A website owner usually wants answers to fairly boring questions.
How many people visited?
Which pages were popular?
Did anyone click the new navigation link?
Did traffic come from search, a newsletter, or another site?
None of those questions automatically requires building a durable advertising identity for every visitor.
Measurement and profiling are different jobs
Analytics becomes much more invasive when the unit of analysis changes from what happened on this site to what this person does across many sites and devices.
A publisher can often measure page views, broad traffic sources, session counts, device classes, or conversion totals without trying to recognize the same person everywhere else on the web.
France’s data-protection authority, CNIL, provides a useful concrete model. Its guidance allows certain audience-measurement trackers to qualify for a consent exemption only under restrictive conditions: the purpose must stay limited to audience measurement or A/B testing, the data must not be cross-checked with unrelated customer files or visits to other sites, the tracker must remain scoped to a single publisher, IP addresses must be truncated, and tracker lifetimes are limited. See CNIL’s guidance on audience measurement.
That is not the only possible privacy-preserving design.
It is useful because it shows the engineering principle clearly: collect enough to answer the measurement question, but do not quietly turn analytics into an identity business.
Aggregate answers lose some detail
Collecting less has tradeoffs.
A system that refuses to create persistent user histories may be worse at answering questions such as:
- Did the same person return six months later?
- Which advertisements did this exact user see before subscribing?
- How does one person’s behavior compare across several unrelated properties?
Those can be commercially useful questions.
They are also the questions that require more durable identity.
A publisher therefore has to separate what it genuinely needs from what is merely interesting because technology makes it possible.
More data is not automatically better measurement
Individual-level histories can create their own errors.
People clear cookies. Families share devices. One person uses several browsers. Privacy tools isolate identifiers. Automated traffic contaminates logs. Cross-device systems make probabilistic matches that may be wrong.
A giant profile can look precise while containing bad joins.
Aggregate measurement has uncertainty too, but at least the uncertainty is closer to the question being asked.
If the question is How many times was this article read?, a system does not necessarily need to answer Who else lives with this reader?
That distinction matters at the end of the Surveillance Economy section.
The choice is not between perfect analytics and total blindness.
There is a large middle ground where websites can measure their own performance without insisting on remembering everybody everywhere.