First-Party Data
Your data is now your competitive advantage.
As third-party signals disappear, the brands that win are the ones feeding their own commercial data back into Google's algorithms. Transaction history, customer value, real margins - this is the data that separates profitable bidding from guesswork.
We help brands build first-party data infrastructure that makes Smart Bidding commercially intelligent.
Your Data Assets
Four data sources Google doesn't have access to
You already own the most valuable bidding signals. The challenge is structuring them so Google can actually use them.
Transaction Data
Order values, product margins, return rates, repeat purchase behaviour - the commercial signals that Google never sees but should inform every bid.
How we use it: Offline conversion import with profit-adjusted values. Smart Bidding learns what a genuinely profitable conversion looks like.
Customer Lists
Your existing customer base is your most valuable targeting asset. Segmented by LTV, purchase frequency, and product category - not just 'all customers.'
How we use it: Customer Match audiences for acquisition lookalikes, suppression of low-LTV repeaters, and bid adjustment by customer value tier.
Email & CRM Signals
Email engagement, browsing behaviour, abandoned carts, and subscription status. These signals predict purchase intent better than any third-party cookie.
How we use it: Enhanced conversions matching, CRM-informed bidding adjustments, and audience segmentation for campaign structure.
Product & Inventory Data
Real-time stock levels, margin by SKU, seasonal demand curves, and supplier lead times. This data determines which products deserve ad spend today.
How we use it: Feed-level bid modifiers, dynamic budget allocation by margin tier, and stock-aware campaign management.
Implementation
First-party data maturity model
You can't do everything at once. We follow a staged approach - each layer builds on the previous one.
Foundation
Get the data flowing
- Enhanced conversions configured with server-side verification
- GCLID capture on all conversion points
- Basic Customer Match audience uploaded monthly
- GA4 ecommerce tracking validated against backend data
Integration
Connect commercial data to bidding
- Offline conversion import with profit-adjusted values
- Customer value segmentation (High/Medium/Low LTV)
- Return and cancellation data fed back to Google
- Automated Customer Match updates via CRM integration
Activation
Use data to drive decisions
- Margin-aware bidding using real COGS data
- Inventory-aware budget allocation - spend follows stock
- LTV-based acquisition targeting - bid more for high-value lookalikes
- Seasonal demand forecasting informing budget pacing
Optimisation
Continuous commercial calibration
- Monthly P&L reconciliation against platform-reported performance
- Customer Match refresh automation with value tier updates
- Incrementality testing to validate 1P data impact on bidding
- New customer rate tracking as a primary acquisition KPI
First-party data is half the picture.
The data infrastructure matters. But so does what you do with it - and how you validate that it's actually working.