Telemetry engineering.
From instrumentation to attribution model. Auditable pipelines, data governance, dashboards that C-suite consults before decisions. not after.
Telemetry engineering. Not vanity dashboards.
Most companies have analytics. Few have telemetry that is actually used for decisions. The difference is in the architecture: events that capture business intent, not just clicks; attribution models that reflect the real customer journey; dashboards that answer C-suite questions without a data analyst intermediary.
What we deliver
Tracking plan & instrumentation
Complete data dictionary, standardized event naming and implementation through GTM or SDK. Documentation with owner, creation date and deprecation criteria for each event.
Auditable data pipeline
Ingestion through Segment or direct sources, dbt transformations with automated quality tests, and Snowflake or BigQuery warehouse. Fully traceable lineage.
Multi-touch attribution models
Data-driven, last-click, linear and MMM models for budget allocation. Model comparison reconciled against actual revenue reported by finance.
Dashboards executivos live
Dashboards in Looker or Hex updated every 4 hours. C-suite layer with business KPIs such as revenue, CPA and LTV/CAC. Operational layer with channel metrics and anomalies.
Anomaly alerts & SLA
Automatic alert system for conversion drops, channel cost spikes and forecast deviations. 4-business-hour response SLA for critical anomalies.
How we operate
Existing telemetry audit (weeks 1-2)
Complete mapping of implemented events, identification of gaps and corrupted data, quality assessment by channel. Deliverable: diagnosis with refactoring priorities.
Data dictionary & tracking plan (weeks 3-4)
Definition of naming, required events by page type, properties and allowed values. Approval with product, marketing and finance teams.
Implementation & testing (weeks 5-8)
Instrumentation through GTM or SDK, QA tests by environment and parity validation across platforms such as GA4, CDP and CRM. Documentation for each event in production.
Pipeline & warehouse (weeks 7-10)
Ingestion setup, dbt transformation with quality tests and warehouse loading. Documented lineage and configured quality alerts.
Dashboards & models (weeks 9-12)
Dashboard construction by audience: executive, operational and channel. Attribution model calibrated against historical revenue and internal team training.
Operation & evolution (ongoing)
Continuous data quality monitoring, model evolution for new channels or products, biweekly reporting and quarterly lineage audit.
Frequently asked questions
Can you work with our existing GA4 setup?
Yes. We start with an audit of the existing setup, identify gaps and implement corrections without breaking historical data where possible. If the setup is too compromised, we plan a clean migration.
What attribution model do you recommend?
It depends on the conversion cycle and channels. For most enterprise clients we implement a data-driven multi-touch model calibrated with MMM (Marketing Mix Modelling) for offline channels.
How does LGPD/GDPR compliance work?
All our implementations include a full tracking plan, data dictionary with retention policies, and Consent Mode v2 for Google. Documentation available for due-diligence.
What is the reporting cadence?
Live dashboard updated every 4h for the operational team. Fortnightly executive report. Quarterly C-level review with CMO and CFO.
Does the client keep access to everything after the contract?
Yes. All dbt code, queries, documentation and dashboards belong to the client. We provision admin access to every tool used. At final delivery, we run handover training with the internal team or the client technical partner.