LawnStarter is the nation's leading on-demand marketplace for lawn care and outdoor services, with $100M+ in annual bookings across three brands. We connect homeowners with vetted local Pros for everything from weekly mowing to landscaping, pool care, and beyond.
The Growth team owns customer acquisition, the engine that powers everything else. We're responsible for bringing in 150,000+ new customers per year across Google Ads, Bing, and organic channels. Paid search is our largest and most complex channel, spanning three brands (LawnStarter, Lawn Love, Home Gnome) across hundreds of local markets with intense seasonality. Core mowing is the heart of the business, and Responsive Search Ads and Dynamic Search Ads are the workhorses that drive it.
You'll own paid search strategy and execution across our entire portfolio. This is an IC role; you're not managing people, you're managing millions in ad spend. You'll work directly in the accounts daily while also thinking strategically about how to scale efficiently.
What makes this role different:
RSA creative testing at scale We run three brands across 200+ local markets, which means hundreds of ad groups each needing relevant, high-performing RSA creative. How do you build a testing framework that surfaces what actually moves the needle—without drowning in variations?
DSA coverage and quality Dynamic Search Ads can unlock long-tail coverage we'd never build manually, but DSA quality depends on page structure and content. How do you audit coverage gaps, suppress irrelevant queries, and make DSA a reliable driver rather than a leaky bucket?
Multi-brand positioning without cannibalization We have three brands bidding in overlapping markets. When should they compete? When should one brand own a market? How do you allocate budget across brands when they're all trying to grow?
Navigating extreme seasonality Demand drops 80% in winter and spikes in spring. Getting the timing right on spend ramps, pausing markets, and reactivation campaigns is the difference between hitting targets and missing them.
Proving incrementality Not all conversions are created equal. Some would have happened anyway. How do you measure true incrementality and shift spend toward campaigns that actually drive new customers?
AI-native. You use AI tools to move faster, whether that's generating ad copy variations, analyzing keyword data, writing scripts, or automating reporting. You're experimenting with AI-powered bidding and creative tools. This is unlikely to be a good fit if you're skeptical of AI or prefer doing everything manually.
Deep in the data. You're happiest inside Google Ads, spreadsheets, and dashboards. You spot patterns others miss and make decisions based on evidence, not intuition. This is unlikely to be a good fit if you prefer high-level strategy without getting into the numbers.
Systems thinker. You don't just optimize individual campaigns; you think about how campaigns interact, how to structure accounts for scale, and how to build processes that don't break as complexity grows. This is unlikely to be a good fit if you prefer ad-hoc optimization over systematic approaches.
Comfortable with ambiguity. You'll often make decisions with incomplete data. You know when to analyze more and when to just run a test. This is unlikely to be a good fit if you need certainty before taking action.
Strong communicator. You can explain what's working and why to people who don't live in Google Ads. You write clear reports, flag risks early, and advocate for your recommendations. This is unlikely to be a good fit if you struggle to translate technical details for non-specialists.
Conversion-tracking fluent. You understand how event tracking, tag management, and attribution models actually work — not just how to read the report, but how to QA the implementation, spot broken conversion loops, and correct data before it corrupts smart bidding. This is unlikely to be a good fit if you rely entirely on platform-reported numbers without questioning whether they're right.
Bias for action. You'd rather launch a test and learn than debate hypotheticals. You ship fast, measure, and iterate. This is unlikely to be a good fit if you need extensive approval processes or prefer lengthy planning cycles.
LawnStarter provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics. We comply with applicable state and local laws governing nondiscrimination in employment.
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