Decisions that survive first-party tracking.
Server-side GA4, consent-compliant attribution, blended CAC dashboards, LTV modeling. We wire your data plumbing once — correctly — then agents watch it, flag anomalies, and answer questions in plain English.
Data infrastructure. Decisions on top.
Data is only useful if it's trustworthy, timely, and explained. We build the plumbing, the dashboards, and the alerting — then agents watch 24/7 so you only hear about what actually changed.
Data integration
GA4, ad platforms, CRM, ecommerce, product — unified into BigQuery / Snowflake / Postgres with documented schemas.
Custom dashboards
Looker Studio, Metabase, or custom. Role-specific views (exec, marketing, product) with shared source-of-truth tables.
Behavior analysis
Cohorts, funnels, retention curves, LTV. Understand not just what users did, but what predicts what they'll do next.
Conversion tracking
Server-side events, consent-aware tagging, cross-device stitching. Works in a post-cookie, GDPR-enforced world.
Predictive analytics
Churn models, LTV forecasts, cohort projections. Practical ML — no deep-learning fantasyland, just tested math.
Agent alerting
Agents watch metrics 24/7 for anomalies, correlate with known inputs, and page the right human — not every human.
How the analytics agent works.
Analytics isn't a quarterly report — it's a 24/7 sensor network. Agents watch the numbers; seniors answer the questions they raise.
Sync every source
Nightly ETL from every platform into your warehouse. Schema tests gate the pipeline — bad data doesn't reach the dashboard.
Agents detect anomalies
Statistical process control on every KPI. Agents compare against rolling baselines, flag outliers, and correlate causes.
Plain-English diagnosis
When an alert fires, agents draft the "why" — which source changed, what correlated with it, what historical patterns match.
Right human, right channel
Slack for urgents, weekly email digest for trends, monthly senior review for strategy. Nobody drowns in alerts.
What you can order
from this engine.
Each deliverable has a scoped unit cost. Mix across services within your monthly allocation, or add 5-unit top-up blocks anytime.
| Deliverable | Type | Units |
|---|---|---|
| Analytics audit — existing setupTag inventory + data-quality report + gap plan | Research | 10= €1,000 |
| GA4 server-side implementationGTM server container + consent + events | Setup | 18= €1,800 |
| Warehouse setupBigQuery / Snowflake + nightly ETL from top sources | Setup | 20= €2,000 |
| Custom dashboard — 1 stakeholder roleExec / marketing / product — role-specific KPIs | Setup | 12= €1,200 |
| Anomaly alertingAgent watchers on top 20 KPIs, Slack-integrated | Setup | 10= €1,000 |
| Attribution modelingBlended CAC / LTV model · quarterly refresh | Agentic | 8= €800 |
| Monthly insight reportWhat changed, why, what to do next | Agentic | 3= €300 |
| Strategy sync — senior analyst45-min analytical review | Consulting | 3= €300 |
Unit estimates are tentative — final scope is set during your first sync. Because agents compress the work, you often get more output per unit than a traditional hourly retainer would predict.
Median uptime on managed pipelines across clients (trailing 12 months).
Agent-detected anomalies confirmed as real by senior review. Not noise, not false alarms.
From anomaly detection to agent-drafted diagnosis in Slack. Before humans even open the dashboard.
Role-specific views on average. Exec + marketing + product + finance + ops coverage.
Three shapes where analytics compounds fastest.
Not every team needs a data warehouse. These are the shapes where the infrastructure investment pays back quickly.
Brands running paid + organic at scale
You can't optimize what you can't attribute. Blended CAC dashboards + server-side tracking close the loop paid teams rely on.
- €15k+ monthly paid spend
- Multiple channels
- Attribution debates in meetings
SaaS with product-led growth
Activation, retention, feature adoption, expansion. Product analytics that actually connects to revenue.
- SaaS model
- PLG motion
- Mixpanel / Amplitude sprawl
Founder / CEO needing one dashboard
North-star KPIs, weekly deltas, agent-flagged issues. One screen that answers "how are we doing?" honestly.
- Reporting chaos
- Multiple sources of truth
- Founder flying blind
Analytics lives inside your monthly unit allocation.
Typical analytics engagement: 18 units GA4 + 20 units warehouse + 12 units dashboard = 50 units over 8 weeks, then 14 units/mo ongoing. That fits comfortably in Liftoff — the tier most clients pick.
Analytics, specifically.
The questions we hear most often about this engine. Don't see yours? Ask us.
Do you work with our existing analytics stack?
Yes. We start with an audit and extend what's working. If you're on GA4 + HubSpot + Shopify, we'll add a warehouse on top, not rip and replace. We only recommend migrations when the current setup is actively breaking.
What about GDPR / CCPA consent?
Consent is built into every tagging implementation. We use consent-mode v2 for GA4, server-side forwarding respects user preferences, and we document data flows for your DPIA. No dark patterns, no gotchas.
Can you help us move off Universal Analytics data?
Yes — we export UA historical data to BigQuery for long-term comparability, then bridge with GA4 going forward. It's surprisingly common a year into GA4, because UA archives sunset.
Do I need a data team to use what you build?
No. Dashboards are designed for the end stakeholder — exec, marketing, product — not for analysts. Agents handle the alerting so you're not monitoring dashboards all day. If you have a data team, we integrate with them; if not, we are them.
How do your agents actually detect anomalies?
Statistical process control with seasonal decomposition (Prophet under the hood) plus LLM-based correlation — an agent that pulls related context when an alert fires. We test every detector on historical data before it ships, so we know the false-positive rate.
Other engines that fire well with this one.
These services share data and playbooks with Analytics — stacking them inside the same package compounds results faster than running them in silos.
Ready to fire the analytics
engine?
We'll audit your analytics setup in 5 days and give you a prioritized list of what to fix first.