Zaventra

D/00 · Analytics and Measurement

Measurement / Data

Measurement that turns marketing data into a defensible source of truth

Most marketing data is a patchwork of pixel tags, broken events, and dashboards nobody trusts. We design GA4, server-side, and warehouse-native measurement stacks that survive iOS, consent, and platform changes, so every team works from the same numbers.

Book a free strategy call→ All digital disciplines
GA4 and server-side tagging Consent and privacy Warehouse modeling Attribution that holds up

D/01 · Overview

A measurement program built on engineering discipline

Measurement is the foundation every other channel sits on. When it is broken, smart bidding optimises against noise, dashboards contradict each other, and quarterly reviews become arguments over which number is right. We rebuild the stack around clean event design, governed implementation, and a warehouse layer your team controls.

Each engagement runs with a measurement strategist, an analytics engineer, and a data engineer. They own event design, GA4 and server-side tagging, consent, warehouse modeling, and reporting, then hand back documentation your team can maintain long after the engagement ends.

D/02 · Scope

What's included in every measurement engagement

A complete measurement program covering strategy, implementation, governance, and reporting run by senior engineers.

  • Scope 01

    Tracking plan and event design

    We design a versioned tracking plan covering pages, events, properties, and identifiers, aligned across marketing, product, and finance so every team is measuring the same things.

  • Scope 02

    GA4 and server-side tagging

    GA4, Google Tag Manager, and server-side containers are implemented or rebuilt with proper event taxonomy, deduplication, and conversion configuration that supports honest reporting.

  • Scope 03

    Consent and privacy

    Consent mode, CMP integration, and regional rules are configured so measurement respects user choice while still providing modeled data where the law and platforms allow.

  • Scope 04

    Warehouse and modeling

    Raw events are streamed into BigQuery or your warehouse and modeled into clean fact and dimension tables your analytics, BI, and finance teams can query with confidence.

  • Scope 05

    Attribution and reporting

    Channel and campaign attribution is built on warehouse data with documented methodology, so reporting holds up to scrutiny from finance, board, and external auditors.

  • Scope 06

    Governance and documentation

    Every event, dashboard, and model is documented in a single source of truth, with change management and review processes so the stack does not silently drift over time.

D/03 · Platforms & Tooling

Analytics and data tools we run

Deep production experience across product analytics, web analytics, warehousing, and BI tooling.

  • GA4
  • Mixpanel
  • Amplitude
  • Segment
  • Google Tag Manager
  • BigQuery
  • Looker Studio
  • PostHog

D/04 · Delivery

How a measurement engagement runs

A four-phase rhythm that moves from audit to a governed measurement program your team can maintain.

01

Audit and tracking plan

We audit existing tags, events, and dashboards, then write a tracking plan that aligns marketing, product, and finance on shared events, properties, and identifiers.

02

Implementation and consent

GA4, server-side containers, consent mode, and CMP integration are implemented or rebuilt, with QA across browsers, devices, and regions to confirm clean, consented data flow.

03

Warehouse and modeling

Events are streamed into your warehouse, modeled into clean fact and dimension tables, and exposed through BI tooling so reporting moves from spreadsheets into governed dashboards.

04

Governance and enablement

We document the stack, train your team, and put change management and review processes in place so the measurement program stays trustworthy long after the engagement ends.

D/05 · Best Fit

Where measurement work pays back fastest

A serious measurement program returns the most for organisations that already feel pain from contradictory or untrusted data.

  • Scaling SaaS and platforms

    SaaS, marketplace, and platform businesses where product and marketing teams need shared event definitions, clean funnels, and attribution that lines up with revenue in the warehouse.

  • Mid-market and enterprise commerce

    Mid-market and enterprise ecommerce brands with multi-region storefronts, complex consent requirements, and finance teams who need attribution they can reconcile against orders.

  • Regulated and global brands

    Healthcare, financial services, and global brands operating under strict privacy regimes that demand server-side tagging, consent mode, and documented data governance.

D/06 · FAQ

Analytics and Measurement - common questions.

Practical answers to the questions buyers ask before they engage on analytics and measurement.

FAQ 01

Do you replace our existing analytics stack?

Rarely. In most cases we extend and govern what is already in place. GA4, GTM, server-side containers, and your warehouse are usually enough when implemented properly. We only recommend swapping tools when a specific platform is fundamentally limiting, and we document the trade-offs before any change.

FAQ 02

How do you handle consent, iOS, and privacy?

Consent and privacy are designed into the stack from day one, not bolted on later. We integrate with your CMP, configure consent mode and regional rules, and combine server-side tagging with modeled data where allowed so measurement stays useful while respecting user choice and regulation.

FAQ 03

What does the warehouse layer give us that GA4 alone cannot?

A warehouse layer gives you raw event data you control, joined to orders, subscriptions, and customer attributes from your other systems. That unlocks honest attribution, cohort and LTV analysis, finance-grade reporting, and the ability to feed downstream tools like CDPs, ad platforms, and BI without being limited by GA4 sampling or schemas.

FAQ 04

How long does a measurement rebuild take?

A focused rebuild for a mid-sized stack typically takes one to two quarters from audit to stable production, depending on the complexity of your products, regions, and existing debt. We deliver in phases so value lands early, with the tracking plan, GA4, and consent in place before warehouse modeling and reporting work.

D/07 · Related

Other digital disciplines that pair well.

Most engagements combine two or three disciplines so the funnel is wired together end to end.

D/08 · Next step

Analytics and Measurement

Ready to make measurement a defensible asset, not a recurring argument?

Share your current analytics stack, consent setup, and reporting pain points. We will respond with a focused diagnostic, the highest-leverage measurement work we would do first, and a clear view of what a senior-run program would deliver.

Book a free strategy call See all digital disciplines
Reply within 1–2 business days NDA-friendly No sales pressure