Run the experiment, or read the history.
Measured is a serious incrementality platform. It runs geo-based holdout experiments: hold spend back in matched regions, keep it running elsewhere, and measure the difference in outcomes. That is a real experiment, and a well-designed geo test is the strongest evidence of causal lift a marketer can buy. We are not going to pretend otherwise.
The trade is cost, latency, and what you have to give up to get the answer. Measured is enterprise-priced and quoted via sales, each test takes roughly four to eight weeks, and the method requires deliberately withholding spend in some regions. You also learn about the window you tested, not the year you already spent.
Causality Engine answers the same question from the opposite direction: causal inference over the GA4 history you already have. No experiment to design, no spend to pause, no region to sacrifice. A per-channel causal read with confidence intervals in 5 to 10 minutes, for €99.
// Measured answers hold spend back in matched geos, wait 4-8 weeks → measured lift for the tested window // Causality Engine answers read the GA4 history you already have → incremental ROAS + confidence interval, 5-10 min
Same question, different answer. Often the opposite answer.
| Causality Engine | Measured | |
|---|---|---|
| Question answered | What did each channel cause? | What did this channel cause, in this test? |
| Method | Causal inference on existing GA4 history | Geo holdout experiment (prospective) |
| Evidence strength | Observational, confidence-interval bounded | Experimental, stronger when well powered |
| Spend paused to learn | None | Yes, in the holdout regions |
| Time to first number | 5–10 minutes | 4–8 weeks per test |
| Price | €99 per read · €299/mo Pro | Enterprise contract, quoted via sales |
| Covers past spend | Yes, any historical period | No, only the window you test |
Which one is the right call for your situation.
Choose Measured when
you have the budget, the spend scale to power a geo test, and a measurement team that will run a formal programme. If a nine-figure media plan turns on the answer, buy the experiment. Observational inference is not a substitute for a properly powered randomised test, and anyone who tells you otherwise is selling something.
Choose Causality Engine when
you want an answer this week rather than next quarter, you cannot justify an enterprise contract to find out, or you need to know about the spend you have already made. It also works as the cheap first pass: run a €99 read to find which channels look non-incremental, then spend the geo-test budget confirming only those. That sequencing costs less and tests the right things.
An enterprise contract quoted via sales, with a four-to-eight-week wait for the first answer, versus €99 on a card with the answer in ten minutes. If the €99 read and the geo test disagree, that disagreement is itself worth knowing, and you found it for €99.
The questions buyers ask about us vs Measured.
- Is a geo holdout test more accurate than causal inference on GA4 data?
- A well-designed, adequately powered geo test is the stronger evidence, because randomisation removes confounders rather than adjusting for them. Causal inference on observational history is bounded by the assumptions in the model, which is why our output carries confidence intervals. The practical question is not which is theoretically better but which you can actually run: a test you cannot afford or power teaches you nothing.
- Can I use Causality Engine and Measured together?
- That is the sequencing we would recommend if you have both budgets. Use a €99 causal read across all channels to find the candidates that look non-incremental, then spend the geo-testing budget confirming those specific channels. Testing everything is expensive; testing the suspects is not.
- Do I have to pause ad spend to use Causality Engine?
- No. That is the main operational difference. Geo holdouts require withholding spend in some regions to create a control group. We infer the counterfactual from your existing GA4 history, so nothing has to be turned off and no revenue is deliberately foregone to produce the measurement.
- How much does Measured cost compared to Causality Engine?
- Measured is enterprise-priced and quoted via sales; it does not publish a price list. Causality Engine is €99 per causal read with no subscription, or €299/mo for Pro. The gap in commitment is why the two tend to serve different-sized brands.
Every causal vs MTA tool in one row each.
They track clicks. We measure cause. Four of these five tools are pixel or multi-touch-attribution dashboards on an annual contract; they reassign credit for conversions that already happened, and they need a script installed and maintained. Causality Engine measures incrementality, the sales a channel actually caused, from your existing GA4 and Shopify export, no pixel, with confidence intervals, for €99 a read. Different question, different bill, different install.
| Tool | Core method | Causal? | Pixel / SDK? | Time to value | Pricing model | Yr-1 fully loaded | Contract |
|---|---|---|---|---|---|---|---|
| Causality Engine | Causal inference (Bayesian) on GA4 + Shopify | Yes, native | None | 5–10 min | €99 per read · €299/mo Pro | €99 one-time · €3,588/yr Pro | Credit card, cancel anytime |
| Triple Whale | Pixel + MTA (Clicks & Deterministic Views) | No | Yes (Triple Pixel) | Days (after pixel install and data) | Subscription, GMV tiers | GMV-priced, quote by store size | Not published |
| Northbeam | ML MTA + MMM + incrementality (2026 add-on) | Partial (newer layer) | Yes (script + UTMs) | Weeks (onboarding) | Starter $1,500/mo; Pro/Ent custom quote | $1,500/mo Starter; $3,500/mo Professional; higher tiers quoted | Not published |
| Rockerbox | MTA + MMM + incrementality (enterprise) | Yes (native) | Yes (integration) | Weeks (config + experiments) | Quote only | Quote only, plus onboarding | Not published |
| Hyros | Server-side click tracking + MTA | No | Yes (watcher scripts, heavy) | 2–12 weeks (setup) | Subscription, demo-gated | Quote only, demo-gated | Not published |
| Wicked Reports | First-party click MTA (LTV focus) | No | Yes (pixel + CRM/UTM) | Days to weeks | Revenue-banded: $499 / $699 / $999 / $4,999+ | $499–$999/mo by revenue band | Monthly billing; term not published |
| Cometly | MTA pixel + server-side + CAPI | No | Yes (Comet Pixel + CAPI) | Days (post pixel install) | Usage-based on pageviews; no free trial | Quote only, usage-based | Monthly or annual (annual −20%) |
| Billy Grace | Deep-learning MTA + Unified Marketing Measurement | Modeled, no CIs | Yes (own first-party pixel) | Demo-gated onboarding | Subscription, by ad spend | €499–3,250/mo + €99 integrations | Demo-gated |
| EYKData | Server-side MTA on owned BigQuery (correlation-based) | Quote-only top tier | Yes (GTM + BigQuery + Stape) | Weeks (stack stand-up) | Subscription, by sales | €399–€529+/mo (Advanced = quote) | Subscription |
| Funnel.io | Data integration / ETL platform | Add-on at quote-only top tier | Connectors / warehouse | Weeks (pipeline build) | Base plan + paid Measure add-on | $300–600 base + $2,250/mo Measure (≥$500k spend) | Billed annually |
| Supermetrics | Marketing data pipeline / connectors | No (claims unverified) | Connectors | Hours per source | Per-source subscription | From $44/mo billed annually; Growth from $177/mo | Annual |
| Elevar | Shopify server-side conversion tracking + data layer | No (not attribution) | Yes (data layer install) | 1–2 weeks (setup) | Subscription, by orders | $225–3,000+/mo + $1k–4.5k install | Monthly |
| Fairing | Post-purchase survey (zero-party) | No (self-reported) | Survey widget | Minutes (install) | Subscription, by orders | Plans by order volume; quote on fairing.co | Monthly |
| Google Ads | Self-attributing network, data-driven attribution | No (window-bound, self-mediated) | Native | Built in | Native to ad platform | Free (with the spend) | Native, no contract |
| Meta Ads Manager | Self-attributing, 7-day click + 1-day view default | No (view-through inflates) | Native + Meta Pixel/CAPI | Built in | Native to ad platform | Free (with the spend) | Native, no contract |
| TikTok Ads Manager | Self-attributing, 7-day click + 1-day view | No (passive-feed view-through) | Native + TikTok Pixel | Built in | Native to ad platform | Free (with the spend) | Native, no contract |
| Shopify Marketing Reports | Last-click (last non-direct), rules-based | No (erases assists) | Native | Built in | Included with Shopify | Free (with the plan) | Native, no contract |
| GA4 | Data-driven attribution, click/visit-based | No (ignores impressions, no control group) | Native GA4 tag | Built in | Free | Free | Native, no contract |
Competitor figures are our estimates of a fully loaded monthly cost in EUR, built from each vendor's published pricing (USD where quoted) on the date shown under this table. A tilde or "est." marks an estimate, "reported" marks a figure from a third-party report, and quote-only vendors are marked as such. Prices change often: verify with the vendor before relying on them. Not vendor quotes to us.
Run the side-by-side. Watch the model work on a sample store first, no signup. Then upload your GA4 export and get incremental ROAS with confidence intervals in 5–10 minutes, €99. Refundable if the first read doesn't pay for itself in one reallocation decision. Keep your current tool; use us as the independent causal second opinion.
We're the only one in this table without an ad budget, or a dashboard subscription, to protect.