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Promote: Google Ads for SMBs

Designed and launched a machine learning-powered ad platform that democratized Google Ads for SMBs, acquired by Web.com.

Mobile and desktop dashboards of a self-serve Google Ads app for SMBs

Impact

High-performing verticals identified to ensure ML efficiency.

Core assets required to get started, resulting in zero-friction onboarding.

Exit

Acquired by Web.com to address poorly served SMB market.

Key Decisions

Identifying the Beachhead

Instead of a generic tool, I used campaign data to find where the ML performed best (e.g., Home Services). This allowed us to build a "narrow and deep" UX rather than a "shallow and broad" one.

Focus on Trust

SMBs have frequently been burned by agencies' empty promises. So I designed for radical transparency instead, allowing SMBs to visualize demand and ROI before asking for a credit card.

Radical honesty as a key differentiator.

Self-Serve Empowerment

To disrupt the high-overhead agency model, I pivoted to a fully automated, self-service platform. This gave SMBs direct control over their ad schedules and budgets, providing the pricing transparency and autonomy they were missing from traditional managed services.

SMBs have the option to control their advertising schedule.

Designing for Localization

To move fast across English and French markets, I designed a responsive UI that can handle any text length, bypassing the need for manual design tweaks for every language.

Service and advertising available in English and French.

Frictionless Whitelabeling

Since SMBs often lack brand kits, I limited customization to a single logo and one color. This constraint ensured a professional, whitelabeled result while removing the "blank canvas" paralysis for users without design assets.

Customization constraints for simple whitelabeling.

Reality Check

The Scaling Trap

We succumbed to internal pressure to scale across hundreds of verticals prematurely. This diluted our focus and confirmed my initial research that a vertical-specific approach was more sustainable.

Missed Validation

We relied on existing agency channels for distribution rather than a pure product-led growth (PLG) model, which limited our ability to fully test the self-service acquisition funnel.

Key Lessons

Transparency as a UX Pillar

For skeptical SMBs, proving the "why" through demand visualization was more important than the "what." Trust is the primary conversion driver for high-stakes automated tools.

The Power of Constraints

Limiting customization didn't just simplify the build; it ensured every user-generated landing page maintained a professional baseline, protecting the product's perceived quality at scale.

Depth Before Breadth

Mastering a single vertical provides the high-quality data ML needs to truly outperform human experts. My experience with Promote solidified that sustainable growth in AI products comes from focused depth before broad expansion.

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