Google Performance Max is built to optimize for conversions. Fast. Automatically. At scale.
But here’s the catch: it doesn’t understand your business. Not your margins. Not your stock levels. Not which products matter most to your strategy. Left untrained, PMax acts like a hyperactive intern — working fast, but with no sense of what really drives your profit.
That’s why smart e-commerce teams are shifting from hands-off automation to guided intelligence. The method? Embed your business logic directly into the system with structured, real-time product data. And that’s exactly what Expanly does.
We create a scoring model for e-commerce ads, map that to your catalog, and then push the data into ad platforms via the Expanly supplemental feed where it shapes every decision the algorithm makes.
Why Feed Optimization for Google PMax Is the Real Power Lever
Performance Max does not give you manual control over keywords, bids, or placements. But it does take its marching orders from your product feed. This makes feed optimization for Google PMax the most powerful lever you have if you use it correctly.
Most advertisers still treat the feed as a product database. Titles, prices, maybe a few categories. But when you view the feed as your campaign brain, everything changes.
This is where Expanly steps in, transforming your feed into a strategic control center with supplemental strategic data.
The Scoring Model: Your Business Logic in Action
At the core of our system is a dynamic, real-time scoring model for e-commerce ads. Every product in your catalog is scored and categorized based on:
Profit margins and contribution
Inventory velocity and stock levels
Return rates and customer satisfaction
Seasonal and regional demand shifts
Strategic roles such as launch, clearance, acquisition
For example:
A product with strong margin, deep stock, and seasonal relevance might get a Score 5/5
A low-margin item with stock constraints and a high return rate might fall into Score 2/5
This model is fully dynamic. As your data changes such as inventory updates, cost fluctuations, or shifting priorities, so do the scores. And this scoring model is not just for internal dashboards. It becomes the basis for how to train Google Ads with business rules.
From Score to Execution: Advanced Feed Segmentation with Expanly
We take the Expanly scoring model and push it into your ad platforms with a supplemental feed. This is advanced feed segmentation, automated.
You don’t need to tag anything manually. Expanly does it for you continuously.
This forms the foundation of your custom product strategy, one that PMax reads and reacts to in real time.
How to Train Google Ads With Business Rules Automatically
Without Expanly, training PMax with business logic is a patchwork of manual feed edits, rule-based campaign structures, and inconsistent data inputs.
With Expanly, training Google Ads with business rules becomes automatic:
Your business logic is defined once and embedded into the scoring model
That model updates continuously as your product data changes
The supplemental feed is enriched and updated automatically with custom labels
Your campaigns reflect live business priorities, not just historical performance
You no longer react to the algorithm. You guide it.
Real Performance, Not Just Conversions
This level of control unlocks real campaign value. You're no longer spending budget on high-ROAS low-profit SKUs or overexposing fragile inventory. You’re scaling ads on the products that matter, whether high-margin, strategic, seasonal, or acquisition-focused.
With Expanly, feed optimization for Google PMax is not about tweaking titles or fixing disapprovals. It is about engineering campaign behavior by embedding your goals into the algorithm’s decision-making process.
Turn PMax Into a Strategic Growth Engine
Performance Max will always carry a level of automation. But with Expanly, you can give that system the intelligence to act in your interest.
