85+
Experiments coordinated
85+ A/B experiments coordinated — zero production incidents
Owned end-to-end delivery coordination for 85+ A/B experiments — intake, sequencing, monitoring, and rollout on revenue-critical flows.
85+ experiments coordinated end-to-end
Zero significant production incidents from experiment conflicts
Consistent experiment throughput across 4+ markets
Winning-variant deployments reduced from multi-week lag to within-sprint execution
Reusable experiment intake and rollout system adopted across teams
Executive Summary
LawDepot's experimentation program sits at the center of its monetization and product strategy. With 85+ experiments running across markets, the coordination surface — hypothesis alignment, market sequencing, QA sign-off, variant deployment, and rollout decisions — was high-risk if unmanaged.
I owned the full experiment lifecycle: intake through teardown. This included aligning on success metrics before experiments launched, sequencing rollouts to minimize market interference, and coordinating the cross-functional review required for winning-variant deployment.
Outcome: consistent throughput across 85+ experiments, no significant production incidents from experiment conflicts, and a repeatable delivery system other teams could run against.
Business Context
Experimentation is LawDepot's primary mechanism for improving conversion and revenue across checkout, subscription, and pricing flows. The multi-market platform means experiment rollouts must be sequenced carefully to avoid market interference. Each experiment has a revenue hypothesis attached — failed coordination means lost learning signal and delayed revenue decisions.
Problem & Constraints
- Experiments ran across markets with different traffic volumes and product configurations
- Engineering capacity for experiment setup and teardown competed with feature delivery
- Stakeholders (Product, Marketing, Revenue) had different definitions of experiment success
- Some experiments had interdependencies that could corrupt results if poorly sequenced
- Winning-variant deployments required QA re-validation before production rollout
My Role & Ownership
I coordinated the end-to-end experiment lifecycle across Product, Engineering, QA, and Revenue stakeholders — intake, sequencing, monitoring, and rollout decisions.
What I owned
- Experiment intake process: hypothesis review, success metric definition, market scope
- Rollout sequencing to prevent experiment interference across markets
- Cross-functional sign-off coordination for winning-variant deployments
- Teardown scheduling and variant cleanup tracking
- Experiment status visibility across Product, Engineering, and Revenue teams
- Delivery cadence for new experiment setups and active monitoring
Not in my scope
- —Statistical analysis and experiment result interpretation (Analytics team)
- —Hypothesis generation and business prioritization (Product team)
- —Engineering implementation of experiment variants (Engineering)
- —Revenue and conversion rate targets (Revenue/Marketing)
Key Decisions
- 01
Established success metrics and market scope at intake — before Engineering picked up the ticket — eliminating mid-experiment goal-post shifts that had caused rework.
- 02
Built a market sequencing protocol to prevent overlapping experiments from corrupting results; reduced statistical noise on high-stakes tests.
- 03
Created a "teardown first" rule: no new experiment could launch in a market until the previous one was fully removed from that market.
- 04
Standardized the winning-variant deployment checklist with QA, so rollout decisions could happen within a sprint rather than blocking for weeks.
- 05
Introduced an experiment status board visible to all stakeholders, removing repeated status-update requests from Engineering.
Actions Taken
Designed and owned the experiment intake form capturing hypothesis, success metric, market scope, and engineering estimate.
Built and maintained the experiment pipeline: from intake queue through active, analysis, and teardown stages.
Ran weekly cross-functional experiment review with Product, Engineering, and QA — decision log shared after each session.
Sequenced experiment launches by market to prevent interference; maintained a live conflict map for active experiments.
Coordinated winning-variant deployments: QA re-validation, Engineering rollout plan, stakeholder sign-off.
Tracked and reported on experiment throughput, active count, and teardown backlog each sprint.
Delivery System & Process Improvements
- Experiment intake form and market sequencing protocol became standard practice
- Winning-variant deployment checklist adopted by QA as standing process
- Experiment status board replaced recurring status-update meetings
Key takeaway
Guardrails at intake and a sequencing protocol at rollout are what make 85+ experiments deliverable without production incidents. Most coordination problems in experimentation are visibility problems in disguise.