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24 pages · Updated November 2026

I lead product strategy and delivery across applied AI, marketing technology, commerce and payments—connecting customer needs, technical requirements and business outcomes.

JUSTIN GRANT SWANSON

New York, NY · Los Angeles, CA | 908-692-1352 | justingrantswanson@gmail.com

linkedin.com/in/justin-grant-swanson

TECHNICAL PRODUCT AND PLATFORM LEADER

AI and Innovation | Payment Integrations | Customer Identity and Access | Enterprise Workflows | Search and Personalization

Full professional profile

Product and innovation leader with 5+ years in product management and 8+ years across digital product, ecommerce and marketing, within a 14+ year career across commerce and creative industries. Led Old Navy’s AI strategy, conversational-shopping product definition and omnichannel initiatives, and global platform delivery across 15+ countries at Ralph Lauren. Connects customer discovery and commercial analysis with technical requirements, integration behavior, data contracts, acceptance criteria and release decisions. Experience spans applied AI, search and personalization, payment integrations, customer identity and eligibility, enterprise workflows and commerce operations. Leads vendor evaluation, investment recommendations, cross-functional delivery, adoption and go/no-go decisions grounded in operational and financial requirements.

Experience scope: 14+ year career span; 8+ years across digital product, ecommerce and marketing, including approximately 7 years and 2 months from Brand Networks onward plus 11 months of paid L'Oreal and Tommy Hilfiger internships. Additional digital experience includes Paper Magazine and Google Community Leaders. Product management accounts for 5+ years within this total; overlapping roles count once.

CORE EXPERTISE

Full expertise
  • Product leadership: Product vision and strategy, multi-quarter roadmaps, discovery, opportunity sizing, business cases, prioritization, product requirements, Agile delivery, vendor evaluation, launch readiness, adoption, and executive communication.
  • AI and digital innovation: Conversational shopping agents, structured LLM context and input schemas, catalog-grounded recommendations, agent-action and session requirements, LLM content workflows, ML/NLP search and recommendations, AI vendor evaluation, interactive prototypes, pilot design, quality and commercial evaluation, workflow automation, and AI adoption.
  • AI evaluation and operating governance: Product-data-grounded generation and recommendations, structured-output requirements, search relevance and catalog-quality testing, LLM content QA, human review and publishing controls, failed-record recovery, brand persona and prompt requirements, policy guardrails, multi-turn context and changed-constraint testing, agent-action confirmation and recovery, scenario matrices and SOPs, regional enablement, API usage limits, response-time requirements, and platform cost evaluation.
  • Ecommerce and customer experience: Search, browse, product-listing pages, product-detail pages, navigation, product evaluation, size and fit, conversion optimization, returning-customer experiences, gifting, mobile apps, and omnichannel fulfillment.
  • Payments and financial operations: Technical product ownership of Klarna Pay in 4 integrations for RalphLauren.com and the RL app and Factory-store Pay Now/Pay in 4 launches through the Klarna app; SFCC/Adyen/Klarna payment handoffs, eligibility and approval outcomes, payment-lifecycle acceptance criteria, order-limit expansion, gifting-payment flows, cancellations, partial fulfillment, refunds and returns, settlement and reconciliation requirements, tender classification, invoicing dependencies, and integration go/no-go decisions.
  • Personalization and marketing technology: Behavioral cohorts, purchase and affinity signals, customer eligibility, gated commerce, CRM activation requirements, customer-data integrations, campaign workflows, promotions, and repeat-purchase journeys.
  • Enterprise workflows and customer identity and access: Structured intake, approval and routing rules, business-user configuration, email-based identity matching, eligibility and entitlement feeds, rule-based customer groups, access grant and revocation scenarios, registration and sign-in requirements, gated navigation and assortments, mixed-basket reporting, preservation of transaction attributes through returns, operational ownership, and cross-system delivery across commerce, CRM, order management and BI.
  • Analytics and experimentation: SQL, funnel and cohort analysis, A/B and usability testing, KPI design, event tracking, attribution validation, dashboards, revenue per visit, conversion, average order value, engagement, returns, and operational efficiency.
  • Technical product ownership and delivery: API and data-feed requirements, request/response behavior, source-to-target mappings, schemas and field definitions, taxonomy and product metadata, integration dependencies, acceptance criteria, UAT, regression testing, defect triage, release controls, fallback and recovery behavior, rollout documentation, training, and change management.
  • Commerce data quality: Product and variant identity, catalog-to-feed validation, price and inventory consistency, eligibility and entitlement feeds, structured content outputs, record-level recovery, transaction handoffs, and source-to-funnel attribution validation.
  • People and partner leadership: Direct-report management at Old Navy; independent product ownership and matrixed delivery across internal teams, contractors and vendors; innovation progress reviews, external engineering coordination, supplier and creative-team direction, and independent-brand consulting.

PROFESSIONAL EXPERIENCE

GAP INC. / OLD NAVY

Senior Manager, Innovation - Online Experience | Aug 2025 - Sep 2026 | San Francisco, CA

Led digital product, AI, personalization, marketplace, and customer-experience initiatives for Old Navy Online. Partnered with Engineering, UX, Data and Analytics, Merchandising, CRM, Marketing, Content Operations, Store Operations, Finance, Gap's Office of AI, and external technology partners from discovery and business case development through delivery and measurement.

Selected highlights

  • Led Ask Navy’s brand-side product definition, integration requirements and prelaunch readiness.
  • DoorDash’s one-month, ten-store pilot recorded $185K revenue; 22% of customers were new to Old Navy.
  • Delivered STDP, removing approximately 27 manual steps per eligible request.
AI strategy and product investment
  • Authored and presented Old Navy's FY26 AI strategy to the VP of Online and Gap Inc.'s Head of Office of AI. Defined priorities across product-data foundations, AI content enablement, site-entry confidence, and personalization; connected brand growth needs with enterprise capabilities and platform constraints. Led internal alignment in January 2026 and initial strategy development in February, then refined priorities through cross-pod planning around discovery, buying confidence, app engagement, internal content enablement, and entry/exit personalization.
  • Built pilot intake, prioritization, and decision frameworks evaluating customer value, financial upside, feasibility, data readiness, operational effort, dependencies, and scalability. Translated broad AI opportunities into specific use cases, requirements, owners, workplans, and executive decisions.
  • Defined success measures across conversion, add-to-bag, average order value, cross-sell, engagement, returns, content-production time, manual effort, quality, and experimentation speed. Used these measures to structure pilot evaluation and recommendations for further investment.
  • Submitted business cases for PDP copy, PDP content, and identity-verification opportunities; mapped ownership and next steps across platform teams, Catalog Operations, and the Office of AI. Assessed product attributes, image-recognition capabilities, and enriched feeds for discovery, recommendations, and outfitting, alongside content tools and entry-source-based badges, messaging, and modules.
  • Facilitated monthly Innovation Lab sessions, bringing customer and operational pain points into structured feasibility reviews, prioritization discussions, and cross-functional follow-through. Managed one direct report early in the role before a reorganization, with weekly innovation touchpoints reviewing project status, progress, and next steps; the employee supported innovation alongside broader UX testing responsibilities. Led matrixed product workstreams across business and technology partners.
Ask Navy conversational shopping and technical delivery
  • Led Old Navy's brand-side product definition, technical integration requirements and prelaunch readiness for Ask Navy, formerly Ask Magic and Hey Navy, on Google's Agentic Applications Shopping Agent platform. Served as Old Navy's main product contact within a group of 13 cross-functional leads and contributors across Old Navy, Gap and Google, coordinating scope across customer journeys, catalog grounding, commerce actions, architecture, UX, analytics and launch criteria.
  • Evaluated Google and Constructor against priority commercial journeys, functional capabilities, brand fit, integration effort, delivery timeline and expected value. Initially recommended Constructor's assistant for its in-chat cart actions, family-matching destinations and merchandising control; used the comparison to secure guided family shopping and QuickShop in the selected Google pilot scope. Distinguished assistant-vendor selection from catalog integration: Constructor also supplied product and availability responses within the Google-based solution.
  • Applied Consumer Insights research from 3,004 US apparel shoppers, including 1,136 Old Navy respondents, to prioritize family-shopping use cases; 36% of Old Navy respondents were very likely to use a styling assistant for coordinated holiday or family-photo outfits. Requested brand-specific family, occasion and parent/non-parent cuts to sharpen pilot questions and distinguish stated interest from interaction and availability requirements.
  • Built the commercial case for the Ask Navy pilot, including QuickShop within chat so customers could select product options and add to cart without leaving the conversation. Modeled approximately $1.12M in incremental demand over eight weeks at 50% US traffic exposure and a 3-basis-point absolute conversion improvement, using 15.5M weekly visits and a $60.41 average order size. Used the forecast and family-basket economics to advocate for in-chat commerce; the estimate was a planning scenario, not a measured postlaunch result.
  • Owned QuickShop functional requirements and acceptance criteria across the conversation-to-cart flow: preserving product, color, size, fit and quantity selections; resolving selections to purchasable SKUs; checking availability; and displaying success only after cart-service confirmation. Defined product and quantity inputs, expected action outcomes and failure-recovery behavior, including retaining customer selections after an unsuccessful action and providing a useful next step. Made the commerce service's response the basis for customer-facing confirmation.
  • Framed QuickShop as a way to preserve conversation context during multi-item shopping and family-set completion. Documented the friction created by repeated exits to product-detail pages and used the business case to support in-chat selection and add-to-cart behavior.
  • Championed the Jingle Jammies family-matching quiz and secured its inclusion in the pilot scope. Defined an optional, three-step journey—print, family composition and sizes—with progressive Constructor filtering before each subsequent step. Sequenced guided discovery with PDP links first and Old Navy-owned QuickShop behind a separate feature gate, allowing the quiz to progress while commerce integration continued.
  • Translated the UX team's Jingle Jammies current-state storyboard and complexity synthesis into product requirements. Addressed the failure pattern of building a set member by member, discovering unavailable inventory late and restarting the journey through earlier availability checks, partial-match transparency, retained family inputs and clear revision and result states.
  • Owned context-engineering requirements translating household members, customer divisions, sizes and relevant fits into guided inputs and retained conversational constraints. Defined how print selection scoped eligible divisions, family composition established whom to serve, and size inputs narrowed products; conversational shopping used the same filters as the quiz. Kept split top/bottom sizing, piece-type questions, ranked fallback tiers, member weighting and adaptive branching in concept exploration outside the three-step MVP.
  • Defined catalog- and inventory-grounding requirements connecting customer intent and family constraints with relevant attributes, purchasable variants and current availability. Established a clear integration contract: Google rendered the quiz and orchestrated Constructor calls, Constructor returned eligible products and availability, and Old Navy defined the experience and owned QuickShop. Kept quiz size filters distinct from cart-ready selections; inheritance of quiz sizes into QuickShop remained an integration decision.
  • Built two working HTML prototypes on the same family-matching model: an on-site guided quiz and an assistant-style conversation with starter prompts and a pinned question card. Added a seasonal availability simulation showing sizes selling through, revised pieces and set totals, and contextual swaps while retaining family inputs. Used the prototypes to validate concepts, expose experience gaps and resolve matching, availability and recovery tradeoffs with business and technical partners.
  • Owned product requirements across customer journeys, assistant persona and naming, prompts, analytics and launch readiness. Defined integration behavior and dependencies with technical partners across product attributes, inventory availability, SKU selection and multi-size shopping; evaluated API architecture options and additional paid capabilities against customer value, implementation effort and MVP scope. Connected brand requirements with the shared Google/Gap integration model spanning merchant-authenticated sessions, Google-hosted conversation services, product-search inputs, frontend experience components and merchant-owned commerce actions.
  • Defined out-of-stock suppression and recovery behavior for family matching. Constrained the quiz MVP to full matches or one partial-match fallback—matching bottoms; when no match remained, the flow reset print choice while retaining family and size inputs. Coordinated merchandising review of recommendation suitability and complementary pairings while keeping broader substitution concepts distinct from the approved quiz fallback.
  • Evaluated assistant responses and recommendations against product data and Gap Inc. AI policies, translating requirements into QA and launch-readiness work with Google. Incorporated policy restrictions on AI-generated product and model imagery into the shopping-assistant experience.
  • Led Old Navy assistant persona development, combining Marketing input, brand identity, and Gap Inc. AI policy considerations. Connected expected assistant behavior with brand voice, shopping guidance, and customer-facing experience requirements.
  • Involved merchandising teams in QA to validate mapped customer journeys against the commercial calendar, particularly holiday peak and family-matching shopping. Used their review to assess recommendation suitability, inventory scenarios, and approved complementary product pairings.
  • Structured the assistant journey review around 15 scenarios: ten general discovery journeys and five Jingle Jammies journeys. Defined expected behavior for complete matches, unavailable sizes, changed constraints, context retention and recommendation suitability, alongside commerce acceptance criteria for service-confirmed cart updates and failure recovery. Used merchandising and technical review to translate gaps into requirements and launch-readiness decisions; Google and Gap technology teams owned production implementation.
  • Defined analytics requirements for the conversational shopping journey, connecting assistant engagement and product discovery with product-page visits, add-to-cart activity and purchase outcomes. Framed evaluation around customer progression, commercial value and failure points, with the shared Google integration specification providing source and action-method attribution for merchant-site activity, customer clicks within the agent and agent-initiated actions.
  • Authored Google shopping-assistant SOPs defining the expected orchestration of clarification, product discovery, recommendation, selection, add-to-cart, confirmation and recovery. Specified when the experience should ask another question, offer an alternative, preserve prior selections, escalate or hand off between systems. Translated expected agent behavior, action outcomes and failure paths into operating guidance for brand, merchandising, business and technology partners.
  • Established the platform evaluation, commercial case, prototypes, product requirements and prelaunch readiness for Ask Navy, publicly announced on October 5, 2026 after my September departure. Google and Gap technology teams owned production implementation; my role covered Old Navy product definition and prelaunch delivery.
View case
AI discovery and merchandising experiments
  • Led Curated For You discovery, vendor evaluation, and prelaunch product definition. Initially designed a three-way experiment comparing incumbent merchandising PLPs, AI-generated PLPs using equivalent taxonomy, and new discovery pages informed by social and search trends; subsequently aligned the approach around direct implementation on selected key pages.
  • Defined MVP features, a two-month workplan, sequencing, risk guardrails, and scale criteria. Evaluated ranking logic, SKU enrichment, recommendations, product-data readiness, taxonomy, SEO/GEO metadata, vendor scope, and the merchandising operating model against conversion, add-to-bag, revenue per visit, bounce rate, and engagement.
  • Defined SEO/GEO landing-page and SKU-enrichment requirements for Curated For You, including regional and event-driven collections. Developed a prioritized portfolio of 14 business use cases and 27 integration and operating requirements, connecting customer problems, commercial hypotheses, market scope, dependencies, ownership, and delivery priorities.
  • Prioritized cultural-event and pre-season trend collections, including major sports moments, festival and holiday shopping, AI-powered sorting on existing PLPs, and family/sibling matching. Defined how external trend signals and image-based product matching could support faster activation, relevant assortments, and basket building.
  • Specified social-to-site trend alignment using signals from TikTok, Instagram, and Pinterest, with YouTube as a potential vendor extension. Defined SEO/GEO trend landing pages and automated SKU-metadata enrichment, including feasibility and GTS dependencies for upstream enrichment and crawlable shopping destinations.
  • Developed Canada-specific trending pages, geographic inventory highlighting, regional weather/seasonal pages, and outfitting use cases. Addressed market-specific assortment, availability, seasonal timing, BOPIS opportunities, and coordinated top-and-bottom shopping journeys.
  • Defined high-value-customer page experiences and segmented landing pages reached from social and email, including cohort definition, CRM/CDP ownership, refresh needs, and personalization options. Established a vendor co-development path for custom trend modules and reporting requirements.
  • Specified inventory and availability requirements targeting 5-15 minute refresh intervals, automatic suppression or replacement of out-of-stock products, threshold-based refresh triggers, and grid reflow that preserved outfit and color groupings.
  • Defined a hybrid AI-and-merchandising grid model combining algorithmic ranking, manual overrides, grouping metadata, and stable rendering contracts. Required product-group and active-variant compatibility, purge awareness, 9-digit color-choice visibility, and ingestion of the standard vendor feed and its available product attributes.
  • Defined refresh and page-performance requirements covering timely full-grid reevaluation after inventory changes, page-load protection, and asynchronous refresh without full-page flicker. Specified API-timeout fallback to the default Old Navy sort or a curated backup and inventory-feed failure handling that prevented invalid purchasable states.
  • Specified full-outfit stock validation and substitution rules when one component became unavailable. Required regional inventory awareness and US/Canada assortment separation to avoid presenting products that could not be purchased in the shopper's market.
  • Defined first-party signal ingestion across clicks, add-to-bag, conversion, and navigation source, plus reporting for engagement, suppression, replacement, AOV, and RPV. Required CID-level enable/disable controls, A/B compatibility with default sorting, major-event grid freezes, and crawlable HTML fallback.
  • Evaluated Firmly and content-QA automation opportunities with business and technology partners, assessing potential use cases and fit with existing QA needs; recommended against pursuing Firmly in that evaluation.
  • Facilitated vendor and use-case discovery for answer engine optimization (AEO), generative engine optimization (GEO), and AI-feed readiness, including Perplexity and Gemini. Connected product-content quality and machine-readable information with opportunities for discovery beyond traditional search.
Google Gemini commerce readiness and AI source measurement
  • Partnered with AI and Analytics Product teams on Google Gemini optimization, connecting customer-experience requirements, product-data readiness, integration validation, and measurement. Helped launch product feeds and improve titles, descriptions, taxonomy, size, color, material, and fit information, including variant mappings and price/inventory accuracy.
  • Defined journey requirements so discovered products corresponded to the correct purchasable variants and appropriate product-page or cart/checkout handoffs. Validated supported discovery-to-purchase journeys for selection continuity, consistent pricing, and successful transaction completion; coordinated fixes and retesting for unavailable sizes and incorrect mappings.
  • Compared representative feed records against the catalog and live shopping experience, checking product identifiers, size/color selections, prices, availability, images, and destination URLs to identify mismatches before or during journey validation.
  • Partnered with Analytics on source-identification and tracking-parameter requirements for major AI platforms, with Gemini as the principal optimization focus. Aligned the capture and classification of incoming parameters and available referral information in Adobe Analytics; Analytics owned the underlying configuration.
  • Validated representative visits to confirm source information appeared in Adobe reporting and that product views, add-to-bag activity, and purchases could be analyzed under the agreed attribution setup. Established a foundation for analyzing identifiable AI-source traffic by landing page and shopping-funnel behavior.
Personalization and returning-customer experiences
  • Led Constructor holiday-personalization planning across six signals: family composition, loyalty/cardholder status, sleep-category affinity, print/pattern affinity, family-member sizes, and gifting intent. Assessed how those signals could influence search, browse, recommendations, and merchandising configuration.
  • Shaped a sleep-category affinity view in Constructor Audience Hub exposing purchase rate, average order value, and revenue by segment. Designed pre/post measurement and modeled approximately $517K in incremental revenue per 1% conversion lift against $51.7M in planned November sleep revenue; used the model for opportunity sizing.
  • Ran a Constructor ranking-diversification experiment to reduce similar-item clustering in search and browse, delivering a 0.37% revenue lift. Translated results into optimization recommendations for product discovery and merchandising.
  • Owned Evergreen Gift Shop and post-holiday strategy and contributed to HOL26 gifting plans. Defined the respective roles of the Holiday Gift Guide and evergreen Gift Shop, post-December 25 traffic handoffs, navigation and search entry points, recommendation modules, asset reuse, measurement, and launch readiness.
Product content and workflow automation
  • Originated and led Straight to Digital Production. Mapped PDP content and asset workflows, identified bottlenecks, and defined a publishing process allowing qualifying PDP tiles and comparison charts to bypass unnecessary Brand Marketing and creative routing. Separated requests needing creative development from assets suitable for direct production, removing unnecessary handoffs while retaining required quality checks.
  • Led build-out sessions and delivered the Q4 2025 Straight to Digital Production MVP, removing approximately 27 manual steps per eligible request across photo planning, creative reviews, design and asset delivery. Established direct-production support for PDP tiles and comparison charts, defined operating requirements and handed ongoing creation and deployment to Content Operations.
  • Defined direct-production eligibility around approved formats, complete product information, and requests requiring no new creative concept. Routed new artwork, unsupported claims, and other exceptions through the appropriate review process.
  • Led build-out of an Airtable intake capturing asset type, product identifiers, copy, imagery, launch/end dates and destination. Defined direct routing to Content Operations for eligible requests, with additional creative review for exceptions; connected program-level targeting through Simple Merge Groups with AV99 fifth-position PDP placement and manual tile removal when products were unmerged.
  • Walked representative requests through the revised process, validated publishing accuracy and exception handling, and documented operational ownership and escalation. Compared original and revised process maps to establish the manual steps removed per eligible request before handing execution to Content Operations.
  • Explored Centric-sourced product details, product lifecycle management (PLM), and bill-of-materials inputs as foundations for AI-assisted copy and attribute enrichment. Assessed how upstream information could improve product content, reduce manual preparation, and support downstream catalog and publishing workflows.
  • Originated the concept for AI-generated product-review summaries and represented Old Navy in brand-side requirements and site testing as the broader team executed it. Reported program outcomes included a 1.2% reduction in return rate and $7.8M in incremental revenue.
  • Launched the Women’s Denim PDP tile automation pilot using Photoshop, existing product photography and existing product attributes for feature copy. Chose automation that met the pilot’s needs at lower cost and deferred generative AI. Focused the pilot on manual Online Experience-to-Catalog Operations workflow steps; wider adoption and deeper systems integration remained roadmap work.
  • Explored opportunities across PDP 2.0, AI fit and try-on concepts, navigation, and omnichannel storytelling with Brand, Merchandising, UX, and technology partners. Captured potential applications for product presentation and future pilots as early discovery and planning.
  • Built the relationship with Gap's Size & Fit product organization and shaped early discovery for a potential BoldMetrics size-guidance integration, including the size-chart redesign approach, ownership model, and dependencies.
View case
OmniHub app strategy and customer engagement
  • Authored Old Navy's app differentiation strategy, competitive review, workshop materials, and three-horizon roadmap; presented the strategy to the Chief Commercial Officer. Began work in August 2025, developed concepts and priorities through late-2025 stakeholder alignment, and continued FY26 planning. Shaped the multi-year OmniHub roadmap spanning navigation, personalized re-entry, stylist recommendations, loyalty visibility, basket-building, Store Mode, and fulfillment.
  • Defined concepts for Continue Shopping, purchase-history recommendations, post-add-to-bag cross-sell, a personalized hub, product scanning, store maps, price alignment, and unified pickup/delivery. Made personalization use cases concrete, including recommending top-rated denim to customers with a history of denim purchases; established KPI focus on app re-entry, engagement, conversion, average order size, and cross-sell attachment.
  • Built the app competitive review across Target, Walmart, Amazon, Nike, Lululemon, A&F, SHEIN, ASOS, and TikTok Shop, drawing on additional Zara and H&M examples. Translated observed patterns into concepts for loyalty wallets, visual discovery and outfitting, one-tap checkout, savings visibility, smart lists, and repeat-use prompts.
  • Defined customer and associate Store Mode concepts spanning local inventory, wayfinding, scanning, price/stock lookup, returns and receipts, membership access, task support, and cart handoff. Connected these concepts with app navigation, store/digital shopping continuity, fulfillment flexibility, and the dependencies required for future delivery.
  • Evaluated dependencies across brand, central product, CRM, Loyalty, Store Operations, and Engineering to inform investment priorities, ownership, experiments, and delivery planning. Early concept validation indicated potential for 23% higher returning-user engagement.
  • Originated custom native in-app landing pages enabling tailored content publishing directly within the app. Aligned experience requirements and dependencies with central teams; the capability was delivered and live in Q1 2026, enabling the team to test content and experiences on app pages.
  • Shipped QR-code app-download tiles across four high-traffic PLPs, generating 358+ installs at approximately 9%-10% scan-to-install conversion. Established AppsFlyer measurement and transitioned ongoing operations to Content Operations.
DoorDash marketplace and omnichannel delivery
  • Led Old Navy’s DoorDash marketplace initiative from a ten-store, one-month pilot through national rollout support in 2025 and continued product ownership in 2026. The nationwide partnership reached more than 1,000 US stores. Coordinated approximately 10 cross-functional contributors across DoorDash, Product, Technology, Store Operations, Analytics, Finance and commercial teams, connecting partner requirements with store readiness and the expansion decision.
  • Led pilot design, assortment and store selection, success criteria, executive readouts, and the scale playbook. Defined measures covering orders per store, new-to-brand customer share, average order value, service-level reliability, ratings, and customer satisfaction; connected customer demand, operational readiness, assortment, and commercial considerations to the expansion recommendation.
  • The one-month pilot recorded $185K revenue, approximately 25% estimated incremental revenue, 3,400 customers with 22% new to Old Navy, and 88% of orders fulfilled in under 35 minutes. Reported performance included 85 orders per store per week, $54 AOV (+4% versus in-store), a 4.5/5 customer rating and 95% order accuracy; used the readout to support scale and operational priorities.
  • Coordinated operational readiness, partner alignment, reporting requirements and feature refinement. After day-to-day marketplace trading transitioned to Old Navy Online, continued performance monitoring and roadmap advocacy through weekly core-team check-ins with the marketplace merchandising lead, Gap Inc. central technology and DoorDash. Translated competitive analysis, commercial feedback and operational issues into enhancement priorities.
  • Shaped catalog and review-feed requirements and follow-on product work for reviews and loyalty. Evaluated roadmap options for unified pickup/delivery selection, marketplace expansion, and same-day delivery on OldNavy.com, clarifying technical, operational, and commercial dependencies.
  • Coordinated DoorDash catalog taxonomy decisions, including whether products should appear in multiple storefront categories, and secured input from commercial and merchandising stakeholders. Worked with Rithum and DoorDash on the feasibility and format requirements for HTML product descriptions through the existing feed and collected business reporting use cases.
View case
Analytics and commercial decision support
  • Owned weekly browse, search, and product-recommendation reporting for Purchase Funnel Management using Adobe Analytics and attribution-model data. Investigated anomalies, reconciled metric definitions, and translated query-, device-, and category-level behavior into executive readouts, hypotheses, requirements, and prioritized actions. Supported Old Navy Online weekly business reviews and merchandising decisions.
  • Built SQL-based cross-source reporting combining internal performance with NPD market-share data. Supported Power BI analysis across category, wearer, channel, retailer, average unit retail, and market-share trends to inform product and commercial decisions.
  • Used customer behavior, qualitative feedback, category economics, and experimentation to frame investment decisions. Applied Claude and enterprise AI tools to analysis, synthesis, documentation, and stakeholder communication.

NORTHSTAR TRAVEL GROUP

Product Manager - AI, Content and Personalization | Jun 25 - Aug 1, 2025 | Short-term contract | Remote

Led technical product requirements and expansion work for existing AI content-recommendation and marketing platforms across a global B2B media network. Partnered with Engineering, Data and Analytics, Editorial, Marketing, CRM, Sales and external technology providers on recommendation experiences, structured LLM inputs, integration planning, experimentation, prototypes and business-user adoption.

Selected highlights

  • Secured adoption of three serving controls: conditional placement, duplicate prevention and clearer sponsored labeling.
  • Defined recommendation-platform expansion requirements and a Marketing/Activation Hub prototype.
Adaptive Content Serving: recommendation pipeline and production expansion
  • Led technical product requirements and expansion planning for the existing Adaptive Content Serving MVP, connecting ML-ranked recommendations, behavioral scoring, ingestion, placement rules and content-container logic. Used the live MVP's baseline snapshot of 51,346 page serves and 288 clicks to inform expansion and measurement planning.
  • Defined requirements for the daily Ektron-to-LeverageLabs-to-BigQuery-to-Template Builder recommendation pipeline, including content ingestion, scoring inputs, cohort assignment and widget placement. Connected Navigator audience/cohort inputs and LeverageLabs recommendation tables with CMS rendering rules; translated the live nine-item article-recommendation experience into expansion requirements for additional sites, placements and content types.
  • Audited page and template compatibility across Northstar Meetings Group, Business Travel News, TravelPulse, Meetings & Conventions, and Successful Meetings. Prioritized expansion using bottom-of-page and right-rail compatibility, editorial value, SEO potential, layout, and evergreen traffic opportunity.
  • Secured adoption of three controls through template audits: conditional widget placement, duplicate-module prevention and clearer sponsored-content labeling. Assessed existing related-content, subscription, advertising and sidebar modules so expanded recommendations could fit page layouts without redundant content or overcrowding.
  • Coordinated recommendation-data validation with Engineering and LeverageLabs, focusing on content ingestion, missing URLs, cohort assignment and scoring completeness. Defined classification and content-type mapping requirements across NetSuite and Ektron, distinguishing editorial, sponsored, vertical-specific and guide content so ingestion and widget selection reflected the intended product and commercial context.
  • Defined a proposed Container → Slot → Widget → Content contract covering container width, eligible widget types, maximum slots, horizontal or vertical slot combinations, padding and supported content types. Specified sponsored-spotlight, newsletter-CTA, event/webinar and content-stack requirements, including sponsor identity and tier, eligibility dates, creative type, destination URL, priority override and labeling; connected newsletter cohort/list IDs, goal measures and A/B variants with targeting and subscriber routing.
  • Specified event and webinar metadata including start/end dates, registration deadlines, locations, speakers, replay availability and urgency flags. Defined proposed freshness, expiration and prioritization behavior, including urgency-based event placement and continued eligibility when a replay remained available. Connected these rules with container/slot constraints, content-type compatibility, campaign management and recommendation logic.
View case
LLM context engineering and content-input specifications
  • Specified the Marketing Hub's structured LLM input schema: title/headline, description/summary, author/source, primary and secondary topics, publication date, URL or asset ID, content type, promotion type, intent category and target audience. Connected fields to semantic classification, credibility and brand-affinity signals, cohort alignment, relevance grouping, freshness, engagement tracking and downstream rendering needs.
  • Extended input requirements with campaign name, sponsor/client brand, CTA and destination link, engagement measures, evergreen status, trending/archive signals and topical urgency. Defined proposed derived attributes, including semantic keywords, optional sentiment, LLM-predicted funnel stage and engagement type, to support richer classification, targeting and relevance decisions.
  • Defined format-specific ingestion requirements for video, webinar, event, newsletter and survey content. Specified video transcripts or summaries, duration, format and CTA; webinar speakers, registration, format and audience vertical; event dates, location, themes and exhibitors; newsletter audience and clickstream context; and survey partners, research findings and gated-report destinations.
Marketing/Activation Hub: generation design, workflow and operating controls
  • Led requirements and prototype work for the GenAI Marketing/Activation Hub within Ektron CMS workflows, supporting nontechnical teams in developing marketing campaigns and managing promotions and widgets, alongside related AI Planner use cases for client sales plans. Defined the business-user flow for selecting a brand and content type, entering metadata, attaching assets or source links, setting audience and duration, configuring placements and submitting content for ingestion. Connected these actions with scoring, BigQuery ingestion and Template Builder/Ektron dependencies; planned email, social, SEO content and additional campaign channels alongside the live onsite recommendation experience.
  • Defined a proposed CMS-based generation workflow in which editors selected approved source content, brand, channel, and communication objective. Specified how those inputs would populate a generation template returning channel-specific drafts, including promotional headlines, email summaries, and social captions, with editing and approval retained before publication.
  • Defined the planned Q4 AI-persona experience, combining a parent persona representing brand voice with optional child-persona style, promotion description and target audience to generate widget-title and description suggestions. Developed prototype guidance for audience, tone, terminology and calls to action, including Professional, Engaging and Analytical variants and a thumbs-up/down feedback interaction. Set QA expectations for fidelity to source content, brand consistency and suitability for each planned publishing channel.
  • Evaluated representative editorial tasks in prototype and requirements work for usable output, editing effort, and completion time. Converted findings into product requirements, measurement criteria, adoption guidance, and rollout-readiness considerations.
  • Owned technical product requirements for the end-to-end flow connecting the recommendation engine, BigQuery, Ektron CMS, analytics and CRM. Specified API and data-flow requirements, fields, schemas, segment and activation rules, validation criteria and downstream dependencies; translated business use cases into implementation requirements and marketing activation behavior with engineering partners.
  • Translated the Activation Hub-to-Navigator/LeverageLabs-to-BigQuery-to-Template Builder-to-Ektron flow and downstream CRM activation requirements into business-user SOPs, partner-facing documentation and integration diagrams. Documented metadata completeness, ingestion confirmation, classification checks, approval status, campaign timing and daily processing dependencies. Combined persona tone and CTA guidance with operating instructions for Editorial, CRM, Marketing and Sales to support brand-consistent content and expansion across publishing brands.
  • Defined operational checks and troubleshooting guidance for missing content, incorrect content types, ingestion delays and publishing failures. Made processing status, data readiness, approval and timing dependencies explicit so business users and technical partners could identify the failing step and coordinate the appropriate correction before activation.
  • Established experimentation frameworks, KPI definitions, dashboards and dashboard requirements, rollout governance, and readiness processes. Connected product decisions to content engagement, recirculation, campaign execution, and operational efficiency across the live onsite recommendation capability and planned Marketing Hub expansion.
  • Analyzed sponsored content and digital-guide formats across brands and documented content-type and NetSuite naming mappings for downstream ingestion and widget configuration. Distinguished analysis and mapping recommendations from the adopted placement and labeling changes.
View case

RALPH LAUREN

Global Digital Technology Product Manager - Platform | Apr 2022 - May 2025 | New York, NY

Owned global product strategy and end-to-end delivery across search, product-listing pages, personalization, content systems, technical SEO, analytics, and size and fit for 15+ countries. Independently led product decisions and recommendations, securing leadership alignment while coordinating Engineering, Architecture, UX, Merchandising, Marketing, CRM, Analytics, regional ecommerce teams, and vendors.

Selected highlights

  • Owned global product strategy and delivery across 15+ countries.
  • Search A/B tests versus Salesforce search recorded +2.2% RPV in North America and +17% in EMEA.
  • Led AI enrichment across 10K+ SKUs, reducing manual metadata-preparation effort by 80%.
Klarna omnichannel payment integrations and lifecycle requirements
  • Owned technical product requirements and delivery for Ralph Lauren's continuing Klarna and cart-and-checkout roadmap, leading Pay in 4 integrations and rollouts across RalphLauren.com and the RL app. Translated payment-provider capabilities, customer journeys and commerce-platform constraints into integration requirements, acceptance criteria, testing and release readiness to expand installment-payment access.
  • Launched Klarna Pay Now and Pay in 4 for Ralph Lauren Factory stores, enabling customers to pay in full or in installments for store purchases through the Klarna app. Led product definition and delivery across the store purchase journey and payment experience, accounting for the differences between digital checkout and app-mediated in-store payment.
  • Defined payment-lifecycle requirements and acceptance scenarios spanning eligibility, approval and decline responses, abandoned approval flows, basket changes, cancellations, partial fulfillment, refunds and returns. Translated these scenarios into expected customer-facing and operational behavior across web, app and store journeys.
  • Owned integration requirements within the existing SFCC, Adyen and Klarna payment environment, connecting storefront eligibility and threshold configuration, on-site payment messaging, Klarna-hosted checkout handoffs, provider responses and downstream order exceptions. Aligned business and technical partners on how payment outcomes should be reflected in the purchase experience.
  • Established measurement requirements across payment adoption, approval rates, checkout conversion, payment-related abandonment, order volume, revenue and support contacts to evaluate customer uptake, commercial performance and operational issues after rollout.
View case
Global product delivery and roadmap ownership
  • Directed a portfolio spanning the Bloomreach search and PLP migration, segmented discovery, Private Store, FY25/FY26 technical SEO, LLM metadata automation, size-and-fit improvements, and analytics enablement. Converted regional priorities and customer opportunities into roadmaps, requirements, investment recommendations, delivery decisions, and measurable success criteria.
  • Drove delivery of 850+ global enhancements and defect resolutions through Agile execution, detailed requirements, decision matrices, data dictionaries, sprint planning, dependency management, UAT, and release readiness.
  • Owned rollout communications, training, enablement materials, and regional operating guidance. Aligned Engineering, Marketing, Merchandising, CRM, and business stakeholders on scope, timing, customer impact, release readiness, and ongoing operational responsibilities.
Bloomreach platform selection, global rollout, and technical integration
  • Led a six-vendor search-and-merchandising platform RFP from evaluation criteria and regional scorecards through technical due diligence, reference checks, catalog-based POCs and executive recommendation. Narrowed the field to Bloomreach and Algolia, directed the final assessment and secured endorsement from the head of DTC and executive leadership.
  • Evaluated competing platforms against comparable query sets and merchandising scenarios, weighing relevance, configuration flexibility, regional requirements, integration effort, customer-facing performance, and cost. Recommended Bloomreach based on the combined merchandising requirements, regional fit, and cost-to-value assessment.
  • Led the 2023–2025 migration from Salesforce search to Bloomreach AI Search and product-listing pages, owning the vendor relationship and phased deployment across North America, EMEA, and APAC. Directed web and RL app requirements, business testing, UAT, adoption, and rollout sequencing; used Global-e markets as the initial APAC deployment phase.
  • Led cross-functional optimization of ML/NLP ranking behavior, synonyms, query intent, clickstream signals and merchandising rules with Engineering, Bloomreach and regional teams. Search A/B tests versus Salesforce search recorded +2.2% revenue per visit in North America and +17% in EMEA. A separate North American readout recorded +7.8% search-engaged RPV during the first three weeks after the September 2023 rollout reached 100%, following three months of 50/50 testing.
  • Led phased product-listing-page delivery and regional validation alongside search. The November 1–28, 2024 EMEA PLP A/B test recorded approximately +1.5% revenue per visit versus SFCC ($4.89 versus $4.82), providing a distinct measurement of listing-page performance from search and audience-personalization experiments.
  • Owned and authored the technical product specifications for SFCC-to-Bloomreach integration, covering source-to-target mappings, data types, field definitions, regional configuration, API response fields, acceptance criteria and exception handling. Defined the catalog and storefront data requirements across product/SKU relationships, categories, localized attributes, active prices, inventory, images and facets.
  • Defined the functional and data-quality requirements for full and incremental catalog, inventory and price feeds, including regional timing, product/SKU additions and removals, availability synchronization and active selling-price logic. Aligned Engineering and Merchandising on expected integration behavior when source records and the search index differed.
  • Specified the integration flow from full-feed catalog creation and incremental product, price and inventory updates to search requests and storefront responses. Defined query and regional context and required product/facet outputs; validated source records against indexed data and live experiences, including product eligibility, localized attributes, prices and inventory.
  • Set performance and usage requirements across API calls per page, request-rate limits, and contracted usage allowances. Incorporated Ralph Lauren’s seven-call page-performance constraint into product tradeoffs to protect response times while accommodating search, merchandising, personalization, and other platform activity.
  • Led the product tradeoff for preserving Ralph Lauren's existing brand hierarchy within Bloomreach ranking. Rejected the grouping-API approach because of custom caching, pagination, SEO, performance and API-call constraints; recommended market-specific numeric brand weights in a single request, with validation as the next implementation step.
  • Managed the Bloomreach integration against a defined response-time target. When the initial implementation missed the target, led cross-functional troubleshooting and coordinated the performance fix in the next sprint release.
  • Led product-side diagnosis of response-time shortfalls with Engineering and Bloomreach, tracing the storefront, integration and vendor components through request sequencing, payloads and component timings. Validated the proposed remediation against performance requirements and regression-tested search-result correctness before the following sprint release.
  • Led assessment of an EMEA PLP performance issue involving approximately 20-second load times and the conflict between caching, experimentation, and merchandising controls. Coordinated the path forward around page-container caching and customer-group-based testing so performance remediation addressed business requirements as well as page speed.
  • Led Bloomreach commercial and contract evaluation with business, technical and Procurement stakeholders, assessing required capabilities, usage allowances, performance constraints, implementation effort and ongoing support. The initial vendor agreement committed approximately $1.2M over two years for subscriptions, implementation, training and strategic services; aligned the platform recommendation with those commercial obligations and expected value.
  • Owned API-demand and cost requirements across search/listing-page traffic, filtering, pagination, repeat searches, normal and peak usage, contractual request-counting rules, allowances and overage exposure. Translated traffic and usage assumptions into scope, performance and commercial tradeoffs with technical and procurement partners.
  • Evaluated additional paid platform capabilities against customer value, regional merchandising needs, implementation effort, support burden, and contractual limits. Led product evaluation and experiment planning for advanced ranking, vector/hybrid search, Search+, real-time segments, slot merchandising, and personalization capabilities with Bloomreach and business teams.
  • Owned testing, cross-system dependencies, release readiness, and regional adoption for the search-and-browse platform. Ensured catalog data, customer context, merchandising logic, and instrumentation met business requirements before increasing exposure.
View case
Platform reliability, release controls, and business operations
  • Defined production rollout controls by site/locale, country, customer group, and category/PLP, enabling regional and audience-specific activation. Distinguished country-level controls from language-specific storefronts and carried eligibility context into the RL app MVP.
  • Delivered SFCC fallback behavior for Bloomreach-backed experiences, distinguishing legitimate empty result sets from provider failures while preserving customer eligibility and analytics requirements. Incorporated degraded-service and recovery scenarios into product requirements and validation.
  • Led product requirements and delivery coordination for feed-recovery behavior, stale inventory and pricing, missing products, and catalog rebuilds. Established ETL alerts, quota monitoring, staging fidelity, future-product previews, and configuration-promotion capabilities to support business operations and dependable releases.
  • Resolved regional merchandising requirements for localized grid breaks and merged facet values, balancing storefront behavior, feed/index dependencies, and different regional trading strategies. Led resolution of parent/variant learning-attribution issues affecting sliced products, working with technical and vendor teams on product behavior and validation.
  • Introduced algorithmic merchandising grids and enabled real-time publishing in place of next-day updates, giving merchandising teams faster control of their digital assortments. Defined operational requirements and worked with business users on monitoring and adoption.
  • Embedded search relevance, catalog quality, and LLM content QA in product requirements, launch criteria, and ongoing platform evaluation. Applied the process across Bloomreach-supported search and product-listing pages to connect technical correctness with the customer experience.
  • Directed repeatable relevance testing across popular searches, misspellings, ambiguous terms, and low-result queries. Coordinated regional merchandising review of returned assortments and manual rules, translating findings into configuration changes and prioritized fixes; used a 1,500-query evaluation in which 96% of the top-20 results were rated relevant.
  • Led optimization of searchable attributes and query matching, with targeted tail-query relevance improving from 89% to 94% and average conversion increasing 12% for the affected queries. Used staging-versus-production relevance checks to assess new attributes before enabling them broadly.
  • Directed search-algorithm experimentation and optimization of ranking signals. The July 2023 algorithm change delivered an 8% RPV improvement, and the January–March 2024 algorithm program delivered a 13% RPV improvement; used successive tests to refine search relevance and commercial performance.
  • Evaluated facet expansion through pre/post analysis of facet users: desktop conversion increased from 8.92% to 12.80% and mobile conversion from 4.73% to 7.50%, with facet-user RPV increasing 27% and 17%, respectively. Used the audience-specific results to inform continued discovery and merchandising priorities.
  • Led recurring working sessions with search and merchandising teams across EMEA, APAC, and North America and with Bloomreach. Used the cadence to review relevance and operational findings, prioritize vendor and internal work, clarify requirements, and coordinate launch and optimization decisions.
  • Authored Bloomreach operating SOPs, training materials and regional support guidance, embedding platform use, relevance review, configuration practices and release learnings across North America, EMEA and APAC. Coordinated access, enablement and regional adoption across a documented network of more than 80 global, regional, vendor and implementation stakeholders.
Behavioral personalization and segmented merchandising
  • Partnered with the personalization product lead to advance Big & Tall and Women's High Sale Affinity search and PLP personalization in Bloomreach, working with regional search and merchandising users, Engineering, Analytics and the vendor. Led integration and merchandising requirements across segment treatments, ranking/filter behavior, implementation, experiments, analysis and rollout recommendations.
  • Defined behavioral cohort logic using product views, category visits, add-to-cart activity, purchases, and fit or sale affinity. Big & Tall targeting used profiles with more than 65% of site interactions in that category; Women’s High Sale Affinity combined a greater-than-65% sale-affinity threshold with a 65% women’s-article threshold. Addressed conflicting memberships, signal freshness, and defaults when customer data was insufficient.
  • Configured product requirements around existing Bloomreach ranking capabilities: Big & Tall products received a global boost within the relevant audience, while Women’s High Sale Affinity prioritized women’s sale products. Improved fit/filter visibility and preserved access to the broader assortment instead of restricting customers to a narrow segment experience.
  • Aligned segment identifiers and eligibility logic with Engineering’s Bloomreach configuration. Tested representative customer profiles for assignment, ranking, filters, overlapping signals, and fallback experiences to ensure the targeted treatment matched the intended audience.
  • Designed and evaluated the Big & Tall merchandising experiment, which delivered 23.8% higher revenue per visit, 10.2% higher conversion, and 6.2% higher average order value within the targeted audience. Used the findings to prioritize relevant-fit discovery and high-intent personalization.
  • Led the Women’s High Sale Affinity experiment, which delivered 39.53% higher revenue per visit and 26.8% higher average order value, with conversion essentially flat. Used the result to distinguish order-value improvement from conversion improvement when recommending the next personalization investments.
  • Designed targeted A/B tests with consistent eligible-visitor assignments and partnered with Analytics to validate exposure, product-view, add-to-cart, and purchase events. Evaluated RPV alongside conversion and order value to explain performance within the tested audiences and guide rollout decisions.
Customer Group Flags and lifecycle activation
  • Developed a Customer Group Flag framework standardizing outlet, loyalty and B2B cohort definitions and enabling tailored pricing, merchandising, ranking and content. The framework supported 14% higher repeat purchase and 11% higher high-value-customer engagement.
  • Led the product definition of customer eligibility, lifecycle changes, conflicting memberships, signal freshness and default experiences with CRM, business and engineering stakeholders. Connected customer-group requirements with differentiated commerce experiences and activation needs.
  • Partnered with CRM and lifecycle stakeholders to translate onsite behavior, customer segments and product metadata into audience and trigger requirements for email, app and paid-media activation, connecting personalized commerce experiences with lifecycle messaging.
Private Store customer identity access entitlement lifecycle and transaction reporting
  • Restored momentum to Ralph Lauren’s stalled Private Store enhancement as global product lead and led product scope through delivery from December 2023 to May 2025. Launched tiered customer-group-based shopping experiences within a controlled digital outlet, aligning customer eligibility, differentiated shopping, integration requirements and cross-functional release readiness. Aligned product leadership and business stakeholders around purchase frequency, lapsed-shopper reactivation and cross-shopping into additional categories and full-price assortments.
  • Sequenced a focused UK/EMEA account-access MVP with the broader customer-group capability that launched as Lux and Premium experiences. Coordinated CRM, Architecture, Engineering and business stakeholders around eligibility and reassignment rules, customer communications and reporting dependencies; kept NA and APAC outside the initial MVP scope.
  • Owned functional and technical product requirements connecting Zeta CDP, Salesforce Commerce Cloud and Snowflake customer data, translating segmentation and eligibility rules into data-feed specifications, customer-profile attributes, integration behavior and acceptance criteria. Led scope, architecture dependencies, UAT and release readiness across CRM, Architecture, Publicis Sapient Engineering, Retail, CX, Analytics and UX.
  • Secured approval for the initial UK/EMEA implementation plan, estimated at $97,702 over approximately 15 weeks. Led scope tradeoffs, estimating, vendor coordination and budget planning with program and project managers, aligning the proposed staffing and delivery approach with customer-access and reporting requirements.
  • Owned product requirements for the daily Zeta-to-SFCC entitlement feed and one-time migration of active eligible customers. Specified email-based identity matching, eligibility flags, profile attributes and dynamic, rule-based customer-group membership, connecting upstream customer qualification with the access decisions enforced in the commerce experience.
  • Defined registration, sign-in and gated-navigation requirements that connected in-store signup with online access. Established how customer identity, eligibility attributes and group membership determined access to the Private Store experience, and incorporated those decisions into integration acceptance criteria and UAT.
  • Addressed an approximately three-week delay between in-store signup and email/SMS access communications. Set a 24-hour access ambition and aligned the implementation proposal around a 2–3-day target, making access speed an explicit product requirement.
  • Defined the customer-access lifecycle and exception requirements for granting, maintaining and revoking eligibility. Covered changed email addresses, duplicate or failed identity matches, inactive customers, revoked eligibility and delayed feeds; translated these scenarios into testable access rules and expected cross-system behavior.
  • Owned Salesforce Marketing Cloud integration requirements for activation messaging, triggers, audience definitions, timing and eligibility checks. Aligned CRM and Engineering on dependencies between customer qualification, access availability and email/SMS communications so the activation journey reflected the customer's current entitlement state.
  • Owned technical product decisions for transaction classification across full-price, Private Store and mixed baskets, including products discovered through search, recommendations and wishlists. Resolved order-header versus order-line classification requirements and coordinated SFCC, OMS/MBS, BI and Zeta/CDP data dependencies to deliver consistent downstream reporting.
  • Defined assortment and selling-environment attributes and reporting requirements across demand, fulfilled sales, returns, net sales, margin, activation and cross-shopping. Connected item-level detail for BI and OMS with order-header classification for Zeta; distinguished delivered transaction-classification behavior from open attribution questions for products exposed in both environments. Analytics tagging and report creation remained outside the initial implementation estimate. Connected buying and merchandising needs with MicroStrategy and Enterprise Planning requirements.
  • Led delivery and UAT of production behavior preserving original demand-order classification through returns, maintaining assortment and selling-environment attribution across order-management, customer-data and reporting systems. Validated transaction-lifecycle requirements and coordinated marketing-channel visibility and cross-system release dependencies.
  • Defined measurement across activation, gated conversion, orders, units, sales and cross-shopping to evaluate an estimated $1M–$5M incremental annual EMEA revenue opportunity. Connected the investment case with operational data and reporting requirements to assess performance after launch.
  • Sequenced the December 2023 account-access initiative, 2024 eligibility and reporting work, and July 2024 strategy for broader segmentation and differentiated experiences. Maintained a phased roadmap across access, personalization and measurement, with further Customer Group Flags enhancements in discovery in March 2025.
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Technical SEO, platform modernization, and organic growth
  • Owned the FY25 and FY26 technical SEO roadmaps on SFCC. Gathered business priorities, assessed technical dependencies, and approved product decisions across canonicalization, hreflang, pagination, sitemaps/indexing, structured data, and accumulated platform debt with SEO, Engineering, Marketing, and regional teams.
  • Delivered FY25 foundational SEO improvements and developed the FY26 expansion roadmap for faceted navigation, personalization, and platform-change readiness. Aligned product scope, implementation sequencing, and release dependencies across Engineering, SEO, regional ecommerce, Content, and Publicis Sapient.
  • Reviewed crawl findings and representative product, category, and regional pages with SEO; grouped defects by root cause and prioritized work by affected page volume, commercial importance, organic opportunity, engineering effort, and dependencies. Favored shared-template fixes where a single change improved many pages.
  • Translated technical SEO findings into engineering tickets with example URLs, current and expected behavior, affected markets, and testable acceptance criteria. Defined preferred-page behavior for canonicalization and aligned canonical tags, internal links, and sitemap entries with the intended URLs.
  • Delivered technical SEO improvements generating 320K incremental organic sessions across North America and EMEA in three months. Developed the investment case forecasting 2.7M annual incremental sessions and $2.6M in annual revenue opportunity.
  • Created the FY26 technical SEO roadmap and secured vendor contract approval for a $568K investment. Built executive narratives connecting discoverability, platform dependencies, implementation sequencing, resource requirements, and expected business impact.
  • Led JSON-LD structured-data requirements across ProductGroup, Breadcrumb, Aggregate Rating, Review, and Video schemas. Mapped catalog and content fields, represented parent-style and size/color variant relationships, and validated product identifiers, prices, availability, and ratings against customer-facing content to support rich-result eligibility and discoverability.
  • Delivered facet-metadata controls that removed unresolved placeholders from titles, descriptions, and H1s and localized facet variables for regional storefronts. Defined bespoke-facet capabilities for manually uploaded metadata, H1s, and copy, retaining generated/refined attributes as fallback when no custom value was supplied.
  • Led requirements for dynamic image-alt tagging, including localizable product-level Smart Tags and composition from product color, name, brand, and SEO attributes. Coordinated language and placement rules with SEO and Engineering to support meaningful image descriptions across regional experiences.
  • Modernized legacy query-string link tracking, including webcat, toward event-based tagging. Addressed duplicate URL variations from navigation parameters while preserving measurement fidelity; partnered with Analytics and Engineering to move navigation context into events and validate preferred-URL behavior and event capture. Treated functional parameters such as pagination according to their purpose.
  • Validated reciprocal hreflang references between equivalent regional pages using appropriate language/country codes and canonical alignment. Defined and reviewed bulk-import behavior, exclusions, and repeat-run QA; checked that deeper listings used crawlable links and distinct URLs and that sitemaps included preferred, indexable destinations while excluding broken or redirected pages.
  • Owned release acceptance and QA across product pages, category pages, parameterized URLs, paginated listings, and multiple locales. Inspected canonical, hreflang, and JSON-LD output; checked response codes, indexability, and sitemap inclusion; tested navigation and analytics events; and repeated representative production checks after release.
  • Partnered with SEO and Analytics to review indexing, structured-data errors, organic sessions, engagement, and conversion. Assessed affected pages and markets around release dates while considering seasonality and commercial activity, and combined opportunity sizing, delivery requirements, and engineering estimates in subsequent funding recommendations.
  • Coordinated SEO-friendly pagination across SFCC and Bloomreach, including multi-grid nofollow behavior and cross-project release dependencies. Combined technical controls with custom 404, store-page, internal-linking, and structured-content work to improve crawlability and customer navigation.
AI Product Enrichment & SEO Publishing
  • Led product requirements and cross-functional delivery for an AI-assisted product-enrichment workflow using Dataiku and GPT-4 across 10K+ catalog SKUs. Connected data science, internal search, SEO and Engineering, extending Smart Tagging into Salesforce Commerce Cloud image alt-text publishing as part of the Global SEO Roadmap.
  • Defined source-to-output requirements connecting product imagery and catalog information with structured enrichment linked to the correct product record. Separated upstream AI enrichment from SFCC storefront formatting so each destination could preserve product identity and apply its own publishing requirements.
  • Defined the SEO alt-text structure using product color, name, brand, an optional enrichment value and image index. Required independent color rendering for products without Smart Tags, with support for base products, variants, localizable enrichment and language-specific ordering.
  • Owned the enrichment-to-publishing integration requirements and acceptance criteria with SEO, data science and Engineering. Coordinated product selection, SFCC field behavior and PDP rendering, including eligible seasonal categories, product-template exclusions, home-product upholstery and finish attributes, and localization edge cases.
  • Reduced manual metadata-preparation effort by 80%. The broader Global SEO Roadmap I led recorded 10.9% year-over-year growth in North American SEO visits, from 19.06M to 21.14M during April-January; this combined US-and-Canada channel result was not attributed solely to Smart Tags.
  • Aligned regional SEO, analytics, data science, product, creative and technology stakeholders with Publicis Sapient delivery. The FY25 plan estimated $310K for the broader Sapient SEO engagement, and delivery reporting identified 10 named Sapient contributors across product/project management and development/QA.
  • Translated the proposal into testable requirements for optional values, variants, exclusions and localization. The SEO validation plan specified confirmation of updated alt tags followed by eight-week pre/post analysis in Google Search Console and SEMrush, covering organic PDP traffic, keyword visibility and image performance.
  • Connected product-enrichment requirements with internal-search stakeholders and the SFCC-to-Bloomreach catalog mapping. Smart Tags were a related search input; SEO publishing operated through SFCC product attributes and PDP rendering, with Bloomreach not required as an intermediate publishing step.
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Global size and fit, localized guidance, and purchase confidence
  • Led the 2023–2024 size-and-fit redesign across global storefronts, replacing legacy guidance with localized, product-specific garment and body-chart modules. Owned requirements and delivery with UX and Engineering, using usability testing and behavioral analytics to improve product evaluation and shopper confidence.
  • Extended product-specific size-chart modals across PDPs, Quickshop, and wishlists, with regional measurement units and country-specific sizing conventions. Defined default category body-chart fallback for customized products without garment measurements.
  • Accommodated the existing True Fit service within the redesigned experience, coordinating modal presentation and business enable/disable controls. Preserved compatibility with the vendor capability while leading Ralph Lauren’s chart and guidance experience.
  • Delivered size-and-fit improvements associated with 5% higher North American conversion, 7% higher North American revenue per visit, and 10% fewer EMEA returns. Connected the redesign with purchase confidence, product evaluation, and return reduction.
  • The EMEA size-chart redesign evaluation recorded 22% higher conversion and 10% higher revenue per visit. Used regional performance to evaluate localized guidance and prioritize further customer-experience improvements.
  • Led scope and MVP development for a separate Size Guide Hub, with globally indexable pages, structured metadata, category/region/fit navigation, and internal links to product and listing pages. Aligned SEO, UX, Content, and Marketing on a projected 30% improvement in long-tail SEO visibility; the Hub had not launched at departure.
  • Explored a PLM-to-PIM-to-SFCC flow to automate garment points of measurement for size charts. Distinguished garment measurements from category-level body measurements already in SFCC and defined data, architecture, and workflow requirements for the proposed automation.
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Analytics, experimentation governance, and incident response
  • Built executive dashboards across revenue per visit, click-through rate, engagement, and operational variance. Used customer behavior and performance evidence to prioritize experiments, evaluate regional outcomes, and communicate investment needs to business and executive stakeholders.
  • Led experiment hypotheses, traffic-allocation requirements, guardrails, exposure validation, significance interpretation, reporting, and recommendations. Defined analytics-pipeline and event-tracking requirements for funnels, attribution, and lifecycle personalization, carrying MVP testing and release learnings into subsequent regional rollouts.
  • Established Adobe as Ralph Lauren’s business source of truth for search performance while reconciling differences in Bloomreach definitions, methodologies, and lookback periods. Coordinated pixel reconciliations, cross-system tests, customer-journey validation, and defect resolution to distinguish measurement discrepancies from actual product performance.
  • Investigated test-allocation discrepancies, including the 2023 North American incident in which Monetate inadvertently directed traffic to 100% SFCC and the gap between intended and observed test splits. Coordinated business, Analytics, vendor, and technical follow-up to protect experiment interpretation.
  • Managed regional performance risk when APAC testing showed 8% higher click-through rate alongside 25% lower revenue per visit. Evaluated commercial outcomes alongside engagement and investigated ranking, event-data, and experience-assignment issues; supported the Korea return to SFCC while the 2025 cross-system test investigation continued.
  • Led requirements, implementation coordination, and QA for Meta Pixel and advertising/analytics tags across clicks and add-to-cart actions. Validated event firing and partnered with Engineering, Analytics, and Marketing to resolve data discrepancies and attribution gaps.

RALPH LAUREN

Associate Product Manager - Platform | Jun 2021 - Apr 2022 | New York, NY

Selected highlights

  • Expanded Klarna’s order limit from $2,500 to $4,000; the initiative’s readout reported +9% AOV.
  • Drove resolution of 531 defects and delivered 369 enhancements.
  • Stopped the planned 4Gifters integration when unresolved implementation and reconciliation requirements outweighed expected value.
Klarna payment expansion
  • Led the RLNA Klarna Pay in 4 order-limit expansion from $2,500 to $4,000 in the September 2021 release, extending payment availability for higher-value purchases following the Home launch and luxury-product adoption. Owned opportunity definition, the business case, vendor alignment, requirements, testing, rollout and measurement; the October 2021 business readout reported a 9% AOV increase for the initiative.
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Platform delivery, operational ownership and experimentation
  • Owned a global ecommerce support queue, assessing, reproducing, prioritizing and driving resolution of 531 defects across analytics, marketing tracking, SEO, navigation, merchandising and customer-facing experiences.
  • Documented reproduction steps, expected versus actual behavior, severity, affected markets and business impact in Jira. Drove Engineering triage, support priorities, stakeholder updates, UAT and regression testing through closure.
  • Delivered 369 enhancements across regional ecommerce experiences. Led requirements and coordinated UX, Engineering, Marketing, Merchandising and business stakeholders through sprint planning, release readiness and execution of Ralph Lauren’s digital flagship roadmap.
  • Led A/B and user testing from setup through analysis and recommendations, combining experiment results, qualitative feedback and competitive benchmarking to prioritize customer-experience improvements.
  • Led product definition for a completed 50/50 Monetate checkout-navigation experiment across desktop and mobile, testing whether simplified navigation reduced opportunities to leave the purchase journey. Specified server-side execution to avoid experience flicker and ease production adoption. Also owned CYO-icon visibility work on product pages, defining placement and experience requirements with UX and delivery partners.
  • Created UAT scripts, rollout guides and enablement documentation to support business adoption and consistent execution across markets.
4Gifters payment integration financial controls and investment decision
  • Led the proposed 4Gifters integration from kickoff through configuration as lead product manager, taking ownership after vendor selection. Owned discovery, scope, customer journeys, technical requirements, operating-model decisions and launch-readiness assessment across North America and Europe, coordinating Architecture, Engineering, Finance and vendor stakeholders.
  • Directed cross-functional investigation of concerns raised by Architecture and Finance, obtaining vendor answers, defining required controls, challenging scope and assessing the business case. Brought Finance, Sales Audit, Tax, Legal, FP&A, Customer Service and engineering teams into decisions on regional feasibility and ongoing operating effort.
  • Owned definition and cross-functional review of settlement, reconciliation and transaction-reporting requirements across SFCC, OMS, IIB, IP, SAP and BI. Specified the need for distinct payment/tender identification, settlement files, sales-audit balancing and monthly invoicing outside the normal PSP settlement flow; connected demand orders, shipped orders, vendor-collected funds and downstream finance reporting.
  • Drove investigation of a payment-control gap: the vendor cartridge did not verify that collected funds covered the final SFCC order total. Defined the control question and coordinated Architecture, Finance and vendor review of changing order values, the vendor's proposed responsibility for payment shortfalls, and the controls needed to resolve funding differences before launch.
  • Led vendor and stakeholder clarification of European voucher, invoicing and VAT scenarios, including recipient changes, additional payments and delivery differences. Connected Tax and Legal interpretations with the customer journey, money flows, order processing and reconciliation requirements.
  • Defined and coordinated review of gifting scenarios spanning multiple contributors, contribution deadlines, inventory availability, recipient acceptance or substitution, additional payments, cancellations, contributor refunds, gift-card returns, price changes and promotions. Worked through order ownership and customer-data implications across commerce, OMS and CRM.
  • Defined cross-system requirements for order ownership, gift acceptance and the handoff from the vendor experience into SFCC and OMS. Worked through inventory availability during the contribution-and-acceptance window, out-of-stock recovery, gift-giver account association, new payment-type propagation, gift-card refund handling and differences between demand and shipped-order visibility.
  • Brought PDP placement, explanatory messaging and gifting comprehension into product definition with UX. Discovery included a 10-user study comparing gifting-button treatments, which found low visibility and confusion around “digital gifts” and informed recommendations for clearer copy and an explanatory modal.
  • Translated regional business needs into vendor requirements for shipping charges and promotion calendars, optional giftboxing and product exclusions, price adjustments and customer-service readiness. Coordinated requirements for contact-center guidance and the handoff between Ralph Lauren and vendor service teams.
  • Coordinated review of commercial and operating terms, including commission and invoicing arrangements, fraud and card-fee responsibility, and proposed regional exclusivity. Connected these terms with Finance, Legal and business requirements during the integration assessment.
  • Assessed the vendor’s SFRA-based cartridge against Ralph Lauren’s existing storefront architecture and evaluated the associated engineering, integration and operational requirements. Used architecture and finance findings to expose the unplanned implementation and business-user effort required before launch.
  • Stopped the planned integration across all regions and phases when unresolved reconciliation and implementation requirements, together with substantial unplanned operating work, outweighed the expected value. Secured alignment across the project team, product leadership and business stakeholders and personally communicated the decision to the vendor before contracts were signed or vendor payments made.
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Additional platform delivery across Ralph Lauren roles
  • Delivered shipping and checkout improvements covering estimated-delivery-date logic in the cart and shipping-method behavior for Unmade customized products. Coordinated requirements and validation so the purchase journey reflected the relevant fulfillment rules.
  • Expanded configurable gift-message character limits across eGift Card and traditional Gift Card product pages and gift purchases at checkout. Defined the business configuration requirement and validated downstream message handling with warehouse examples and testing.
  • Owned product work on out-of-stock PDP redirects and giftboxing experiences, translating customer and operational needs into changes to product-page behavior, gifting options and supporting messaging.
  • Shipped removal of misleading “Currently Unavailable” messaging from non-shoppable product pages and coordinated retirement of server-side ticker-banner test code, bringing customer-facing behavior and platform cleanup through delivery.
  • Enabled regional teams to localize facet meta titles and descriptions in SFCC Business Manager. Created the operating guidance used by SEO and contractor teams to apply the controls across regional experiences.
  • Delivered business-user controls for canonical tags in SFCC Business Manager and product-detail-page structured-data improvements, translating SEO needs into configurable platform capabilities and implementation requirements.
  • Delivered the ability for merchandising teams to hide category filters instead of deleting them, expanding business control over the customer-facing filter experience while retaining the underlying configuration.
  • Led requirements and delivery coordination for Twitter tracking, the Facebook Tracking API initiative and new RLEU display pixels, working with marketing, analytics and engineering stakeholders on tracking implementation and validation.
  • Delivered size-chart updates for men’s casual and dress shirts and Women’s Collection extended sizes. Coordinated specification needs and customer-facing chart changes within the broader size-and-fit backlog.
  • Drove platform work enabling ME/GE configuration in Pacenotes and a new inventory file supporting Forge’s local-inventory requirements. Coordinated business and technical stakeholders on the required configuration and data outputs.
  • Delivered the Ralph Lauren browser-tab favicon update as part of ongoing brand and customer-experience maintenance.
  • Advanced the Notify Me email redesign through requirements and vendor/procurement coordination, incorporating redesigned templates into the Zeta statement-of-work scope and delivery-planning discussions.
  • Developed discovery and test proposals for increasing Size and Fit Guide visibility and exposing gifting services on PDPs, preserving these opportunities in the roadmap alongside broader page and experience redesign work.
  • Investigated excessive OneTrust banner display with technical and vendor stakeholders; closed the issue after the behavior could no longer be reproduced.

COS / H&M GROUP

E-Commerce Site Planner and Publisher | Jun 2020 - Jun 2021 | New York, NY

  • Managed daily US site planning and seasonal campaign execution across product setup, publishing, enrichment, price updates, studio assets, navigation, and product-listing structures. Coordinated content and QA for accurate, timely launches, applying global ways of working to the US commercial calendar.
  • Built and maintained the US homepage, department landing pages, COS Magazine, and other editorial/non-PLP experiences in Adobe Experience Manager. Used custom HTML, CSS, and JavaScript to adapt content and customer-facing layouts within the platform's publishing constraints.
  • Configured customer-group promotions in SAP Commerce/Hybris, translating campaign requirements into eligibility, offer rules, codes, dates, and segment-specific ecommerce offers. Built IDC codes in Backoffice and coordinated promotion changes with US email, customer-service, and commercial partners.
  • Led US content A/B testing and experience optimization across homepage, category, PLP, and navigation surfaces using Optimizely, Google Analytics, Contentsquare, and customer insights. Partnered with UX to analyze click, scroll, exposure, and conversion behavior and refine key page designs and layouts.
  • Partnered with Product, UX, SEO, Merchandising, Marketing, IT, and Customer Service on feature development, seasonal drops, campaign delivery, and content optimization. Connected commercial priorities with platform capabilities and operational requirements.
  • Defined US-market business requirements for payment and checkout implementation, including Apple Pay, and translated customer-experience needs into integration and acceptance-testing scenarios with Product and Engineering. Represented the US business in validation of market-specific purchase behavior and communicated issues affecting the checkout experience.
  • Contributed US mobile-checkout requirements and ACCV testing across delivery/payment messaging, product trays, cart presentation, guest/sign-in options, checkout hierarchy, Klarna messaging, PayPal express, and shipping-threshold communication. Assessed which changes could be made through AEM/HTML and which required experimentation or Business Technology development.
  • Monitored conversion, site speed, click-through rate, exit rate, and campaign performance using Dynatrace, Google Analytics, and Contentsquare. Assessed platform bugs, escalated incidents, and translated analytics and customer feedback into merchandising, page-layout, and content improvements; maintained reporting for US trade and site-performance reviews.

URBAN OUTFITTERS

Web Content Optimization Coordinator | Jan 2020 - Jun 2020 | Philadelphia, PA

  • Planned, published, and monitored North American web and app content across homepages, app surfaces, category banners, landing pages, PLPs, and PDPs. Supported content operations spanning approximately 1,500 content pieces and 2,500 products per month.
  • Coordinated content QA, product presentation, publishing updates, and launch readiness to support merchandising and campaign calendars.
  • Measured content and commerce performance using Google Analytics and Dynamic Yield. Partnered with SEO, UX, Email, Search, Merchandising, Social, and Production on product-page performance, cross-sell, average order value, and units per transaction.

BRAND NETWORKS / UNILEVER ACCOUNT

Media Analyst - Paid Social | Aug 2019 - Jan 2020 | New York, NY

  • Worked within Brand Networks, a B2B SaaS advertising-technology business, using its proprietary platform to manage Unilever campaign operations, performance analysis, budget pacing, and optimization.
  • Owned paid-social campaign delivery and ongoing optimization for commercial initiatives across Meta, Twitter/X, Pinterest, and Snapchat. Managed trafficking, audience and placement setup, creative tests, budgets, pacing, optimization, and reporting in coordination with brand and agency partners.
  • Monitored delivery, click-through rate, and cost per acquisition; translated performance findings into targeting, creative, and budget recommendations for brand and agency partners.
  • Introduced a weekly spend-actualization check in the Twitter campaign pacing process to reconcile delayed platform reporting and improve budget oversight across managed campaigns.
  • Worked directly with Meta account and technical support teams on delivery, tracking, creative, and platform issues. Reproduced defects, documented campaign impact, managed support cases and priorities, and validated resolutions.
  • Met monthly with Meta teams in New York to review campaign performance, advertiser needs, and optimization opportunities. Combined platform troubleshooting with client-facing performance communication.
  • Proposed improvements to product managers for client data visualization and campaign optimization, drawing on hands-on use of Brand Networks' proprietary platform, campaign analysis, and client reporting needs.

EARLY MARKETING AND ADVERTISING EXPERIENCE

GOOGLE COMMUNITY LEADERS PROGRAM

Marketing and Events Team | May 2018 - May 2019 | Rutgers University

  • Developed digital marketing strategies for local nonprofit organizations using a $10K Google Ads budget, with goals of increasing community engagement, donations, and volunteering.
  • Connected nonprofit priorities with campaign planning and digital outreach through the university-based community program.

TOMMY HILFIGER

Advertising Intern | Sep 2018 - Dec 2018 | Greater New York Area

  • Supported stakeholder and campaign coordination across advertising, influencer activity, events, and social media.
  • Contributed to planning for the Zendaya Spring 2019 New York City out-of-home campaign within a budget below $400K, connecting campaign requirements with media and execution planning.

Regional Marketing and Retail Engagement Intern | Jun 2018 - Aug 2018 | Greater New York Area

  • Supported store activations and collection launches for North American marketing campaigns, coordinating collateral production and retail-facing execution needs.
  • Conducted competitive research across social marketing and drive-to-store activity to inform campaign and activation planning.

L'OREAL / MATRIX

PPD Global Digital Marketing Intern, Matrix DMI | May 2017 - Aug 2017 | New York, NY

  • Produced original Instagram and YouTube content and copy supporting marketing campaigns. Managed the social content calendar and curated high-performing user-generated content.
  • Coordinated with regional social teams across countries on local influencer activations, connecting global campaign priorities with regional execution.
  • Developed an Instagram Stories strategy focused on sales-supporting advertising features and targeted content planning; presented the final college-internship project to leadership.
  • Led brainstorming sessions with US and global media teams for upcoming product launches and always-on social content. Tracked earned media value across UGC, influencer activations, and campaigns and synthesized results for senior management.

PAPER MAGAZINE

Business Development and Advertising Intern | Jun 2016 - Aug 2016 | Greater New York Area

  • Supported development of Fortune 500 advertising campaigns spanning online, social, and print media.
  • Created RFP responses and integrated marketing presentation materials connecting client objectives with cross-channel campaign concepts.

ENTREPRENEURIAL AND CONSULTING EXPERIENCE

J.GRANT LLC

Founder and Consultant - Ecommerce and Brand Operations | 2025 - Present | Independent business

Build and operate the J.GRANT swimwear and apparel brand from product concept and sourcing through ecommerce launch, customer acquisition, fulfillment, and creative partnerships. Manage Tony's Collections brand and ecommerce consulting through J.GRANT LLC, partnering with its founder on strategy, product storytelling, creative direction, website-refresh planning, and wholesale presentations.

Selected highlights

  • Launched four swimwear colorways in XS–XL and a live Shopify-backed buying experience.
  • Own product development, sourcing, brand direction and commerce operations.
J.GRANT brand ownership and operations
  • Launched a four-colorway swim brief assortment in sizes XS–XL and a live Shopify-backed buying experience. Own product concepts, assortment planning, positioning, pricing and go-to-market decisions, translating design intent into product specifications, visual identity, merchandising and customer-facing storytelling.
  • Coordinate manufacturers, pattern makers and production partners on samples, fit, construction, sizing, quality feedback, quantities, schedules and shipping. Resolve revisions and supplier delays while aligning inventory with launches and collaborations. Subsequent fit development defines requirements for a reusable master block, graded specifications and construction notes.
  • Direct suppliers, sampling studios, and freelance photographers across product development and creative execution. Set deliverables, coordinate schedules, consolidate feedback, and manage revisions across external partners.
  • Manage Shopify storefront operations, product listings, merchandising, inventory, fulfillment, customer service, and performance review. Manage Amazon Seller Central listings, marketplace strategy, FBA planning, and shipment preparation.
  • Develop campaign concepts, product photography, styling directions, social content, and landing-page presentations. Use customer feedback and performance signals to refine offers, product positioning, assortment, and creative.
  • Manage Meta Ads Manager campaign setup, audiences, placements, creative tests, budgets, pacing, and performance monitoring. Connect acquisition activity with merchandising and landing-page decisions.
  • Develop wholesale line sheets, product/pricing presentations and retailer-specific introductions, including English and Spanish materials. Align pricing, landed product cost, available stock and buyer terms before wholesale commitments; coordinate stockist outreach, samples, product seeding and brand-partnership discussions.
  • Led creative and retail planning for the October 2026 Mexico City pop-up and content activation with Eugenio and Tony's Collections. Coordinated assortment, campaign assets, styling, product allocation, sample shipping, production milestones, pricing, and partner requirements.
  • Create partner and sponsorship proposals defining the concept, participating brands, audience evidence, social deliverables, and onsite presence. A prior collaborative post generated 7,209 views, with 47.7% of the audience in Mexico and 63.3% aged 25-34, informing activation planning.
View case
Tony's Collections client consulting

Brand and Ecommerce Consultant | 2026 - Present | Client engagement through J.GRANT LLC

  • Use DALL-E, Adobe Firefly, and Miro AI for apparel ideation, concept visualization, creative boards, and styling direction in collaboration with the founder.
  • Develop product-presentation and campaign concepts; select and style garments and accessories for planned photography and retail activations. Coordinate creative feedback, model suitability, and product selection with partners.
  • Lead brand and ecommerce consulting for Tony's Collections, including ecommerce strategy, product storytelling, website-refresh planning, campaign direction, and wholesale presentations in collaboration with the founder. Connect product and brand positioning with customer-facing imagery, merchandising, and sales materials.
  • Coordinated with the founder and Eugenio on the October 2026 Mexico City content and retail activation, including creative concepts, product allocation, partner feedback, and production milestones.

ADDITIONAL PROFESSIONAL EXPERIENCE

METROPOLITAN PROPERTY GROUP / OXFORD PROPERTY GROUP

Real Estate Agent | 2023 - 2024 | New York, NY | Part-time

  • Created and marketed residential rental listings, wrote property descriptions, and photographed apartments to present properties to prospective renters.
  • Managed rental clients and conducted apartment showings, building direct experience with agent workflows, client needs, listing content, and the rental-search journey.

COMMUNITY LEADERSHIP

  • Ralph Lauren Pride ERG, Project Manager Chair: Led global DEI activations and cross-functional storytelling initiatives in partnership with brand and marketing teams.
  • Creative community programming: Hosted and curated fashion and cultural events across New York, San Francisco, and Los Angeles, connecting community interests, creative partnerships, and brand storytelling.

EDUCATION AND CERTIFICATIONS

University of Illinois Urbana-Champaign

MBA, in progress | Business Analytics focus

M.S. in Management, December 2025

Completed Gies specializations: Strategic Leadership and Management; Value Chain Management

Rutgers University

B.A., Marketing and Art | Minor in Entrepreneurship

Central Saint Martins, University of the Arts London

Foundation Diploma, Fashion Design

Professional Scrum Product Owner I (PSPO I) | Lean Six Sigma Black Belt

TOOLS AND TECHNICAL EXPERIENCE

  • Analytics and experimentation: SQL, Adobe Analytics, Google Analytics, Tableau, Power BI, BigQuery, Optimizely, Monetate experiment requirements and diagnostics, Contentsquare, Dynatrace, AppsFlyer, A/B testing, cohort analysis, event instrumentation, and attribution validation.
  • Commerce, search, and content: Salesforce Commerce Cloud, SAP Commerce/Hybris, Bloomreach, Constructor.io, Dynamic Yield, Adobe Experience Manager, Contentful, Ektron CMS workflows, Shopify, Amazon Seller Central, and Klarna; technical product ownership across Adyen-supported payment flows, hosted-checkout handoffs, payment outcomes and order exceptions.
  • Customer identity, access and marketing technology: Snowflake and Zeta CDP customer-data project experience; email-based identity matching, eligibility flags, entitlement feeds, dynamic customer groups, registration/sign-in requirements, access grant and revocation scenarios; Salesforce Marketing Cloud activation requirements, customer segmentation, audience definitions and lifecycle communications.
  • Technical product delivery: Jira, Confluence, Airtable, Figma, Miro, API and feed specifications, request/response behavior, source-to-target mappings, schemas, field definitions and data dictionaries; integration acceptance criteria, UAT, regression testing, defect triage, failure recovery, release documentation and adoption guidance.
  • Payment and financial-operating requirements: SFCC/Adyen/Klarna integration behavior, approval/decline outcomes, cancellations, partial fulfillment, refunds and returns; order and tender classification, settlement files, reconciliation, Accounts Payable and invoicing dependencies, regional tax and voucher questions, mixed-basket attribution, net-sales and margin reporting, inventory-feed exceptions, and vendor go/no-go decisions.
  • AI and prototyping: ChatGPT, Claude, DALL-E, Adobe Firefly, Miro AI, HTML/CSS/JavaScript interactive prototypes, production LLM metadata workflows, structured prompts and outputs, product-data grounding, human-review and publishing controls, conversational-shopping product requirements, prompt and persona refinement, and AI vendor/use-case evaluation.
  • Context engineering and grounded AI product design: Structured LLM input schemas, source-content and catalog grounding, retrieval-augmented generation (RAG) concepts, audience and intent attributes, parent/child brand personas, conversational constraints, multi-turn context, content freshness and eligibility rules, format-specific ingestion, output requirements, human approval and source-fidelity evaluation.
  • Conversational-agent integration architecture: Google's Agentic Applications Shopping Agent, ChatMessenger/Web SDK and Sales Service API; merchant identity and token-service boundaries, InitializeSession/ExecuteChat session and conversation flow, session reuse and token-refresh concepts, product-search inputs, multi-item cart callbacks, product/quantity payloads, explicit success/error responses and CreateShoppingEvent attribution. Product requirements and platform integration knowledge spanning managed agent services and merchant-owned commerce actions; familiarity with Model Context Protocol (MCP) tool integration through the Google Shopping Agent architecture.
  • AI data and content platforms: BigQuery and BigQuery ML, Google Vertex AI, LeverageLabs recommendation and NLP/LLM services, Navigator audience/cohort inputs, Template Builder and Ektron CMS. Technical product work across recommendation tables, content scoring, metadata schemas, source-to-rendering dependencies, brand and audience configuration, campaign activation and operational validation.
  • AI product evaluation and operations: Google-versus-Constructor shopping-agent evaluation; Bloomreach-versus-Algolia RFP and pilots; inventory-grounded recommendation rules; merchandising QA and signoff; agent persona and policy requirements; elicitation UI and fallback design; multi-turn context and changed-answer scenarios; SKU resolution, service-confirmed cart outcomes and failed-action recovery; agent and regional SOPs; API request limits, usage allowances, latency targets, and vendor cost/contract evaluation.
  • Paid media and discovery: Meta Ads Manager, Meta Pixel, Google Ads, Pinterest Ads, Snapchat Ads, Twitter/X Ads, technical SEO, JSON-LD schema requirements, AEO/GEO discovery, Google Gemini feed and shopping-journey readiness, and Adobe AI-source measurement.
  • Product information and creative operations: Centric/PLM product-data exploration, proposed PLM/PIM/SFCC measurement flows, product attributes and taxonomy, digital-asset handoffs, content QA, supplier coordination, fit feedback, product photography, and creative direction.
  • Data and content validation: Source-to-index and feed-to-catalog comparisons; product and variant mapping; catalog-grounded assistant QA; cohort eligibility and experiment-event validation; localized metadata and keyword-relevance checks; structured-output validation, review staging, and failed-record retries.
  • Brand consulting and commerce operations: J.GRANT LLC consulting, independent-brand management, Shopify operations for J.GRANT, website-refresh planning, wholesale and retailer presentations, campaign direction, and cross-brand retail/content activation planning.