What you'll do
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Own the activation & retention strategy across the B2C funnel (signup, onboarding, first value, recurring value winback).
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Run high-velocity experiments: define hypotheses, success metrics, guardrails; design variants; coordinate builds; analyze results; document learnings.
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Instrument the journey with a clear event taxonomy; ensure dashboards/funnels/cohorts are trustworthy and actionable.
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Translate Userback insights into action: triage, tag, and synthesize qualitative feedback; validate with quant; turn into clear problem statements and specs.
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Optimize onboarding & habit loops: progressive disclosure, checklists, templates, nudges, education, and lifecycle messaging.
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Reduce churn: identify drop-off drivers; ship reactive and preventive retention tactics (e.g., in-app prompts, saveoffers, reactivation flows).
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Partner cross-functionally with Eng/Design/Data/Marketing/Support to deliver experiments and durable features end-to-end.
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Communicate openly: weekly growth reviews, experiment pipeline, post-launch readouts, and roadmap updates.
Outcomes you'll drive (KPIs)
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Activation: +X% D1/D7 activation; +X% onboarding completion; reduced time to first value.
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Retention: +X% W1/W4/M3 retention; X% churn; +X% reactivation of dormant users.
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Experimentation: X experiments/month with robust analysis and decisioning within X days; shared learnings library.
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Quality of insight: 100% of priority features backed by a combination of Userback qualitative synthesis and quantitative evidence.
Qualifications
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48+ years PM experience with growth/PLG in a B2C product; a track record moving activation and retention via in-product changes.
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Strong analytical toolkit (funnels, cohorts, retention curves, survivorship, power & sample size basics); comfortable with SQL/Excel.
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Hands-on with modern analytics/experimentation stacks (e.g., Amplitude/Mixpanel/GA4 or equivalent).
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Experience operationalizing qualitative feedback (Userback or similar) into problem statements, hypotheses, and specs.
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Excellent product sense and UX instincts; crisp communication; bias to action and iteration.
Nice to have
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Mobile app growth (iOS/Android) and app store conversion/retention tactics.
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Pricing/packaging, trials/freemium, and paywall/plan upgrade experience.
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Personalization/targeting (rules-based or MLassisted) for lifecycle and in-product nudges.
How you'll work
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Experiment operating model: hypothesis design, build/flag QA launch, analyze, decide, document scale/retire.
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Evidence standards: preregistered success metrics & guardrails; minimal detectable effect; power checks; counter metrics for UX/engagement.
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Backlog hygiene: ideas scored by impact × confidence × effort; weekly grooming; monthly prioritization tied to KPI gaps.
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Userback loop: tagging taxonomy, monthly synthesis reports, and Voice of Customer snapshots in growth reviews.