Senior Product Manager (User & Lifecycle Analytics)

TL;DR

Senior Product Manager (User & Lifecycle Analytics): Lead product strategy for user segmentation and lifecycle analytics, helping customers understand how different groups of users behave over time with an accent on conversion, engagement, and retention. Focus on building audience workflows, cohort/user-level analysis, and predictive lifecycle intelligence while partnering across Engineering, Product Design, data, identity, and applied AI teams.

Location: London area

Company

hirify.global builds analytics and intelligence products for understanding customer behavior.

What you will do

• Define product direction, roadmap, and success measures for user segmentation and lifecycle analytics.
• Drive customer discovery and market understanding across product analytics, customer data, marketing technology, and lifecycle/retention use cases.
• Improve segmentation and lifecycle analysis workflows, including segment creation, reuse, cohort/user-level insights, and retention analysis.
• Explore predictive intelligence such as lifecycle classification, engagement scoring, automatic segment suggestions, and conversion/retention/churn predictions.
• Partner with Engineering, Product Design, and data/identity/platform teams to deliver shared capabilities and measurable outcomes.
• Set and track product KPIs (adoption, usefulness, quality, performance, and customer value) and iterate post-launch.

Requirements

• 5+ years of product management experience in B2B software or another complex data product, owning strategy, roadmap, and measurable outcomes.
• Experience with product analytics, customer data/audience platforms, marketing technology, lifecycle/retention products, and experimentation or closely related areas.
• Practical understanding of segmentation, funnels, cohorts, conversion, engagement, and retention analysis.
• Strong customer discovery skills using qualitative feedback and product data together.
• Experience working with Engineering and Product Design on products relying on shared data, APIs, identity, or analytics services.
• Technical depth to discuss data quality, semantics, performance, and architectural trade-offs with engineers.

Culture & Benefits

• Hybrid workplace based in the London area.
• Cross-domain collaboration across Engineering, Product Design, data, identity, and applied AI teams.
• Focus on measurable customer value through KPIs and post-launch iteration.
• Equal opportunity employer; human review of hiring decisions.

Hiring process

• Application review using AI-assisted tools, with final hiring decisions made by human reviewers.