Services/Experimentation & Learning Loops
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Experimentation & Learning Loops

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Design and run a structured experimentation programme that accelerates learning, reduces risk and compounds performance over time.

The scealy Acquisition System
Part of our integrated acquisition architecture: strategy, media, creative and data as one system.
Strategic overview

What this service actually does

Experimentation is the most defensible competitive advantage in performance marketing. Companies that test more, learn faster. They compound those learnings into a performance lead that's very hard to close. We build the infrastructure and culture for systematic experimentation.

Most experimentation programmes fail because they run too few tests, test the wrong variables, or fail to document and apply learnings. We build programmes that are high-velocity, well-documented and connected to business outcomes.

Areas of focus

What we actually work on

We establish an experimentation framework: hypothesis format, test prioritisation scoring, statistical significance thresholds, and a shared learnings library. We run tests across landing pages, ad creative, email sequences and onboarding flows.

Learnings are documented and made accessible to your whole team, so insights from one test inform the next, and your organisation accumulates a growing body of knowledge about what works for your specific audience and market.

How we work

Our process, step by step

01

Infrastructure Setup

We implement your experimentation stack: testing tool configuration, event tracking, statistical framework and documentation templates.

02

Backlog Build

We conduct a full-funnel opportunity review and build a 90-day experiment backlog, prioritised by impact potential and feasibility.

03

Test Execution

Experiments run with controlled variables, defined success metrics and statistical significance thresholds. Clean, actionable results every time.

04

Learnings Integration

Every experiment is documented in your shared learnings library: insights searchable, accessible and applicable to future decisions.

"We ran experiments before, but we never learned from them. Every quarter we'd basically start over. scealy built a proper programme: hypothesis format, statistical thresholds, a shared learnings database. Eighteen months later we have 80+ documented insights and our A/B test win rate has more than doubled because we're testing smarter hypotheses."
D
Daniel R.
Growth Lead, SaaS Platform, €25M ARR
What you get

Key deliverables

Every engagement includes a defined scope with concrete outputs, not vague ongoing "management" with no deliverable accountability.

Experimentation platform configuration (Optimizely, VWO, or native)
Experiment hypothesis framework and prioritisation model
90-day experiment backlog with ranked priority
Statistical significance framework and decision rules
Shared learnings library (searchable, team-accessible)
Monthly experimentation velocity report
Capabilities covered
Experiment DesignHypothesis FrameworkStatistical RigourLearnings LibraryMulti-Channel TestingVelocity Optimisation
FAQ

Common questions

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Ready to start with Experimentation & Learning Loops?

Book a free strategy call. We'll scope the engagement, define expected outcomes, and tell you honestly if it's the right fit.

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