Owning a CRO program
Hotjar → Optimizely testing loop across 10+ builds → 35% lift in inbound leads, with release QA and consent checks before anything ships.
Overview
Built and ran a structured CRO program across 10+ lead-generation web properties, using behavioral analytics to inform hypotheses and a disciplined testing loop to validate changes.
Problem
Web properties were being redesigned based on opinion rather than data. No systematic testing existed, and changes shipped without QA or consent compliance checks.
Constraints
- Must work across 10+ independently managed web properties
- Changes must pass release QA and consent checks before shipping
- Testing velocity must not compromise site stability or user experience
Approach
Established a Hotjar-to-Optimizely pipeline: behavioral analytics surface opportunities, structured A/B tests validate hypotheses, and a release process ensures QA and consent compliance before anything goes live.
Key Decisions
Gate every test behind release QA and consent checks
CRO velocity means nothing if a test breaks the site or violates consent requirements. The gate adds a day but prevents costly rollbacks and compliance issues.
- Ship tests immediately with post-launch monitoring
- QA only high-risk tests
Centralize the testing loop across all properties
A single methodology and toolset across 10+ properties enables cross-property learning and prevents teams from running conflicting tests.
Tech Stack
- Hotjar
- Optimizely
- GA4
- Google Tag Manager
- Consent Mode v2
Result & Impact
- 35% liftInbound leads
- 10+Properties instrumented
Shifted web optimization from opinion-driven redesigns to a data-driven testing culture. Every change now has a measurable hypothesis and documented outcome.
Learnings
- The testing loop matters more than any single test — process discipline compounds
- Consent checks belong in the release process, not as an afterthought
Full case study in progress.