How P.Max Labelizer helped Slate.sk achieve a profit of €2,588.50 and a ROAS of 548.64%

Imagine having nearly 1,500 products in your store, only for your Performance Max algorithm to start pushing the ones with the lowest profit margins, while your actual bestsellers gather dust without getting a single impression. A nightmare for any e-commerce business, right?

This exact nightmare scenario was reality for the online store Slate.sk, which sells everything from household essentials to baby supplies. The solution? Stop relying on luck and bring a precise system to P.Max.

Slate.sk is a family-oriented Slovak online store that brings a wide range of household, health, and family care products under one roof. The core of their offering consists of health and hygiene items, accessories for mothers and babies, alongside home decor, household supplies, and footwear. Beyond just selling products, Slate.sk focuses on building genuine relationships with its customers, demonstrated not only through fast, personalized customer support, but also through their dedicated online magazine.

Problem Definition

When managing an e-commerce store with hundreds of products (1,491 products in this case), standard P.Max campaigns make it nearly impossible to manually track which products are using the budget effectively and which are simply “burning” it without results. Without segmentation, you risk having the Google Ads algorithm favor products with high data volume but low profit margins, or completely ignore potential bestsellers that haven’t been given a fair chance yet. P.Max Labelizer solves this problem by continuously analyzing the performance of each product and labeling it using custom labels directly in the feed.

Tool Implementation and Configuration

Labelizer acts as an intelligent filter that analyzes the performance of each individual product and assigns a label to it directly in Google Merchant Center. The initial settings were configured as follows:

Timeframe	Set to 30 days
Margin and Break-even Point	With a specified profit margin of 30%, the critical ROAS (Critical %ROAS) was automatically calculated at 333.33%. This represents the break-even threshold, products below this value generate a loss for the client
Profitability Threshold (Labelizer %ROAS	The system automatically set the threshold for the “Star” category to 416% (which sits at an ideal 25% above the break-even point)
Minimum Conversions	The threshold required to trigger label assignment was set to a minimum of 30 conversions

Strategic Distribution of Products into Campaigns

By exporting labels into custom label fields, we created three specific campaigns tailored to different business objectives:

1. “Star, Helper, and Core” Campaign

Maximum support for bestsellers. This campaign generates the primary profit and achieves an overall %ROAS of up to 423.01%. In this campaign, we also leveraged a great feature from BlueWinston, ensuring that only products with a minimum price of €24.99 are displayed. The “Loser” label is also included here; since the client currently has only one product with this tag, further segmentation isn’t strictly necessary right now, though it will definitely be advisable to separate this label in the future.

2. “Ghost & Zero” Campaign

Covers 1,416 products and achieves an impressive ROAS of 693.06%. It ensures that products previously ignored by Google get a chance to collect data,without this campaign, they would remain “invisible.” We also configured this campaign with a minimum product price requirement. By enabling the Use Zero label setting, products with zero impressions were identified and moved together with the client into this campaign.

3. “OFF” Campaign

Includes products with high spend but a ROAS below the critical 200% threshold. Instead of completely excluding them (via the ExcludedDestinationsForOffProducts feature), these products are kept running with a minimal budget. This allows you to capture occasional conversions at low cost without driving the campaign deep into losses (the current ROAS for this campaign stands at 133.75%).

What the Numbers Tell Us and Where We Stand

The tool’s effectiveness became fully apparent when comparing the long-term outlook against the most recent month:

Improved Profitability	Overall ROAS rose to 548.64% (an 11% increase)
Recalculation Efficiency	Thanks to the automatic mode (AutoUpdateInterval), the system checks data stability and updates labels in cycles ranging from 7 to 30 days, preventing chaotic changes caused by insufficient data.
Total Profit	Overall profit reached €2,588.50
Average Cost per Conversion	Stabilized at €10.49

Good to Know

The system operates fully automatically, fetching fresh metrics in 24-hour cycles to evaluate the placement of new products. If you need to react immediately to a margin adjustment or the start of a new season, you can use the ForceLabelUpdate feature, which recalculates labels during the very next update. Sending the updated labels to Google Merchant Center occurs every 4 hours, ensuring Google always has access to the freshest data for bid optimization.

Key Takeaways and Next Steps

Deploying Labelizer allowed the client to transition from broad targeting to a performance-driven structure. The current strategy of running a low-budget OFF campaign combined with an aggressive Star segment yields consistent results. Furthermore, setting a 30% margin alongside specific ROAS targets ensures the campaigns remain profitable and scalable over the long term.

The client appreciated not only the results achieved, but also the seamless implementation process: “Great communication with Patrik while setting up Labelizer.” Thanks to this close collaboration, we were able to integrate the tool quickly and without unnecessary delays, which immediately translated into better campaign structure.