Google’s results are starting to feel like a product listing page. Filters, carousels, and product grids now sit above classic organic links and often take most of the mobile viewport. For large ecommerce teams, that changes how category demand turns into traffic and how product pages earn visibility.
Will Critchlow hosted this session with ecommerce SEO specialist Brodie Clark. Together they unpacked where grids appear, why some Search Console metrics mislead, how Merchant Center interacts with PDP content and schema, and how to measure progress with experiments that stand up in the boardroom.
Useful resources:
- How to Win in Google’s Product Listings
- Google Free Listing Types
- Free Local Listings
- AI Mode Tracking in Google Search Console
- Google Marketplace SEO
Key takeaways
Product grids now shape many ecommerce queries, including some brand terms. CTR inside grids can mislead because an impression may only exist after a user action. PDPs, feeds, and schema behave as one system, and a small miss can remove free listings. Variant richness often lives in the feed, so plans need to reflect that reality. Controlled experiments create proof that leadership can back, which is the path to control mode.
Google Product Grids Now Mimic PLPs: What That Means for Ecommerce SEO
The Popular products grid triggers on a large share of commercial queries and often arrives with siblings like Deals, In stores nearby, and Fast shipping. On mobile, the grid can take several scrolls before any classic result shows. This is not limited to generic category searches.
Brodie sees grids on brand terms where resellers with local stock divert clicks from brand pages. That shift means PLP and PDP owners now compete inside the grid first, then on the rest of the page. Popular items tend to hold grid presence, which then reinforces popularity. Consistent inventory, clean pricing, and reliable availability feed the system that decides what shows.
Why Search Console CTR Looks Inflated in Product Grids and AI Features
Search Console treats many grid impressions differently from classic web results. In several grid types an impression appears only after a user expands or clicks to reveal the URL. CTR rises because the user filtered first and the impression came second. A similar quirk shows up in some AI features on mobile when the URL is hidden by default.
Teams celebrate sky-high CTR, then wonder why revenue does not line up. Treat grid CTR as a clue, not a victory. Explain when and how impressions are created, track grid composition over time, and line up those shifts with changes to feeds and PDPs so the story holds together.
Merchant Center Feeds vs PDP Content and Product Schema: What Drives Visibility
Brodie’s working order of influence is simple: start with the page, then the feed, then schema. All three matter. A small schema mistake can remove free listings even when the feed looks perfect. One site-wide deploy dropped the image field from Product schema and listings vanished until the fix shipped. Strong programs treat the feed as strategy, not plumbing. Include every PDP image rather than only the hero, keep GTINs and brand data consistent, and keep price and availability truthful.
Use more expressive feed titles than the on-page H1 or title tag so variant attributes are visible at scale. Validate in the Merchant Listings report in GSC and in Merchant Center diagnostics.
Variant Pages, Canonicals, and Feed-Only Inventory: How Grids Pick Winners
Feeds list every size and color. Sites often canonicalize those variants back to one PDP. Your feed can be ten to one hundred times larger than your set of indexable URLs. The grid can match variant intent that your site does not expose as pages, which helps relevance and complicates analytics.
Some teams keep canonicalization and push richer variant detail into feed titles and attributes. Others index a small set of high-value variants, often top colors or sizes, then test whether that changes inclusion in grids or lifts total traffic to the product family. Internal linking and module placement also help crawlers map variants to demand without creating a page for every option.
Google Product Grids vs ChatGPT Shopping: Depth, Variants, and Freshness
Brodie’s testing shows ChatGPT Shopping often links to a single variant, while Google’s grid exposes a switcher that lets users flip variants inside the result. Merchant Center gives Google a reliable path to fresh signals like inventory, price, and offers. That depth and freshness still guide a lot of product discovery.
People want answers that connect to the right page, not a homepage that forces more work. Google’s newer AI surfaces are moving toward richer linking, which helps merchants that care about sending visitors to the exact PDP.
How to Measure Product Grid Impact with Controlled SEO Experiments
Grids and AI features scramble query buckets. LLM referrers sometimes send visitors to unexpected URLs. Relying on one metric bends the picture out of shape. Will’s view is clear. Treat clicks, impressions, and PDP traffic as a system, then prove lift with controlled tests and clear readouts.
At SearchPilot we run controlled SEO experiments on clicks and, when sensitivity helps, on impressions from Merchant Center or Search Console. Inclusion in a grid is a leading signal, so impressions can provide faster reads. We also track total organic clicks to PDPs and PLPs to capture net impact across classic results, grids, AI Overviews or AI Mode, and new referrers. The output is an executive-ready narrative that ties expected lift to engineering requests so the right work ships first. Teams move from validation to a steady cadence, then into control mode where search is a managed performance channel.
Marketplace SEO: Why Differentiated Inventory Outperforms Aggregators
Undifferentiated aggregators rarely hold organic share for long. Marketplaces with unique supply, real transaction control, or a clear value wrapper perform better. Treat the marketplace like a product. If listings simply mirror what Google already aggregates, organic growth stays limited. If the marketplace brings inventory that does not exist elsewhere or delivers value Google cannot replicate, search becomes a viable source of growth.
Monday Plan for Product Grid SEO: Feeds, Variants, and Tests to Ship
Start with grid readiness. Close Merchant Center errors, confirm that all PDP images flow to the feed, and encode key variant attributes in feed titles. If you operate stores, review the path to Local Inventory feeds since those units can appear on brand queries.
Clean up the data story. Annotate feature rollouts. Document how grid impressions are formed, then train stakeholders so CTR spikes and dips do not trigger false alarms. Track grid composition over time and align it with feed and template changes so cause and effect are clear.
Queue experiments per template. Enrich feed titles against a baseline. Surface the attributes that people filter for inside PDP modules. Strengthen category and brand clusters with internal link modules. Test selective variant indexation where demand exists. When the surface is a product grid, use impressions as a leading indicator, then confirm the final story with clicks and revenue.
Design the program to build trust. Ship short summaries that answer one decision each time: ship, refine, or stop. As win rates and confidence grow, expand the cadence across PLPs, PDPs, content, and navigation. That is how teams move search out of react mode and into control mode.
Put search in control mode with SearchPilot
Search is often the biggest channel and the least understood. SearchPilot makes SEO testable so leaders can move from guessing to knowing. We run controlled experiments across PLPs, PDPs, navigation, and content, then report clear uplift with timelines and confidence. Teams progress from quick validation to a steady test cadence to full control, which turns search into a performance channel you can plan and fund.
If product grids, Merchant Center, and variant handling sit on your roadmap, we can start with a focused plan. We will review feed quality, encode variant attributes in titles, improve image coverage, and design a round of tests that match how people filter and buy. We will also set up measurement that reflects how grids form impressions and how that flows into clicks and revenue.
Stop trying to predict the future. Experiment to discover it. If you want tailored test ideas for your top PLPs and PDPs, schedule a demo and we will share a starter list and a clear path from validation to velocity to control.
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