Digital Adoption & Lifecycle Manager

Overview

Own Mixpanel's customer lifecycle communications program across onboarding, adoption, retention and expansion, with digital-only customers as the primary test of whether the programs work.

What you'll do

• Build the lifecycle communication program end-to-end across onboarding, adoption, retention, and expansion, from strategy through copy, build, launch, and iteration
• Create programs that serve the full customer base while working hardest for digital-only customers, and decide where messaging should differ for accounts with a dedicated team
• Design behavior-based segmentation using product usage, health signals, lifecycle stage, and account attributes; define the triggers that decide who hears from us and when
• Write clear, useful customer-facing copy across email, in-product messaging, and other digital channels that reflects Mixpanel's voice and gives customers a reason to act
• Build and ship campaigns in tools like Customer.io, HubSpot, and Statisfy, including the audience logic, templates, and QA that keep them reliable
• Partner with Marketing on the shared email calendar, coordinating timing, frequency, and audience overlap so customers get a coherent experience
• Support product-led adoption initiatives by translating launches and feature pushes into lifecycle moments that get customers to try the thing, and report back on whether they did
• Keep the library of lifecycle messaging current as the product changes, retiring what's stale and rewriting what no longer matches reality
• Define success metrics for every program, instrument them in Mixpanel, and run a regular reporting cadence on engagement, adoption lift, and downstream retention and expansion impact
• Run experiments on subject lines, timing, sequencing, channel mix, and audience definition, and kill what doesn't work
• Work with customer-facing teams to learn what resonates in conversations, translate it into programs that reach customers without proactive account teams, and make sure digital touches complement rather than collide with human ones
• Pilot agentic approaches to scaled customer success, where an AI agent can personalize a touchpoint, surface the right next action, or handle a customer interaction end-to-end, and develop a point of view on what should be automated, what should stay human, and how to tell the difference
• Identify gaps in data, tooling, and process, and propose what to fix first

What you'll need

• Experience in customer lifecycle communications, ideally in B2B SaaS, focused on post-sale adoption, retention, and expansion rather than demand generation or pre-sales
• An excellent writer who can be concise, specific, and useful to a technical audience
• Hands-on with lifecycle and marketing automation platforms (Customer.io, HubSpot, Braze, Iterable, or similar); builds campaigns yourself rather than handing off a brief
• Fluent in product analytics (Mixpanel or similar) and comfortable pulling your own data to define segments and measure results
• Familiar with customer success platforms (Statisfy, Gainsight, Totango, or similar) and how health signals and customer data feed scaled programming
• Strong at segmentation: able to reason about cohorts, behavioral triggers, and audience overlap, and knows when a segment is too small to matter
• Data-driven in practice: forms a hypothesis, measures the result, and changes course based on what the data says
• Comfortable being measured on business outcomes, not open rates alone; has directly contributed to metrics like GRR, NRR, activation rate, and time to first value
• Genuinely collaborative: has coordinated a shared calendar with Marketing, taken input from customer-facing teams, and supported someone else's launch without needing it to be their project
• Experience working alongside customer-facing teams and comfortable earning their trust when programs touch their customers
• Able to drive projects forward independently across teams, with the judgment to prioritize, make tradeoffs, and keep things moving without a defined playbook
• Comfortable with ambiguity and energized by building from the ground up
• Actively experimenting with agentic customer success, with a point of view on where AI agents can take real action in the customer lifecycle and what is and isn't ready
• Uses AI purposefully day-to-day: drafting and iterating on copy, analyzing campaign performance, scaling research and segmentation work

Nice to have

• Experience launching a scaled or digital customer success program at a company that didn't have one before
• Experience serving a long-tail or self-serve customer base where digital is the only channel, alongside segments that have dedicated account teams
• Experience with in-product messaging tools and lifecycle orchestration beyond email
• Hands-on experience deploying an AI agent into a real customer-facing workflow, at any scale, including ones that didn't work

Details

• Location: San Francisco, US (Remote)
• Compensation range: $132,000 to $162,750 USD (total target cash compensation), plus equity consideration and benefits