Pakistani Perfume Brand Scaling: 43% Conversion Rate Uplift via Performance Max

Performance Max campaigns presented two major structural challenges.

First, search term reporting was unavailable at the time, requiring traffic quality to be managed through account-level negative keywords and carefully segmented campaign structures.

Second, placement visibility was extremely limited. Without clear insight into where ads were being shown, budget optimization and waste prevention became increasingly complex. Additionally, heavy reliance on machine learning risked exposing ads to overly broad, low-intent audiences if not guided by precise data signals.

Unlocking PMax Transparency:

Our strategy focused on placement visibility, script-based exclusions, and audience signal refinement specifically tailored to the fragrance e-commerce market. Despite platform limitations, Admoon implemented a performance-focused framework built on control, insight, and AI guidance.

Search Term Control via Campaign Structuring

To compensate for missing search term data, we implemented account-level negative keyword lists and segmented campaign structures. This allowed us to control traffic quality and prevent budget leakage into irrelevant queries.

Placement Analysis and Exclusions

Advanced reporting methods were developed and exported to uncover hidden placement data. This visibility enabled us to identify low-quality placements and systematically reallocate spend toward higher-impact inventory.

Audience Signal Refinement for Fragrance Buyers

To counter overly broad machine-learning targeting, we supplied Performance Max with highly relevant audience signals and accurately defined search topics. This ensured the campaign reached high-intent users actively interested in perfumes and online fragrance purchases.