HAVE YOUR DATA ready for experimentation IN DAYS
Experimentation Data Foundation
A structured data layer built on top of your existing experimentation stack — making every experiment measurable, comparable, and defensible. Three engagement tiers depending on where you are: diagnose what’s broken, build the foundation, or scale a full data system across teams.
Who This Is For
Results Are Disputed
You’re running experiments but results are disputed or quietly ignored.
Metrics Don’t Match
Metrics don’t match across your CRO tool, analytics platform, and warehouse.
Lifts Can’t Be Tied to Revenue
You can’t tie experiment lifts to revenue or downstream KPIs.
Want to Scale Experimentation
You want to scale experimentation across teams but the data foundation isn’t there yet.
Need a Data Partner
Your CRO agency or in-house team needs a data partner, not another tool.
Scope of Work
Three engagement tiers — pick based on where you are and what you need.
Experimentation Data Audit
- Tracking and event audit across every tool
- Metric and attribution review
- Tool stack assessment
- Prioritised fix-list and roadmap delivery + readout session
Audit + Setup
- Everything in Tier 1
- Re-implemented tracking plan and aligned metrics across tools
- Attribution and revenue deep-dives (acquisition + retention)
- Experiment QA framework
- Dashboard view (10 data use cases across 2 teams)
Full Experimentation Data System
- Everything in Tier 2, ongoing
- Per-experiment QA and validation
- Weekly and monthly insight reviews and QBRs
- KPI standardisation across teams (20 KPIs, 2 dashboards, 3 monthly deep-dives)
- Data warehouse and modelling support
- Expert lens from practitioners at Booking.com, Adidas, Make.com, and more
Project Outcomes
- A validated data layer your whole experimentation team can trust
- Metrics aligned across your CRO tool, analytics platform, and warehouse
- Experiment lifts tied to revenue and downstream KPIs — not just p-values
- Stakeholder-ready dashboards in business language: revenue, margin, payback
- Cross-test learnings that compound over time
- A data foundation that scales as your programme grows
Roadmap
Clear timelines for each tier — from a 2-week audit to a 6-month data system build.
Experimentation Data Audit
- Week 1: Kickoff, tool access, current experiment history review
- Weeks 1–3: Full audit — tracking, metrics, attribution, tool stack
- Weeks 3–5: Prioritised fix-list and roadmap delivery + readout session
Audit + Setup
- Weeks 1–3: Full audit (same as Tier 1)
- Weeks 3–6: Implementation — tracking plan, KPI alignment, integrations
- Weeks 6–8: Dashboard build, experiment QA framework, team enablement + delivery session
Full Data System
- Month 1: KPI definition across teams, data mapping, architecture blueprint
- Months 2–4: Implementation, integration testing, Dashboard 1 + Analysis 1 & 2
- Months 5–6: Dashboard 2, Analysis 3, data cleaning, AI-ready data model
- Ongoing: Weekly insight reviews, QBRs, per-experiment QA, continuous support
FAQs
No — we plug in on top of whatever you already use. VWO, Optimizely, AB Tasty, Convert, Kameleoon, Statsig — we work with all of them. No migration, no political battle.
If you’re not sure whether your data is trustworthy, start with Tier 1. If you already know what’s broken and need it fixed, start with Tier 2. If you need a full data system built across teams on an ongoing basis, that’s Tier 3.
Yes — every engagement can be delivered white-labelled to your spec. If you’re a CRO agency or consultant referring clients, ask us about our partner programme.
That’s fine for Tiers 1 and 2. For Tier 3, we can recommend and support the right warehouse setup as part of the engagement.
Everything — tracking plans, dashboards, documentation — is yours. We never retain ownership of any work product.