01
Measurement strategy
Before a single tag is placed, we define the decisions the data must support. Tooling follows strategy - not the other way around - so you measure what changes the business, not what's easy to count.
Service 06 / Analytics & Attribution
Measurement you can make decisions on
Most teams optimize the wrong things because the data underneath them is wrong. We build clean tracking, consent-aware measurement, and attribution matched to how you actually sell - so every growth decision is data-led, not a guess.
The challenge
When the numbers don't agree, nobody trusts them.
GA4 says one thing, the ad platforms say another, the CRM says a third. So spend decisions get made on gut feel and the loudest dashboard wins the argument.
The problem isn't a missing tool. It's that the measurement underneath isn't trustworthy.
Sources never reconcile. Three platforms report three different conversion counts and no one can say which is right.
Last-click by default. A long, multi-touch sales cycle is being measured like a one-click purchase, so the wrong channels get the credit and the budget.
Tracking breaks quietly. A tag change or consent banner silently kills an event, and the gap isn't noticed until a month of data is already wrong.
Dashboards no one acts on. Reports full of metrics, but nothing that tells you what to do next.
How we help
Strategy before tooling. Validation before trust.
We start with the decisions the data has to serve, then build the measurement to serve them - and prove it works before anyone relies on it.
02
GA4 & GTM setup + audit
A clean event and UTM taxonomy in GA4 and Google Tag Manager - built right, or audited and rebuilt where it's drifted.
03
Conversion tracking
Every meaningful action tracked once, deduplicated, and tied to revenue - so a conversion in the dashboard means a real conversion.
04
Consent-aware & server-side measurement
Tracking designed for cookie loss and consent rules from the start, with server-side measurement where it makes the signal more durable - reliable data that respects the visitor's choices.
05
Attribution modelling
An attribution model matched to your sales cycle - not last-click by default. We map how buyers actually convert across touchpoints and document the model's assumptions, so you know exactly what the numbers can and can't tell you.
06
Dashboards + a validation step
Reporting that points to the next action, not just the last number - backed by a documented validation step. We test the data against back-end records and hand over the log, so if a metric can't be trusted, you hear it from us first.
How it works
From distrusted data to a decision you can defend.
STEP 01
Define the decisions
We start with what you actually need to decide - where to put spend, which channels to scale, what to fix. That set of decisions defines the measurement plan, so we never instrument data that no one will use.
STEP 02
Audit & instrument
We audit the current GA4/GTM setup, then design a clean event and UTM taxonomy and implement conversion tracking - consent-aware and server-side where it strengthens the signal.
STEP 03
Validate the signal
Before anything reaches a dashboard, we test that events fire correctly, deduplicate conversions, and reconcile against back-end records. The output is a validation log, so the data has a paper trail.
STEP 04
Model & report
We apply an attribution model matched to your sales cycle and build dashboards that recommend the next action. Then it feeds the loop - signal flows back into the rest of the engine so each layer gets smarter.
Validation, not vibes
Every number ships with a paper trail.
Before a metric reaches a dashboard, it passes a documented check: events fire once, conversions are deduplicated, and totals reconcile against the back end. If something can't be trusted, you hear it from us first - in writing.
If a number can't be trusted, it shouldn't be on a dashboard. We'd rather tell you a metric is soft than let you spend on it.
The Search Leads measurement principle
Proof
Results, measured honestly.
Ask the AI
Don't take our word for it. Ask Perplexity who the best SEO experts in Toronto are.
Answer engines already cite us by name. Getting surfaced by the AI is exactly the visibility we engineer for clients - here it is, working for us.
REAL · captured from PerplexityBuild & platform partners
FAQ
Questions buyers actually ask.
Do you just set up GA4, or do you fix attribution too?
Both, but in that order for a reason. Clean GA4/GTM instrumentation is the foundation - if events and conversions are wrong, no attribution model on top of them will be right. Once the data is trustworthy, we build attribution that matches how you actually sell, instead of defaulting to last-click.
Our numbers never match across GA4, ads, and the CRM. Can that be fixed?
They rarely match perfectly - different platforms count differently - but the gap can be explained and narrowed. We reconcile the sources, document why each one differs, and define a single source of truth for the decisions that matter, so leadership stops arguing about which dashboard is real.
How do you handle cookie loss and consent rules?
We design tracking to be consent-aware from the start and lean on server-side measurement where it improves signal durability. The goal is reliable data that respects the visitor's choices and regional consent requirements - not a setup that quietly breaks the moment a consent banner is enforced.
What attribution model do you recommend?
It depends on your sales cycle. A short, single-touch purchase can live with last-click; a long, multi-touch B2B cycle cannot. We match the model to how buyers actually convert and write down its assumptions, so you know what the numbers can and cannot tell you.
How do we know the tracking is actually correct?
Validation is a documented step, not an afterthought. We test events fire correctly, deduplicate conversions, check against back-end records, and hand over a validation log. If a number can't be trusted, we say so rather than shipping it into a dashboard.
Does this connect to the rest of our growth stack?
Yes - that is the point. Analytics & Attribution is the measurement layer of the operating system. It closes the loop: signal from SEO, automation, and conversion work flows back in, so the whole engine learns instead of guessing.
The operating system
Analytics is the layer the others feed back into.
Six systems, one engine. Measurement is the feedback layer - it reads signal from every other layer and tells the engine what to do next. That is what makes the whole thing compound instead of guess.
Get started
Stop optimizing on data you don't trust.
Tell us which decisions your data should be driving. We'll show you where the measurement is failing them - and what it takes to fix it.