Senior Product Manager, Digital

ExpressColumbus, OH
Onsite

About The Position

The Senior Product Manager, Digital will serve as the key architect of the end-to-end customer journey across Express and Bonobos, synthesizing web, mobile, and physical store touchpoints—including retail locations and Bonobos Guideshops—into a cohesive omnichannel ecosystem. Operating at the intersection of technology, data science, merchandising, and digital operations, you will define and execute the strategic roadmap for core commerce funnels, customer acquisition, loyalty platforms, and post-purchase pathways. By collaborating with Engineering, Data Science, and Marketing teams, you will leverage both traditional product management frameworks and AI-powered personalization (such as semantic search and recommendation engines) to build scalable, high-conversion features that drive customer retention, brand loyalty, and measurable growth across both brands.

Requirements

  • Bachelor’s Degree in Business, Computer Science, IT, or a related field; or equivalent practical experience.
  • 7+ years of Digital Product Management experience, with a proven track record of owning consumer-facing eCommerce products, AI/ML-powered search relevance and recommendation systems, customer checkout funnels, loyalty platforms, or digital marketing technologies.
  • Prior background working in retail eCommerce, multi-brand consumer platforms, or omnichannel environments (such as integrating physical point-of-sale systems with digital profiles) is highly preferred.
  • Demonstrated success scaling digital products from pilot to high-volume coverage, resulting in measurable customer conversion gains or transactional efficiency.
  • Mastery of data-driven decision-making, using web analytics (e.g., GA4), customer metrics (CAC, AOV, LTV), and statistical hypothesis testing (A/B testing).
  • Outstanding communication skills with a proven capacity to lead and align cross-functional teams of Software Engineers, UI/UX Designers, Data Analysts, and business stakeholders without direct reporting authority.
  • Familiarity with modern eCommerce platforms, Order Management Systems (OMS), Customer Data Platforms (CDPs), or content management system (CMS) integrations.
  • Possess a deep understanding of varied personalization strategies, including hybrid models, content-based filtering, and collaborative techniques alongside modern AI/ML methodologies.

Responsibilities

  • Establish a long-range strategy for AI-driven personalization. Manage a complex framework utilizing proprietary datasets, machine learning models, and external technology solutions to optimize customer LTV, retention, and acquisition.
  • Oversee the full lifecycle of recommendation engines across digital platforms, such as mobile apps, email, and commerce pages (Cart, PLP, PDP, and homepage). Engineer filtering and ranking logic to boost conversion rates and product visibility.
  • Drive continuous conversion rate optimization (CRO) across landing pages, product listing pages (PLPs), search discovery, and the shopping cart. Own the global checkout architecture to minimize purchase friction and increase Average Order Value (AOV).
  • Lead the product strategy for digital loyalty programs and account portals. Partner with CRM and Marketing teams to leverage marketing automation platforms (email, SMS, and push notifications) to deliver targeted customer lifecycle campaigns that increase customer retention and Lifetime Value (LTV).
  • Own the digital customer experience from order confirmation to doorstep delivery. Define the roadmap for transaction tracking, shipping alerts, order routing, and modern omnichannel fulfillment pathways like Buy Online, Pick Up In Store (BOPIS), Curbside Pickup, and Ship-to-Store.
  • Actively evaluate, pilot, and manage third-party software vendors (e.g., search engines, payment gateways, review platforms, loyalty engines, and CRM systems). Run structured RFPs and Proof of Concept (PoC) tests to balance proprietary builds against external integrations.
  • Establish a rigorous culture of experimentation. Plan, launch, and analyze systematic A/B and multivariate tests spanning acquisition pages, checkout variants, post-purchase flows, and lifecycle campaigns to validate customer value and financial return.
  • Utilize AI/ML to minimize product returns—specifically those related to fit—extending personalization beyond top-line revenue. Prioritize LTV cohorts and return reduction as core success metrics.
  • Translate complex technological initiatives and platform performance metrics into clear, executive-friendly business cases and financial metrics (CAC, LTV, Conversion, Return Rate Reduction) to align senior leadership across the Phoenix brands.
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