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    AI Product Manager for B2B SaaS

    B2B SaaS is unforgiving: long sales cycles, demanding enterprise buyers, complex integrations, and churn that compounds quietly until it is too late. I help B2B SaaS companies ship the right features, nail onboarding, and embed AI into their product — as a fractional AI PM who understands both the technical and commercial levers.

    Why B2B SaaS products need an AI PM who understands the full funnel

    B2B SaaS product decisions have a disproportionate effect on commercial outcomes. A poorly designed onboarding flow does not just frustrate users — it inflates CAC and drives churn that shows up six months later. A missing integration kills enterprise deals that took nine months to close. A PLG motion applied to the wrong product burns engineering time without generating pipeline.

    I bring a revenue-aware, full-funnel perspective to B2B SaaS product work: I have worked alongside sales, CS, and engineering to ship product that closes deals, activates users, and drives expansion — and I layer AI capability on top of that foundation to compound the advantage.

    $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 B2B SaaS teams as your AI PM / PO

    • PLG vs. sales-led growth strategy: defining the right motion for your ACV, buyer profile, and product complexity
    • Enterprise onboarding redesign: auditing activation funnels, identifying drop-off, and shipping flows that drive time-to-value
    • Integration ecosystem roadmapping: prioritising the native and API integrations that unlock the most ARR
    • AI feature development: opportunity mapping, LLM integration specs, prompt design, and outcome measurement frameworks
    • Churn diagnostics: cohort-level analysis of retention drivers and a prioritised roadmap to improve NRR

    Engagement models

    Structured for B2B SaaS companies at Seed through Series B — whether you need embedded product leadership, a focused audit, or a partner to ship your AI feature roadmap.

    Fractional PM/POActivation & onboarding auditAI feature roadmapEnterprise readiness sprint

    FAQs

    How do you decide between a product-led and sales-led growth motion for a B2B SaaS product?

    The decision hinges on the complexity of the value proposition, the buyer vs. user distinction, and the ACV. PLG works when the end user can experience value in a self-serve trial before procurement gets involved and when ACV is low enough that the cost of a sales-assisted motion exceeds the revenue. Sales-led is typically necessary when the buying committee is large, when integrations require IT sign-off, or when the product cannot demonstrate value without significant configuration. Most growth-stage B2B SaaS companies actually need a hybrid: PLG-qualified leads that are handed to sales at a defined expansion threshold. I help teams instrument that handoff and build the product surfaces that make it work.

    What is your approach to reducing churn in a B2B SaaS product?

    Churn is almost always a product problem masquerading as a customer success problem. I start with activation — most churn is determined in the first 30 days, not at renewal. I audit the onboarding funnel for the moments where users fail to reach the "aha" moment, redesign those flows, and instrument them properly so the team can measure impact. For existing churners, I run cohort analysis to identify the leading indicators — which features correlate with retained accounts, and which behaviours precede cancellation. The output is a prioritised retention roadmap, not just a list of CS interventions.

    How do you manage integrations as a product surface in B2B SaaS?

    Integrations are often the highest-leverage unbuilt feature in a B2B SaaS product. I treat the integration ecosystem as a product in its own right: I map the integration-driven revenue, define a tiered integration strategy (native, embedded iPaaS, webhook/API), and work with engineering to build an integration layer that scales without becoming a maintenance burden. For enterprise deals, integrations are often gate items — I prioritise the integrations that unlock the most ARR and sequence them against engineering capacity realistically.

    Can you help a B2B SaaS company add AI features to an existing product?

    Yes — this is a core part of my practice. I help B2B SaaS teams identify which workflows in their product are high-friction, repetitive, or data-rich enough to benefit from AI augmentation, then define the feature specs and LLM integration requirements. I am careful to scope AI features around real jobs-to-be-done rather than shipping AI for its own sake. Deliverables include an AI opportunity map, LLM integration architecture requirements (in collaboration with engineering), prompt design specifications, and a measurement framework to validate whether the AI feature is actually improving outcomes for users.

    Ready to build a B2B SaaS product that retains and expands?

    Let's identify the product investments that will move your activation, retention, and expansion metrics — and build a roadmap to get there.

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