Style Intelligence POC
From £1,500
Validate the experience using a limited catalogue and defined recommendation workflow.
Discuss this optionStyle & personalisation
Move beyond basic "customers also bought" recommendations. AI Personalised Style Intelligence builds a customer preference profile using interactions, selected preferences, behavioural signals and purchase history to create increasingly relevant product discovery experiences.
Your project investment
From £3,500
Starting price · GBP
Final price agreed after we confirm your scope.
Built for your next step
Best for: Fashion, beauty, jewellery, footwear, accessories and lifestyle brands with medium or large product catalogues.
Test recommendation relevance with a representative catalogue, verify customer profile persistence and feedback flows, then measure recommendation engagement as preferences evolve.
A clearly defined scope
Personal style onboarding
Style preference questionnaire
Customer preference profiles
AI style profiling
Behaviour-based preference learning
Personalised product recommendations
Outfit/product pairing suggestions
Similar-product discovery
"Complete the Look" experiences
Personalised collections
Customer-specific homepage recommendations
Search personalisation
Recommendation analytics
CRM/CDP integration
Customer profile persistence
Feedback-driven recommendation improvement
Product categories, catalogue size, channels, workflows and integrations are agreed before delivery. Features depend on your platform and the selected providers; each option covers a defined scope.
Choose your starting point
Start with the scope that fits your store. Each option is agreed around your catalogue, platform and integration needs.
From £1,500
Validate the experience using a limited catalogue and defined recommendation workflow.
Discuss this optionFrom £3,500
Preference profiling and personalised product recommendations.
Discuss this optionFrom £7,500
Behavioural learning, personalised collections, styling recommendations, advanced analytics and multiple customer touchpoints.
Discuss this optionCustom pricing
Custom recommendation infrastructure, large catalogues, omnichannel customer profiles and advanced integrations.
Discuss this optionFrom preferences to discovery
The customer selects preferred colours, categories, styles, sizes and price ranges.
The system builds a structured style profile.
Products, collections and recommendations are ranked using customer preferences.
Clicks, saves, purchases and feedback provide additional signals.
Recommendations evolve as customer behaviour changes.
From first conversation to handover
Review your challenge, systems and dependencies. Agree deliverables and acceptance criteria.
Implement the agreed workflows, with regular reviews and feedback from your team.
Test the agreed journeys, support deployment and hand over to your team.
The details that matter
A few things to know about scope, timing and working together.
The displayed prices are indicative. We agree a defined scope, acceptance criteria and a project quote before work starts. Requests beyond that scope are estimated separately.
A product or operations contact, access to the agreed systems and documentation, representative test data, and timely feedback. We confirm access and integration dependencies before scheduling delivery.
The target delivery window is 4–8 weeks, starting once scope, access and dependencies are ready. Third-party approvals or changes to the agreed scope can affect timing.
We hand over the agreed deliverables and documentation with a walkthrough for your team. Further features, monitoring and ongoing maintenance can be scoped as a separate engagement.
Prices are indicative GBP project ranges. Final scope, deliverables, acceptance criteria and price are agreed before work starts. Timelines assume defined scope, available technical access and compatible third-party integrations. Vendor, infrastructure, regulatory and licensing costs are excluded.
Let’s make progress
Tell us about your product and what’s slowing you down. We’ll help define the right scope for AI Personalised Style Intelligence.