It is not a bug
Run two analytics tools side by side and they will disagree, often by a wide margin. People lose days trying to reconcile them. The gap is expected, it is explainable, and once you understand where it comes from you can use it.
Where the difference comes from
Different definitions of a session. One tool ends a session after thirty minutes of inactivity, another at midnight, another when the campaign source changes. Same visitors, different arithmetic.
Different blocked rates. A script served from a well-known advertising domain is blocked far more often than a first-party lightweight one. This is usually the single largest source of difference, and it is why the "privacy" tool frequently reports more traffic, not less.
Consent. If one tool is gated behind a consent banner and the other is not, every visitor who declines is missing from the first. On a typical banner that is not a rounding error.
Bot filtering. Every tool maintains its own bot list and applies its own heuristics. Server logs, which filter nothing by default, will always show the largest numbers of all.
Timing. One tool fires on page load, another after the page becomes interactive. Visitors who leave in the first second are counted by the first and missed by the second.
Timezone and attribution windows. A conversion attributed to the click date in one tool and the conversion date in another will never line up on a daily chart.
Which one is right?
None of them, exactly, and it does not matter.
The number that is definitely true is in your own database: orders, signups, subscriptions. Everything else is an estimate of the traffic that produced it.
So the correct posture is: trust your database for outcomes, pick one analytics tool as your reference for traffic, and use it consistently. A consistent estimate is a decision-making tool. Two inconsistent estimates are an argument.
Using the gap deliberately
The difference between sources is itself information.
Analytics against server logs gives you an estimate of your blocked rate — the share of real visitors that JavaScript-based measurement never sees. It is usually higher than people expect, and it is a genuine reason to be cautious about small percentage changes.
Analytics against your database gives you the conversion tracking ratio. If analytics normally sees four of five orders and this month it sees three of five, something broke — and you found out because you were comparing.
Two analytics tools against each other, during a migration, give you the conversion factor between them, so a year of history in the old tool stays comparable with the new one.
Practical rules
1. One reference tool for traffic decisions. Write down which one.
2. Your database is the truth for anything that involves money.
3. Compare monthly, and record the ratios rather than trying to eliminate them.
4. Investigate step changes, not small differences. A 5% discrepancy is normal. A 40% overnight change is a broken tag.
5. Never present two tools' figures in the same report without saying which is which. That is how organisations end up arguing about numbers instead of decisions.
The underlying point
Analytics measures a proxy for reality, through a browser that may or may not cooperate, filtered by a visitor who may or may not consent. Precision was never available. Direction and magnitude were, and they are enough for almost every decision you will make with the data.