AI-Powered Trade Acquisition Engine
An AI-driven attribution and audience engine that feeds the ad networks a cleaner, customer-aware signal — so their machine-learning bidding optimises for high-value trade acquisition rather than raw conversion volume.
Key Results
The Challenge
The client sells natural stone to two completely different audiences from one website. Trade buyers — landscapers, contractors, garden designers — place orders that can run to five figures. Retail buyers spend a fraction of that, often starting with a small sample. Both look identical to the paid ad networks: a 'Purchase' is a 'Purchase'. So the platforms' AI bidding engines optimised against a conversion event worth, on average, very little — pulling budget toward easy retail clicks while the trade customer, the one actually worth acquiring, was a rounding error in the optimisation logic.
The Solution
We built a bespoke attribution and audience engine — an AI-driven layer between the client's customer database and their paid media accounts that feeds the ad networks a cleaner, customer-aware signal. Each purchase reports its true value and customer type, segments learn from live order data daily, and lookalike, suppression and retargeting audiences are all built from real trade behaviour — so the platforms' bidding AI can finally optimise for high-value trade acquisition instead of conversion count.
Key Capabilities
AI-Driven Customer Segmentation
Every customer is classified by purchase behaviour and account type — trade purchase, retail purchase, trade sample, retail sample, plus lapsed segments for each. The segmentation logic learns from live order data daily and re-scores customers as their behaviour shifts.
Server-Side Conversion Feed with True Value
Each purchase fires a conversion to the ad networks with the customer type and true order value attached. A high-value trade order arrives tagged as exactly that, not an undifferentiated 'Purchase' — giving the platforms' bidding AI the right thing to chase.
AI Lookalike Modelling & Suppression
Each segment seeds the ad networks' lookalike AI so prospects resemble the client's actual trade buyers, not their retail base. Existing trade and retail account holders are suppressed from acquisition campaigns so budget goes to net-new buyers rather than people already on the books.
AI-Timed Retargeting & Trade Sign-Up Goal
Abandoned baskets and sample orders are retargeted by funnel stage, lapsed trade buyers see add-on product ads timed to their predicted buying window, email audiences are suppressed during send windows so the client never pays twice, and trade account sign-ups are tracked as a secondary conversion goal the AI can optimise against.
By the Numbers
Want similar results?
Talk to our team about how AI can transform your business operations.
Loading contact form...
More AI Case Studies
Related AI Agency & Consultancy Content
London's leading AI agency — comprehensive AI consultancy, implementation, and enablement for ambitious businesses
Explore Our Complete AI Agency & Consultancy Solutions
Discover our comprehensive approach to ai agency & consultancy and how we can help transform your business.
Learn more