What complete data means
The technical difference between what GA4 measures (on one real store, 29% of visits went unrecorded) and what you need to defend a number to your CFO.
"Complete data" is one of those phrases that sounds obvious until you try to define it. This chapter draws the line — what we mean when we say Sealmetrics doesn't depend on consent, what GA4 means when it shows the dashboard you've been reading, and why the difference is a budget problem, not a vocabulary one.
Written for measurement leads, performance marketers, and anyone who has to defend a conversion number to finance.
Where the gap comes from
There is no universal figure for how much traffic GA4 misses. There is a mechanism: three stages that every analytics tool relying on client-side cookies is exposed to. GA4 doesn’t see part of your traffic because of consent rejection, ad blockers and browser restrictions, plus sampling on top. How much depends on the store and the channel.
Each stage applies to the visitors the previous one left — the cascade is multiplicative, not additive.
Visitors who say no. In our experience with clients, between 40% and 60% of traffic doesn't accept cookies, and of those who do, 40% don't accept on the first pageview — the page that carries the traffic source. Where a site lands depends on sector, brand strength, traffic mix and banner design.
Tags stripped silently. Some of those who accepted run uBlock, AdGuard, Brave Shields or Pi-hole. Analytics requests are stripped silently — the user sees your site, GA4 does not see the user. The share is higher on desktop and in technical audiences.
Sessions broken apart. Safari ITP, Firefox Total Cookie Protection and Brave's defaults expire or block the cookies GA4 needs to keep sessions intact. Returning visitors look new; multi-session journeys fall apart.
Which is why "we'll improve our consent UX" doesn't recover the loss — it only narrows the first stage. Ad blockers and browser restrictions still apply to everyone who accepts.
A mechanism is not a number. To put a size on the gap you have to measure it, and here is what one store showed. Incapto, a specialty coffee brand on Shopify, ran GA4 with Consent Mode and Sealmetrics side by side for 48 days. GA4 did not record 29% of visits or 45% of pageviews. Sealmetrics, reconciled against Shopify's own orders, recorded 96% of real orders and 97% of revenue. The method and the full figures are in the case study.
The more useful finding is where the gap sat. Against GA4, Sealmetrics saw 11% more direct traffic, 62% more organic search, 73% more affiliate and 133% more organic social. The channels that bring new people in lose the most; direct loses the least, so in GA4 it looks more important than it is. That is a budget problem before it is a measurement one.
You can estimate your own gap before measuring it with our data loss calculator.
The consent range is our experience with clients, not a market average; ad blockers and browser restrictions vary too much by audience to state as one number. The Incapto figures are measured on one store over one period. More in our published analysis.
Sampling vs complete measurement
What reaches the dashboard is already partial. The dashboard, in turn, samples it.
GA4 applies sampling when a query exceeds certain thresholds — by default, 10 million events per query in the standard tier. Above that, it analyses a subset of events and extrapolates the result. The report is presented as a measurement. It is an estimate of a measurement.
The sampling rate is not always surfaced. Some reports show a "sampled data" warning; many do not. For high-volume eCommerce sites with deep filters, the analysed ratio can drop below 1% of events on complex queries — a sample of a sample.
"What appears as a 1.3% conversion rate is a calculation on a sample of a fraction of the real population. Defending that number to a CFO is a coin toss dressed as analytics."
Sealmetrics does not sample. Every event lands in ClickHouse at full resolution. A query against 4 billion events queries 4 billion events. We pay for the storage and the compute so that the answer matches the question.
Modeling vs measuring
When GA4 cannot measure — because consent was rejected, the ad blocker stripped the request, the cookie expired — it does not leave the cell empty. It models.
"Modelled conversions", "behavioural modelling", "consent mode v2": all variants of the same mechanism. A regression trained on the events GA4 can see predicts the events it cannot. The output is reported as a number, indistinguishable in the UI from anything that was actually observed.
Modelling has legitimate uses — directional analysis, time-series smoothing, exploratory work. Optimising a media budget against modelled conversions is not one of them. The bidding algorithm interprets a modelled conversion as a real one. The budget shifts toward whichever channel scored highest in the model. The channel that drove the actual converter is, by definition, the one whose data was missing — and the budget never reaches it.
Complete means measured.
Sampled is a degradation. Modelled is an inference. Each step away from measured is a step further from a decision being defensible. Wherever the phrase "complete data" appears in Open, it means: measured server-side, before any of the three losses fires, on visitors who accept and reject the banner alike.
Where Sealmetrics sits
Three tiers operate in analytics today. The category matters because comparisons across tiers are dishonest — and most published comparisons quietly are.
Enterprise analytics
GA360, Adobe Analytics, Piwik PRO, Sealmetrics
Six- and seven-figure decisions. Complete data, compliance posture, and audit trails are non-negotiable.
Lightweight privacy analytics
Plausible, Fathom, Simple Analytics, Umami
€9–50/month. Page-level metrics, beautiful UIs, zero PII. Excellent at what they do — and not built for revenue attribution or billion-event datasets.
Free with sampling
GA4 default
Free at the entry tier. Constraints (consent loss, sampling, modeling) compound at scale.
Sealmetrics competes in Tier 1. The lightweight tools are not competitors — they are the right choice for a different problem. If you are evaluating Sealmetrics, you are not choosing between us and Plausible. You are choosing between complete data and the budget consequences of the alternative.
The rest of Open builds on this definition. Chapter 05 describes the infrastructure that makes it possible. Chapter 09 lists what we will not do with the data we collect. The chapter on GDPR compliance — and the one on how the pixel works internally — are in progress; in the meantime, the legal grounding lives at /security.
Continue with chapter 05 — Architecture and performance.
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