Add an AI delivery layer — so capacity and depth stop being a hiring race.
02Do the work of a whole agency, as one person, without building the machine yourself.
03Punch above your size — a consumer-grade model wrapped in a real ecosystem.
04Senior-led AI capability that stands up in days, not quarters — with ownership built in.
Hire a dedicated marketer or team — AI-superpowered — from a simple starter plan upward.
02Scoped to a specific project or goal, priced to the outcome you want to hit.
03Pay for defined work, gated on a quality bar you set — flexible and lean.
Analytics and tracking operated as the foundation every other marketing decision stands on. GA4, server-side, data layer, attribution, event design, warehouse-native measurement — built right, kept right. Built with you, owned by you. The numbers don't lie because someone is watching them.
Something changed. For a decade, marketing tracking was a one-time setup project. The cookie deprecation, iOS privacy changes, and AI search broke the assumption that client-side tags would just keep working. Now tracking is a permanent discipline: server-side collection, data layer architecture, ongoing sanity checks, attribution reconstruction. The teams winning from here aren't the ones with more dashboards. They're the ones whose numbers hold up at the next board review.
A tag manager update, a website redeploy, a consent banner change, a third-party script update — any of these can break events without throwing an error. The data still flows; it just flows wrong. Quarterly reports go out on broken numbers. Decisions compound into the wrong strategy. By the time someone notices, the data history is contaminated. Tracking treated as one-time setup is the structural reason marketing decisions don't hold up under scrutiny. Until eighteen months ago, the operating discipline to fix this required an in-house data engineer. AI changed the economics.
Tracking ops was too expensive to outsource. Weekly sanity checks, deliverability monitoring, data layer evolution, attribution reconstruction, consent-stack maintenance, server-side migration — each is senior work. Most agencies sold setup because setup priced cleanly; ongoing tracking ops priced by the hour and clients couldn't justify it. The data decayed; the dashboards lied; the strategy drifted.
Continuous trust becomes affordable at depth. Weekly sanity checks, automated anomaly detection, data layer maintenance, server-side ops, attribution model evolution — held in one operating system, directed by senior people. Built with you, directed alongside you, owned together. The numbers hold up because someone is watching them — not because nobody is looking.
An AI ecosystem is AI configured by fundamentals, directed by senior people, and stitched into a system that holds knowledge, sequence, and preparation in place — as opposed to AI used as a standalone tool. Analytics and tracking is the foundation; the layers below are what keep the numbers trustworthy. Hover or tap any segment to see what lives in it.
Hover or tap any layer or segment — its details appear right on the diagram.
For a decade, tracking capped out at clean setup. AI changed the ceiling — above-average implementation with AI-assisted GTM configuration is what every analytics partner now claims. But that ceiling is commodity. The new game — tracking operated as a permanent discipline with numbers that hold up — is what only an AI ecosystem reaches.
We own the number you're judged on — end to end, with skin in the game. The strategy is built with you, the system is owned by you, the outcome is shared between us.
Reciprocity. A 20-year operating ethic embedded in the name: build for others as you would for yourself. It's why the work is honest.
Frameworks · 50+ industries of pattern recognition · full-stack delivery. The AI ecosystem makes senior depth scalable. Human-in-the-loop pushes it above the commodity ceiling.
Fixed-plus-variable on every engagement, a portion held against quality. Plus the 5-Day Experience — we deliver the strategy before you commit. We go first because we're confident.
Every analytics partner promises clean tracking. The real question is whether they can keep the numbers trustworthy — not just stand up the implementation. Don't leave it to chance. Experience the work in five days — on your stack, your events, your decisions.
A 60-minute call. We agree your current tracking state, the decisions made on the data, and what you'd want trusted. The Day 0 call is with the operator who will run the work — not a sales lead.
We produce a tracking audit (what's broken, what's missing, what's decaying), a data layer specification, a server-side migration plan if needed, and a 90-day measurement roadmap — on your real stack.
You see the audit, the data layer spec, the migration plan, the measurement roadmap. You judge whether the depth is real. If yes, we talk about an engagement. If no, you keep the work — no charge, no obligation.
Sample Documents are anonymised client-facing deliverables — the actual artefacts an analytics and tracking engagement produces.
The audit a senior measurement lead would deliver at week one: event-by-event accuracy check, data layer review, server-side coverage, attribution reliability, consent compliance.
View sample →The full data layer specification a senior analytics engineer would design: page-level context, user-level state, event vocabulary, business properties, naming conventions that survive platform changes.
View sample →The actual Day-5 artefact from a mid-market analytics engagement: tracking audit, data layer spec, server-side migration plan, 90-day measurement roadmap.
View sample →Selectivity is part of the work. Here's who an analytics and tracking engagement is built for — and who it isn't.
Audit, identify the structural breaks, rebuild the data layer, migrate to server-side, reconstruct attribution against the new reality, restore decision-grade reliability. The work that turns “our tracking is a mess” into “the numbers hold up.”
Weekly sanity checks, anomaly detection, data layer evolution, server-side hygiene, attribution recalibration, consent stack maintenance. The work that keeps the numbers trustworthy as the platform, the privacy regime, and the channel mix keep changing.
A dedicated analytics team operating your tracking foundation — remediation + ongoing operations. The full AI ecosystem behind them. Owned alongside you.
Recurring · from a starter plan upwardA defined tracking project (GA4 migration, server-side migration, data layer rebuild, attribution model reset) priced to the outcome. Goal-aligned economics with a portion held against quality.
Goal-pricedThe lightest engagement: discrete tasks — a tracking audit, an event spec rebuild, a consent-mode v2 implementation — priced and delivered task by task. The simplest way to co-create a first piece of work.
Per-task pricingWork-first. We deliver, then charge. A portion held against quality, every engagement.
Because nobody is monitoring them. A tag manager update, a website redeploy, a consent banner change, a third-party script update — any of these can break events without throwing an error. The data still flows; it just flows wrong. Six months later, decisions made on broken numbers compound into the wrong strategy. Tracking operated means someone watches the numbers for sanity every week, not just every quarter.
GA4, Google Tag Manager (web + server), BigQuery, Looker, Snowplow, Segment, Mixpanel, Amplitude, Heap, Plausible, server-side gateways (Stape, Addingwell), CDPs (Segment, RudderStack, Hightouch), warehouse-native attribution. We'll work in your existing stack or recommend one if the current setup is the bottleneck.
Server-side tracking moves event collection from the browser to your own server before forwarding to destinations. It survives ad blockers, iOS privacy changes, cookie deprecation, and reduces client-side weight. If your business depends on accurate event data for paid attribution, lifecycle triggers, or product analytics, server-side is no longer optional — it's table stakes.
A data layer is a structured object on every page describing what the user is doing — what page they're on, what they're interacting with, what the business context is (logged in? plan tier? funnel step?). Every tracking event reads from this layer. Without a real data layer, tracking is a tangle of one-off triggers that break every redeploy. With one, tracking is portable, predictable, and survives platform changes.
A GA4 consultant configures the platform. We operate analytics and tracking as the foundation layer of marketing — GA4 is one destination among several (warehouse, attribution model, lifecycle tool, ad platforms), and the data layer underneath all of them is where most of the work is. We rebuild from the foundation up, not from the platform down.
Yes — attribution is one of the most reliable signals to break in 2024-26. Cookie deprecation, iOS privacy, walled-garden API changes — all reshape what attribution can see. We rebuild attribution against your actual data reality (server-side events, MMM where appropriate, marketing-mix triangulation), not against the model the platform defaults to. The result is decisions you can actually defend.
Three things. The cookie deprecation made client-side tracking unreliable. iOS privacy changes broke the attribution stack most B2C marketers relied on. And AI search engines started serving traffic that doesn't appear in standard analytics. Tracking that ignores any of these is producing decisions on numbers that don't hold up.
Three engagement models — Build a dedicated team, Project & goal-based, Task & quality-driven. All three operate work-first with fixed-plus-variable economics — we deliver, then charge; a portion is held against quality. Specific pricing is configured per engagement and shared on the Day 0 call.
Deep, foundation-focused pages built for specific platform × data-shape combinations.
Built TechShu over 15+ years across 50+ industries. Now operating techshu.ai — the AI-era avatar — where the AI ecosystem does the heavy lifting and senior judgement directs every output. The 5-Day Experience is run personally; the Day 0 call is the same person who will direct the tracking foundation work if you decide to engage.
Every analytics partner promises clean tracking. The real question is whether they can keep the numbers trustworthy — through platform changes, privacy regime changes, channel-mix changes. Don't leave it to chance. Experience the work. If the foundation depth isn't real, you keep the audit and the roadmap — and we move on.