Your Google Shopping Feed Is Working. But Is It Actually Optimised?
Your Google Shopping campaigns are running, your products are approved and Performance Max is spending money. Brilliant.
But when did you last properly look at your product feed?
I don't mean checking that everything is approved in Google Merchant Center. I mean reviewing the information you're actually sending to Google: your titles, descriptions, attributes, categories and images. All the data that helps Google understand what you're selling.
Because a working product feed and an optimised product feed are two very different things.
I recently joined Chloë Thomas on the Keep Optimising podcast to talk about one of my favourite subjects (yes, I'm a bit of a feed geek). We covered product titles, Merchant Center rules, custom labels, SEO collaboration and the growing importance of richer product data.
But there's one thing I wanted to explore further. There's so much you can do with advanced feed optimisation, yet it's rare that I come across a feed that's actually ready for it. And that's genuinely quite sad. Especially when so many of the fundamentals aren't difficult to fix; they just need someone to take the time to review the data properly.
With Google continuing to develop AI-powered shopping experiences in 2026, there's even more reason to pay attention to the data you supply. So whether you've just connected your first feed or you've been running Shopping campaigns for years, let's look at what you should be doing, what you could be doing, and why the foundations still matter more than every shiny new feature.
🎙️ Keep Optimising Podcast: Google Ads Product Feed Optimisation
I had the pleasure of joining Chloë Thomas for episode 322 of the Keep Optimising podcast, Google Ads: Optimizing Your Product Feed for Better Results. If you're managing Shopping campaigns, I'd love you to give it a listen, especially if you've not had a proper look at your feed in a while.
In just over 30 minutes, we covered why product feeds deserve far more attention than they get: getting the basics right, and what you can do with titles, descriptions, categories, product types and custom labels. We also talked about something I feel strongly about: why SEO and PPC teams need to work together, rather than relying on feed rules to fix problems that should be solved on the website. And, of course, why accurate, detailed product information matters more than ever with AI.
Listen to the full episode:
And while we managed to squeeze quite a lot into just over 30 minutes, there's so much more we could have discussed, particularly when it comes to advanced feed optimisation.
So I thought I'd expand on some of those points here, explore the opportunities we didn't get time to cover and look at what Google's latest developments could mean for advertisers in 2026.
Your Product Feed Isn't Plug-and-Play
One of Chloë's first questions was whether a genuinely plug-and-play feed solution exists. My answer? It depends. Obviously.
Plenty of tools promise to connect your website to Google Merchant Center in a few clicks, and technically they can. Shopify has integrations that send product information to Google automatically, and dedicated platforms such as Channable offer more advanced capabilities. But connecting your products doesn't mean the information is complete, accurate or optimised.
Businesses with strong websites and solid SEO foundations usually start in a much better position, because their product information is already well structured. Others have titles that haven't been touched in years, inconsistent descriptions and missing attributes. And in my audits, it's rarely just one issue; it's usually a mixture of titles, categories, attributes and information that hasn't been reviewed properly. Both have technically connected their feeds to Google.
But they're certainly not starting from the same place.
Even with advanced tools, there's still work to do. Rules need creating, data needs reviewing, and somebody needs to know what they're trying to achieve.
A feed management tool should make optimisation easier, not replace the need for a strategy. And before any advanced work, you need to understand what's actually being passed to Google.
Start With Your Product Titles. Seriously.
If there's one thing every eCommerce advertiser should review, it's product titles. They help Google understand what you're selling and help shoppers decide whether your product matches their search. Yet I regularly see titles that are inconsistent, missing key information or built around internal naming conventions rather than how customers search.
Take a clothing brand selling Jeans called Joni. Internally, everyone knows the Joni Jeans... a LOT of people who had already been to a Topshop store knew what Joni jeans were. But how many people are searching for "Joni jeans" if they've never heard of the brand? They're far more likely to search for "High waisted Skinny jeans". Your title needs to say what the product actually is.
Google allows titles of up to 150 characters, but shoppers won't always see all of them, as titles can be truncated depending on placement. So put the most useful information first. Below is an example of a shoe :
Before: Gasella - Pewter - Brand Name
After: Silver Metallic Kitten Heel Slingback Shoes - Gasella - Brand Name
The second version immediately communicates the colour, finish, heel type and shoe style, while retaining the product name and brand, making it easier for Google to understand the product and match it to relevant searches.
I also recommend testing brand placement, particularly for retailers selling their own products. If your brand name takes up valuable space at the start of every title, moving it towards the end may let you lead with more useful information. That's not a blanket rule, though. For well-known manufacturers, or where brand is a major purchase factor, a prominent brand can make sense. Understand what customers search for, and test accordingly.
You're optimising your feed for the people buying your products, not to keep your internal brand team happy.
You don't need to rewrite thousands of titles by hand. Merchant Center's attribute rules (previously feed rules) can transform existing product information. If your feed already has separate attributes for colour, size and brand, you could create a rule that combines product type, colour and size into a more descriptive title.
The catch? The information has to exist in your data first, and the rules need checking. There's no point adding a colour to thousands of titles if half your products have the wrong colour. Automation is useful. Blind automation? Not so much.
Stop Ignoring the Rest of Your Product Attributes
Titles matter, but they're only part of the picture. Your feed contains a whole range of attributes, from price and availability to detailed product characteristics, and this is where I often find opportunities during audits.
Are your colours consistent? Are sizes correctly mapped? Do descriptions explain the actual product? Are you including the relevant product identifiers? What about material, pattern, age group or technical specifications where they apply?
These details help Google understand your catalogue and support more relevant product matching. Someone buying a television might care about screen size, display technology and resolution. Someone shopping for bedding might want material, thread count, dimensions or care instructions. Someone buying electrical equipment may need specific technical details before purchasing.
The more useful and accurate information you provide, the better Google can understand what you're selling. That doesn't mean stuffing keywords into every field. It means putting relevant information in the right attributes. There's a difference.
Google can categorise products automatically from the information it receives, which sounds fantastic until it gets something wrong. On the podcast, I mentioned how something as simple as nail varnish could be confused with automotive paint if the product information isn't clear enough. Google's systems are increasingly sophisticated, but automated categorisation isn't infallible.
The google_product_category attribute lets you supply a category from Google's predefined taxonomy. For unusual products, specialist industries or ambiguous descriptions, it's worth reviewing and, where appropriate, supplying the correct category yourself.
Before experimenting with anything advanced, make sure Google actually understands what you're selling. It sounds obvious, but you'd be surprised how often it's overlooked.
Now we're getting into the fun stuff. Unlike Google's predefined categories, product_type lets you create your own product hierarchy, up to five levels deep. A fashion retailer might use:
Women's Clothing > Dresses > Maxi Dresses > Wedding Guest Dress >
This organises your catalogue in a way that makes sense for your business and supports product grouping and reporting in Google Ads. Chloë and I also discussed seasonal or occasion-based classifications, such as wedding guest dresses, Christmas party dresses or a particular seasonal collection. Just make sure those classifications are accurate and useful.
One thing worth clarifying: product types aren't a magic keyword-targeting field. Adding "Black Friday TV Sale" to your product type doesn't guarantee you'll show for that search. Product types exist to help you classify and organise products, so use them strategically rather than as somewhere to stuff extra keywords.
Custom Labels: Small Fields, Big Opportunities
If you're running Shopping or Performance Max, custom labels can be incredibly useful. Google allows five, from custom_label_0 to custom_label_4. They aren't shown to customers; they exist to help you organise products for campaign management, reporting and bidding. You might group products by category, price range, profitability, seasonality or performance. There's no single correct approach.
I tend to reserve Custom Label 4 for promotions and offers. Promotions rarely cover a whole catalogue. A retailer might discount selected ranges for Black Friday, run a seasonal clearance or offer promotional pricing on specific collections, and a dedicated label makes those products easy to identify and group.
For the rest, I look at what makes sense for the business. For example:
Custom Label 0: Main product grouping
Custom Label 1: Product subcategory
Custom Label 2: Price range
Custom Label 3: Profit margin or performance grouping
Custom Label 4: Promotions and seasonal offers
This is an example, not a universal structure. A business with thousands of products and varying margins will need something very different from a retailer with a small premium collection. What matters is a structure that supports how you want to manage your campaigns. Get that right, and custom labels become the foundation for much more advanced optimisation, which we'll come back to shortly.
Your SEO and PPC Teams Should Be Working Together
This is something I feel strongly about. Feed optimisation shouldn't sit entirely with the PPC team, or entirely with whoever manages the website. It needs collaboration.
Your SEO team may be improving product page content and descriptions, adding structured data and keeping the site technically sound. Your PPC team, meanwhile, has search term insights, Shopping performance, conversion data and a clear view of what customers actually buy. Those insights should be shared.
If PPC data shows customers regularly search for a product characteristic that isn't prominent on your website, the SEO team should know. Likewise, better product descriptions and structured information on the site improve the data flowing into Merchant Center.
As I said to Chloë, we shouldn't keep using feed rules to put plasters over problems. The more plasters you add, the more complicated everything becomes. If product information is wrong or missing on the website, fix it there first, so the improvement benefits your site, your feed and every other channel using that data.
There are times when attribute rules are the most practical answer, such as a different title structure for Shopping or information that doesn't belong in the visible product title. That's absolutely fine. But feed rules shouldn't become an excuse to ignore poor data at the source.
We also discussed Google's changing image requirements, and there's an important deadline coming.
From 31 January 2027, Google is raising the minimum image resolution to 500 × 500 pixels across product categories and marketing methods. Google began issuing warnings in 2026 for images that won't meet the new requirement. Previous minimums for many placements were lower, so retailers with older catalogues should check whether their images need updating. Google also recommends 1,500 × 1,500 pixels or larger where possible. You can find the full requirements in Google's official product image documentation.
Image optimisation isn't only about dimensions, though. Are your images clear, accurate and representative of the item? Is each variant using the correct image? Do you have additional angles or detail shots? Are they suitable for the different surfaces where Google might show them? With richer, more visual shopping experiences, your images deserve as much attention as your titles and descriptions.
Here's something I've seen happen in real accounts. A team decides to optimise its product feed. Fantastic. They update product types, change some categories and make everything look much cleaner. But nobody checks how the Google Ads campaigns are structured, and suddenly products stop appearing in their expected product groups, because the campaign subdivisions relied on values that no longer exist.
Not quite the performance improvement they were hoping for.
This is one reason I prefer stable custom labels for campaign structures where appropriate, rather than relying entirely on attributes that change often. Before making significant feed changes, check how those attributes are used in Google Ads. And if multiple teams or agencies work on the account, communicate first. It sounds incredibly basic, but I've seen what happens when people don't.
Advanced Feed Optimisation: The Fun Stuff (If You're Ready for It)
As I mentioned earlier, I rarely come across feeds that are ready for advanced optimisation. Which is a shame, because this is the stuff I could happily geek out about for hours. Once those fundamentals are sorted, there's so much more we can explore.
But here's the exciting part. Once the foundations are right, there's so much more you can do: supplemental data sources, smarter custom-label strategies, title testing, profitability data and richer product attributes. And Google's work on AI-powered shopping gives us even more to explore.
Supplemental Data Sources
Supplemental data sources let you add information or update existing attributes alongside your primary product data source.
Say you want to test a new title structure on a selected group of products. Rather than changing titles on your website, you can create a supplemental data source with the product IDs and alternative titles, and apply them through Merchant Center. You can also use supplemental sources to add custom labels, fill in missing information or introduce new attributes.
You don't need an expensive feed platform to start, either. A Google Sheet works as a supplemental data source once you've enabled Advanced data source management in Merchant Center. Just remember that supplemental sources don't replace your primary feed, and they shouldn't become another way of ignoring problems with your website data.
Profitability and Smarter Segmentation
This is one of my favourite advanced opportunities. Two products might each generate £100 in revenue, but if one has a 50% margin and the other 10%, they're not equally valuable to the business. Look only at revenue and ROAS, and you may not be giving that difference enough weight.
Custom labels help here. You can group products into profitability tiers, identify higher-margin categories or separate products by commercial priority, then use those groupings for campaign segmentation, reporting and bidding decisions.
That doesn't mean putting your highest-margin products in their own campaign and expecting everything to improve. You still need to consider conversion volume, demand, competition and wider business strategy. There's also an important distinction between using margin data to segment products and actually optimising bidding towards profit. The latter needs reliable profit data and the right measurement and bidding setup. With those in place, though, you can have a far more interesting conversation than whether ROAS went up or down.
Testing Product Feed Changes
When Chloë asked how I approach feed experiments, my answer was: start small. I select a manageable group of products, make a change, and monitor what happens before considering a wider rollout. I might test whether putting material or size earlier in titles improves performance, or whether a different structure works better for a particular category.
The key is to compare like for like. If you're testing titles in October, don't simply compare against products that performed well in August without considering seasonality. Demand, promotions, competitor activity and your bestsellers all shift through the year. A before-and-after comparison gives useful directional insight, but it doesn't prove your feed change caused the difference. Use controlled testing methods where possible.
And don't forget the human element. AI tools can analyse performance data and spot patterns, but they don't understand your customers, your client's commercial priorities or why a product suddenly took off. That context still matters. The aim is to learn what works for your products and customers, not to make changes just to say you've optimised something.
This is where the SEO and PPC collaboration I mentioned earlier becomes useful for testing. Say a bedding retailer spots searches for "hotel quality cotton sheets", but its product titles only use collection names. That gives the team a specific hypothesis to test: would an accurate, more descriptive title perform better? Shopping and Performance Max don't always provide the same search term visibility as Search campaigns, so I'd also draw on SEO research, customer feedback and on-site search data when choosing what to test.
Getting More From Your Product Listings
Beyond campaign grouping, it's worth reviewing the information customers see in your listings: sale prices, delivery details and product ratings. Some rely on feed attributes; others involve separate Merchant Center settings or programmes, and availability varies by market. If you're running an offer, make sure the details are consistent across your website and Merchant Center. That's separate from the Custom Label 4 example earlier, which is about how you organise products within Google Ads.
Conversational Attributes: Preparing Product Data for AI Shopping
This is one of the more interesting developments of 2026. Google has introduced six optional conversational attributes in Merchant Center, designed to provide richer product information for conversational shopping experiences, including AI Mode.
Think about how people increasingly search. Instead of typing "washing machine 9kg", someone might ask: "What's a good washing machine for a family of five that has a quick wash cycle and isn't too noisy?" Google's AI shopping experiences are being built to understand and answer questions like that.
Question and answer: Answers to common product-specific questions.
Document link: Supporting PDFs, such as product manuals or installation guides.
Related product: Accessories, replacement parts and other related products.
Item group title: A shared title for products with multiple variants.
Variant option: Additional detail about the differences between variants.
Popularity rank: A product's relative popularity within your inventory.
These could be valuable for retailers selling technical products or items with many variations. An electrical equipment retailer could supply installation documents, compatibility information and answers to common questions rather than relying on a generic description. A fashion retailer could explain the differences between variants more clearly. I'm excited by the potential here, but I wouldn't rush to implement these just because they're new. If the existing product information is incomplete, that's still where I'd start.
But here's the important bit: these attributes complement your existing product information; they don't replace it. Google specifically advises against duplicating information already provided in descriptions, product highlights or product details. And adding them doesn't guarantee your products will appear in AI-generated recommendations. They're another way to supply useful information, not a magic visibility button. Read more in Google's official conversational attributes documentation.
One question worth addressing is whether these conversational attributes replace FAQs on your product pages. They don't. Your product page and your Merchant Center feed serve different purposes, even though they should work together. Product page FAQs help customers on your website understand what they're buying, address purchase concerns and cover information that doesn't fit a standard description. Conversational attributes supply structured product information directly to Google. They're complementary, not interchangeable.
A retailer selling a waterproof jacket might have a product page FAQ explaining whether it's suitable for heavy rain. That same fact could also be useful in its Merchant Center conversational data. What matters is that the information is consistent and accurate. And while structured data helps search engines understand your content, adding FAQ schema doesn't automatically mean Google will show FAQ rich results; those have separate eligibility rules.
AI Shopping Is Changing. Your Product Data Needs to Keep Up.
Conversational attributes are one example of how Google Shopping is developing, but they're not the whole picture. Visual search, richer product listings and AI-assisted discovery all create different opportunities for retailers to explain what makes their products relevant.
Before getting too excited about the newest attributes, remember that Google already supports extra product information through product_highlight and product_detail. These let you provide selling points and structured specifications beyond the standard description, and they're often overlooked.
A furniture retailer might include materials, dimensions, assembly requirements and care instructions. An electronics retailer might add battery life, connectivity, compatibility or technical specs. You may not even need new content: much of it may already exist in your product pages, specification sheets or manufacturer documentation. You might already have half the information you need. You're just not sending it to Google. The job is to spot what's missing and work out how to include it.
Beyond the image quality and accuracy checks I mentioned earlier, product video is another area worth exploring. Google has expanded support for product video in Merchant Center, and it could be particularly useful for clothing brands showing fit and movement, beauty brands demonstrating application, or equipment manufacturers showing products in action. A static image can only say so much.
Video isn't a substitute for good product photography, though, and supplying one doesn't guarantee Google will display it. Supported formats, policies and the shopping experience all affect where richer media may appear.
I'm not against these developments; quite the opposite. I'm interested in how retailers can use richer product data to answer more specific questions and show their products in more useful ways. But I'd rather test something because it solves a genuine problem than add it simply because Google has launched it. More data and more automation only help when you know what you're trying to achieve.
If you run Shopping campaigns alongside physical stores, accurate online product data is only part of the picture. You also need to consider local stock availability, store locations and how you connect online searches with in-store visits. This is where Local Inventory Ads and Performance Max with store goals become relevant.
A shopper might want to know whether a product is available to collect locally rather than wait for delivery, and Google needs accurate product, location and inventory data to support that. It wasn't the focus of my conversation with Chloë, but Hannah Zora Strong explores it in her episode of the Keep Optimising Google Ads series. It's another example of why accurate product data matters well beyond standard Shopping campaigns.
Where Should You Start? My Product Feed Optimisation Checklist
If you're now wondering whether your own feed needs attention, here's how I'd approach it. This isn't about making things complicated or buying another tool; it's about checking what's already there, spotting the gaps and fixing them.
Stage 1: Get the Foundations Right
Check your Merchant Center diagnostics. Review disapprovals, warnings and missing information.
Review your product titles. Are they consistent, descriptive and focused on how customers search?
Check product categorisation. Make sure Google understands what you're selling.
Audit your attributes. Look for missing colours, sizes, materials, identifiers, descriptions and specifications.
Review your product images. Check quality, accuracy and the upcoming 2027 resolution requirements.
Speak to your SEO and website teams. Identify which improvements should be made at the source.
Stage 2: Start Optimising Strategically
Once your data is accurate and consistent, look at:
Supplemental data sources and attribute rules
Custom labels and product segmentation
Profitability and margin-based groupings
Search term insights and title testing
Promotions, product ratings and additional product information
And check how any changes could affect your existing Google Ads campaigns.
Stage 3: Explore Advanced Opportunities
With those foundations in place, you can consider:
Conversational attributes
Product highlights and structured product details
Product videos and richer imagery
Product relationships and variant information
Emerging AI-powered shopping experiences
Not every business will need all of these. Focus on what will genuinely add value for your products and customers.
🔹 Final Thoughts
After years of working with Google Shopping feeds, it still surprises me how often they're overlooked. Businesses spend hours on campaign structures, bidding strategies, audience signals and Performance Max settings, yet the feed telling Google what they actually sell sometimes hasn't been looked at in months.
I get it. Feeds aren't the most glamorous part of digital advertising, and depending on your catalogue size, they can mean a lot of spreadsheet work (although personally, I quite enjoy that bit).
I'd love to spend more time exploring advanced feed optimisation, especially as Google's shopping experiences develop. And if you've already got the essentials sorted, I'd genuinely love to geek out about what else we could do with your data.
You don't need an expensive tool or the latest feature to make progress. Start with a proper audit, decide what needs fixing and build your experiments around what matters to your customers and your business.
Don't Panic. Just check what you're sending Google first.
More From the Keep Optimising Google Ads Series
A huge thank you to Chloë Thomas for inviting me onto the Keep Optimising podcast, and to Jyll Saskin Gales for recommending me as a guest!
My episode was part of a five-part Google Ads series featuring some fantastic people from across the PPC industry. The other episodes cover:
Jyll Saskin Gales: Which newer Google Ads features are worth exploring, and which to approach with caution.
Hannah Zora Strong: Using Google Ads to drive in-store visits, including Google Business Profile, Performance Max and Local Inventory Ads.
Ger Hayden: How Google Ads strategies are evolving and what advertisers should be reviewing.
Silvia Correas Osorno: Taking a full-funnel approach to Google Ads rather than focusing on individual campaigns.
If you're unsure where your feed stands, a product feed audit is a good place to start. It's about identifying what's missing, what could be improved and which opportunities are actually worth exploring. You can get in touch with me at 4M Digital Consulting if you'd like a second pair of eyes, or if you've already nailed the basics and fancy a conversation about advanced optimisation. And if you haven't listened to my episode with Chloë yet, do give it a listen!
You can also join our free Don't Panic PPC community, where we share knowledge, ask questions and help each other navigate the wonderful, occasionally frustrating world of paid advertising.
4M Digital is a Google and Microsoft Ads Partner specialising in paid search and paid social, from Google and Microsoft Ads to Meta, LinkedIn, Pinterest and TikTok. Working in paid media since 2010, we help brands, retailers and agencies grow through campaign management, audits, training and white-label PPC support.
