What they remember. Or what actually caused the sale.
Choose Fairing when your channel mix has dark-social, podcast, influencer, or offline components that pixels and last-click can't see, and you want the customer's own answer about discovery. Stack Causality Engine alongside when the question is quantitative: what did each channel actually cause, next to what last-click gave it.
€99 once, excl. VAT. Keep Fairing; use us as the causal second opinion.
Same question, different answer. Often the opposite answer.
- Fairing answers
- What does the customer remember?Post-purchase survey on the thank-you page
- Causality Engine answers
- What actually caused the sale?Causal inference, next to last-click
| Compared on | Causality Engine | Fairing |
|---|---|---|
| Method | Quantitative causal inference on a GA4 export | Self-reported post-purchase survey |
| Surfaces dark / offline channels? | No: a GA4 export has no offline data; Direct is split back to tracked channels | Yes, directly (survey response) |
| Install | None | Survey widget on thank-you page |
| Price | €99 per read · €299/mo ProExcl. VAT | Plans by order volume; quote on fairing.co |
Competitor pricing is each vendor's publicly listed pricing as read on the date shown, and it changes without notice: verify on the vendor's own site before relying on it. Vendors without a public price are marked as such. Comparisons set Causality Engine's one-time €99 analysis against subscription models.
The short version. What each one is for.
Fairing (previously Enquire Labs) runs zero-party post-purchase surveys on the Shopify thank-you page. 'How did you hear about us?' lands a self-reported answer that pixels and platforms can't see: dark social, podcasts, word of mouth, an influencer five weeks ago. For brands acquiring through channels their pixel doesn't track, that signal is uniquely valuable.
What it isn't: a statistical measurement of incremental impact. Reviewers consistently flag recency bias and recall error, and Fairing's own guidance frames it as a complement, not a replacement. Pricing is by order volume; the published plan prices render only in the browser, so none are quoted here.
Which one is the right call for your situation.
Choose Fairing when
your channel mix has dark-social, podcast, influencer, or offline components that pixels and last-click can't see, and you want the customer's own answer about discovery. That qualitative signal is uniquely Fairing's lane.
Stack Causality Engine alongside when
the question is quantitative: what did each channel actually cause, next to what last-click gave it. Self-reported survey answers and causal inference are different evidence; many brands run both and triangulate.
Take it to your CFO.
Not the same question. Surveys recover signal pixels can't see; causal inference quantifies what would have happened anyway. Run both; the budget decision sits on the causal side.
The questions buyers ask about us vs Fairing.
Is Causality Engine a Fairing alternative?
Not directly. Fairing captures customer self-reports; we quantify causal incrementality from your data. Brands often run both.Do you measure dark social or offline?
Indirectly. The causal model surfaces unexplained spend or residual variance the platforms can't account for. For named-channel discovery, Fairing's survey is the direct tool.
Your platforms guess.
We run the math.
Upload a GA4 export and see what each channel caused, next to last-click, in 1–2 minutes. The read is yours to keep.
Free, in your browser: your file is not uploaded. The full read is €99, refundable within 30 days. Prices exclude VAT.
Or book a 30-min call.