Managing thousands of products in Performance Max often leads to budget imbalance. Some products take most of the spend, others get no visibility, and waste increases. At the same time, scaling Search campaigns without losing control is not easy.
Can you reduce waste, improve product coverage, and scale both Performance Max and Search efficiently? One of our clients proved that you can.
The client is one of the world’s largest sporting goods retailers, designing and selling equipment, clothing, and accessories across dozens of sports categories. The company operates both physical stores and a strong e-commerce platform. Due to a wide and diverse product catalog, campaign structure and automation are critical to maintaining scalable performance.
A detailed audit via Product Analytics (focused on Shopping & Performance Max data) uncovered structural inefficiencies in product-level budget allocation. The data showed:
This created a risky situation. Budget concentration was high, product coverage was low, and scaling could easily reduce efficiency.
The client’s goal was clear: Increase total revenue and scale campaigns, but keep the ROAS effectivity as it is or better.
Without restructuring, scaling would only amplify existing inefficiencies.
The solution was not about increasing budgets. It was about smarter segmentation and better distribution. The strategy focused on two main pillars:
Originally, the account had three Performance Max campaigns divided by product categories. While simple, this structure did not reflect real product performance.
A new segmentation model based on a ROAS Product Strategy was introduced. Products were grouped according to ROAS and click performance into clear brackets:
This structure changed budget logic completely. Instead of letting Google distribute spend across categories blindly, allocation became performance-driven at product level. Underperformers were controlled. Profitable products gained visibility. Scaling became predictable.
Performance Max was then safely slightly expanded: +7% spend, +15% revenue growth
Revenue grew faster than spend which means that scaling did not damage efficiency.
While Performance Max was optimized using ROAS-based product segmentation, Search was rebuilt structurally for scale and coverage expansion.
Campaigns were created for all strategically important categories:
This significantly expanded reach while maintaining control.
Dynamic Search Ads (DSA) were implemented to cover product-level searches. Instead of manually building thousands of keywords, automation handled large-scale coverage while maintaining performance monitoring.
Both strategies allowed Search campaigns to grow aggressively without increasing operational complexity. The result was strong and controlled growth with spend growing by 104% and revenue by 108%.
To further improve customer experience, client used Dotidot to scrape data they did not have in their feeds yet. They extracted detailed product attributes such as weight, size, usage and other parameters or technical specifications.
This enriched data was exported to a ChatBot system, which now uses it to recommend relevant products in real time.
This way, client’s team connected performance marketing with customer support. Wow!
