You can have a strong product, clean creative, and a healthy budget – and still get mediocre Google Shopping results for one simple reason: Google does not “see” your catalog the way customers do. It sees a feed.

If your feed is incomplete, inconsistent, or overly generic, Performance Max and Shopping campaigns will spend, but they will not consistently win the auctions that matter. The fix is rarely a new bid strategy. It is product feed optimization for Google shopping – tightening the data that drives matching, eligibility, and prioritization.

This is the work that makes results repeatable: higher impression share on the right queries, fewer disapprovals, better click-through rate, and more stable ROAS when you scale.

Why feed quality drives performance (more than most teams admit)

Google Shopping is not a creative-first channel. It is a data-first channel.

Your feed influences three things that directly affect revenue: eligibility (can you show at all), relevance (will Google match you to the right searches and audiences), and competitiveness (will your offer win the auction once matched). When any of those breaks, you get the classic symptoms: spend concentrates on a handful of SKUs, search terms look off-target, CPCs drift upward, and your “best sellers” carry the account while everything else stalls.

The trade-off is that feed work is operational. It is not glamorous, and it requires discipline. But once it is done correctly, it compounds. A well-structured feed keeps working while you test creative, expand budgets, and run promotions.

The feed optimization framework we use in performance accounts

Most brands try to fix everything at once and end up creating new problems. A better approach is to optimize in layers, in the order Google evaluates products.

Layer 1: Clean eligibility and reduce preventable disapprovals

Before you improve performance, you remove friction. Start by auditing Merchant Center diagnostics and your product detail pages. The goal is simple: eliminate issues that throttle coverage.

Common culprits are price mismatches, shipping inconsistencies, missing identifiers, and policy flags caused by landing page content. These are not “nice to fix later” items. A disapproved product is dead inventory in your ad account.

Also be careful with aggressive automation. If your platform updates prices frequently and your feed refresh is slow, you can trigger recurring mismatches. The best setup depends on how often your catalog changes and how reliable your store data is.

Layer 2: Build titles that win queries without looking spammy

If you only fix one feed attribute, fix titles.

A high-performing Shopping title is not poetic. It is structured. It reflects how customers search and how Google understands the item. For most catalogs, this means leading with the core product type and the strongest differentiator, then adding the attributes that clarify intent.

For example, “Women’s Running Shoes” is a category. “Women’s Running Shoes, Cushioned, Size 8” starts to map to an actual query. The right structure varies by vertical, but the rule holds: put the highest-signal terms first because mobile truncation is real and Google also weights early terms.

There is a trade-off here. Overstuffed titles can reduce click-through rate and trigger a low-quality feel. The best titles balance query coverage with readability. You should be able to scan the SERP and feel confident yours belongs.

Layer 3: Fix product types and categories so Google stops guessing

Google_product_category and product_type are not the same.

Google_product_category is Google’s taxonomy. It helps with eligibility and matching and is especially important for regulated or sensitive categories. Product_type is your own hierarchy. It is how you segment, report, and steer performance.

A common failure mode is leaving product_type blank or dumping everything into one level. That makes it harder to isolate issues, harder to build asset groups around meaningful collections, and harder to understand what is driving performance.

Keep product_type consistent and multi-level where it helps decision making. Think in terms of how you would budget if you had clean data: category, subcategory, use case, margin tier.

Layer 4: Use images as a performance lever, not a brand exercise

Shopping is visual, but “high quality” is not specific enough. You are competing in a grid.

Your main image needs to read instantly at thumbnail size. That usually means clean background, strong contrast, accurate color, and a crop that makes the product obvious. Secondary images should support conversion on the landing page, but the primary image is what wins the click.

If you sell products where variants matter (pattern, finish, size perception), test images with your top SKUs the same way you test ads: one variable at a time, measured on CTR and CVR.

Be careful with lifestyle-only hero images. They can work, but they can also reduce clarity. If the product is not unmistakable, Google can misclassify, and users can bounce.

Layer 5: Feed pricing, promos, and shipping like a CFO

Google Shopping is brutally price-sensitive because comparison is built in.

If your pricing is not competitive, the feed will not save you. But you can prevent unforced errors by ensuring shipping is accurate, delivery times are realistic, and promotions are cleanly implemented.

This is where many brands lose margin without realizing it. They run blanket discounts, see a short-term lift, then discover the incremental volume came from low-intent clicks. A better approach is to align promotions to inventory and contribution margin, then reflect them correctly in the feed so Google shows the right annotations.

Layer 6: Add custom labels to control spend and testing

Custom labels are how you bring performance management into the feed. Without them, you are flying blind in PMax and Shopping because everything gets blended.

If you want structured testing, you need structured groupings. Use custom labels to tag margin tiers, seasonality, bestseller status, price buckets, and clearance inventory. Then you can set priorities, separate asset groups, and read results in a way that maps back to profit.

The “it depends” part is how many labels you use. Too few and you cannot control. Too many and you create noise. For most scaling brands, 3-5 well-defined labels are enough to steer budget decisions without turning reporting into a spreadsheet project.

The highest-impact attributes to prioritize

Not every attribute moves the needle equally. If you are looking for the 80/20, focus on the fields that affect matching and conversion signals.

Titles and product types usually drive relevance. Price, shipping, and promotions influence competitiveness. Images and reviews influence CTR and conversion.

GTINs and other identifiers matter more than many brands expect. In categories where Google has strong product graphs, missing identifiers can reduce visibility or push you into less favorable comparisons.

If you have to sequence the work: fix eligibility first, then titles and categorization, then images and offer competitiveness, then labeling for control.

How this plays with Performance Max

Performance Max uses your feed as the foundation. Even if you have strong creative, the feed is still the system of record for what you sell and how it is understood.

If your feed is messy, PMax often leans into a small subset of products and repeats the same learning loop. If your feed is structured, you can segment asset groups around meaningful product sets and evaluate performance with fewer confounding variables.

One caution: if you make too many feed changes at once, you can destabilize learning and misread results. Treat feed improvements like experiments. Stage them, measure them, and keep a changelog.

A practical operating rhythm for ongoing optimization

Feed work is not a one-time project, especially for brands that add SKUs, change pricing, and run promotions.

Weekly, you review Merchant Center diagnostics, product coverage, and any sudden drops in impressions or approved items. Monthly, you revisit title patterns, category mapping, and performance by custom label to find where efficiency is leaking.

Quarterly, you do a deeper audit: are your best queries still mapped to your best products, are new competitors forcing pricing pressure, and are your top images still competitive on the SERP.

This rhythm keeps you out of the reactive cycle where the feed only gets attention when performance breaks.

What “good” looks like when it is working

You will feel the difference when the feed is doing its job.

Search term quality improves. Spend distributes more intentionally across profitable SKUs. New products get traction faster because Google can classify them correctly. And when you increase budget, you see more volume without the same ROAS collapse.

The goal is not perfection. The goal is controllability. A feed that is structured, consistent, and tied to margin gives you levers you can actually pull.

If you want a performance partner to implement a structured feed system as part of a full-funnel Google Ads program, Proline Web builds these operating models for scaling brands at https://prolineweb.com.

Your catalog is already a dataset. Treat it like one, and Google Shopping starts behaving less like a gamble and more like an acquisition channel you can run on purpose.