Analytics and Tracking

Measurement comes before optimization, because every decision downstream rests on it. Almost every account we open has at least one conversion action that's wrong, and until that's fixed nobody in the room is discussing real numbers.

What Goes Wrong With Conversion Tracking

The same handful of faults, repeatedly, and all of them are invisible unless somebody checks.

• A Thank-You Page Counted on Every Load
  One inquiry becomes four when the visitor refreshes or returns via the back button.
• Spam Counted as Conversions
  Bot submissions inflate the total until the real rate is unknowable.
• A Form That Reports Success Without Sending
  The tracking fires on the button, not on the delivery, so the numbers look healthy while nothing arrives.
• Every Form Treated Identically
  A newsletter signup and a quote request recorded as the same event, so the metric averages two unrelated things.
• Tracking That Never Fires on Mobile
  Frequently a script that fails silently on one browser.

The consequence is not just bad reporting. Ad platforms optimize toward whatever you tell them a conversion is, so a broken signal actively directs budget at the wrong people.

How to Check Whether Tracking Is Honest

By reconciling against something outside the analytics. Count the inquiries that actually reached a person over a month and compare that with what the platform reported. If those numbers are far apart, the reported one isn't usable.

That comparison is cruder than a technical audit and it settles the question faster. Everything else follows from knowing whether the number can be trusted.

What a B2B Site Should Measure

Resist tracking everything. An account with forty events has no hierarchy, and the important one gets lost among scroll depth and video plays nobody acts on.

Platform Numbers and Analytics Disagree by Design

Because they attribute differently and they count different things. An ad platform credits itself for a conversion within its attribution window; your analytics assigns it to the last channel it saw. Neither is lying and they will never reconcile exactly.

The workable approach is to use platform figures for optimizing inside that platform, analytics for comparing channels, and inquiries that actually arrived as the number the business is judged on. Trouble starts when one of the three is presented as the truth.

The Traffic You Cannot See

A significant share of visits arriving from AI assistants carry no referrer and land in Direct. Analytics also only ever records a citation somebody clicked; a brand mentioned in an answer that influenced a decision leaves no trace at all.

So Direct isn't a synonym for "typed the URL", and a channel report is a floor rather than a measurement. Where the assistants are identifiable we group them explicitly, and where they aren't we say so rather than reporting a number we can't support.

What the Work Involves

• Audit What Is Installed
  and what each event actually records, as opposed to what it is named.
• Define Conversions
  that map to business outcomes, with spam and internal traffic excluded.
• Implement and Verify
  , including on mobile, by submitting real test inquiries end to end.
• Group Channels
  so assistant and AI referrals are visible rather than absorbed into Direct.
• Reconcile Monthly
  against inquiries that arrived.

Where This Fits

Analytics is the first stage of conversion optimization and the prerequisite for testing, which cannot work against an unreliable signal. It also underpins paid media, since campaign optimization is only as good as the conversion data feeding it.

Frequently Asked Questions