attribution, Compass measurement, and your business context | Causal MMM and experiment results |
| Execution | How changes get made | Supported ad changes, set to review-required or automatic | Approved media changes pushed to ad platforms |
| Human control | Where approval sits | Your team chooses, within required approval gates | Human approval before every change |
| Outputs | What you get at the end | Reports, ad changes, creative, audiences, and Shopify pages | Budget recommendations with evidence and confidence sizing |
| Best for | The team it fits | Teams that want insights carried into daily work | Teams making causal-first budget decisions |

### Triple Whale

- **Approach:** [Moby is Triple Whale's AI teammate](https://www.triplewhale.com/moby-ai) for commerce. It's built on three layers: the Data Platform, which shows what's happening; the Measurement Layer, which helps evaluate what's contributing; and the Context Engine, which shapes the response to how your business works.

- **Context:** You can give Moby your metric definitions, goals, operating rules, and brand guidance. Saved context carries into future work, so your team spends less time re-explaining the business every time it starts a task.

- **Analysis:** Moby can diagnose performance changes, spot possible friction on landing and product pages, and assess how your creative is performing.

- **Automation:** [Moby Automations](https://www.triplewhale.com/moby-ai/automations) use saved performance rules and campaign exclusions to prepare supported budget or status changes as recurring work. Changes can wait for review or run automatically where account settings allow it. Moby can also build scheduled reports, such as performance summaries and budget-pacing reviews, and send them to Slack or email.

- **Action:** Moby carries insights into the next piece of work. It can make supported paid media changes, generate and refresh creative, sync customer segments to ad and lifecycle platforms, and build and publish Shopify promotional pages under your store's domain.

- **Keep in mind:** Available actions depend on supported tools, account access, and required approvals. Review generated creative before using it, and note that Creative Studio is focused on images.

- **Use it for:** Taking repeatable work off your team's plate and turning a decision into a finished deliverable, whether that's a report, a campaign change, a creative asset, or a landing page.

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### Haus

- **Approach:** Architect is Haus's causal media optimization system. It turns incrementality test data into budget decisions across paid media channels, so every recommendation traces back to experiment evidence.

- **Scope:** Architect recommends the next best action across channels, campaigns, and ads for both online and offline media. As of September 2026, it's integrated into Causal MMM, with capabilities that include predictive planning, promotional strategy, and seasonality optimization.

- **Evidence:** Each recommendation comes with the evidence behind it, and Architect sizes recommendations based on confidence. That transparency helps when finance needs to see why a budget should move.

- **Execution:** Once you approve a recommendation, Architect can push the change to your ad platforms. Every change requires human approval first, so routine adjustments can't run unattended.

- **Keep in mind:** Architect centers on media investment decisions. Work like creative production, audience building, or landing pages would sit in other tools. Access is available to existing Causal MMM customers.

- **Use it for:** Budget reallocation grounded in causal data, especially for teams that want every recommendation backed by experiment evidence before money moves.

## Triple Whale vs Haus: profitability and customer cohorts

Triple Whale connects measurement to product costs, operating costs, and customer purchase history. Haus's published product focus is causal marketing measurement and media planning.

### Triple Whale

Triple Whale supports COGS, shipping costs, payment fees, and custom expenses for profitability reporting. Keep the definition of each view clear: summary net profit and attributed ad-level profit do not necessarily include the same costs.

Triple Whale Customer Cohorts group customers by their first purchase and track observed value, repeat purchases, retention, and second-order behavior. Filters and exports support analysis of defined customer groups.

Triple Whale's Meta Profit Optimization sends an additional net_revenue field through Conversions API alongside standard order value. The documented calculation includes discounts, shipping revenue and costs, COGS, payment fees, and handling fees. Meta controls eligibility and activation.

Triple Whale's Google Ads profit workflow uses a conversion for purchases that exceed a revenue-minus-COGS margin threshold. Google Ads goal setup and Enhanced Conversions configuration are also required. This is a different calculation from Meta's net_revenue value.

Triple Whale lets authorized users view customer names in Live Orders when the account owner enables PII access. Customer-level access depends on permissions and the reporting model.

### Haus

Haus estimates marketing's incremental impact and uses that evidence for spend decisions. To evaluate profit, apply the relevant product and operating costs to the measured outcomes.

If your team needs cohort analysis, named-order investigation, or ongoing cost reporting, ask Haus to demonstrate those specific workflows. The reviewed public sources do not establish a complete inventory of Haus's capabilities.

## Platform approach: built for commerce vs. built for measurement

#### What's the difference between a commerce platform and a measurement platform?

A measurement platform focuses on one question: which marketing is driving results. A commerce platform answers that question too, but connects it to the rest of the business, including costs, profit, customer value, and the work that follows each decision. The right fit depends on whether you need a specialist tool for measurement or one system for running growth.

|  | What to look for | Triple Whale | Haus |
| --- | --- | --- | --- |
| Core focus | What the platform is built around | Running a commerce business, with measurement built in | Causal marketing measurement |
| Profitability | Whether you can see what you're making | Cost inputs feed profit reporting down to the ad level | Centers on incremental revenue and spend efficiency |
| Customer value | What happens after the first order | Cohorts track repeat purchases, retention, and LTV | Focused on measuring marketing's impact |
| Ad platform signals | What you send back to Meta and Google | Profit-based conversion values for supported workflows | Centers on measurement and budget decisions |
| Order investigation | How far you can dig into a sale | Named-customer lookup for authorized users | Causal Attribution data doesn't link customer names |
| Best for | The team it fits | Brands that want growth, profit, and execution in one place | Brands that need a dedicated causal measurement partner |

### Triple Whale

- **Approach:** Triple Whale is built around the full commerce operation. Measurement sits alongside your store data, costs, customers, and the tools your team uses to act, so an insight and the work it leads to live in the same place.

- **Profitability:** You can maintain COGS, shipping costs, payment fees, and custom expenses in Triple Whale. Those costs support Triple Whale’s profitability reporting. Summary net profit and attributed ad-level profit can use different cost definitions, so you can see what you're really making instead of stopping at revenue ROAS. Accurate cost settings are essential for this to work.

- **Customer value:** Customer Cohorts group shoppers by their first purchase and follow what they do next: lifetime value, repeat-purchase rate, retention, and second-order behavior. You can filter cohorts and export the results.

- **Profit signals for ad platforms:** Triple Whale can send profit information back to the platforms that optimize your ads. For Meta, you can pass a net revenue value through Conversions API. For Google Ads, you can set up a margin-threshold conversion based on revenue minus COGS. Either way, you're changing what the algorithm optimizes toward, beyond just how much you spend.

- **Order investigation:** When you need to look into a specific order, an account owner can let authorized users see customer names in Live Orders. Names stay hidden from anyone without that permission.

- **Keep in mind:** Capabilities vary by plan, connected data, and permissions. For profit signals, Meta controls activation, and goal setup happens in Google Ads.

- **Use it for:** Connecting marketing decisions to margin and customer value, and keeping reporting, measurement, and execution in one system.

### Haus

- **Approach:** Haus positions itself as a leader in enterprise marketing measurement and decisions. Everything in the platform ties back to causal evidence from experiments, which gives its recommendations a clear scientific footing.

- **Strengths:** Haus goes deep on one job: proving what marketing causes. That focus shows in its experiment design, its Causal MMM, and Architect's evidence-backed recommendations, all covered in earlier sections.

- **Keep in mind:** Haus centers on measurement and media decisions. Built-in cost tracking for ongoing profit reporting, first-purchase cohort analysis, and audience building would likely sit in other tools. Its Causal Attribution data also doesn't link customer names or contact details, so named-order lookups happen elsewhere.

- **Use it for:** A dedicated measurement layer, especially for enterprise teams that already have separate tools for profit reporting, retention analysis, and execution.

## Using Triple Whale and Haus together

Triple Whale handles daily and weekly attribution and commerce reporting; Haus validates defined marketing bets with geo-lift experiments. Teams can use both when a separate experimentation program fits their measurement needs.

Assign each decision a method and owner. Use Triple Whale to investigate eligible journeys and current performance. Use Haus experiments to evaluate causal lift within the tested campaigns, markets, and dates.

Before comparing results, align sales definitions, time periods, geography, campaign scope, attribution windows, and spend denominators. A channel-level test result should not be treated as proof about every ad.

Confirm how Haus results would enter your Triple Whale planning workflow. This article does not establish an automatic Haus-to-Compass integration. Triple Whale's own MMM and incrementality options may also reduce the need for separate tools.

## Triple Whale vs Haus: Key summary

Haus is a measurement specialist. Triple Whale is built for commerce, with measurement as one part of a larger system that also covers profit, customer value, and the work that follows each decision. If you want a focused causal measurement partner and already run the rest of your stack elsewhere, Haus fits that role. If you'd rather see growth, margin, and customer value in one place and act on them there, Triple Whale does more of the job.

- Choose Haus if experimentation and causal measurement are the center of your decision process, and your team has a separate operating stack for the rest of the work.

- Choose Triple Whale if you want measurement connected to current commerce performance, profit and customer value, recurring reporting, and supported execution workflows.

- Whichever you choose, remember that click, view, attribution, marketing mix modeling, and incrementality signals use different methods and refresh on different schedules. Your connected sources, plan, and permissions also shape what your team can use or automate.

## Triple Whale vs Haus: Frequently asked questions

Teams evaluating both platforms tend to ask a few of the same questions.

### Does Haus offer multi-touch attribution?

Haus offers experiment-calibrated Causal Attribution with first-click, last-click, and linear comparisons. Triple Whale offers pixel-based MTA with multiple explicit credit rules and survey-informed weighting in Total Impact.

### Is Triple Whale an incrementality platform?

Triple Whale includes supported GeoLift and Meta Conversion Lift workflows alongside attribution and MMM. Its current help documentation lists incrementality on Enterprise. Haus also offers incrementality experiments, with self-serve options in supported packages.

### Which is better for offline media?

Haus Fixed Geo Tests address region-specific campaigns such as billboards and store openings. Triple Whale MMM can include offline media through supported inputs and custom uploads. Compare the method needed for the campaign rather than assuming all offline measurement uses the same design.

### Can I use Triple Whale and Haus together?

Yes. Triple Whale can support daily and weekly attribution and commerce reporting while Haus experiments evaluate causal lift for selected decisions. Confirm data-transfer workflows and align definitions before combining their results.

### Does a Meta partnership prove independent measurement?

No. For Triple Whale and Haus evaluations, distinguish platform optimization integrations, controlled tests, and provider independence. An Apex-style passback integration alone does not establish independent causal lift.

### How should we sequence attribution, MMM, and tests?

Use Triple Whale attribution for daily and weekly investigation and available MMM for broader planning. Use Triple Whale or Haus experiments to validate high-stakes decisions or investigate disagreements. Match the experiment to the decision and review uncertainty before changing spend.

### Is a unified platform worth it?

Triple Whale can reduce the work of reconciling commerce reporting, attribution, and available Compass signals. Haus may fit teams that need a separate, experiment-led measurement program. Compare supported workflows, data quality, total cost, and the time your team spends moving results between tools.

## See the workflow in context

Bring one real marketing decision to a Triple Whale walkthrough. See the measurement read, the business context behind it, and the work that follows.

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