Will customers feel surveilled?

We design for the opposite. Personalisation is grounded in the customers own behaviour on your store, not third-party tracking. We avoid the dark patterns (fake urgency, manipulative copy) that make personalisation feel intrusive.

What lift should I expect?

Personalisation lift varies wildly by category, traffic profile and current state. Most stores see 5 to 15 percent revenue lift on recommended-product placements alone; homepage personalisation typically adds another 3 to 8 percent. Honest target after discovery.

How do you measure lift?

Control cohort. A randomly assigned slice of traffic gets the non-personalised baseline; the rest gets personalised. Both populations are statistically identical so the conversion delta is real, not coincidence.

What about GDPR and consent?

Customers who opt out of personalisation cookies get a non-personalised experience. We store no personally identifying data in the personalisation models. Documentation goes to your DPO.

Can the merchandising team override?

Yes. Curated placements, pinned products, banned recommendations all manageable from the merchandising console. The model is a starting point; humans have the final say.

AI Automation for Ecommerce

AI Personalisation

AI personalisation across product recommendations, homepage, email and on-site copy. Privacy-first, consent-aware.

Timeline: 6 to 10 weeks
Surfaces: Recs + home + email + copy
Privacy: Consent-aware
Measurement: Control cohort

Overview

What it is.

AI-driven personalisation across product recommendations, homepage layouts, email content and on-site copy. We deploy our published personalisation module or build a custom integration. Privacy-first by default: consent-aware, no third-party trackers, model decisions auditable. Most engagements ship in 6 to 10 weeks. Lift measurement against a control cohort holds for the duration of the engagement so we can prove the business impact, not just the conversion delta.

What you get

Deliverables.

Personalisation engine integrated with your platform
Product recommendation modules (you-might-like, frequently-together, recently-viewed)
Homepage personalisation rules per customer segment
Email content personalisation
On-site copy variations driven by intent signals
Control cohort for lift measurement
Privacy and consent compliance documentation
Operations runbook for your merchandising and marketing teams

Honest limits

What it isn't.

Personalisation lift depends on traffic volume; very small stores may not see significance
We respect consent; customers who opt out get non-personalised experience
Some personalisation surfaces (checkout, account) are intentionally excluded

Not sure if it's a fit? Email us. We'll tell you straight.

How it works

From inquiry to handover.

01
1. Discovery
Audit current behaviour. Confirm surfaces to personalise. Map consent posture.
02
2. Foundation
Engine integrated. Control cohort split. Privacy and consent flows verified.
03
3. Build
Personalisation surfaces shipped in priority order. Each measured against control.
04
4. Optimisation
Ongoing tuning of rules and models. Monthly lift reporting.

Frequently asked

Questions we get from people about to book.

Will customers feel surveilled?: We design for the opposite. Personalisation is grounded in the customers own behaviour on your store, not third-party tracking. We avoid the dark patterns (fake urgency, manipulative copy) that make personalisation feel intrusive.
What lift should I expect?: Personalisation lift varies wildly by category, traffic profile and current state. Most stores see 5 to 15 percent revenue lift on recommended-product placements alone; homepage personalisation typically adds another 3 to 8 percent. Honest target after discovery.
How do you measure lift?: Control cohort. A randomly assigned slice of traffic gets the non-personalised baseline; the rest gets personalised. Both populations are statistically identical so the conversion delta is real, not coincidence.
What about GDPR and consent?: Customers who opt out of personalisation cookies get a non-personalised experience. We store no personally identifying data in the personalisation models. Documentation goes to your DPO.
Can the merchandising team override?: Yes. Curated placements, pinned products, banned recommendations all manageable from the merchandising console. The model is a starting point; humans have the final say.

Ready to start?

Tell us about your project.

A member of our team reads every message. Replies within one business day. No sales call required.

See all services

AI Automation for Ecommerce

AI Personalisation

AI personalisation across product recommendations, homepage, email and on-site copy. Privacy-first, consent-aware.

Timeline: 6 to 10 weeks
Surfaces: Recs + home + email + copy
Privacy: Consent-aware
Measurement: Control cohort

Overview

What it is.

What you get

Deliverables.

Personalisation engine integrated with your platform
Product recommendation modules (you-might-like, frequently-together, recently-viewed)
Homepage personalisation rules per customer segment
Email content personalisation
On-site copy variations driven by intent signals
Control cohort for lift measurement
Privacy and consent compliance documentation
Operations runbook for your merchandising and marketing teams

Honest limits

What it isn't.

Personalisation lift depends on traffic volume; very small stores may not see significance
We respect consent; customers who opt out get non-personalised experience
Some personalisation surfaces (checkout, account) are intentionally excluded

Not sure if it's a fit? Email us. We'll tell you straight.

How it works

From inquiry to handover.

01
1. Discovery
Audit current behaviour. Confirm surfaces to personalise. Map consent posture.
02
2. Foundation
Engine integrated. Control cohort split. Privacy and consent flows verified.
03
3. Build
Personalisation surfaces shipped in priority order. Each measured against control.
04
4. Optimisation
Ongoing tuning of rules and models. Monthly lift reporting.

Frequently asked

Questions we get from people about to book.

Will customers feel surveilled?: We design for the opposite. Personalisation is grounded in the customers own behaviour on your store, not third-party tracking. We avoid the dark patterns (fake urgency, manipulative copy) that make personalisation feel intrusive.
What lift should I expect?: Personalisation lift varies wildly by category, traffic profile and current state. Most stores see 5 to 15 percent revenue lift on recommended-product placements alone; homepage personalisation typically adds another 3 to 8 percent. Honest target after discovery.
How do you measure lift?: Control cohort. A randomly assigned slice of traffic gets the non-personalised baseline; the rest gets personalised. Both populations are statistically identical so the conversion delta is real, not coincidence.
What about GDPR and consent?: Customers who opt out of personalisation cookies get a non-personalised experience. We store no personally identifying data in the personalisation models. Documentation goes to your DPO.
Can the merchandising team override?: Yes. Curated placements, pinned products, banned recommendations all manageable from the merchandising console. The model is a starting point; humans have the final say.

Ready to start?

Tell us about your project.

A member of our team reads every message. Replies within one business day. No sales call required.

See all services

AI Personalisation

What it is.

Deliverables.

What it isn't.

From inquiry to handover.

1. Discovery

2. Foundation

3. Build

4. Optimisation

Questions we get from people about to book.

Tell us about your project.

AI Personalisation

What it is.

Deliverables.

What it isn't.

From inquiry to handover.

1. Discovery

2. Foundation

3. Build

4. Optimisation

Questions we get from people about to book.

Tell us about your project.