Help advertisers grow

Scale high-performing campaigns

Scaling budget guidance, designed 0 to 1.

As the lead designer, I drove one of Meta Ads' highest-impact initiatives: helping advertisers scale their best-performing campaigns. Advertisers struggled with identifying which of their successful campaigns were worth putting more money into, because raising the budget felt like it might break what was already working. I strategized and prototyped the concept to earn leadership buy-in, then designed the 0-to-1 experience across web and mobile and across surfaces. I later added an outcome forecaster, built from a new ML model that forecast outcomes for different levels of budget increases, so advertisers could see a visual, tangible view of the potential improvement before committing more money. It increased adoption by 400%+ and generated 0.15% incremental revenue.

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Opportunity score integration

Scaling guidance within opportunity score.

For opportunity score integration, I worked on how the new optimization score experience showed up in Ads Manager, including how it consolidated recommendations and ranked them by estimated performance impact. I helped design how several items from our guidance inventory were surfaced in that flow, with a focus on integrating the scaling high-performing campaigns guidance and showing it with its delivery status alongside other performance upgrades advertisers could apply.

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Unused budget

Redistribute unused budget to campaigns/ad sets that could benefit from additional budget.

I designed the unused budget experience in Ads Manager, which helps advertisers find budget that would otherwise go unspent and put it to work in the campaigns and ad sets that can use it. The experience showed advertisers where their unused budget was sitting and which campaigns and ad sets could benefit from additional budget, and let them confirm the redistribution without rebuilding their campaigns or raising their total spend.

Fix what is hindering delivery

Fragmentation

1-click ad and ad set consolidation.

On the advertiser guidance team, I designed the guidance and resolution flow for ad fragmentation, a common performance inhibitor where advertisers split budget across too many similar ad sets. I created a one-click ad consolidation resolution that turned a complex structural fix into a guided flow.

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Broken links

Broken link resolution.

I designed a 0-1 broken links experience, another guidance inventory item within the ad edit flow, which showed advertisers how to find and fix links in their ads that pointed to pages that could not be found or failed to load, so those issues stopped hurting performance.

Ad limits

Unblock delivery with ad limit guidance.

I designed the ad limits unblocking flow that surfaces as a tracker through the Ads Manager home page as well as within the campaign management table, which walks advertisers through resolving ad limit blocks without needing to contact support. It turned a confusing policy dead end into clear, actionable steps.

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Account spend limits

Unblock delivery with account spend limit guidance.

I also designed the account spend limit unblocking experience through a delivery status and guided workflow within the campaign management table, helping advertisers understand their caps and unblocking step to get their campaigns spending again.

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Give advertisers control and clarity

Automatic adjustments

Advertiser control over automation.

I designed the setup and management experience for automatic adjustments in Ads Manager, which lets advertisers choose which performance recommendations Meta can apply automatically to active campaigns and ad sets. The focus was control and visibility, with recommendation categories advertisers could enable deliberately, plus notifications and a clear record of changes after they were applied.

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Learning phase

Guidance around the learning phase.

I designed guidance around the learning phase in Ads Manager, with a focus on advertisers facing signal loss from EU data and consent rules, including GDPR and ePrivacy. When those rules reduced the conversion signals available to Meta, ad sets could take longer to gather roughly 50 optimization events in 7 days and were more likely to stay learning limited. The guidance explained what the Learning status meant, which edits could restart learning, and what advertisers should avoid changing while delivery was still stabilizing.

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Test guidance before it ships

Guidance Dogfooder

Testing guidance with real ad accounts.

I designed the entire product and built the backend for the Guidance Dogfooder, an internal tool that let anyone on the guidance team test advertiser guidance experiences before advertisers ever saw them. Before this tool, testing meant navigating broken queries, unknown experiment combinations, and scattered docs, which wasted time and made quality testing harder. In the tool, a person could select a guidance type like fragmentation or auction overlap, add parameters like experiment variant and surface, and get a list of test ad accounts to launch from, then walk through the full guidance flow in practice to find bugs and check how it worked. I built the backend data model for saved selections, while also fixing UI bugs. The tool reached about 150 users, launched Ads Manager more than 7,000 times, and saved about 266 hours of testing time, while making bugs easier to find and helping new team members learn the guidance inventory by trying it themselves.

Guidance that meets advertisers where they work

Guidance works when it meets advertisers inside the tools they already use, ranks what matters most, and makes the fix the easiest next step.