Match the tier to where the client is.
Every engagement is delivered by Adasight, white-labelled to your spec if you prefer. Pick by what the client needs, not by what they say.
Diagnose
from €5,500 to €10,500 mo
A full audit of metric alignment, tracking accuracy, and attribution logic across every tool.
→ See what's broken — and where the leverage actually lives.
- →Tracking & event audit
- →Metric & attribution review
- →Tool stack assessment
- →Prioritized fix-list & roadmap
"We know what's broken — and how to fix it."
Diagnose + Build
from €7,500 to €20,000
Audit plus support on implementation of changes — tools set up, KPIs defined (5 data use cases), 1 dashboards live, team enabled.
→ Make the analysis observable — leadership and product on shared numbers.
- →Re-implemented tracking plan
- →Aligned metrics across tools
- →Attribution & revenue logic
- →Experiment QA framework
- →Documentation & handover
"We trust our experiment results and act on them."
Full Data System for Experimentation & Growth
from €5,500 to €10,500 mo
Scalable experimentation data system across teams — 15 KPIs, 2 dashboards, 3 deep-dives monthly.
→ Make the analysis operable — a continuous detect → analyze → test loop.
- →Per-experiment QA & validation
- →Monthly deep insight reviews for hypothesis
- →KPI standardization across teams
- →Data warehouse / modeling support
- →Embedded with your CRO partner and team of experts from Booking.com, Make.com, Sony, Careem and many more
"Experimentation drives company-wide decisions."
We don't write or touch your production code. We hand your engineering team a clear implementation spec — event schemas, tracking plans, KPI definitions, dashboard logic — and review their work end-to-end.
What we do build: tracking plans, data models in your warehouse (SQL / dbt), dashboards (Looker / BI), and the QA framework that validates every release.
What we don't do: ship code to your app or website, run your A/B test platform day-to-day, or replace your engineers. We make their work trustworthy — not redundant.
Pick by your data foundation, not your test count.
Tools disagree on revenue. No event spec. Tracking was set up once and never revisited.
Tracking exists but results aren't trusted. No shared KPIs. Dashboards are bespoke pulls.
Warehouse in place. Experiments running across teams. But no continuous detect → analyze → test loop.
Not sure? A 30-min partner call places the client in the right tier.
When clients say things like this — call us.
"We don't trust experiment results."
"Tools show different numbers."
"Tracking is unclear or broken."
"We can't connect experiments to revenue."
Tool-agnostic. Stack-fluent.
We plug into the stack you already run — no rip-and-replace. These are the tools we instrument, align, and validate against day-to-day.
Don't see your stack? We've probably worked with it.
The questions clients keep coming back to.
Same framework, different angle. Once the data layer is in place, these analyses re-run on demand instead of becoming bespoke projects.