MC8 · E-Commerce · AI Personalisation
AI Personalisation for E-Commerce — Product Recommendations and Dynamic Pricing
Amazon built its dominance on personalisation — every customer sees a different store based on their behaviour, preferences, and purchase history. AI personalisation systems bring this capability to independent e-commerce brands, increasing average order value by 15–35% and repeat purchase rates by 20–40%.
The real problems we solve
Average order value increased by 22% with AI product recommendations
Email personalisation increases click-through rates by 3×
Abandoned cart recovery rate doubled with personalised follow-up sequences
Repeat purchase rate increased by 28% in the first 90 days
Customer lifetime value increased by an average of 35%
Frequently asked questions
How does AI personalisation work for e-commerce?
AI personalisation analyses each customer's browse history, purchase history, and real-time behaviour to predict what they are most likely to buy next. This drives product recommendations on the website, personalised email sequences, and dynamic homepage content that changes based on who is visiting.
Do I need a large customer base for AI personalisation to work?
AI personalisation becomes more accurate with more data, but it can deliver value from day one using collaborative filtering — recommending products based on what similar customers have purchased. Most stores see meaningful improvements with 1,000+ customers.
Can AI personalisation work with my existing email platform?
Yes. We integrate with Klaviyo, Mailchimp, Omnisend, and most major e-commerce email platforms. The personalisation layer feeds dynamic content into your existing email templates without requiring you to change your email workflow.
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