Senior Lifecycle Marketing Manager

LawnStarter is the largest on-demand marketplace for lawn care and outdoor services in the country, booking more than $100M a year. We run three brands — LawnStarter, Lawn Love, and Home Gnome — on a single shared platform, and we're expanding beyond lawn care into the rest of home services.

Our customers come to us with a problem they want solved now: the lawn needs mowing. Many of them start a signup and then stop, and what we say to them in the minutes, days, and weeks that follow is lifecycle marketing's job. At our volume, a tenth of a percentage point is real money.

The program spans three brands and roughly 1,750 unique message templates going out to customers today. It was built to convert, and it does. We've already put AI to work inside it — every SMS reply a lead sends us now routes to an AI rather than a person, and that change moved the numbers. But it's the floor, not the ceiling, and that's where you come in.

You'll own the end-to-end customer lifecycle marketing across LawnStarter, Lawn Love, and Home Gnome; driving quantifiable growth through customer acquisition, reactivation, and cross-sell expansion. Ownership encompasses the strategy, roadmap, copy, execution, and measurement of every message we send, along with the health of the transactional messages our customers depend on.

Central to your strategy is the deliberate, high-impact application of AI. You’ll decide where and how AI powers segmenting, copywriting, and campaign execution to scale output and amplify overall ROI.

One of our core values is AI or Extinction: every task, AI-first, no exceptions and no excuses. We mean that literally, and this is the role where we expect it to show most clearly. We're not looking for someone who drafts a little faster with a chatbot. We're looking for someone who changes what lifecycle marketing is capable of doing:

• Personalization at a grain no person can reach - Writing and personalizing for segments too small to manually create, and then testing at that size.
• Conversations rather than sends - Our inbound SMS for leads already routes to an AI, and you'll take that further into the lifecycle.
• Tests we wouldn't have thought of - Using models to find the segment, shape the hypothesis, and interpret the result.
• Agents that handle the build - Assembling canvases, checking them against our rules, and catching a broken message before a customer ever sees it.
• Monitoring that runs without you - Roughly 400 transactional messages fire 63,000 times a day, and no person can eyeball that. You'll put AI on the send data so a message that arrives late, sends twice, or contradicts another channel gets caught and diagnosed on its own — and where it's safe to do so, corrected before a support ticket tells us about it.
• Ideas that aren't on this list - We expect you to arrive with approaches we haven't considered, and if the tooling shifts six months from now, we expect to hear about it from you first.

Whoever takes this role should end up being the person the rest of us come to when we want to work this way. If you've been the most advanced AI user everywhere you've worked, this is a job where that really counts for something.

We'll ask you to show this work, so come prepared to walk us through what you've built and what it did.

• You do the work yourself - There's no agency and no contractor pool. You write the message, build it in Braze, send it, and read the results.
• The program already works - You're not starting from nothing, and you're not cleaning up after someone else. You're taking something that already performs and making it considerably better.
• You’ll implement brand strategy - None of our three brands has a written voice or design standard applied to its messaging, which leaves roughly 1,750 messages waiting to be rewritten and redesigned (AI first). You’ll partner with the brand team to create the look and feel for three distinct brands.

How we use AI

What gets automated, what gets personalized, what an agent handles, and what stays human. You set that direction and then build it. We've tested the lead drip hard for two years and the easy gains are spent — what's left is personalization and segmentation at a level of detail no person can produce by hand, which makes it an AI problem, and nobody here has cracked it. This is the single biggest reason the role exists.

Strategy and roadmap

The full customer journey across all three brands, covering lead conversion, onboarding, retention, and winback. You decide what gets built and in what order. Most of our testing energy has gone to the start of the funnel, so retention and winback messaging is comparatively thin — even though a customer we keep is worth considerably more than a lead we convert. That's the clearest open opportunity in the program.

Every message, and the words in it

Email, SMS, in-app, and push: who gets it, what triggers it, when it lands, how often it repeats, and whether it's right before it goes out the door. You write the copy yourself, and what you write is what customers read.

The brand build

Roughly 1,750 message templates grew one message and one test at a time, each built to convert, but no voice or design standard was ever applied because none was ever written. You'll partner with the brand team to write those standards, then work them into every message across all three brands — sequenced, tracked, and shipped as a program. The writing isn't the hard part. The hard part is absorbing that much work while the program keeps running, and having the discipline to leave the messages that already win alone.

Transactional health

Roughly 400 messages go out about 63,000 times a day, telling customers their Pro is on the way, the work is finished, their payment failed, or their Pro has changed. They're the messages we send most often and the ones customers trust most, and nineteen of those journeys fire across email, SMS, and push simultaneously. When one arrives late, says the wrong thing, sends twice, or contradicts what another channel said an hour earlier, the customer notices before we do. You'll build the monitoring that catches it and stay with engineering and support until it's actually fixed.

Measurement, and what counts as a result

The testing roadmap, the analysis behind it, and the call on what becomes the new control. You set the bar for significance and you hold the line on it, including when the answer is that your own idea lost.

The boundary with CRO

They own what happens on the page; you own what happens in the message. Where the two meet — a quote abandoned on-site, a price that surprised someone — you'll work it out together.

• AI is doing work we couldn't do before — more than one capability in production, each handling something no person here could have done by hand, and each with a number attached to it
• Conversion is up— more leads become customers in the window you own, and the tests demonstrate it
• Retention has moved— a winback and retention program tested as rigorously as the lead drip is today, with impact you can point to
• Test velocity is considerably higher — many more tests each quarter than we run now, held to the same standard for what counts as a result
• Transactional problems get caught, not reported — you learn a message has broken from your own tracking rather than from a support ticket, and there's a record of what broke and what you did about it
• Every message carries the brand — all three brands rewritten and redesigned, with conversion performance held

You build with AI, and you push it further than the people around you.

You use it daily and you build with it rather than simply querying it.You've built something that runs when you're not sitting there, and you know exactly how it fails. You read what's new every week and try it the same week, and when a tool can't do what you need, you find your way around it. This is unlikely to be a good fit if your AI use amounts to drafting emails and summarizing documents.

You start from what the customer is feeling.

Someone who abandoned a quote because the price surprised them needs a different message than someone who's been waiting three days for a Pro to show up. You work from what the person is thinking, then decide what the message has to do about it. AI will write you a hundred variants and a test will tell you which one won, but neither one tells you which hundred were worth writing. This is unlikely to be a good fit if you reach for the tactic before the motivation, or if you'd rather test your way to an answer than form a view about the person first.

You write, and you read the numbers.

You'll draft the SMS and interpret the significance test on it, because both belong to you and you're genuinely good at both. This is unlikely to be a good fit if you write well but hand off the analysis, or analyze well but hand off the words.

You work in the tool.

You'll be in Braze building the canvas rather than reviewing someone else's. This is unlikely to be a good fit if you've spent your career directing an agency and would find the build work beneath you.

You change your mind when the data tells you to.

You hold strong hypotheses and give them up quickly, and you say so out loud when you were wrong. This is unlikely to be a good fit if you need to be right, or if you import practices from another company without testing whether they apply here.

You chase down errors.

When a customer reports getting the wrong message, you'll follow it back through the canvas, the event, and the data until you find where it broke, and then stay with engineering until it's actually fixed. This is unlikely to be a good fit if you regard debugging as beneath the strategy work, or if you'd rather build the next campaign than understand why the last one misfired.

• A place to learn AI on the job - We need someone already working this way who has results to show for it. If you're curious but early, this isn't the role.
• A management role - No direct reports and no agency to direct. If your next step is leading a team, this isn't it.
• Brand strategy - You'll apply each brand's voice across every message, but you won't decide what that voice is or write the guidelines, and you'll be judged on conversion and retention rather than on creative. If you want to own the brand, you'll be frustrated here.
• An execution-only role - Nobody hands you the roadmap. You decide what to test and what to build, then defend it with results.
• Demand generation - Lead volume and lead quality belong to paid acquisition, and you own what happens after the lead arrives. If you want the top of the funnel, that's a different job.
• Pro lifecycle - This is the customer side; another team handles the roadmap, strategy, and copy for Pros, although you’ll partner to handle the execution.

• Base salary: $120k-$150k
• Equity: Conversion and retention determine a good part of what this company is worth, so you should own a piece of it.
• Healthcare: Medical, dental, and vision
• Fully remote (US): Writing well and reading tests carefully both take uninterrupted time, so we trust you to work where you work best.
• Flexible PTO: We judge results.

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.