Director of Conversion Rate Optimization

Role Overview

• You are the conversion performance engine for LawnStarter. You own the landing pages in Webflow, build and run A/B tests in VWO, and use AI, Tableau and Hotjar to find the next thing to test.
• You report to the CMO and are the primary executor moving the visit-to-customer rate — the metric that matters most for growth.
• This is not a strategy-and-slides role. You build variations yourself, configure goals yourself, debug tracking yourself, and ship yourself. You have no engineering support and you don't need it. Your Webflow and VWO skills are production-grade.
• Today this is a solo operator role. The expectation is that you build the program, prove the value, and design the function that scales it.
• Conversion performance — visitor-to-lead (landing pages you control directly) and lead-to-customer (booking funnel you optimize via testing). These two levers compound into the visit-to-customer rate.
• Webflow and landing page architecture — paid landing pages, thousands of organic city/near-me pages across all brands and services, and the CMS structure that makes them scalable without engineering. You own conversion optimization across the entire landing page surface area.
• The experimentation program — a multi-quarter testing roadmap for the acquisition funnel, from ad click to first completed service. You build the methodology, run the tests, and feed learnings back into the next cycle.
• AI-accelerated testing workflow — use AI for hypothesis generation from behavioral data, result summaries within 24 hours of test completion, and variation copy/design briefs that increase test throughput.
• The experimentation function model — by end of Year 1, you've documented the team structure, tooling stack, and processes needed to scale from solo operator to a repeatable function.

Requirements

• Lives in Webflow. You spend most of your time building pages, not reading reports. Webflow is your production environment, not a design tool. You find friction through screen recordings, customer calls, and sales emails — then you ship the fix yourself.
• Statistically sharp. We currently use two-tailed p-tests and build our own Tableau dashboards to call tests. You should have a point of view on when that's the right approach and when it's not. One of your first contributions will be documenting methodology standards for the team.
• AI-native. You use AI for hypothesis generation, variation copy, and analysis acceleration — every day, not occasionally. If you describe AI as something you're "exploring," this isn't the role.
• Ships fast. You measure weeks in tests launched and learnings captured, not decks delivered. You'd rather run the test and learn than plan it perfectly.
• Gets the stats right. You catch underpowered tests, peeking, and interaction effects. You know when NOT to test. You can explain results to a non-technical stakeholder without losing them.
• This Role Is NOT
• A strategy role. You will set strategy, but you also build the pages, configure the tests, and pull the data. If you want to think about experimentation without doing it, this isn't the role.
• A people management role (yet). This starts as a solo operator. You'll design the function and make the case for headcount, but Year 1 is about proving the model yourself.
• An engineering-supported role. There is no frontend dev building your variations. There is no data engineer setting up your tracking. You are the implementation layer.

Tech Stack

• Tableau

Benefits

• Competitive salary of $160,000-$180,000
• Equity: Every point of conversion improvement flows directly to revenue across all brands. We want you invested in the long-term outcome of the experimentation program you're building.
• Healthcare: Medical, dental, and vision
• Fully remote: Work from anywhere in the US
• Unlimited PTO: Focused on outcomes