Lovesize: Boosting Performance in Plus Size Fashion through Geeko DCO

Our strategy for Lovesize was built around a profitability-first performance marketing mindset, combining solid tracking, a clear Meta Ads structure, and the effective use of the Dynamic Creative Optimizer (DCO).

The foundation of every high-performing campaign is reliable data. Initial focus was placed on accurate event tracking and utilization:
● Optimization of Meta Pixel & Conversion API.
● Event prioritization with emphasis on purchases and order value.
● Clear funnel mapping (View Content → Add to Cart → Purchase).

The goal was not simply to “track” conversions, but to provide Meta with high-quality signals, enabling optimization toward users with genuine purchase intent.

The advertising structure was designed with sustainability and net profit in mind, not just sales volume.
● Strong focus on catalog campaigns (Sales / Purchases).
● Use of historical data for more efficient targeting.
● Gradual budget scaling only on ad sets with positive performance.

Performance evaluation was done holistically, taking into account: ● CPA
● CTR & CPC (as relevance indicators)
● Overall efficiency in relation to product profit margins

This approach ensured that scaling decisions were based on real profitability, rather than on metrics that look good on paper but don’t reflect true business impact.

DCO was a key tool in improving relevance and performance.
● Connection of the Lovesize product feed
● Creation of dynamic creatives adapted to: the product, user behavior, and the stage of the funnel.

The dynamic rotation of images, headlines, and products enabled:
● Better product–user matching.
● Higher engagement.
● Lower cost per click and per purchase.

The strategy remained flexible and data-driven, with continuous optimization at its core:
● Daily performance monitoring.
● Creative testing through DCO instead of isolated ads.
● Identification and gradual scaling of winning combinations.
● Reduction of spend on underperforming segments.

The result was a self-optimizing advertising system that continuously learns from data and adapts to maximize efficiency.