AI Datasets for Meta & Google Ads Scaling

Custom training datasets built to feed Meta and Google ad algorithms for scale.

Book a demo See what we build

At scale

Creative variants per campaign

Revenue

Seeded lookalikes

Dynamic

Creative optimisation

Automated

Feed refresh cycle

Overview

Systems that generate custom audience datasets and creative variants at scale, engineered to feed Meta and Google ad algorithms in ways the platforms reward. Removes the two hard ceilings on paid media scaling: audience quality degradation and creative fatigue.

What we build

Inside the AI Ad Datasets build

First-Party Audience DatasetsLarge custom audience datasets from your first-party data, enriched with behavioural and demographic signals, formatted for Meta Custom Audiences and Google Customer Match.
Revenue-Seeded Lookalike ConstructionLookalike seed datasets built around closed revenue signals rather than top-of-funnel events, so the algorithm learns from your best customers.
Creative Variant Generation at ScaleDozens to hundreds of ad creatives per campaign with controlled variation across hook, visual style, copy length, CTA, and proof point.
Creative Metadata StructuringAuto-tagging and structuring of creative metadata so Meta and Google dynamic creative optimisation can attribute performance correctly.
Performance Feedback LoopPipes performance data back into the generation system, winning patterns inform the next batch, losing patterns are suppressed.
Product Feed OptimisationFeed generation for Advantage+ Shopping, Performance Max, and catalogue campaigns with enriched product data and optimised titles, descriptions, and imagery.

Sample workflows

How it runs in practice

Weekly Creative Refresh Pipeline

System analyses performance of live creatives each Monday, identifies fatigue patterns, generates 40 new variants based on winning signals, and queues them for review before Tuesday launch.

Revenue-Seeded Audience Build

Pull closed revenue data from CRM, build structured seed file with top 500 customers, enrich with behavioural signals, upload to Meta as a Custom Audience for lookalike generation.

Stack

Tech we work with

Meta Ads APIGoogle Ads APIClaudePythonMakeMidjourneyRunwayn8n

Frequently asked about this build

How many creatives can the system generate per batch?

Depends on your approved brand guidelines and generation budget. We've run batches of 200+ variants for campaign launches. Volume scales with compute, not manual effort.

Does this require access to our ad accounts?

Yes, we need read access to pull performance signals and write access to push audiences and feeds. We use official platform APIs and follow least-privilege principles.

Can this work alongside our existing media buying team?

Yes. This is an augmentation layer, not a replacement. Your buyers define strategy and review outputs. The system handles the production and structured data work they don't have time for.

Every build is shipped from scratch around your exact workflows and tools, and the source code is yours to keep.

Book a Call