Google Merchant Center feed optimisation
Fix product eligibility first. Then improve what helps the right buyer find the right item.
A practical Merchant Center workflow for eligibility, stable IDs, variants, titles, taxonomy, images, commercial fields and product-level feedback.
Treat the feed as an evidence loop: make products eligible, improve the information that supports matching, then connect product performance back to the data.
Merchant Center is an evidence loop
A feed is never permanently perfect.
First make the right products eligible. Then improve the data that helps them match relevant demand.
Establish that prices, availability and destinations are accurate. Then improve the information that helps a product match a relevant search. Finally, connect product-level results back to the feed.
An order of work that avoids wasted effort
Diagnose the inventory before rewriting the feed.
The source workflow starts with scope, then source-of-truth reconciliation, then a controlled improvement.
Identify the affected inventory
Group issues by reason and product family. Distinguish account-wide restrictions from individual product problems. Prioritise eligible, in-stock products with defensible economics rather than fixing by row count alone.
Reconcile the source of truth
Check the storefront, platform export and Merchant Center record for the same variant. Record where each field originates. Repeated mismatches often need a source-system repair, not a spreadsheet override.
Test a controlled improvement
Change a defined group, keep a dated before-and-after export, and record other campaign or promotion changes. Use query and product feedback to decide whether the revised data better describes buyer intent.
Product identity and variants
Keep product identity stable and the advertised variant truthful.
Do not change identifiers simply to clear an error.
Product IDs should remain stable across routine updates. Use genuine GTIN, MPN and brand values where applicable, and do not invent identifiers for products that lack them.
- Keep routine product IDs stable
- Use genuine identifiers where applicable
- Match size, colour and other attributes to the selected landing-page variant
- Group variants consistently and do not present unavailable sizes as available
Title and description decisions
Describe the item in the order the buyer evaluates the category.
A useful title identifies what the item is and the attributes that distinguish it.
The source example changes “Oak Table” to “Oak dining table, 180 cm, natural finish”. That is only appropriate when every attribute is true for the advertised item.
A pet-food pack may instead need species, life stage, formulation and pack size. A fashion item may need product type, material, colour and size.
Keep descriptions factual and consistent with the store. Do not append a list of popular queries. When an attribute attracts irrelevant searches, investigate whether the wording is ambiguous before adding more terms.
Taxonomy, images and commercial fields
Build product data that supports both matching and decisions.
Taxonomy, imagery, price, stock and commercial labels should each have a defined job.
Taxonomy
Use product_type to express a useful store taxonomy. Use Google product category according to the applicable specification, and do not confuse the two.
Images and destination
Check that the primary image represents the exact product clearly. Review variants, image quality and whether the destination supports what the shopper sees.
Price, stock and delivery
Reconcile price, currency, availability, delivery information and promotions with the destination and checkout.
Custom labels
Use custom labels for decisions you can act on: contribution bands, seasonality, stock depth or test groups. Avoid labels that simply repeat product types.
Cost-of-goods data
Where COGS is used, check coverage and accuracy. COGS is not total variable cost and does not automatically turn a revenue ROAS target into a profit target.
Commercial feedback
Connect search-term relevance, product performance and store conversion before deciding the feed needs another rewrite.
Close the feedback loop
Keep a decision log so every change has evidence and a review condition.
Maintain a small record of product group, issue, evidence, proposed change, owner, date and review condition. Review search-term relevance, product performance and store conversion together.
If traffic improves but orders do not, check price competitiveness and product-page uncertainty before rewriting the feed again.
Stop an experiment when the implementation is wrong, the product set becomes incomparable or the stock position invalidates the decision. Do not call a change successful simply because revenue rose during a promotion.
Too many feed, campaign and store issues at once?
Turn the account review into a prioritised roadmap.
The €650 eCommerce Diagnostic reviews the wider acquisition system, including product economics, measurement, Merchant Center, campaign structure and the store experience, then turns the evidence into a prioritised action plan.
Continue the diagnosis
Put product data back into the wider acquisition system.
Once feed quality is understood, review the broader account, campaign structure and contribution.
41-point eCommerce checklist
Review economics, measurement, Merchant Center, feeds, campaigns, product pages and reporting.
Use the account checklistPerformance Max vs Standard Shopping
Choose the campaign structure around the learning job, measurement quality and product economics.
Compare Shopping and Performance MaxeCommerce profitability
Connect product groups and product data to contribution, acquisition limits and commercial decisions.
Connect product data to contributionOfficial documentation
Check the current Merchant Center specification before implementation changes.
Platform features and requirements change. The source page references these Google Merchant Center documents.
Diagnose before rewriting the catalogue
Fix the product-data constraint that is actually limiting the account.
If eligibility, product identity, campaign structure, measurement and economics are competing for attention, the €650 eCommerce Diagnostic turns the review into a prioritised roadmap.