Marketing Messages at Meta — the detailed walkthrough
A deeper look at the strategy, the operating model, and the process behind two paid-messaging products — one shipped, one a 0→1 strategy. Written for recruiters and hiring partners.
Shipped · GA launch
WhatsApp — onboarding & audience growth, in depth
Aug 2024 → Nov 2025
Design lead · pod of 6 · onboarding funnel + audience acquisition
The strategic problem
Marketing messages only work if a business has an opted-in audience to send to. The bottleneck wasn't the message — it was everything upstream: helping a business discover the capability, get people to opt in, and grow a subscriber list worth sending to. I owned that upstream funnel end-to-end for the general-availability launch.
How I led it
I led a pod of six designers, splitting the funnel into ownable workstreams while holding the end-to-end journey coherent. We started from a full customer-journey map — discovery → opt-in → audience growth → first marketing message — and prioritized by where users actually dropped off, not by what was easiest to build.
What made it hard
Regulatory reality
Messaging is a consent-governed channel. Every opt-in pattern had to clear legal and policy review — design and compliance had to move together, not in sequence.
Global scale
The funnel had to work across very different markets and business sizes, from sole operators to large enterprises, in a GA launch.
My contribution, concretely
End-to-end concept design for the funnel; the design-strategy documentation that aligned the pod and partners; leadership reviews; the customer-journey artifacts the broader team worked from; and the project management to keep six designers shipping coherently toward one launch.
🔒 Confidential — NDA · do not redistribute
The full case-study deck (56 pages)
The end-to-end review deck — context, success metrics, the full walkthrough, and next steps. This is the internal version, including specific figures. Please keep it to your evaluation only.
Design lead · end-to-end product & design strategy
The brief
Bring marketing messages to a different messaging platform — but not by copy-pasting. Messenger has its own context, entry points, and user expectations. The work was to define, from a blank page, what this monetization surface should be: the onboarding, how businesses manage subscribers, where people enter, and how conversations start.
How I worked the 0→1
I framed the opportunity, designed the core surface and flows, and — most importantly — made it concrete enough that leadership, PM, engineering, legal, and policy could all evaluate and pressure-test it. 0→1 at a company this size is as much about building shared belief and legibility as it is about screens.
The honest arc
After roughly five months, leadership reprioritized the initiative and it didn't proceed to launch. I'm including it deliberately. Defining a net-new product surface from nothing — and getting an organization to seriously engage with it — is the senior skill. Reprioritization is a normal outcome of ambitious strategic work, and the capability transfers directly to the next ambiguous 0→1 problem.
What I'd take forward
A sharper instinct for sequencing 0→1 alignment earlier with the deciders, and for tying a net-new surface to a near-term, measurable wedge so momentum is easier to sustain through reprioritization cycles.
⚙️ Operating model
How I make design ship
Design war rooms → a playbook
I ran focused, time-boxed war rooms to force high-stakes design decisions to resolution, then documented the model into a repeatable playbook adopted across the team — so the operating improvement outlived any one project.
Critique, redesigned
I restructured a large design crit into a two-track format — deep focused critique plus broad cross-team visibility — driven by a team survey, balancing craft depth with org-wide awareness.
🤖 AI workflow, in practice
Building AI into the design process
Pre-review evaluation
A multi-lens AI workflow that reviews a design across several quality dimensions before formal review — surfacing gaps while they're still cheap to fix.
Second-brain system
A persistent memory + context setup that makes research and task management compound over time instead of resetting each week.
Enablement
Office hours and hands-on workshops that took non-technical designers from "AI-curious" to "AI-native," with published setup guides reused across teams.
Why it matters
The goal was never speed for its own sake — it was freeing the team's attention for the creative, high-judgment work only designers can do.
The specifics
The confidential numbers, I'll share live
Exact revenue projections, subscriber scale, and internal artifacts stay off the public web by design. I'm happy to walk through them in an interview or a private screen-share.