Turning paid social into a high efficiency acquisition engine

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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Oct - Dec YoY (2022 vs. 2023)

+39% in Orders

Refined segmentation across audiences, products, and creative enabled stronger identification of high impact entry products, driving higher order volume from new customers without sacrificing efficiency.

-50% in CPNB

Clearer signal quality and tighter prioritization significantly reduced the cost to acquire new buyers, improving unit economics across both new and returning customer segments.

+64% in ROAS

Better alignment between business level performance data and account structure increased flexibility and accuracy in optimization, leading to materially improved return on media investment.

+14% in Revenue

Structural and efficiency gains supported sustained revenue growth, demonstrating a more durable and self sustaining paid social model.

The problem

FRAME needed to improve the efficiency and margin profile of its Meta program while maintaining its role as a growth driver within paid social. Performance to date had been inconsistent, with limited clarity around which tactics, products, and audiences could support profitable scale.

New customer acquisition costs were approaching unsustainable levels relative to average order value, creating an over reliance on retention to drive growth. To unlock incremental upside, the program required clearer signal quality, stronger prioritization across products and audiences, and a structure capable of scaling without eroding margin.

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How We Did It

The Meta program was rebuilt around structure, prioritization, and signal clarity.

Campaigns were segmented by audience type, separating prospecting, retargeting, and retention to improve budget control and provide clearer optimization signals for new customer acquisition. Within this structure, product categories and product lines were tested independently, allowing performance to be evaluated and scaled based on true contribution rather than blended results.

Rapid testing across product groupings identified a set of high performing introductory products that resonated strongly with new customers. Investment was then concentrated behind these products, enabling the program to unlock both scale and efficiency early in the engagement.

Creative strategy reinforced this structure. Greater emphasis was placed on video formats to expand reach and engage new audience segments, while diversified messaging and creative styles allowed FRAME to maintain relevance across a competitive and visually crowded marketplace.

Together, these changes transformed Meta from an inconsistent performance channel into a more predictable and efficient acquisition engine, capable of driving growth while improving margin discipline.