Most analytics setups break in the same three places
After deploying tracking on more than 167 sites, the failure modes are predictable. Pixels fire on the wrong page. Conversion events double-count refunded orders. Attribution credits the last campaign instead of the one that did the work. The reports look fine until someone tries to make a budget decision from them, and then the numbers stop holding up. We build tracking that holds up: implementations clients can take to a board meeting and an ad audit without flinching.
What we mean by an analytics and tracking project
A tracking project at Enderon covers the full stack a modern marketing team needs to make ad-spend decisions:
- GA4 implementation. Property setup, data streams, event taxonomy, custom dimensions, conversion configuration.
- Google Tag Manager. Container architecture, data layer specs, click and form tracking, cross-domain measurement.
- Server-side tagging. When first-party data accuracy matters more than convenience, we move tags to a server container on Cloud Run or Vercel Edge Functions.
- Conversion API integrations. Meta CAPI, Google Ads Enhanced Conversions, TikTok Events API, LinkedIn Conversions API.
- Consent mode. GDPR-aware dual-mode tracking that keeps NZ Privacy Act and AU Privacy Principles defensible without nuking your data.
- Reporting layer. Looker Studio dashboards, GA4 Explorations, GTM-fired Slack alerts on broken events.
We build the spec first, then the implementation, then the QA. No tag goes to production without a written event plan, a debug-mode walkthrough and a 7-day post-launch reconciliation.
Tools we deploy with
GA4. Google Tag Manager (web and server). Meta Pixel and CAPI. Google Ads conversion tracking. Microsoft Advertising UET. LinkedIn Insight Tag. TikTok Pixel. Hotjar or Microsoft Clarity for session-level diagnosis. Stape, Cloud Run or Vercel Edge for the server container. We don't push specific tools because the tools are downstream of the question: what decision will this number drive?
Who this works for
You already run paid traffic, organic search has been going somewhere, and you can no longer trust the numbers your team reports each week. Common signals: GA4 events that say one thing and Stripe says another, ad platforms each claiming credit for the same conversion, a "data team" that's actually one person manually pasting CSVs into a spreadsheet. If any of that is uncomfortably familiar, this is the project.
We do not work on early-stage tracking for pre-revenue companies. The math on a tracking project only makes sense once there's enough traffic and spend to act on the data.
Where we've shipped this
E-commerce, lead-gen, marketplace, B2B SaaS, multi-location service businesses. Stack agnostic: we've built the same architecture on Shopify, WooCommerce, Webflow, Next.js, headless WordPress and custom rails. The pattern transfers. The implementation details don't.
