About
A product designer based in the Bay Area (San Jose).
Most recently I was at Meta, leading the Marketing message experience team — building 0→1 AI-powered creative tools and working closely with PMs, engineers, and data scientists along the way.
Before that, I was at Walmart Marketplace leading the seller acquisition and communications team — designing the Seller Center homepage, onboarding, notifications, and the overall seller experience.
Earlier in my career I did a completely different kind of design — experiential and brand work. Different medium, same job: I've always been a designer.
A WhatsApp MM is a promotional message delivered straight to an opted-in customer's inbox, not a feed. Unlike standard ads, a reply opens a real conversation.
MM can be sent through multiple channels. One is Meta Ads Manager, where it runs as a placement alongside existing ads — letting businesses reach opted-in WhatsApp customers with their existing ad spend.
MM setup was buried in a separate modal most advertisers never reached, and since it wasn't required, they skipped it — so MM often wasn't sent at all. The fix was structural: I moved it into the Creative flow itself, with its own field pre-filled from the ad text so it's never blank but still clearly distinct. That alone lifted delivery rate from near-zero to 95%.
MM was zero-to-one for most advertisers, so giving it its own field made it legible as distinct from ad copy — pre-filled from the ad text so it's never blank.
We added Gen AI text generation natively in the creative wizard, surfacing performance-optimized alternatives advertisers can accept or refine without leaving Ads Manager.
MM was being sent, but CTR was low, and only 1.4% of advertisers customized the message text. Multi-text variants were already proving their value on the ads side — a +16.33% CTR lift — so the opportunity was clear: bring that same lift to MM.
Phase 1 showed MM was buried at the bottom of the ad creative flow. Phase 2 opened a new path: since advertisers were already writing multiple ad text variants, we could extend those to MM automatically, without adding yet another input to an already complex workflow.
I explored three directions before deciding how to move forward:
I recommended Direction 2 as the MVP — always visible without adding UI complexity, and the lowest engineering lift.
With Direction 2 chosen, the open question was how visible to make the customization option, so I ran an A/B test.
Shows options only when needed; ads copy is used for MM by default.
Displays all options at once for immediate comparison.
We measured MM customization rate across a 10% then 50% rollout.
Full visibility made the option easier to find and act on — Option B won.
To push customization further, we redesigned Gen AI for MM — from one suggestion advertisers had to fully replace their text with, to up to 5 variants they can pick from at once.
We synthesized ~17,000 Marketing messages to find what drives high CTR in MM — tone and structure that work in direct messaging differ from standard ads. That informed Gen AI's suggestions: selective emoji use, personalization, under 550 characters, no sale-heavy language.
The more text options an advertiser adds, the more variants the system tests — surfacing whichever resonates most per consumer, and compounding the impact over time.
As the ads team began reworking the creative setup, I partnered with them early since MM and ads creative share the same space. That raised a bigger question: instead of two separate inputs, what if we unified them?
This is what that unified experience could look like.
This became the north star for where MM and ads creative should converge next: a single input, with Gen AI tailoring suggestions for each surface behind the scenes.
A WhatsApp MM is a promotional message delivered straight to an opted-in customer's inbox, not a feed. Unlike standard ads, a reply opens a real conversation.
MM can be sent through multiple channels. One is Meta Ads Manager, where it runs as a placement alongside existing ads — letting businesses reach opted-in WhatsApp customers with their existing ad spend.
Auto Reply and Quick Replies moved out of Creative into their own dedicated card — Chat Builder — at the same level as Creative in the L1 flow.
We didn't start from scratch: Click to WhatsApp (CTWA) already had a Chat Builder, and most MM advertisers are also CTWA users, so we built on the same pattern for one consistent setup surface.
Apply a full automation setup in one click from a saved configuration — Chat Builder auto-saves your setup every time you publish.
See what's configured before you publish — both automations shown inline.
Quick reply buttons delivered with the MM — when a consumer taps one, that response is sent instantly.
Triggered automatically when a consumer sends any message. Pre-filled by default so advertisers can publish immediately without any setup.
No live preview. Advertisers published without seeing the consumer experience.
Right panel updates in real time as advertisers configure.
Preview shows exactly what the consumer will see and receive.
Replaced nested fields with flat layout — button and response relationship is clearer.
Updated placeholder text to better match the quick reply configuration component.
Business AI closes that gap by turning every marketing message into an intelligent two-way conversation. AI responds instantly within the 24-hour free messaging window, so advertisers pay nothing extra to reopen conversations.
Existing MM advertisers complete a one-time BizAI onboarding, then the feature surfaces directly inside the Conversations card and Chat Builder — no new surface to learn.
I also redesigned the quick reply placement, moving the buttons below the CTA to visually separate the marketing message from the conversation entry point — the hypothesis being that a clearer distinction drives higher conversation initiation.
I audited Amazon, eBay, Etsy, and Shopify to understand what sellers experience elsewhere. All four had dedicated homepages with task guidance and growth features. Walmart had none of these — and was the only platform without a dismissible notification system or a promotions discovery surface.
| Platform | Guided tasks | Contextual metrics | Growth tips | Lifecycle-aware |
|---|---|---|---|---|
 |
✓ | ✓ | — | ✓ |
 |
✓ | — | ✓ | — |
 |
✓ | ✓ | ✓ | ✓ |
 |
✓ | ✓ | ✓ | ✓ |
 |
— | — | — | — |
I ran a content workshop with the product team to determine the essential requirements across three core areas: key business metrics, tasks, and growth. From there, we mapped each piece of content to the seller's lifecycle stage — whether they're onboarding for the first time or already an active seller — so the homepage surfaces the right information at the right moment.
A week-one seller and a three-year veteran need completely different things. I mapped the full journey to design an experience that adapts to where sellers are.
I explored several directions before converging on the final approach — testing how to balance metrics density with task clarity.
After several iterations, we developed the initial version of the homepage — a single layout organizing everything sellers need into three focused sections: To-dos, KPIs, and Promotions.
We tested this first-round design using the PURE (Practical Usability Rating by Experts) method with 5 evaluators. To set a baseline, we first tested the original onboarding flow, then integrated that onboarding into the new homepage to see how the To-do section improved seller comprehension.
The original onboarding prioritized the "Add Items" banner over the actual setup steps — sellers were pushed toward listing products before completing essential account setup, causing confusion and drop-off.
By integrating onboarding into the To-do section, sellers could clearly see what setup steps remained — in the right order, with the right priority — without being distracted by promotions.
The redesigned homepage brings together three focused sections in one scannable layout — adapting to each seller's stage and surfacing the right information at the right time.
In collaboration with the Content Designer, we developed a framework to determine what content belongs on the homepage and where — including where seller alerts should be routed, how each module is prioritized, and when content appears or retires based on the seller's lifecycle stage.
Promotional banners were a major pain point — they'd pile up, go stale, and drown out more important tasks. I designed a lifecycle system that controls how banners appear, surface, and expire.
