Payhip With Causality Engine: Check What Visitor Sources Miss
By Joris van Huët
Enterprise Interim CMO & Marketing Leader · 15+ years · 50+ orgs
Published
2026-11-11
The short answer: a Payhip store has two ledgers that rarely agree, and neither is wrong. Payhip, the checkout and storefront for downloads, courses, coaching and memberships (entry), lists where visitors came from by referrer, and counts any visit whose referrer is hidden as Direct (Visitor Sources). Once GA4 is connected, Payhip sends a Purchase key event by default whenever a checkout completes (Google Analytics article). That event is the raw material for a causal read. Causality Engine reads the GA4 export it lands in, and the first finding is free on the start page.
Disclosure: I founded Causality Engine and own it, and this page recommends it. Every claim about it links to Causality Engine's own pages.
What to settle first:
- The free-download sum. For example, 2,400 completed checkouts in a quarter, of which 1,980 are a $0 lead magnet and 420 are paid. Payhip's conversion figures include free products (Conversion Rate), so a 2,400-checkout month may hold 420 / 2,400 = 17.5% paid orders. Know which number a report is showing.
- The ID field you already have. The measurement ID goes in Account, Settings, Advanced Settings, Google Analytics, and the Purchase key event needs no further setup (Google Analytics article).
- The cookie banner setting. In the store builder, Change Store Style, Cookie Banner decides whether analytics cookies wait for consent or are off altogether (Cookie Banner). It sets how many buyers GA4 can see.
Payhip and the read in one table
| Topic | Payhip | Causality Engine |
|---|---|---|
| What it is | A store for digital and physical products (entry) | A causal read of one GA4 export (entry) |
| Its own traffic report | Referrer-based sources such as Google, Bing, Facebook, Pinterest and Direct (Visitor Sources) | Each channel's caused share next to a last-click rebuild (how it works) |
| Rule that credits a sale to someone | Affiliates: a 30-day cookie, commission to the last touchpoint (Affiliates) | No rule; an estimate of what would not have sold without the channel |
| What reaches GA4 | A Purchase key event on every completed checkout, by default (Google Analytics article) | Reads whatever channels the export records |
| GA4 channel for the visit | Set by source and medium under Google's rules (default channel group) | Same file, no tag of its own |
| Connection | None; Payhip is not among the listed integrations (integrations) | None |
| Price of checking | Payhip's reports come with the store | First finding free; €99 for one full read, excluding VAT (pricing, checked on 11 November 2026) |
How Payhip counts traffic and sales
Payhip's analytics page holds three views, each documented in a short article:
- Sales and Views. Daily visitors, daily sales in dollars and sales by product, all in UTC; your own visits do not count while logged in (Sales and Views).
- Conversion Rate. Views, started checkouts (a click on Buy or Download) and completed checkouts, free products included (Conversion Rate).
- Visitor Sources. The referring site, with Direct for visitors who typed the address and for sites that hide their referral (Visitor Sources). Payhip itself recommends GA4 for anything deeper.
None of these hands a sale to a marketing channel by a window. The one place Payhip does credit a sale is the affiliate tool: each affiliate gets links carrying a unique key, the cookie lasts 30 days, and commission goes to the last touchpoint the buyer converted from (Affiliates). That is a sound rule for paying partners. It is not a measure of what the partner added, because a buyer who would have bought anyway inside those 30 days still earns the commission.
Getting Payhip's buyers into the right GA4 channel
None of the Payhip articles read for this page describes a setting that adds UTM tags to shared links, so the channel in GA4 depends on the link you post. Google files a visit by source and medium (default channel group): a medium of email lands in Email, a medium of affiliate in Affiliates, and a social site as source with a medium such as social in Organic Social. An untagged affiliate link arrives as a referral from the affiliate's own site, if the browser passes one.
Three leaks are specific to a digital product store:
- Links inside what you sell. A link in a PDF ebook to your next product carries no referrer. Google's (direct) / (none) page says traffic from offline documents such as PDFs is classified as direct. Tag every link in the file before you upload it.
- Consent. With "Disable analytics cookies" chosen under the banner, Payhip stops tracking analytics until the visitor consents, and a separate option turns tracking off even after consent (Cookie Banner). The article lists the banner as a place to check when GA4 shows no data at all.
- The payment detour. If buyers leave for a payment page on another domain and come back, Google's unwanted referrals page names exactly that case. Check whether the processor's domain appears as a source in GA4, and exclude it if it does.
One question Payhip's articles leave open: whether a $0 download also sends the Purchase event. The conversion article counts an email entered for a free product as a completed checkout; the Google Analytics article does not say. Download your own free product and watch Realtime in GA4 for a minute. If the event arrives, filter by value before you trust a purchase count.
A worked example: a launch quarter
For example, figures made up for this page, not a store's results: a template shop on Payhip books 420 paid orders in a quarter, $13,860 in sales at a $33 price. Its own reports and its partners say:
| Figure | Orders |
|---|---|
| Payhip affiliate orders (30-day cookie, last touch) | 96 |
| The founder's estimate from Instagram link-in-bio clicks | 140 |
| A newsletter sponsor's report of clicks that bought | 61 |
| Pinterest ads, platform-reported | 118 |
| GA4 Purchase key events, value above $0 | 371 |
| Payhip paid orders | 420 |
Claims add up to 96 + 140 + 61 + 118 = 415, which looks close to 420 until GA4 is opened: it files 109 of its 371 purchases under Direct, buyers no claimant saw. Count them too and 415 + 109 = 524 orders are spoken for, 104 more than the store sold. GA4 saw 371 / 420 = 88.3% of paid orders; the 49 others belonged to buyers who refused cookies or blocked the tag.
A causal read starts with that Direct row. Per the how-it-works page, it splits Direct back to the channels that sent those buyers, sets every channel's caused share beside a last-click rebuild of the same export, scores data health from 0 to 100, and suggests raise, cut or hold with a test in one region first. If it gives Affiliates less than 96 orders' worth, the commission rule is not wrong. It is answering a different question.
The free check: switch one channel off, watch the daily graph
No tool needed. Payhip's Sales and Views page plots sales per day (Sales and Views). Choose the channel you doubt most, stop it for 14 days, and change nothing else.
For example, a store averaging 4.6 paid orders a day over the prior 28 days that averages 4.1 during the pause has lost 4.6 - 4.1 = 0.5 a day, or 7 orders over 14 days, against a claim, if the channel were Pinterest, of 118 / 90 = 1.31 a day. Seasonality can blur a two-week test, so run it in an ordinary month. The by-hand answer is enough to act on.
What the read will not do here
The read needs GA4 history: 12 months or more, per the how-it-works page, and a store with a few dozen paid orders a month risks landing under the floor, where a channel under 1% of credit on both methods is called too small to act on. It works under GA4's consent and browser limits, so the 49 missing orders stay missing. It reads channels; which affiliate or which product sold remains a Payhip question.
Look at who the affiliate default serves. A 30-day last-touch cookie keeps partners promoting, and on the $0 plan Payhip keeps 5% of every sale, the ones that cookie catches included (pricing, checked on 11 November 2026); the seller then pays the commission on top, even for buyers who were coming anyway. Keep the affiliate report as the payout record and read it as nothing more.
After the pause test
Once the free test has answered one channel, take the rest together. Export GA4's Attribution paths report and drop it on the start page, where the first finding runs in your browser at no cost. Causality Engine, which I founded, charges €99 once for the full read of that file, excluding VAT and refundable within 30 days (pricing, checked on 11 November 2026).
See also
- Payhip: plans, fees and who it suits
- How to use Payhip: turning a free download into paid sales
- Payhip on the marketplace: Payhip's affiliate program terms
- Causality Engine: what the read costs and when it declines
- How to use Causality Engine: export, read, then a regional test
- Causality Engine on the marketplace: the program's terms, as the owner's own
- Sellfy vs Payhip: two creator stores, fee against cap
- How to find what Direct traffic is hiding: where untagged buyers end up
FAQ
Does Payhip send data to Causality Engine?
No, and nothing needs to be connected. Payhip sends its Purchase key event to your own GA4 property; Causality Engine reads the export you download from GA4, as its integrations page describes.
Why does Payhip show more Direct visits than GA4?
Payhip's Visitor Sources names the referring site and counts visits from sites that hide their referral as Direct (Visitor Sources). GA4 reads the UTM tags you add, so a tagged visit from such a site gets its source back there.
Do Payhip's affiliate numbers belong in the read?
They sit beside it. Affiliate visits reach GA4 as a channel only through their links, ideally tagged with a medium of affiliate, while the affiliate report pays by its own 30-day rule (Affiliates).
ABOUT THE AUTHOR
I am Joris van Huët, an enterprise interim CMO. 15+ years, 50+ organizations, including ING, P&G, Nestlé, BNP Paribas, WeTransfer and Vinted. I take on innovation projects (venture building, design sprints), agentic marketing (setting up and running AI agents) and hands-on multi-channel work. See the track record.
I wrote and published this with AI assistance, and I answer for it. Claims about my own experience are limited to the track record above, and a statistic links to its source or is labelled as an example. I sell interim and fractional CMO work, which is why this site exists. How this site is written.
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