Show every visitor the products most likely to convert them. We implement AI-powered personalisation across your Shopify store: product recommendations, personalised emails and dynamic content.
A returning customer who bought trainers does not want to see the same homepage as a first-time visitor browsing running gear. AI personalisation uses browsing history, purchase data and behaviour signals to show each visitor the most relevant products, offers and content, increasing conversion rate and AOV.
Shopify customer data, purchase history and browsing behaviour assessed for personalisation readiness.
AI recommendation engine configured: homepage, product page, cart and post-purchase recommendations.
Klaviyo personalisation blocks set up: dynamic product recommendations, personalised subject lines and content.
Personalisation uplift measured via A/B test: personalised versus non-personalised experience.
Product recommendations plus email
/month
Full on-site and email personalisation
/month
Enterprise AI personalisation programme
/month
Tell us about your store and goals. We reply within 24 hours with a tailored proposal.
We typically use: LimeSpot or Rebuy for on-site product recommendations, Klaviyo for email personalisation and dynamic content, and Shopify native personalisation features where available. Tool selection depends on your budget and existing stack.
Amazon attributes 35% of revenue to its recommendation engine. For Shopify stores, realistic expectations from AI personalisation are 10-25% increase in conversion rate and 15-20% increase in AOV. Results vary significantly by product catalogue breadth and traffic volume.
Basic personalisation (most popular products, recently viewed) works from day one. Meaningful algorithmic personalisation requires minimum 1,000 monthly visitors and ideally 100+ monthly orders for the recommendation engine to learn. We advise on what is achievable at your current traffic level.
Yes but differently. With under 50 SKUs, personalisation focuses on: new vs returning visitor experience, browse-to-purchase path optimisation and email segmentation. Product recommendation engines need 100+ SKUs to be meaningfully different from curated collections.
Via A/B test: visitors in the personalised group versus a control group. We measure conversion rate, AOV and revenue per visitor over a minimum 4-week test period. This isolates the personalisation impact from other variables.