Google Ads for Fashion eCommerce

Start with the wearable inventory

A style can be advertised while its useful size range is almost gone. Review stock depth by size and colour, not only whether the parent product is in stock. A bestseller label is less useful when the variant a shopper wants cannot be bought. Define when a product should be reduced, paused or grouped differently as availability changes.

Build product information around the buying decision

Map garment type, material, fit, colour and size to accurate feed fields and landing-page variants. The title should help a shopper recognise the item. Avoid using a season or trend term that the product does not support. For an illustrative linen dress, fabric and cut may distinguish intent better than an internal collection name.

Price returns into acquisition

Revenue before returns can exaggerate the room available for advertising. Compare returns by category, fit and promotion cohort where data permits. Separate the refunded revenue already removed from the cost of handling a return. A campaign that sells more units with poor fit may increase the operational burden as well as reduce contribution.

Treat seasonality as an inventory decision

Plan around the time available to sell stock at a defensible contribution, not only the volume of seasonal searches. Record markdown periods and stock movements before interpreting a campaign test. A clearance group may deserve different economics and objectives from a replenishable staple.

Connect Shopping and Performance Max to product groups

Use segmentation only when it changes a decision: stable replenishment, seasonal stock, contribution or return risk. Do not create tiny campaigns for every collection without enough evidence to manage them. Evaluate branded demand and repeat purchases separately where the data supports it.

Make the mobile product page answer the fit question

Review the first screen, size guidance, model/fit context where available, variant availability, delivery and returns. Use accurate imagery to reduce uncertainty. A CRO hypothesis should name the missing answer and the behaviour it is expected to change, then be tested against comparable traffic.

Example diagnostic sequence

Methodology example: start with a high-revenue style that leaves weak contribution. Inspect discounts and returns, identify available sizes, compare the feed with the selected variant, then review the mobile size decision. The next action might be better size information or a stock rule rather than a new bid target. This is not a client result.

How I would start

First establish the measurement and product economics, then choose the feed, campaign or store constraint worth addressing. The €650 diagnostic provides a prioritised roadmap and review call. Ongoing management is scoped by catalogue, markets and implementation complexity.

Continue the diagnosis

• Merchant Center and feed guide
• Calculate order economics
• Use the 41-point checklist

Want this reviewed in your own account? See the €650 eCommerce Diagnostic. For ongoing ownership, explore Google Ads Growth for eCommerce.

About the author

Written by Andrei Visan, a hands-on Google Ads consultant since 2010. The examples here explain a diagnostic method; they are not client performance claims.