Defending efficiency while scaling search and shopping in a competitive market

FRAME uses Last Click Attributed results captured in Shopify. All figures below are tied to the Business Source of Truth, not reliant on platform attributed results or incremental measures.

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First 12 Months

+22% in AOV

Improvements driven by product strategy shifts and new approaches focused on selling higher AUR apparel.

+7% in ROAS

Despite higher CPCs and changes in product strategy, return on ad spend improved through stronger structure, relevance, and budget control.

+53% in Revenue

Gains in AOV, conversion rate, and CTR unlocked new investment opportunities and drove meaningful upside in total revenue.

The problem

FRAME needed to restructure its Google Ads program to unlock scalable growth while preserving efficiency. The existing account lacked sufficient segmentation across Search and Shopping, limiting relevance, suppressing Quality Scores, and making it difficult to allocate budget intentionally by brand category, geography, and product focus.

At the same time, increased competition from wholesalers and resellers placed sustained pressure on the Brand landscape, driving CPCs higher over time. This combination of rising costs and structural inefficiency required a more disciplined approach that could both defend high intent demand and enable incremental growth without eroding ROAS.

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How We Did It

Nodus rebuilt FRAME’s Google Ads account with a focus on precision, control, and scalability.

Across Search, we restructured campaigns to improve relevance and performance through deliberate segmentation. Campaigns were split by geography to enable tighter control over spend and efficiency at a regional level, and further segmented by gender to support more tailored messaging, improved landing page alignment, and clearer budget prioritization across FRAME’s core audiences.

At the foundation of the Search strategy was a focus on protecting and maximizing high intent Brand demand. Using historical performance data and keyword research, we restructured campaigns around FRAME’s most valuable brand terms to fully own the brand landscape at peak intent. As alignment between keywords, ads, and landing pages improved, Quality Scores increased materially, strengthening efficiency and competitiveness in the auction.

For Shopping, we applied the same discipline around structure and intent. Campaigns were segmented by geography, audience, and product category, with clear separation between Brand and Generic traffic. This allowed Generic campaigns to absorb broader discovery demand while Brand campaigns remained focused on high intent searches. Budgets were actively reallocated toward the categories and segments delivering the strongest combination of revenue growth and efficiency.

Together, these changes created a durable foundation that allowed FRAME to scale across Google while improving overall efficiency, even under sustained competitive pressure.