MarTech Strategy & Digital Marketing · Remote
Strategy that ships.
MarTech strategy & digital marketing: AEM, e-commerce platforms, GenAI operations. I operate at the intersection of marketing strategy and technical execution: seven years turning business goals into systems that deliver measurable outcomes.
(01 · About)
Same instinct,
different scale.
I operate at the intersection of marketing strategy and technical execution. In an enterprise setting, that means bridging marketing, IT, and product: owning platform strategy, content governance, and web production in Adobe Experience Manager, and carrying a central role in a large-scale AEM Cloud migration, where I authored the overwhelming majority of migrated content.
On the brand side, the loop closes end to end. A DTC activewear label scaled from zero to profitability as a single operator: paid media across Meta, Google, Pinterest, and TikTok, combined with SEO, CRO, A/B testing, and lifecycle email. Alongside that, an early-stage hardware brand, first year in, same playbook pointed at a harder problem.
GenAI and agentic workflows are my force multipliers: custom integrations, automation pipelines, and dashboards that connect GA4, Search Console, Meta, and Google Ads into unified decision-making tools. A front-end background means I implement, not just spec. I think in systems, move fast, and measure everything.
(02 · Strategy)
The machine is only
half of it.
Automation without strategy is just noise, faster. Everything I scale starts the same way: deep audience research, a sharp angle, copy built as a system, then tested until the data picks the winner. This is that side of the work.
Audience research that reads
like a case file.
Before any creative, media, or landing page decision, there's a documented profile of who it's actually for: her pains, the false beliefs holding her back, every alternative she's already tried, her exact objections, and the angle that finally lands. Below is the anatomy behind all eight avatars built this way: the fields that matter, and why each one earns its place.
Not the category-level complaint: the exact, sensory detail she'd use in her own words. That specificity is what makes copy feel written by someone who's actually listened.
The quiet internal objection standing between her and the decision, usually inherited from a past bad experience, not the product itself.
Every real alternative and near-substitute, with what specifically failed. Not to trash them, but to know exactly which gap this has to close.
Her own words, reflected back sharper than she could say them herself: the line that makes her feel understood before it makes a claim.
Copy is a system, not a vibe.
Every campaign ships five primary-text angles, not one guess: each with a distinct job, each testable on its own. The framework is brand-agnostic; the tone underneath adapts to whoever it's speaking for. Below: the five angles, and the psychological job each one is built to do.
Feeling
The emotional payoff of using it
Wins by making the reader picture the moment before she pictures the product: emotional, not descriptive.
Lifestyle
Where and how she actually uses it
Shows the product fitting into a life that's already full, instead of asking her to make room for one more thing.
Challenger
Direct contrast with the status quo
Names what she's already using and draws a clean line: comparison does more work than invention.
Social proof
Evidence other people already decided
A specific number always outperforms a vague claim: "customers love it" convinces no one; a real repeat-purchase rate does.
Product truth
The mechanical reason it's actually better
The one technical fact competitors can't say, explained simply enough that a non-expert still believes it.
Voice rules I set for this case: no emojis · no exclamation marks · no discount language · statements, not questions
I ran an A/B test on Meta's AI.
The human won.
When Meta offered its AI Marketing Assistant beta, I didn't adopt it. I tested it. Four weeks, controlled split: my hand-built campaign structure against the machine's. The AI spread budget across six generated creatives and diluted itself. The disciplined structure delivered a 24% lower CPA. Verdict: AI belongs inside the workflow, not in charge of it.
(03 · Selected work)
Four systems,
one operator.
Enterprise scale · 2022 to present
Platform & Governance
Web platform strategy & content operations
End-to-end web production and content governance for a Fortune 100-scale digital ecosystem: intake to publish across multiple business units, with regulatory compliance, WCAG accessibility, and structured QA on every deployment. Central to a large-scale AEM Cloud migration, authoring the overwhelming majority of migrated content alongside a global team.
- Reusable AEM template systems, documented for scale
- GenAI workflow adoption across marketing operations
- Adobe Analytics + SiteImprove performance reporting
The decision it drivesWhich page ships, when, with proof it's compliant before it goes live.
Independent brand · 2018 to present
Growth Engine
Full-funnel strategy, growth & platform
A premium DTC activewear brand, scaled from zero to profitability as a single operator. Catalog imagery is generated by a custom AI pipeline, visualized below: reference-based, color-accurate, catalog-ready. The store runs on reusable Liquid template systems across 23+ collections, and the blog publishes twice a week with zero manual intervention.
The decision it drivesWhere the next dollar goes: creative, budget, or inventory.
Internal tooling · ongoing
Systems &
Automation
R&D, self-directed
The machinery behind everything else. A Next.js command center unifying GA4, Meta, Google Ads, and Shopify into one real-time interface. An AI blog engine doing keyword research, writing, schema injection, and index submission on its own. An image pipeline that turns one reference photo into a full product catalog. A voice-controlled coding agent. None of it existed off the shelf.
- 3-layer tracking: GTM Web + Server-Side + Meta CAPI
- Full-funnel journey stitching: every ad, email, and organic touch mapped to the order it converts
- Proactive alerts: stock velocity, ad fatigue, baselines
- eBay integration: 60+ listings, bidirectional 30-min sync
The decision it drivesA hundred small calls a week, made correctly, without me.
Early-stage build · year one
Ground-Up Build
Product, growth & platform from zero
An early-stage hardware brand, starting where the growth engine above didn't: market research, competitor teardown, and demand signal before a single dollar of media spend. Same infrastructure, automated content, everything tracked, now pointed at a harder problem. Year one is about building the machine before scaling the noise.
The decision it drivesProve the model works before the budget scales it.
(04 · Capabilities)
What I actually do.
The technical layer isn't the job. It's how the strategy gets proven. Every capability below feeds the same loop: decide, ship, measure, adjust.
Platform & channel strategy
Owning the roadmap across AEM and e-commerce infrastructure: deciding what ships, in what order, and why. Architecture and template systems are the output, not the goal.
Growth & paid media
Meta, Google, TikTok, Pinterest. 50+ A/B tests across creative, landing pages, and checkout, decided by data, shipped by me.
Analytics & attribution
GA4, Adobe Analytics, GTM web + server-side, Meta CAPI. Full-funnel journey tracking, not last-click guessing, is the proof layer every strategic call is built on.
Technical SEO
Schema/JSON-LD, sitemaps, internal linking, Core Web Vitals. Measurable organic growth.
GenAI & automation
Claude API pipelines for content, imagery, and QA: a force multiplier for the strategy, not a replacement for it.
(05 · Contact)
Let's build something that runs itself.
Strategy, systems, and the data to prove it worked: one person, the whole loop.
Let's talk strategy