Lifecycle Marketer, Self-Serve
London, StockholmFull-timePosted 3mo ago
About the role
Lifecycle Marketer responsible for executing Lovable’s lifecycle marketing for the self-serve base—activation, engagement, retention, and reactivation. AI-first, data-driven, and focused on personalized, timely messaging across channels.
Responsibilities
- Operate lifecycle marketing for the self-serve base across activation, engagement, retention, and reactivation.
- Lifecycle PoC for product launches, experiments, and GTM moments
- Design intelligent, rules-based or algorithmic lifecycle programs that dynamically decide who to message, when to reach them, which channel to use (email, inbox, push, and emerging CRM channels), and what content to send, based on behavior and context
- Work AI-first across your entire workflow, applying AI and automation to content generation, personalization, segmentation, decisioning, and analysis
- Build experimentation and data-driven optimization into every lifecycle program, measuring true incremental impact rather than surface-level engagement
- Partner closely with Data, Product, and GTM teams so lifecycle messaging feels native, timely, and valuable
Qualifications
- 5+ years in B2C lifecycle, CRM, or growth marketing at consumer or PLG scale
- 3+ years of deep, hands-on expertise with a modern lifecycle marketing platform like Braze, Iterable, or Customer.io
- Fluency in Liquid templating and email HTML/CSS, segmentation logic, and event-driven campaign architecture, experience with CDPs, event pipelines (e.g., RudderStack) and SQL for self-serve analysis
- Experience building adaptive, evolving lifecycle systems, not just static journeys
- Hands-on experience applying AI and automation to content creation, personalization, segmentation, and decisioning logic
- Comfort operating in ambiguity and designing systems that improve over time
- Content craftsmanship to ensure content going out always builds on Lovable’s brand
Skills
Required:Lifecycle marketing platformsLiquid templatingEmail HTML/CSSData collaboration
Last updated Sep 9, 2026. Interested? Apply on the company site.
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