This post was sponsored by Channable. The opinions expressed in this article are the sponsor’s own.
Ever watched your top-selling SKU eat up the majority of your ad spend?
All while other high-margin or emerging products struggle to get any delivery?
You’re not alone.
Since launching in 2021, Google’s Performance Max (PMax) has fundamentally changed the ecommerce advertising landscape. But for many PPC teams, it also introduced a major drawback: limited visibility into spend distribution and performance drivers.
Without clear reporting on which placements, audiences, or creative assets are generating results, it’s easy to feel like you’re optimizing in the dark.
The good news? You don’t have to stay there.
This guide breaks down a practical framework for regaining control of your Performance Max campaigns, enabling you to segment products based on actual performance, improve budget efficiency, and make data-backed optimization decisions instead of relying solely on Google’s automation.
Where Performance Max Ad Spend Actually Goes
Most ecommerce brands start by organizing PMax campaigns around categories. Shoes in one campaign. Accessories in another. That seems logical and clean but can completely ignore how products actually perform.
Here’s what typically happens:
- Top-selling products monopolize ad spend. Google’s algorithm naturally prioritizes SKUs with strong historical performance, meaning your hero products continue to dominate delivery while other revenue-driving items struggle to scale.
- New arrivals never gain traction. With little to no performance history, new SKUs can’t compete in the auction, preventing them from generating the data needed to prove value.
- “Zombie” products remain invisible. Some SKUs have real potential, but rigid or static segmentation keeps them from ever receiving meaningful traffic.
- Manual optimizations drain time. Every adjustment requires pulling reports, making incremental changes, and hoping performance improves.
The result? Wasted potential, uneven budget distribution, and marketing teams stuck reacting instead of strategizing. You’re already doing the hard work; this framework helps that effort go further and helps you set and manage your PPC budget efficiently and effectively.
How To Make PMax Work Better
Instead of organizing campaigns by category, segment by how products actually perform.
This approach creates dynamic groupings that automatically shift as performance data changes with no manual reshuffling.
Step 1: Classify Your Products into Three Groups
Start by categorizing your catalogue based on real performance metrics: ROAS, clicks, conversions, and visibility.
Star Products
These are your proven winners, with high ROAS, strong click-through rates, and consistent conversions. Your goal with stars is to maximize their potential while protecting margins.
- Set higher ROAS targets (3x–5x or above based on your margins).
- Allocate budget confidently.
- Monitor to ensure profitability stays intact.
Zombie Products
These are the “invisible” items that haven’t had enough exposure to prove themselves. They might be underperformers, or they might be hidden gems waiting for their moment.
- Set lower ROAS targets (0.5x–2x) to prioritize visibility.
- Give them a dedicated budget to gather performance data.
- Review regularly and promote graduates to the star category.
New Arrivals
Fresh products need their own ramp-up period before being judged against established items. Without historical data, they can’t compete fairly in a mixed campaign.
- Create a separate campaign specifically for new launches.
- Use dynamic date fields to automatically include recently added items.
- Set goals focused on awareness and data collection rather than immediate ROAS.
Step 2: Define Your Performance Thresholds
Decide what metrics determine which bucket a product falls into. For example:
- Stars: ROAS above 3x–5x, strong click volume, goal is maximizing profitability.
- Zombies: ROAS below 2x or insufficient data, low click volume, goal is testing and learning.
- New Arrivals: Date-based (for example, added within last 30 days), goal is building visibility.
Your thresholds will depend on your margins, industry, and historical benchmarks. The key is defining clear criteria so products can move between segments automatically as their performance changes.
Step 3: Shorten Your Analysis Window
Many advertisers’ default to 30-day lookback windows for performance analysis. For fast-moving catalogues, that’s too slow.
Consider shifting to a 14-day rolling window for better analysis. You’ll get:
- Faster reactions to performance shifts.
- More accurate data for seasonal or trending items.
- Less wasted spend on products that peaked two weeks ago.
This is especially important for fashion, home goods, and any category where trends move quickly.
Step 4: Apply Segmentation Across All Channels
Your segmentation logic shouldn’t stop at Google. The same star/zombie/new arrival framework can (and should) apply to:
- Meta Ads.
- Pinterest.
- TikTok.
- Criteo.
- Amazon.
Cross-channel consistency compounds your optimization efforts. A product that’s a “zombie” on Google might be a star on TikTok, or vice versa. Unified segmentation helps you connect products to the right audiences on the right channels and distribute budget accordingly.
Step 5: Build Rules That Move Products Automatically
Here’s where the real efficiency gains come in. Instead of manually reviewing every SKU, create rules that automatically shift products between campaigns based on performance.
For example:
- If ROAS exceeds 3x–5x over your analysis window – Move to Stars campaign.
- If ROAS falls below 2x or clicks drop below your average (for example, 20 clicks in 14 days) – Move to Zombies campaign.
- If product was added within a set time limit (for example, the last 30 days) -Include in New Arrivals campaign.
This dynamic automation ensures your campaigns stay optimized without requiring constant manual intervention.
Get Smart: Let Intelligent Automation Do the Heavy Lifting
The steps above are effective, but implementing them manually across thousands of SKUs and multiple channels is time-intensive. Product-level performance data is fragmented across platforms, SKU-level ROAS requires stitching together multiple data sources, and building custom automation from scratch demands technical resources most teams simply don’t have.
This is where the right use of feed management and the right use of PPC automation really helps. For example, it can merge product-level performance data into a single view and let you build rules that automatically segment products based on criteria you define.
To see what this looks like in practice, Canadian fashion retailer La Maison Simons offers a useful reference point. They faced the same challenges-category-based campaigns where top sellers consumed the budget while newer items never gained traction.
After shifting to performance-based segmentation, they saw measurable improvements without increasing ad spend:
- ROAS nearly doubled over a three-year period.
- Cost-per-click decreased while click-through rates improved.
- Average order value increased by 14%.
- Their dedicated new arrivals campaigns consistently outperformed expectations.
- Perhaps most notably, their previously “invisible” products became some of their strongest performers once they received dedicated visibility.
The takeaway isn’t about any single tool, it’s that performance-driven segmentation works. When you stop letting one popular item take all the budget and start giving every product a fair shot based on data, the results tend to follow.
Learn more about the success story and the full details of their approach here.
Quick Principles to Keep in Mind
- Segment by performance, not category: Budget flows to what works, not what’s familiar.
- Use 14-day windows for fast-moving catalogues: Capture fresher signals, reduce wasted spend.
- Give new products their own campaign: Build data before judging against established items.
- Automate product movement between segments: Save time and stay responsive without manual work.
- Apply logic across all paid channels: Compounding optimization across Google, Meta, TikTok, and more.
Your Next Step
Performance Max doesn’t have to feel like handing Google your wallet and hoping for the best. With the right segmentation strategy, you can regain control, uncover overlooked opportunities, and make more intentional decisions about how you allocate your budget.
Curious whether your product data is ready for this kind of optimization? A free feed and segmentation audit can help you find gaps and opportunities, no commitment, just clarity.
Because better data leads to better decisions. And better decisions lead to results you can actually control.
Image Credits
Featured Image: Image by Channable Used with permission.
In-Post Images: Images by Channable. Used with permission.
