Using First-Party Data in Google Ads After Cookie Deprecation

Who this is for

If you are an SME owner, ecommerce director, or analytics lead, this guide focuses on the decisions that improve revenue and profit without drowning you in platform jargon.

What ‘AI-powered’ really means in Google Ads

Google’s automated campaigns can combine signals across audience, creative, bidding, and placements. The upside is reach and efficiency at scale. The downside is reduced visibility and control unless you set the account up properly.

The foundations that make automation work

1) Conversion quality and attribution

• Track the conversion that maps to profit (usually purchase or qualified lead, not a soft micro conversion)
• Ensure values are accurate (revenue, margin proxy, lead scoring where possible)
• Audit consent and first-party measurement so data does not disappear when tracking is restricted

2) Feed and landing page readiness

• Keep product titles, categories, and attributes consistent and complete
• Fix out-of-stock handling and ensure best sellers land on fast, persuasive pages
• Use clear pricing, delivery, returns, and trust signals on product pages

3) Account structure and guardrails

• Separate brand from non-brand where reporting and control matter
• Split campaigns by margin or product group if you have mixed profitability
• Use negative keywords and URL exclusions where appropriate to reduce waste

A practical optimisation routine

• Weekly: search terms and insights review, budget movement based on profit, feed health check
• Fortnightly: creative and asset refresh, landing page improvements based on behaviour data
• Monthly: incrementality checks, new product/category expansion, bid strategy review

Common mistakes to avoid

• Optimising to the wrong conversion event or poor-quality leads
• Mixing too many objectives in one campaign and then wondering why reporting is unclear
• Changing too many things at once and losing the ability to learn what worked