Linking Online Behaviour to Real UK Households
Most platforms stop at the cookie. Outra resolves anonymous online activity back to the household. Here's how reverse ETL makes it work.
The cookie tells you someone visited. The household tells you who.
Most analytics stacks stop at the session: a device, a path, maybe a conversion. The work of turning that signal into a real, addressable customer happens somewhere else. Or, more often, doesn't happen at all.
Household resolution is the bridge between the anonymous visit and the named buyer.
Why most identity graphs break at the front door
Browser-based identity is fragile by design. Cross-device matching is probabilistic. Cookies expire, get cleared, or are blocked outright. The result: you can describe sessions in detail, but you can't tell two visits from the same household apart.
The unit of media spend should be the household. The unit of measurement usually isn't.
What reverse ETL means in plain English
ETL moves data from your operational tools into a warehouse for analysis. Reverse ETL moves it the other way. Back out of the warehouse into the tools where it actually changes outcomes: Meta, Google, Klaviyo, your DSP.
For household data this matters because the intelligence is useless sitting in a table. It's only valuable when it's in the audience you're about to spend against.
Sync household-level audiences from Klaviyo to your ad platforms
No data warehouse, no engineering. Outra pushes household-resolved segments, Recently Moved, Owner-Occupied Homes, Ultra-High Purchasing Power, to Meta, Google and TikTok in minutes.
What Outra knows about every UK household
All attributes and segments are tied to a single identifier: the household, not an email, not a cookie.
- Employment stage
- Move stage
- Age band
- Family stage
- Occupancy status
- Property type
- Bedrooms
- Property size
- Property value band (£)
- Garden
- Garage
- Parking / Driveway
- Area type
- Region
- Purchasing power band
- Household income band
- Credit score band
- UHW (ultra-high wealth)
The Outra pipeline
- Signal in. First-party identity, logged-in users, hashed emails, form fills, flows in from your stack.
- Household resolved. Each identity is matched against the 30M+ UK household graph and described by named attributes.
- Audience back. The resolved household audience is pushed back into Meta, Google and your other ad platforms as a Custom Audience or onboarded segment.
What this unlocks
- Suppression. Stop spending on existing customers at the household level, not the cookie level.
- True incrementality. Hold-out cells you can actually trust because they're matched at the household, not the impression.
- Offline attribution. Tie an in-store purchase or a postal order back to the household that saw the ad.
Privacy posture
All resolution uses lawfully sourced address-level data and respects suppression and consent at the household level. No third-party cookies, no covert tracking. See cookieless targeting for UK D2C brands for the wider context.
The bottom line
The platforms that already run your media are good at delivery. They are bad at knowing who's on the other side. Reverse ETL is how you fix that, household first, channel second.
Sync household-level audiences from Klaviyo to your ad platforms
No data warehouse, no engineering. Outra pushes household-resolved segments, Recently Moved, Owner-Occupied Homes, Ultra-High Purchasing Power, to Meta, Google and TikTok in minutes.
