Skip to content

    AI Product Manager for Ecommerce

    Ecommerce products live and die by conversion, retention, and operational execution. I help ecommerce teams ship product improvements that move the metrics that matter — conversion rate, AOV, repeat purchase, and CAC payback — as a fractional AI PM who understands the full funnel from acquisition through fulfilment.

    Why ecommerce products need an AI PM focused on the full funnel

    Most ecommerce product teams are either too close to the conversion funnel (optimising checkout while ignoring discovery and retention) or too far from operations (shipping product features that the fulfilment chain cannot support). The result is a product that converts at 2% when it should be at 4%, and an ops team that spends half its time firefighting product-generated exceptions.

    I take a whole-funnel view: from search and discovery through to post-purchase experience and repeat purchase mechanics, with explicit alignment to inventory, ops, and logistics constraints. And I layer AI-powered personalisation and automation on top of that foundation to compound the conversion gains over time.

    $20M+

    Revenue influenced across product launches

    1B+

    Impressions generated through product and growth execution

    12+

    Products launched from 0→1 across multiple sectors

    How I help ecommerce teams as your AI PM / PO

    • Conversion funnel audit and A/B test roadmap: diagnosing drop-off, prioritising interventions, and building a structured experimentation programme
    • Cart abandonment reduction: checkout friction removal, guest-first flows, and AI-powered recovery sequence design
    • Product discovery and search optimisation: AI-driven search ranking, faceted navigation, and personalised merchandising
    • Ops and inventory alignment: building product features that reflect real fulfilment constraints and turn ops data into conversion signals
    • Personalisation at scale: sequenced roadmap from rules-based targeting through ML recommendations and LLM-powered product discovery

    Engagement models

    Flexible structures for ecommerce companies at every scale — from DTC brands looking to break through a conversion plateau to enterprise retailers rebuilding their product and personalisation capability.

    Fractional PM/POConversion audit sprintPersonalisation roadmapAI search & discovery

    FAQs

    How do you diagnose and fix conversion rate problems in an ecommerce product?

    Conversion problems are almost never caused by a single thing — they are the accumulated effect of friction across the funnel. I start with a structured funnel audit: mapping the drop-off rate at each step from landing to purchase, segmenting by acquisition source, device type, and user cohort to isolate where the problem is concentrated. I then run heuristic UX reviews of the highest-impact drop-off points and design a prioritised A/B test roadmap. The test hypotheses are grounded in the specific friction observed — not generic best-practice changes. I also ensure the analytics infrastructure is correctly set up before drawing conclusions; many ecommerce teams are optimising against misconfigured funnels.

    What is your approach to reducing cart abandonment?

    Cart abandonment sits at the intersection of product, UX, and ops. On the product side, the most common causes are unexpected costs at checkout (shipping, fees), forced account creation, and checkout flow friction. I audit each of these against your specific abandonment data and run interventions in priority order. On the recovery side, I help teams design and instrument re-engagement sequences — email, push, and retargeting — with the product surfaces that support them (persistent cart, guest checkout with late account creation, cross-device cart sync). AI-powered abandonment recovery that personalises the re-engagement message based on the user's browse and cart history consistently outperforms generic sequences and is a high-ROI investment for growth-stage ecommerce.

    How do you align the product roadmap with inventory and operations constraints in ecommerce?

    Ecommerce product teams that operate in isolation from ops and inventory create expensive problems: features that promise delivery speeds the 3PL cannot support, personalisation that surfaces out-of-stock SKUs, or search results ranked by margin that ops cannot actually fulfil. I build alignment mechanisms between product and ops early: a shared product-ops planning cadence, shared OKRs that span fulfilment rate and product metrics, and explicit inventory and ops constraints in story acceptance criteria. When ops data is available via API or data warehouse, I also help teams build product features — dynamic shipping estimates, availability-aware search ranking, low-stock urgency signals — that turn operational reality into a conversion lever.

    How do you approach AI-powered personalisation for an ecommerce product?

    Personalisation in ecommerce has a wide capability spectrum, and the right starting point depends on your data maturity and engineering bandwidth. I help teams build a personalisation roadmap sequenced from low-complexity/high-impact (rules-based merchandising, cohort-level content targeting) through to ML-driven individual recommendations and LLM-powered product discovery. Each step in the sequence delivers measurable value before the next investment is made. For teams with sufficient transaction data, AI-driven recommendations on PDP, cart, and post-purchase surfaces typically deliver 10–20% uplift in AOV. I define the product requirements, work with engineering and data science on the model integration, and set up the experimentation framework to validate impact.

    Ready to move your ecommerce conversion and retention metrics?

    Let's audit your conversion funnel, identify your highest-leverage opportunities, and build an AI-powered product roadmap to unlock the next stage of growth.

    Book a strategy callExplore servicesRead the blog